Every B2B SaaS team is fighting for the same, ever-so-budget-strapped buyers in an ever-so-crowded market with thousands of competitors.

Especially if you’re in MarTech, you’re entering an industry growing new players 100X in 10 years at a 39% CAGR. With demand being tight on budget, and your competitors scaling up quickly, it’s harder than ever to stand out.

But also, even the smallest competitive edge in go-to-market execution can make the difference. Here’s the challenge though: most competitive-intelligence workflows are still manual — a Slack channel full of random links, a never-maintained spreadsheet of half-baked notes, or pricey SaaS point solutions that only track narrow slices of the market and serve you “intel” back in the aforementioned Slack channel.

In the best scenario, you have a series of competitor pages to show your buyers how you’re better, but that won’t get you actual competitive intel to inform your product and marketing strategy.

An underlying question arises: how can GTM leaders and their squads unlock always-on, full-funnel intelligence without hiring an army of analysts?

Enter AI agents that continuously scrape and synthesize every public competitor signal — from blog posts to ad creatives to Glassdoor reviews — and pipe structured data straight into product strategy, demand generation, and pipe-building motions.

Why competitive intelligence? And why now?

In the post-ZIRP, AI era, the productivity miracle of LLMs is adding immense pressure to deliver to GTM teams, making revenue targets constantly growing while budgets and teams keep shrinking. In this scenario, CMOs must squeeze as much pipeline as possible from fewer and fewer dollars.

Meanwhile, ever-crowded categories and “AI-powered” feature parity mean a hard-won product differentiator can disappear in weeks, not quarters — making speed of execution and adaptability the actual differentiator of this generation. That is, if you have the right intel to execute on.

In this hyper-paced environment, traditional “intent” data or quarterly analyst reports only tell you what happened after the deal already slipped away, yet teams are already drowning in raw activity logs with zero context.

That’s why competitive intelligence can flip that script; autonomous agents continuously scrape every public signal — not just black box intent, but new blog posts, webinar decks, pricing tweaks, ad creatives, regional spend shifts, hiring surges, one-star G2 reviews. And then translate the noise into real-time insight.

1) Turning competition into an ongoing intel channel

AI-powered competitive-intelligence agents turn scattered market noise into a living, searchable feed that every GTM leader can use with confidence.

In a market where competitors abound — and their activity across product, marketing, and sales — competition itself becomes a live intel channel that can power three high-leverage plays: sharper product and PMM strategy, smarter demand-gen distribution, and high-intent prospecting for buyout or switch campaigns.

They wipe out the Monday-morning slog of copy-pasting links into a “CI roundup,” then widen the lens far beyond social mentions by scraping blogs, webinar decks, pricing pages, release notes, ad libraries, regional spend shifts, hiring trends, and even one-star G2 reviews.

Because the system cross-references those signals, it surfaces patterns a single-point tool can’t catch — think messaging pivots that precede a price hike or a surge in EU ad creative that hints at a regionally focused land-grab.

And unlike DIY sleuthing or single-thread social-listening tools, and even modern “competitive intelligence platforms” like Crayon, or Klue, today’s CI stack stitches all those inputs into one actionable feed, letting you act before rivals even hit publish.

This approach is different also from intent signals tools for outbound such as Common Room, Attention, or Regie — these agents structure every insight around your roadmap and campaigns beyond just pipe generation or deal closing use cases. They can surface which features to prioritise, which claims to defend, which personas to target, and which channels to double-down on.

The payoff is clear: faster product bets, sharper positioning, and a demand-gen engine that reacts in hours, not quarters.

2) Fueling product, marketing, and positioning decisions

Competitive-intelligence agents turn a chaotic firehose of market signals into a single source of truth your product and PMM teams can act on daily.

Some of the powerful product and PMM use cases include:

• Auto-summarizing every competitor launch to monitor feature parity and direction

• Scraping job boards — or LinkedIn posts of people leaving — for hiring bursts or layoffs that hint at company health, roadmap bets, or pivots

• Highlight sudden tweaks in packaging or pricing that could unsettle your own tiers

• Scrape AI-tagged sentiment from thousands of one-star G2 reviews to expose feature gaps buyers feel — or segment sentiment across industry, buyer role, and more

• Add in constant monitoring of webinars, landing pages, blog themes, changelogs, and product documentation to spot messaging and content pivots weeks before they hit the front page of LinkedIn.

The result is faster, evidence-based prioritization and strategy, at massively cheaper gathering and processing costs — so you ship the right capabilities, sharpen positioning before the market narrative shifts, and carve out points of differentiation that stick even in an AI-accelerated arms race.

Want to setup competitive intelligence as your fresh strategy channel? Book a call with one of our seasoned advisors to discuss your challenges.

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3) Multiplying demand gen and lead gen impact

Armed with the knowledge of the right things to track — and AI agents set up correctly — competitive intelligence isn’t a rear-view mirror anymore. And whether product and PMM use cases we’ve seen above are key for broader strategy, this channel is also fresh fuel for repeatable, high-conversion plays that move pipeline.

With an always-on feed of ad libraries, keyword moves, customer sentiment, and hiring signals, high-performing teams orchestrate can orchestrate two core motions:

1. Distribution intelligence for demand gen teams: by scraping every piece of a demand gen play across ads, content, and lifecycle, plus the profiles of who click or comment, you can spin up counter-campaigns or fill in white-space content before they cement momentum. Imagine the following:

   • Track every creative across LinkedIn, YouTube, Meta ad libraries, channel presence, headlines and creatives, spend surge, regional competitors test, plus who clicks or comments.

   • Layer (gated) content topic and keyword analysis, landing pages, newsletters, and organic social from thought leaders accounts and company pages to identify correlation across reactions, sentiments

   • Spin up ad counterattacks and current responses with dedicated landing pages, ads, or tailored creatives that spotlight your edge before rivals scale budget.

   • Identify white-space keywords or keywords hijacks by monitoring SEO/SEM shifts, then intercept emerging terms with optimized content and paid bids to own share-of-search.

   • Build competitor-intent retargeting audiences from users engaging with rival ads, then serve tailored proof-points like industry-adjacent testimonials, case studies, or ROI calculators to help reframe the evaluation.

2. Prospecting and retention fuel for outbound and success teams: flag accounts lurking in a competitor’s community, disgruntled G2 reviewers, or buyers stuck in legacy contracts and trigger plays while intent is hottest. The best teams package these raw signals into these plays:

   • Scrape in-demand prospects from one-star reviewers or negative segment social comments to time tailored outreach that is backed by superior performance, pricing, or proof points.

   • Combine the above sentiment with abrupt pricing hikes with your new product releases to time tailored outreach that suggests how well you’ve done your research, and how your product can better match customer needs compared to alternatives.

• Equip sellers with segment-specific battlecards that update in real time and show how the competitor pitches RevOps vs. Marketing vs. other personas, the feature gaps to press, the best pricing, packaging and negotiation levers, and the poof points to share.

• Trigger switch-incentive plays across landing pages and outbound bundle migration help, ROI calculators, and time-boxed discounts that create urgency while intent is hottest.

• Last but not least, tie those plays together with playbook inversion: reverse-engineer public onboarding docs, product tours, and case studies to expose cracks in how competitors sell and deliver, then feed the insights back into your own nurture flows and demo scripts. The result is a bigger, faster pipeline—powered by actionable context that no spreadsheet could surface.Run a churn-surge monitor for leadership exits, Glassdoor declines, or surprise price hikes, and immediately outbound with stability-first messaging.

The result? Larger, faster pipeline, delivered by insights no spreadsheet could surface and no quarterly report could catch in time. Bonus: layer these plays one on top of the other to see your pipeline and strategy differentiator compound across the entire GTM motion.

Closing thoughts

To wrap, competitive intelligence is no longer a static slide deck — it’s a living dataset that can sharpen every product decision, amplify every campaign, and pinpoint prospects the moment they’re ready to switch.

By wiring AI agents into the public exhaust of your rivals — ads, reviews, pricing pages, changelogs, even Glassdoor chatter — you trade lagging indicators for real-time cues.

Product and PMM teams spot roadmap gaps before they make the roadmap; demand gen leaders launch ad counterattacks and keyword hijacks while competitors still A/B-test headlines; sellers trigger switch-incentive plays the minute a one-star review drops or a pricing hike lands.

Layer these moves and the effect compounds: faster differentiation, bigger pipeline, and a GTM engine that learns as quickly as the market shifts.

Ready to use agents to turn competitors into your most reliable and current strategy source AND growth channel? You better be, otherwise your competitors will.

Gen AI and Gen UI are driving product commoditization faster than ever, making SaaS websites and apps virtually indistinguishable. If you add that saturated, costly acquisition channels have eroded traditional differentiation, the real challenge becomes how to break through the mold and build a distinctive brand.

One answer lies in embracing community-led growth, a strategy that moves beyond one-size-fits-all marketing to harness the power of authentic user relationships and third-party endorsements.

By creating a vibrant community around your product, you foster deep connections, cultivate loyalty, and earn trust from users who become your most passionate advocates. It’s easier said than done, but what it means is that instead of competing for attention in crowded channels, you stand apart through genuine engagement, meaningful dialogues, and long-term value exchange — ultimately establishing a brand identity that thrives on collaboration and shared purpose.

In this post, we’ll dive deeper into community-led growth, frameworks to think through your community strategy, and execute on it with top-tier, real-world examples from leaders like GitHub, SaaStr, Clay, Strapi, and more.

1. Understanding Community-Led Growth

By shaping a go-to-market strategy that places a passionate network of users at its center, community-led growth aligns a company's goals with the needs of its members, creating a self-sustaining flywheel where every participant is motivated to contribute and collaborate.

Imagine a new member joining your community, immediately feeling welcomed, and soon finding ways to exchange value — whether by sharing insights, leveraging new templates and integrations, or offering support.

This steady stream of member-driven content and resources naturally attracts fresh participants, further strengthening the entire ecosystem. To understand this, we can reference the CAMPER framework by Lloyed Lobo, which he used to bootstrap his startup boast.ai to $10M ARR.

• Connection: Build strong relationships through shared values and goals.

• Autonomy: Empower members with control over their contributions and growth.

• Mastery: Foster learning and skill development.

• Purpose: Align the community with a clear mission and vision.

• Energy: Infuse enthusiasm into every interaction.

• Recognition: Celebrate member efforts and successes.

Another similar framework to understand community is Late Checkout’s founder Greg Isenber TRIBE:

• Togetherness: How (often) are people coming together?

• Rituals: What are people coming here to do? Are there recurring things they do?

• Identity: How do people identify in the community? (eg. name, image, aesthetics)

• Belonging: What are people's shared goals, interests, beliefs, and status?

• Engagement: How do people engage with each other?

As Greg mentions:

“The difference between an audience and a community is which way the chairs are facing”

What Greg means is that, unlike audience-focused social channels where you broadcast content one-way via platforms like Twitter, or Substack, a true community thrives on two-way dialogue, making tools like Discord, Slack, WhatsApp, Circle, or Telegram better suited for active engagement and networking.

2. Why Community now?

In an era where growth hinges more on authentic relationships rather than brute-force growth tactics, investing in community-led strategies has never been more important.

As we return to more and more in-person work environments and seek IRL human contact, communities that foster shared identities and enable strong emotional ties can evolve into brands people genuinely care about.

Additionally, as AI and bot activity is emerging in content and search engines, people are hinging more and more towards peer-to-peer feedback — they seek human thought and conversation.

Especially if you’re targeting younger, Gen Z audiences value authenticity and peer insights over traditional review platforms — engaging them through community, bottom-up narratives resonate far better than stale, top-down ones.

And regardless of demographics, with innovation moving at a breakneck pace, members increasingly look to communities of peers for education, mentoring, and skill-building that keep them ahead of the curve.

Communities are not just about targeting and branding, but also about business impact. Well-executed and managed communities can massively increase brand awareness and deliver higher conversion rates at lower CACs, relying on member enthusiasm rather than expensive paid channels. And unlike AI-generated content and advertising, communities built on deep trust and active participation become incredibly harder to replicate, granting you a lasting moat that nurtures retention and compounds back into acquisition.

Harnessing collective knowledge from members doesn’t just contribute to growth, but can also offset support, R&D, and hiring costs, transforming your community into an engine of growth, feedback, and an extended workforce of product advocates.

3. Community Types

Communities aren’t one-size-fits-all; they can embody different forms to meet different goals. When thinking through your community-led growth strategy, consider how each type can fit into your go-to-market strategy:

• Community of product: Centers around a specific product, where members share insights, solve issues, and offer feedback. By enabling community-led support, content creation and product insights, they continuously differentiate their products and brands, while building a strong acquisition and activation muscle.This approach not only reduces support costs but also builds trust among users, just like Strapi, Clay, Webflow, Salesforce Trailblazers or GitHub’s community.

• Community as the core product: Platforms like Circle, Discord, Skool, Stack Overflow, or Dev.to position community at the heart of their value proposition, enabling users to co-create the product experience through active participation and peer-to-peer knowledge sharing.

• Community of practice: Focuses on shared professions or skills, helping members advance their expertise through collective learning and knowledge exchange. Established references of this category is Reforge for growth and product, whereas a more emerging one is Cargo’s GTM Engineering community.

• Community of interest: Revolves around shared passions or hobbies, allowing users to connect and learn organically. These communities foster brand trust and attract like-minded customers — think of any subreddit for the most niche or disparate topics.

As we’ve seen in these examples, communities aren’t just for one type of company; they bring value across various sectors by forging trust, sparking dialogue, and encouraging members to invest emotionally in a brand’s journey.

• Developer tools: Enable developers to share expertise, solve complex problems together, and gain recognition for their work, making your product ecosystem more appealing and resource-rich.

• SaaS & Enterprise software: Scale user onboarding and training efficiently through peer support, expert Q&A sessions, and user-generated tutorials, reducing reliance on high-touch sales and support channels.

• Consumer products with cult followings: Cultivate brand advocates who share testimonials, tips, and inspiration, much like dedicated communities around Peloton or Duolingo, amplifying word-of-mouth growth.

• Crypto & Web3: Nurture trust, transparency, and active participation by involving members in governance and decision-making, driving engagement and stable token economies.

• Creator economy & education platforms: Empower creators, learners, and mentors to network, collaborate, and showcase achievements, keeping audiences engaged longer and encouraging sustainable growth for your platform.

Now that we’ve covered the basics of community-led growth, we can move onto the strategy and execution part of the playbook.

4. Setting clear Community goals

To build a thriving community that truly drives growth, start by setting clear goals. In the context of community, that means guiding members from low affinity to high affinity, gradually building trust and commitment over time.

Consider trust as a rechargeable “battery” that fills slowly with every positive interaction and can deplete quickly when expectations aren’t met. Inspired by community practices at Shopify, the battery framework highlights the importance of nurturing credibility and reliability.

To get started with your community goals, you have to also define a minimum viable community that articulates who you’re bringing together, what support or knowledge you’re offering, and why they should care.

Strengthen this foundation by crafting a powerful manifesto that speaks to your community’s purpose, its overarching vision, and a compelling backstory that resonates emotionally. By aligning these elements, you create an environment where members feel genuinely welcomed and intrinsically motivated to engage, support each other, and ultimately help drive sustainable growth.

• Who: Identify your target members, such as entrepreneurs or developers, so you can tailor content and discussions to their needs.

• What: Define what the community offers — support, knowledge sharing, or mentorship — so members know exactly what to expect.

• Why: Articulate the benefits of joining, like accessing resources, networking, or even influence within the industry.

Once these basics are established, this guiding narrative will not only inspire potential members but will also provide existing ones with a sense of purpose and belonging, setting the stage for long-term engagement and sustainable growth.

5. Choosing your community platform

Once you have the foundations laid out, the big next steps of your community strategy is about selecting the right platform to host your community.

Doing so effectively means understanding your audience’s needs, familiar stack and UIs, communication styles, and desired level of interaction. For example, if you’re targeting enterprise software business users, they might be more used to MS Teams as a chat platform and rely on multiple Zoom meetings for sync interaction. On the other hand, if your community is made of indie developers, they might prefer more async comms styles like Slack, Discord, or Reddit to share info and keep in touch with each other.

Before committing to any platform, work back from your community MVP outlined above:

• Member needs: Determine if members require support forums, content libraries, peer networking, or event hosting.

• Engagement frequency: Consider how often your community engages and pick a platform that accommodates their rhythm.

• Affinity spectrum: Factor in the level of affinity you want to build within your community, and work back which medium of communications is best for that.

• Synchronicity preferences: Decide between real-time conversations or asynchronous threads to match member schedules.

• Openness: Also think about openness — do you envision a public forum or a private, invite-only group? Pick your balance of accessibility, privacy, and exclusivity.

• Cost: Factor in platform pricing models to align with your budget without compromising member experience.

By carefully evaluating these elements, you ensure that your chosen community platform not only resonates with your members but also fosters meaningful connections that drive sustainable growth. Also, your community could run on multiple platforms — you could have a Discord or Slack for synchronous communication, a Discourse Forum for async knowledge transfer, and a public GitHub repository for actual product feedback and contribution — all running in parallel.

Just make sure each has a different purpose or serves a specific segment so you don’t dilute your growth loops and increase operational complexity too much.

6. Building community engagement

Community Engagement Cycle

Crafting a thriving community means not only attracting members but also guiding them through a journey of increasing involvement and value creation. Think of your community-led growth strategy like a growth loop, or as CMX defined it, a community engagement cycle. This is another great framework that helps to break down and execute on a community-led growth strategy.

1. Define community identity: help users find their role, identity and sense of belonging within their community. Tactics like introducing themselves publicly, setting their handles, PFPs (profile pictures), recommending specific channels based on interest, language or geography, use shared vocabulary, or using role tags are great for establishing strong community identities.

2. Earn community trust: once your members know their role in the community, you need to build trust with them quickly to avoid churn. To do so, ensure you have a strong yet simple onboarding, and provide free upfront value to hook them in.

3. Encourage participation: after building trust, you have to keep your members engaged and expand their level of engagement within their community. Use rituals, games, challenges, hackathon or quests — and hint the promise of rewards — to get them to action.

4. Give recurring rewards: blend a mix of social, financial, knowledge, time, mastery, or joy incentives as rewards for their participation. This reward is the basis for strengthening their community role and identity, and going through the loop once more.

As with every framework, this is just a simplification of reality to guide your strategy and execution. Where in real life people move fluidly along this journey as their interests and schedules, it’s important for your team to think through each engagement state deeply.

By thoughtfully orchestrating every phase — from initial onboarding to advanced contributions—you create a sustainable cycle of growth, loyalty, and shared success for your community.

The Commitment Curve

Designing a community engagement model involves defining clear participation and commitment stages and guiding members through an ever-growing and rewarding journey that encourages lasting involvement. David Spink’s Commitment Curve is a great model that helps articulate each level’s commitments and related engagement states to give participants a transparent roadmap for deepening their connection.

As mentioned before though, flexibility is key — your members should feel free to explore and advance at their own pace, reflecting the natural ebb and flow of their interests and schedules.

• Clearly define stages: Outline distinct engagement levels and package them as “roles” or “milestone” so members know what each entails, and get them.

• Set commitments and rewards: Communicate what members gain at every stage, from exclusive content to recognition.

• Ensure flexible movement: Allow individuals to move forward or step back as their priorities shift.

• Incorporate rituals and challenges: Add structured activities that lend meaning, excitement, and purpose to each level of involvement.

• Attach custom roles and badges: Celebrate achievements and give members a sense of status and identity within the community.

• Keep a visible leaderboard: Display roles and progress through a directory, leaderboard or profile indicators, providing recognition and motivating members to learn, advance, and inspire others.

7. Combining the two engagement models

You can interlace the Community Engagement Cycle and the Commitment Curve models together to chart your community programming and define each key component — from identity to reward.

Let’s take Clay creator program as an example.

Bootstrapping engagement — Community Onboarding

Design a clear onboarding sequence that welcomes them, sets expectations for culture and purpose, encourages personal introductions, and points them to valuable resources. This approach is key to bootstrap initial engagement and avoid churn — one of the biggest risks in community-led growth models.

Make sure to check these use cases when onboarding your new members:

• Welcome message: Gree them immediately upon joining.

• Set expectations & resources: Share expected member goals, next steps, and useful links

• Member intros: Encourage people to connect, sharing their stories or goals.

• Engagement incentive & recognition: Recognize supportive individuals and give people a strong incentive to help each other.

• Resources: Guide members to valuable content and prompt participation.

  

Expanding engagement — Community Programming

Once the foundational initiation is laid out, maintain momentum with a well-structured community programming and calendar that keeps members engaged at a steady rhythm.

The goal is to use your community programming to guide members through increasing levels of engagement and complexity. Work back your programming by helping newcomers reach their “community aha moment,” then gradually introduce more frequent interactions and higher-stakes activities.

For example, as we saw above with Clay’s example, a member might progress from reading a weekly newsletter to sending daily messages on Slack, to creating and sharing content, attending a meetup, or eventually organizing an event themselves.

As you chart your community programming, you can use these strategies to expanding your member engagement:

1. Use case transition: use incentives to transition members to progressively more complex use cases. For example, from reading your manifesto, to attending an AMA, or create a LinkedIn post.

2. Increase frequency: expand engagement by transitioning members to progressively more frequent use cases. For example, from reading a weekly newsletter to sending a message in the community on a daily basis.

3. Increase intensity: encourage members to progressively higher effort/rewards use cases, like creating a X post, which is short and sweet, to a LinkedIn post, to a long-form playbook. Or from attending a webinar, to an IRL meetup, to eventually organizing a meetup themselves.

To bring the above strategies to life you can chart a community programming so that your members keep engaged and are always looking forward to the next interaction.

Having a recurring program sets a rhythm, helping members plan their commitment and deepen their relationships. By mixing online and offline touchpoints, you encourage natural conversations, meaningful connections, and a sense of belonging that transcends the screen.

Here are some of the tactics in your kit to consider.

• Stable foundations: Ensure everyone feels safe by establishing clear community rules, setting expectations, and providing examples of good and great behavior. Define specific contribution roles — who plans events, who moderates discussions, who runs weekly sessions — and support these roles with recognition. Ensure moderators engage at least once a day, and consider hiring a community manager if needed to moderate content and guide member interactions. By doing this, you build a strong cultural backbone that encourages trust, motivates learning, and ensures your community thrives over the long term.

• Events and prompts: Consider adding regular highlights like weekly AMAs, recurring Q&As, or recurring prompts that inspire show-and-tell moments. Offer daily technique classes, run monthly masterclasses, or organize annual retreats, and even parties or concerts. A variety of gatherings — whether that’s to gather product feedback or give back value to your members — keeps them curious and engaged.

• Personal connections: Foster introductions and networking by incentivizing members to meet over Zoom or in person at IRL meetups. Maintain a visible community directory with basic info, tags, backgrounds, and goals so members can easily discover shared interests. Promote member spotlights, challenges, and quests, then congratulate and reward positive behaviors and contributions to reinforce community values.

• Automated engagement comms: set up helpful reminders — notifications, emails, digests, and social alerts — to keep people informed and motivated without overwhelming them.

8. Tactical examples of effective community-led growth

When you create transparent communities, you foster a sense of ownership that leads to sustained engagement, loyalty, and advocacy. Here are some of our favourite real-world examples that bring community-led growth to life.

Building trust and safety — Strapi

Strapi’s public roadmap lets users track and influence product direction, while its handbook offers a window into internal operations. By using RFCs on GitHub for community feedback, Strapi builds trust and shows that member input matters. They also foster transparency through forums, AMAs, and regular updates that keep members informed and valued.

Empowering members through autonomy — Airbyte

Airbyte indexes Slack discussions on public forums, boosting its SEO with user-generated content and compounding an additional growth loop on top of their community.

This approach not only amplifies brand discoverability but also harnesses member expertise to enrich the community’s knowledge base. It ultimately allows members to take ownership by enabling them to contribute code, create content, and organize events.

Cultivating a learning ecosystem — GitHub

GitHub connects developers through its Community Exchange, encourages leadership via the Campus Experts program, and supports skill-building with training resources, workshops, and office hours. Badges and prizes reward engagement, further fueling collaborative learning.

With their learning ecosystem, GitHub makes mentorship, training, and continuous learning part of their community’s DNA. Recognize achievements to motivate members and reinforce a growth mindset.

Recognizing and rewarding champions — Docker

Docker turns highly active members into brand ambassadors called Captains by providing tailored rewards and VIP opportunities, organically increasing loyalty and advocacy.

Understanding that a small group often drives most community activity, they offer personalized rewards, exclusive experiences, and unexpected gestures to show appreciation and keep VIP members inspired.

By applying these tactics — establishing trust, granting autonomy, encouraging learning, and celebrating top contributors — you create a thriving community that grows stronger over time. The result is not just user satisfaction but also a sustainable engine for product feedback, brand advocacy, and market differentiation.

9. Measuring Community-led growth

Measuring and validating the success of your community initiatives is about more than just counting members — it’s about understanding their engagement, trust, and willingness to contribute over time.

Focus first on right-sizing your audience, aim to grow it to 25,000 to 100,000 members, then closely monitor growth trends and spikes in interaction.

Assess participation quality through member interviews and community surveys, gauge affinity and engagement levels by tracking the shift from low to high engagement states, and keep a close eye on trust by observing how often members interact and rely on one another for support.

Ultimately, the goal is to create a dynamic environment where members move naturally from initial curiosity to enthusiastic participation, validating their journey through clear metrics like conversion, retention, and growth in both influence and activity.

Closing thoughts

In an era where products are commoditized and acquisition channels are crowded, a vibrant community becomes a powerful differentiator.

It’s not just another marketing channel — it’s a living ecosystem that thrives on member input, feedback loops, and collective learning. By anchoring your growth strategy in community building, you earn lasting loyalty, higher-quality feedback, and a support network that drives sustainable success.

Getting started doesn’t have to be complicated. Here are five steps to recap this post and get you going with confidence.

1. Understand where: Begin by pinpointing where potential members already gather, then immerse yourself in those spaces to understand the culture, motivators, and pain points.

2. Meet leaders: Engage with the most involved individuals to learn the community’s unwritten rules, goals, and preferences.

3. Choose the right fit: With these insights, select the best community type and platform aligned with your business model, industry, and company stage

4. Prioritize initiatives: Focus on programs that align with member interests and help you achieve your business targets — whether product feedback and contributions, brand awareness through content creation, or events, and overall user support and retention

5. Measure success: Track a north star metric to validate the impact of your community-led growth efforts.

By investing in community-led growth and adopting a thoughtful, metrics-driven approach, you not only deepen relationships with your audience but also empower them to play an active role in shaping your brand’s future.

The result is a resilient, trusted, and ever-evolving community that consistently delivers value, boosts your market presence, and sets you apart in a highly competitive landscape.

The Go-To-Market landscape is at an inflection point. Inboxes and social feeds are overwhelmed with low-quality automated outreach and AI-generated content, making it harder than ever to send ‘the right message to the right person at the right time’, or just stand out on any distribution channel. 

Simultaneously, products have never been easier to build thanks to no-code and AI, flooding virtually every niche with like-for-like competitors with much faster time-to-market, making differentiation harder and increasing overall market risk.

In B2B SaaS land, companies like Ramp, Rippling, Gorgias, and Samsara broke new records with their growth trajectories by leveraging innovative growth strategies. They were early adopters of automated outbound, personalization at scale, and the use of signals and intent data — long before these became ‘democratized’ with the likes of Clay and RB2B. 

However, as these tactics become commonplace, the competitive advantage they once offered has diminished. Volume-based outreach has led to crowded inboxes, desensitized prospects, and stricter spam controls, making it increasingly difficult to stand out.

So how can the next generation of startups learn from the likes of Ramp and effectively break through the noise and drive sustainable growth?

This new breed of challenges demands a new breed of talent — with a different mindset, set of skills, and tooling — the Go-To-Market (GTM) engineer. This post is about why, what great ones look like, and how you can become one yourself (if you wish to!).

The case for GTM engineers

For us at Hypergrowth Partners, we’ve been making the case for GTM engineers for years already — we’ve been evangelizing this growth mindset in growth teams of the likes of Ramp, Gorgias, Vercel, Drift, and more.

The case for GTM engineers is clear to us — however, the AI revolution is making it even more important. Let’s unpack some of the key root causes.

ZIRP, tech layoffs, and AI

In today's hyper-competitive market, every product category is saturated. Even groundbreaking innovations like OpenAI face numerous competitors such as Anthropic, LLama, Qwen, DeepSeek, Cohere, and Grok. The post-ZIRP (Zero Interest Rate Policy) era, coupled with widespread tech layoffs and the rise of AI, is intensifying pressures on productivity, efficiency, and revenue per employee. 

Companies are being pushed to "do more with less," necessitating rapid execution and adaptability. In this market, only the teams that embrace this tempo and productivity demanded by the market will stay ahead of the curve. Otherwise, you’ll drown into a sea of undifferentiated, like-for-like average players; or simply go bust.

GTM SaaS-ification

The explosion of GTM SaaS — Marketing, Sales etc. — is productizing entire job roles through vertical and or horizontal SaaS tools.

For example, carrying out lead generation and qualification operations once required teams of SDRs that would manually create lists of potential customers, calling them one by one to verify potential fit, and then pass them onto the sales team to start the sales cycle. Now, you can use various intelligence platforms to collect signals within and outside your properties, and predictably score and qualify them — and automatically reach out to them on the right channels with a hyper-tailored messaging. All without lifting a finger!

The same is slowly happening in content marketing, SEO, performance marketing, sales, PLG, and more, with specialized tools and AIs that are enabling better outcomes with much less resources. Examples include:

• Content: byword.ai, AirOps, EasyGen, Writesonic, Engyne, Synthesia, Ideogram, HeyGen

• Outbound: Clay, Instantly, Smartlead, Unify, Lemlist, LaGrowthMachine, Sendspark, Apollo, Koala, Salesloft, Letterdrop

• TAM/List building: Keyplay, Ocean, Common Room

• Enrichment: Fullenrich, Common Room, Waterfall, BuiltWith, Zoominfo, Clearbit, Cognism

• Signals: Common Room, Waterfall, Clay, RB2B, Madkudu, Pocus

• Research: Tome, Poggio, Endgame

• Product Marketing: Octave, Humata, Relume, Gamma

• Website: Mutiny, Userled

• SEO: Ahrefs, SERanking

• Paid marketing: DemandBase, NRich, Smartly, Metadata, Primer, RollWorks

• Sales: Orum, Gong, Nooks, Attention

• Training: Hyperbound, Blue

• Revenue Orchestration: Cargo, Warmly

• Lifecycle: Userflow, Customer.io, Crisp, Intercom, Refiner

In the most extreme scenarios, we’re seeing solopreneurs who can setup, maintain, and even scale multiple go-to-market workstreams — content, outbound, and SEO — by just leveraging a set of AI-powered tools.

This is putting further pressure on building knowledge of the latest tools on the market to carry out complex outcomes with small, lean teams.

Operationalization

Operationalization has become another byproduct of this shift. Every GTM function now has its own "ops team" — marketing ops, sales ops, dev ops, product ops. These teams are quickly gaining more and more popularity in tech startups, and for good reason. They’re:

• Both technical and business savvy: they combine understanding of the customer journey, ICP, and business model, with technical skills of data and SaaS management.

• Data management: Know how to collect, clean, and mine customer data from large datasets, and use them for business purposes like messaging personalization and distribution — tying them to real business impact.

• SaaS stacking knowledge: Can comfortably jump into, learn, and master multiple SaaS tools — setting up custom workflows that reflect the customer journey — stacking the right tools together based on the company stage and needs, while also imbuing data into each of them to guarantee personalization at scale.

Operationalization means data and tooling knowledge — and the ability to leverage both across the entire customer journey — are becoming critical traits of modern tech talent that yields above average results, faster, and with less resources.

Cross-functionalism and use-case focus

Cross-functionalism is another critical factor that makes the case for the GTM engineer. Since the first Reforge course came out back in 2016, lines between core GTM functions — product, sales, data, and marketing — have been blurring, requiring professionals to build more and more T-shaped skill sets.

As we mentioned above, GTM teams must zoom in and out of the entire customer journey, wearing multiple hats and plugging into different skills to address problems wherever they arise in the funnel.

• Monetization: customers are not upgrading from our free trial. Is it a pricing model problem, a UX/UI problem, or a product one that is preventing customers from monetizing?

• Retention & Engagement: customers are not combing back with the product. Is it a UX/UI, feature parity, messaging, or targeting problem?

• Acquisition: customers are not signing up. Is it an awareness, messaging, UX/UI, targeting, or channel problem?

These problems relate to the key use cases of a tech business — how to acquire, engage, retain, and monetize their users — and transcend the typical problems that relates to the function of the business — marketing, product, sales, etc.

Customers are buying products via a multi-touch and cross-channel experience. To effectively cope with this mindset, tech teams need to transcend their siloed view in terms of a company function — from marketing, product, and sales — and instead embrace a cross-functional use-case view of the business — to acquisition, retention & engagement, and monetization. 

This requires modern teams to be able to understand and manage the end-to-end customer journey, strategize experiments throughout it, and quickly switch gears to solve different types of problems. This adaptability makes modern talent more of generalists with knowledge in 2-3 key areas.

Growth mindset

In this new, fluid and fast-paced landscape, mindset outweighs hard skills. 

While hard abilities remain important, soft skills like risk-taking, adaptability, rapid learning, modular thinking, lean operations, speed, and execution are now more paramount than ever. 

That’s why experience in early- or growth-stage startups — where the speed of growth forces teams to undergo massive change and fast learning curves — become most formative and in-demand. Because it’s what helps forge the growth mindset as we define it at Hypergrowth Partners.

It’s easier now to see how the case for the GTM engineer is clear.

• ZIRP, tech layoffs, and AI are putting pressure on teams to be smaller and more productive

• GTM SaaSificiation is enabling small teams to achieve better outcome with less resources

• Operationalization puts the focus on tech stacks and data knowledge as critical skills

• Cross-functionalism is forcing smaller teams to own the full journey and wear multiple hats

• All of the above make execution and mindset more important than hard specializations

Now that we’ve made the case for the GTM engineer, let’s dive deeper into what great ones look like, and how they differ from other common profiles we’ve been seeing in growth teams in the last few years.

What makes GTM engineers different

GTM Engineers represent a new paradigm in growth teams, distinct from more ‘now traditional’ positions like growth marketers and growth engineers. Before understanding what a GTM engineer is, let’s make some distinctions as to what it’s not.

GTM engineers vs. Growth marketers

Growth marketers focus primarily on customer acquisition. Their objectives revolve around attracting new users through channels like SEO, paid advertising, content marketing, and social. Their focus is on top of the funnel and related topline metrics, like traffic, signups, and activations. To do so, they rely on tools such as web analytics, social platforms, SEO and paid ads software to set up, optimize, and scale campaigns. In some cases, their remit extends to the signup and activation flows, including landing page and UX/UI optimization for the top-of-the-funnel. Their mindset is centered around channel tactics, A/B testing, ICP knowledge, and messaging.

In contrast, GTM Engineers go beyond just acquisition to encompass the entire customer journey. They act as system orchestrators across all stages — from awareness to revenue, retention and churn. They integrate multiple SaaS tools, set up end-to-end custom workflows, and handle large datasets to create a seamless and personalized experience, with or without code. Their holistic approach integrates a solid RevOps and data fluency, while also being knowledgeable in messaging and ICP more typical of growth marketers.

GTM engineers vs. Growth engineers

Growth engineers are software programmers focused on growth product experiments. Their goal is to build or scale experimental features that drive engagement, retention, or revenue. They work closely with growth PMs and growth designers to “build” out these experiments, track their impact via A/B or multivariate tests, and validate them before passing them onto core product and engineering teams. To do so, they use a mix of Python, JavaScript, and SQL too. Their mindset is deeply technical yet scrappy, focused on building aggressive and scalable solutions.

GTM Engineers differ by not being confined to the product itself. Differently from growth engineers, they integrate expertise in the user journey, ICP, messaging, and business acumen (e.g. pricing, forecasting, etc.). Like growth engineers, they can code, but can also quickly jump into managing multiple SaaS, connecting them together, managing data pipelines, and ensuring alignment between GTM teams. 

In addition, GTM Engineers master prompt engineering — and beyond just ChatGPT. Prompt engineering means knowing multiple AI models — Perplexity, Llama, OpenAI, etc. — and knowing how to scope them and leverage different use cases to deploy scraping, scoring, routing, personalization and inject efficiency and scalability to the GTM motion. It’s about how to ensure consistent results at scale.

They make their data fluency actionable by injecting it directly into (AI) tooling to optimize the end-to-end funnel — for use cases like signal-based plays and personalization across the entire funnel — bridging gaps between product, marketing, and sales. 

GTM engineers vs. Growth Product managers

Growth PMs focus on scaling growth by managing a pipeline of product growth experiments. Their objectives include analyzing product data to mine growth opportunities, coming up with hypotheses for experiments, and prioritizing them on a roadmap to drive engagement, retention, or revenue. They work with growth designers, growth engineers, and growth analysts — and tools like product analytics, user feedback platforms, and A/B testing software — to run these experiments. Their mindset balances product, design, and UX/UI with business growth.

While Growth PMs concentrate on the product's evolution to stimulate growth, GTM engineers adopt a more comprehensive scope. Unlike Growth PMs who focus on product experiments, GTM engineers focus on integrating product, marketing, and sales strategies as one, unified growth system. They leverage cross-functional data and insights, intertwine multiple (custom) tools to ensure that every aspect of the customer journey is cohesive and effective.

GTM engineers vs. Growth hackers

The term "growth hacker" often suggests a focus on quick, overnight wins through unconventional tactics. This mindset can set false expectations, positioning the role as one that seeks shortcuts rather than sustainable strategies. We’re not big fans of this term.

GTM Engineers differ significantly in this regard. They prioritize building robust systems and processes over short-term hacks. Their approach is iterative, thoughtful, and scientific, emphasizing scalability through automation and sustainability by working back from business forecasting. By avoiding the "hacking" mentality, GTM Engineers aim for long-term growth and scalability.

GTM Engineers: The Holistic Growth Orchestrators

The challenge now lies in defining and recognizing these professionals. Titles like Chief of Staff, Head of Growth, GTM Ops, RevOps, or Special Projects have been used, but none fully capture the essence of this role. 

Let’s examine even more what their day-to-day looks like, deep diving into their background and real-life examples.

Goals

Concretely, GTM Engineers own pipeline and revenue growth. They’re able to forecast and workback from key business metrics and build workflows and systems — across every customer touchpoint that reliably and directly tie into the business bottom-line.

Ownership

GTM engineers own the entire buyer journey, from identifying the right Ideal Customer Profile to building pipeline and converting it into revenue. They find the most cost-effective ways to turn accounts into dollars, whether through AI, automation, off-the-shelf tooling, product experiences, data vendors, paid programs, or traditional sales. What matters is that it works efficiently.

Their responsibilities include setting up signal-based, cross-channel demand generation programs — such as outbound, paid, content, and SEO — and extending their influence to the bottom of the funnel through lifecycle marketing, expansion, cross- and up-selling, and churn prevention. 

In the early-stages, they set up and execute on setting up these workflows from scratch with a focus on sustainability, repeatability and scrappiness. Then, as the organization matures, they switch into optimization and testing, by coming up with hypothesis-driven experimentation typical of growth teams.

Cross-functional expertise

They embody the cross-functional convergence of marketing, sales, product, engineering — and business! — acting as the link between every functional GTM team. They integrate a unique, T-shaped blend of:

• ICP, user behavior, and messaging knowledge

• End-to-end customer journey

• Business forecasting and modeling

• (Semi)-technical knowledge of coding, SaaS, data, and APIs

Because of that, they don’t think as ‘marketers’, ‘PMs’, or ‘engineers’, but can switch gears to solve system-level problems of ‘acquisition’, ‘retention’, or ‘monetization’. 

Combining technical and creative skills

Standing out requires a blend of technical prowess and creative acumen. Smaller, leaner, cross-functional GTM teams are becoming essential, composed of individuals who can connect the dots across various functions and embrace allbound strategies. These are the "Internet plumbers"—cross-functional generalists who deeply understand each stage of the funnel, are fluent in the latest technology and automation, and can orchestrate large, modular growth stacks. They're more comfortable in tools like Clay than traditional CRMs like Salesforce, and their favorite acronyms are ICP rather than MQL.

Combining large datasets — first-, second-, and third-party signals — with messaging testing, and SaaS tooling, they blend technical and creative skills to build scalable and modular systems tailored to the ICP and the customer journey.

Growth mindset

Because of their cross-functionality, fluency in AI and SaaS tooling, and system thinking, GTM engineers can comfortably operate within lean, small teams, wearing multiple hats and taking full ownership of pipeline metrics. They stay abreast of the latest tools and maintain a growth mindset that prioritizes fast-paced thinking, risk-taking, and execution excellence. Hands-on in building custom tools and integrating systems, they develop high-impact solutions tailored to their organization's needs. Operating. They can work closely with:

• Sales & CS: as their work tie directly to revenue and business impact

• Marketing: as they have deep understanding of the ICP and messaging

• RevOps & Engineering: as they know how to code, use, and interlink multiple SaaS and AIs

• Product: as they operate also on the bottom-of-the-funnel, at churn and expansion

In shorts, GTM Engineers bridge strategy and execution across the entire funnel. Sounds hard or close-to-impossible? And it’s exactly that rarity that makes this type of talent extremely valuable.

Background

This new breed often comes from two, opposite backgrounds: 

• Technical marketers and business operators with a creative flair, such as Hank Taylor, who combine marketing savvy with technical skills and branched out in  more cross-functional, GTM role roles.

• Engineers who have developed a keen interest in revenue generation and GTM strategies, like Rory Conroy and Raman Hundal, leveraging their deep understanding of tech and SaaS to drive revenue initiatives.

Then there are 360° GTM professionals like Sylvain Giuliani, who seamlessly integrate multiple disciplines, embodying a full-spectrum approach to go-to-market strategies. In essence, leading GTM Engineers are versatile problem-solvers who bridge the gap between technical execution and business growth.

Real-world examples of GTM Engineering teams

Gorgias

Consider Gorgias' approach (they have one of the best GTM engineering teams on the planet) — their objective was to understand why Zendesk users were migrating to Gorgias. 

• A traditional growth marketer might listen to Gong calls and manually extract insights—a time-consuming and less scalable method. 

• In contrast, their GTM Engineer developed a script using prompt engineering and natural language processing to analyze these calls automatically. They extracted core reasons for migration, applied these insights strategically, and integrated the findings into GTM systems. When specific signals were detected, they fed personalized, AI-crafted emails at scale.

Gorgias also utilized Cargo to optimize their email outreach. They replaced static segmentation with dynamic, AI-driven content generation, built conditional logic flows for real-time email customization, and integrated with the Instantly API for automated email dispatch. 

This sophisticated orchestration led to a 70% increase in conversion rates compared to previous sequences.

Datadome

Similarly, Datadome exemplifies the GTM Engineer's impact by building a systematic pipeline for lead generation. 

• For each closed-won deal detected in their CRM, they automatically generated lookalike accounts. 

• They retrieved key information from the original deals to craft resonating messages for these similar accounts. 

• The GTM Engineer identified and enriched the right stakeholders within these accounts, allocated them to sales, and pushed them into a sequence where the first email was drafted using deal information combined with AI.

In essence, leading GTM Engineers transcend traditional functional roles by integrating scalable tech, workflows, data — as well as messaging, creatives, and business logic — into complete GTM strategies, resulting in increased efficiency, personalization, and revenue generation.

Here’s a list of top GTM engineers for you to connect with and learn from:

• Trevor Fox

• Hank Taylor, HyperGrowth Partners & Laravel — ex Vercel, GitLab

• Gaurav Vohra, Superhuman

• Sylvain Giuliani, Census

• Rory Conroy, Gorgias

• Jeff Ignacio, Keystone AI

• Diego Martinez, Pigment

• Marcel Santilli, HyperGrowth Partners & GrowthX Labs — ex Deepgram

• Guillaume Aubert, Gorgias

• Raman Hundal, Rhombus

• Vincent Bonjean, Qobra

• Diego Martinez, Pigment

• Aurelien Aubert, Cargo

• Maxence de Villepion, Cargo

• Keerthivasan C, Omni

• William Borges, Veriflow AI

• Nicolas Druelle, The Revenue Architects

• Callum Hamlett, Arquit

How to become a GTM engineer

So, you want to become a GTM engineer? There are multiple pathways to do so. 

• If you come from an engineering background with an interest in revenue and go-to-market strategies, you can leverage your technical skills to build custom data and SaaS architectures that operationalize GTM programs like personalized outbound, lead scoring and routing, or signal-based plays. Developing proficiency in SaaS, AI, customer journeys, personas and messaging can complement your technical and problem-solving abilities and position you to design GTM systems that drive real growth.

• If your background is in marketing or sales, you can acquire the necessary technical skills to transition into a GTM Engineer role by attending coding bootcamps like Ironhack, Le Wagon, or Codesmith.io and get equipped with knowledge in AI, automation, data operations, and programming languages like JavaScript. 

Joining a growth engineering team — perhaps within Hypergrowth Partners' portfolio companies or organizations building GTM engineering tools — can provide the best practical experience and exposure to real-world challenges. Think of companies like:

• Ramp

• Vercel

• Ashby

• Together.ai

• AirOps

• Attention

• Clerk

Also, engaging with GTM engineering communities allows you to network with like-minded professionals and stay updated on cutting-edge developments. Finding a mentor who specializes in growth engineering can also accelerate your journey, offering guidance and insights that refine your skill set.

Regardless of your starting point, the key is to continually expand your T-shaped skillset across both technical and creative domains. By combining technical skills with strategic understanding, you position yourself as a versatile asset capable of orchestrating holistic growth initiatives that span the entire customer journey.

Conclusion

The future of GTM engineering lies in the formation of smaller, tech-enabled teams that leverage AI to drive efficiency and revenue growth. 

• As AI increases revenue per employee, the need for large, specialized teams diminishes, making lean, cross-functional teams of GTM Engineers the new norm. 

• Sales roles will evolve accordingly, with sales representatives becoming key touchpoints within a technology-orchestrated customer journey rather than sole drivers of the sales process. 

This shift paves the way for GTM Engineers to emerge in leadership positions; future CROs and CMOs will need both technical and strategic expertise, and GTM Engineers are natural fits for these evolving roles. Their unique blend of skills positions them to lead organizations in a landscape where tech and strategy are increasingly cross-functional and intertwined.

As traditional growth strategies lose their edge in an increasingly competitive B2B SaaS landscape, the role of the GTM engineer has become crucial. By bridging technical expertise with business strategy, GTM engineers are the new architects of growth.

Implementing GTM engineering in your organization is not just a competitive advantage — it's becoming a necessity. Embracing this shift will position your company at the forefront of industry evolution, ready to outpace competitors and capture new market opportunities.

B2B growth strategies often differ significantly between Europe and the US, influencing multiple facets of the related markets, such as the number of growth stories, IPOs, but also talent.

It’s renowned that the European landscape of B2B companies is perceived to generally lag in the above metrics, as reflected by the lower numbers of European B2B SaaS going public or expanding to the US, compared to the larger American counterparts crushing the public markets and the European expansion. The same comparison is true when looking at the talent market enabling such innovations — the EU’s top talent market is much smaller, more inexperienced, and not rewarded for the long term.

Despite exceptions like Alan, Personio, Pigment, and a few more unicorns, these aspects make it challenging for EU startups to scale sustainably and across the entire market geography.

What is this lag attributed to? Does it depend on a more conservative, perfectionist approach that prioritizes “more than good enough” products vs. an MVP mindset? Does it come down to a different risk-reward profile of founders and the VC ecosystem funding them? Or is it a regulatory and cultural fragmentation — across languages and customs — that prevents founders from making swift changes in their staff due to labor laws, or rewarding their talent properly with long-term equity incentives?

And most importantly, how can European B2B companies get inspired by their American counterparts and adjust their growth and hiring strategies to be competitive on a global scale?

In this post, we’ve talked to Loic Jeanjean, our latest addition to the HyperGrowth Partner’s roster and fractional CMO who previously headed up growth functions at European unicorns like Ledger and Pleo, but also in numerous US-based B2B SaaS companies, to find out!

As a European based in Lisbon and advising both EU and US companies, Loic gives us his unique take on the key reasons why European startups fall behind, and key tactical insights about how they could get back on track and aim for a successful scale, including US expansion. 

In a nutshell, European businesses need to embrace swifter operations in line with the fast-paced markets of the roaring 2020s, and a much more customer-centric approach if they want to aspire for global scale. Let’s dive in.

1. Embrace Customer-Centricity, Good Enough & Risk Taking!

In Loic’s experience, European companies tend to be more risk-averse and slower than their American counterparts. This attitude shows in things like over-documenting their operations, micromanaging teams’ decisions, and ultimately seeking perfection in product, marketing, and sales. 

We could speculate that to be a symptom of an idealistic culture, but it most likely comes down to the fact that many European teams don’t know what good and great products look like, or even what good enough is!

Speculations aside, this attitude toward product building leads to slower execution and responsiveness to market changes, which is reflected in delayed launches and scale.

When it comes to product releases, the focus should be on velocity — ship more times, faster. You should aim for consistent, weekly releases. As a good forcing function for your team to build such velocity, aim for shipping 80% of your plan. If you have 10 improvements, commit to shipping 8 instead, as long as you hit the mark of doing it every week.

When European teams embrace the ruthlessness of the growth mindset, made of continuous experiments at a highly tactical level, they’ll be able to quickly kill something that no longer works, and revisit it at a later stage; or swiftly double down on what does work, and push their limits to incrementally improve it. 

“I love the LVR metric — Lead Velocity Rate — and advise founders to aim for a minimum 10% MoM. This pushes Marketing & Sales teams to take more risks and come up with more tests to iterate on their work every month.”

Another key difference between American and European product teams is that the latter are generally less customer-centric; rather, they tend to develop products over-indexing on the founders’ internal conviction or personal experience, which ultimately silo their team and product from their target market.

“If you’re in product or GTM, this might sound like a broken record, but it’s impressive how many teams we see that still don’t just pick up the phone and talk to customers.”

If you’re heading up a customer-facing team in Europe, you should set a goal to speak to at least one prospect or customer per week; that includes not just sales and product, but also marketers. Surveys are not enough to grasp the nuance needed to compete in today’s market; you need to pick up the phone and invest the time to build a system to have in-depth, regular conversations about their:

• Business: who they are, their goals, and how they operate

• Pain points: what keeps them up at night

• Tooling: what they use to run their business, or their fave app on their phone

• Channels: where they learn and hang out with others, on- and off-line

• Decision-making: who they follow and respect, and influence their decisions

Build these habits and you’ll not just quickly emerge in the European market, but you’ll soon graduate to the World’s League and be able to compete on a global scale.

2. Broaden your Horizons of what Good and Great GTMs Look Like

Founders, CXOs & VPs, but also team leads, in Europe often lack experience in what successful GTM looks like, as they are often first-timers in their roles. 

Additionally, they tend to benchmark their TAM ambitions and set goals against local customers and competitors, drastically reducing their vision of what’s possible, and in general what good and great look like. In the worst cases, this leads to complete tunnel vision and even arrogance, which discards valid tools in your GTM’s arsenal.

For example, many European companies we’ve worked with question tactics like offline events and webinars because they “have already tried this in the past”, or “won’t scale”; when in reality the issue is a lack of expertise in executing them properly.

In turn, this attitude leads to an inability to execute the right strategies, accumulating strategy and tactical debt across the board. This debt is very hard to identify and course correct, because it compounds in the medium term, and impacts negatively virtually all functions — product, marketing, sales, data, brand, and hiring. 

Founders and C-levels who want to avoid this need to have the maturity and self-awareness to identify what’s under the hood, and typically this comes down to having seen the movie already a couple of times.

Set Global-scale References of What Great Looks Like

Even if you don’t have direct experience, you can learn from others. Expanding your horizons and learning from global-scale success stories can provide valuable insights and motivation for European founders and teams. This is especially true across GTM and hiring which are quickly becoming the more challenging aspects of sustainable scale. 

Start with building the right mindset and attitude towards learning. In the US, it’s common sense that you have to invest resources upfront to make a return. In other words, you have to break an egg to make an omelet. That’s not always the case in Europe.

You need to be humble enough, willing to acknowledge that and invest your resources into painting a picture of what good and great look like on a global scale. 

In the Internet era, you don’t need millions to get started. Just join cutting-edge e-learning platforms like Reforge & CXL to access the top thinking and tactical frameworks to empower your team with the right tools.

And please read the classics of Go-to-Market and Leadership — books like Good to Great, E-Myth, Obviously Awesome, The Ultimate Sales Machine, From Impossible to Inevitable, Crossing the Chasm, Predictable Revenue, The Sales Acceleration Formula, The Cold Start Problem, Play Bigger, Managing Oneself, Measure What Matters, Radical Candor, High Output Management, and more.

Bring in External Advisors to Set World-Class Examples

It’s a no-brainer that investing in your team is one of the best things you could do; not just for your individual contributors, but also, most importantly, your leaders.

Get your leaders an advisor to mentor them. Engage advisors with repeated, real-life experience in the “wild wild US market”, ideally those who have worked in companies that are already past your current and next stage of growth. Task them to help you reshape your team and operating culture, and transform your GTM.

Focus advisors on what we have discussed so far —  helping you build velocity and take more, bolder, shots at the net, tight feedback loops with customers, and a higher risk-reward attitude. But also uncovering blind spots!

External advisors or fractional executives who have experience in leading hypergrowth companies have a much better compass for identifying real problems and course corrections. Just be open to listening to them, and implement their advice, or you’ll be fooling yourself twice! We’ve seen many examples of leaders investing tens of thousands in advisory, ignoring their advice, and ultimately going bust.

3. Leverage a Distributed Remote Network of Talent and Investors

Engage VCs with the Right Operating Team

Last but not least, there’s another key difference between Europe and the US — how funding is released, hiring is made, and equity compensations are structured, with the European VC and talent market being smaller and slower. 

According to , that’s exactly where European sluggishness comes from:

"The European ecosystem as a whole is more risk averse, and that starts at the VC level. EU VCs expect more revenue, and more maturity at an earlier stage than their US counterparts. That culture permeates into the companies through the founders and creates more frequent positive outcomes but smaller ones. Unfortunately, the venture business is not about getting ‘1 more X’, it's about getting the ‘100X’"

According to , it comes down to culture: 

“I think there’s a lack of culture of ‘good advisory’. Most VCs in Europe have never seen it, never done it, never tasted the good stuff. They’re also reluctant to pair founders with advisors who can push them to do better and give them the blueprint. Overall, Europe plays risk-averse in an asset class that's based on huge risks”.

The European venture capital ecosystem also tends to have fewer experienced operators and successful founders compared to the US, which can impact the quality of advice and support provided to portfolio companies. This creates a "vicious circle" where the lack of success stories makes it harder to build a strong VC ecosystem, and founders rely on average advice to approach hiring and GTM.

Loic’s advice is to inspect carefully former operators in VC teams to determine what good looks like. Bonus point if they have members who successfully led the US expansion of European companies, or worked in a US SaaS before in a high-impact position like CRO, CMO, or VP of Sales & Marketing.

Hire and Reward Risk Takers in Your Team

When it comes to hiring, the nature of the European market is even grimmer. According to Loic:

“I've always been a huge fan of hiring for potential, but at some point in your startup journey, you'll need to bring people who have seen the movie once or twice. Once you pass 5-10M in ARR, it's hard to wing it.”

Hiring and nurturing talent can be more challenging in Europe — causes are both cultural and regulatory. A tendency to keep employees that “have been with us since the beginning” results in hiring and keeping inexperienced talent, and builds reluctance to make changes when needed. Managers conflate “being nice” with “making the right business decision”. In parallel, strict labor laws prevent letting people go when they’re not the right match. These hurdles can make it more difficult to adapt to swift market changes and proactively evolve company structure and culture as required.

But there are strategies to mitigate these problems. Using EOR solutions like Deel or Remote to get globally distributed talent can be a good starting point, as it increases your talent TAM and your experience range. Especially after COVID, lots of Europeans who worked in the US are slowly coming back to Europe bringing their SaaS experience to the continent — that’s an amazing opportunity to get these unique profiles — with exposure to both cultures —  into your organization. 

And once you hire the right people, adapt compensation practices to reward risk-taking and scale operations more aggressively. Don't punish risk-takers, but get them to share their learnings — the good, the bad, and the ugly — with the rest of the org. This will transform your culture, boasting transparency, accountability, learning, and curiosity.

Also, uncap your commission plans — make it really exciting for people to crush their goals. And make these commissions accessible to your entire GTM team, not just sales. For example, a marketer who gets a €100,000 base salary could have a variable plan with 50% of their bonus based on overall company performance — uncapped, to encourage team collaboration — and 50% pegged to their impact — tied to pipeline, marketing-generated revenue or a blend of several metrics, also uncapped. 

Remember, the culture we build in our organization is reflected in your incentive scheme. To build a risk-taking, competitive culture to compete on a global scale, set the carrot and the stick accordingly.

Closing Thoughts

By transitioning from a perfectionist approach to one that values agility and customer centricity, European B2B companies can enhance their competitiveness and achieve greater success in global markets.

This strategic shift requires embracing risk, focusing on rapid iteration, and putting the customer at the heart of all business operations. These changes not only align with global business practices but also pave the way for sustained growth and market penetration, especially in challenging markets like the US.

Why Most Growth Teams Are Wildly Inefficient

if your growth team's playbook hasn't seen an update in the last 3-5 years, chances are, you're not exactly leading the pack. 

When your team's days are chock-full of reporting, drowning in emails, and bouncing from one meeting to another, you're setting the stage for a productivity nosedive — not to mention the morale taking a hit. It's like running in quicksand; the harder you try, the deeper you sink.

A 2023 report from the Wall Street Journal indicated that employees are spending two full days a week on email and meetings, leading to burnout and low productivity. This is especially worrying for growth teams, where creativity, innovation, and speed are crucial for success.

A significant portion of these hours is consumed by project updates and check-ins, which, although necessary, can often be time-consuming and disruptive. 

It also kills one of the big advantages startups have over more established competition, speed. The ability to go from idea to execution in hours. No big meetings, internal buy-in, legal for approval, or brand guidelines to abide by.

So what is the answer?  How can startup founders and marketing leaders reignite their growth teams and drive steady results without succumbing to both burnout and meeting overload? 

In this post, I’ll give you 6 ways I have found to work well.

Foster a Culture of Focus, Clarity, and Testing

1. Define a Clear North Star Goal

Establish a revenue-centric objective (e.g. revenue or pipeline, but not MQLs!) that serves as the guiding light for all marketing initiatives, giving your teams a forcing function to optimize their activities for the bottom line. 

It is far too easy to get tied down to projects that drive leads or traffic without any meaningful impact on your revenue goals. 

There are a lot of things right now your marketing teams spend time on that just aren’t adding value. One of the best ways as a leader to help your team is to give them the right goals so they have the permission and confidence to say no.

• Say no to you as the leader.

• Say no to the founder.

• Say no to meetings that should have been an email.

“This is definitely something we could explore but right now we are focused on these 3 big projects to help drive more revenue this quarter. Would be happy to discuss if we still want to pursue but for right now I am going to move it to the backlog unless you think otherwise”.

What Founder or CMO says no to that?

2. Empower The Team to Take Bigger Risks

When you build a team culture focused and obsessed with hitting goals, you need to also help them be fearless in trying out new things. Markets are crowded. Everyone is doing paid advertising, creating content, posting on social media, podcasting, sending emails, etc. 

If we sell a marketing automation solution we aren’t competing with the other 300 companies selling the same thing, we are actually competing with all 12,000 martech solutions going after the same buyers. That one buyer is being crushed with emails, ads, and cold calls from hundreds if not thousands of other companies all vying for their time. 

That could mean your creative, your offer — really anything. And that’s the fun part of growth — figuring out what can set you apart. 

A great real-life example — during my time leading growth at G2 we invested heavily in Direct Mail. Now direct mail certainly isn’t a novel approach. However we did something wildly different, we sent people Pinatagrams with the message “Beating this cute pinata isn’t nearly as fun as beating your competition on G2. We coupled it with BDR outreach and saw a 20% meeting booked rate.

This also means being okay with failure. If companies are operating at a high speed, rapid failure is going to happen. And that is a good thing if you are learning from those failures. They should be celebrated and help you find your wins faster.

3. Hire Talent with a Growth Mindset

When I sit down with founders, a big part of our discussions revolves around the art of hiring growth marketers onto their teams. It's a tricky area, and I've noticed it's where many stumble. So, why is it so challenging? 

For starters, marketers are natural at selling themselves, especially the more senior they are. They're adept at weaving a narrative with acronyms and industry jargon. Growth is a role that requires a very broad set of skills that expand what any standard marketing questions can reveal. Secondly, startups often hire for positions that candidates haven't exactly filled before, especially those transitioning from larger organizations to a head of growth role at a nimble startup. It's tough to gauge if they're truly up for it based on an interview alone.

Here's my approach to evaluating growth talent:

• Test for metrics knowledge. Firstly, during interviews, I pay close attention to the metrics candidates mention. If a candidate says they're gunning for a specific goal, like driving sales pipeline, I jot that down. What's the target? How do they plan to hit it? Understanding their strategy and what channels they're leveraging gives me a clearer picture of their method.

  • Great: Know every metric of their funnel inside all the way to revenue.

  • Good: They know the growth side of the funnel but struggle with knowing the broader business metrics like LTV, CAC and how they are impacting those. 

  • Bad: The metrics they share don’t add up to a cohesive story.

• Break down the customer journey’s KPIs. Secondly, I delve into their current role's specifics in a follow-up interview. I ask them to lay out their marketing funnel. From lead generation to the final sale, I want the numbers. It's a telling exercise. Those who know their stuff can walk you through their process without missing a beat. The ones who falter, often those who've padded their achievements, their inconsistencies become glaringly obvious.

• Test for mental agility. And then there's strategic agility. Can they pivot and scale their strategies when needed? I often pose hypothetical case study questions; if your CEO doubled your goal and handed you a substantial budget to make it happen, where would you invest? This question not only tests their strategic thinking but also their intimate knowledge of their current business and its growth potential.

  • Great: They have an endless list of big ideas they want to test. 

  • Good: They have ideas they want to test but most are pretty standard approaches

  • Bad: They only share how they would invest in what they are already doing. If it truly already works for the business, why aren’t they scaling it already? 

I've yet to regret hiring someone who could confidently navigate both these aspects, whether they're in growth, demand generation, content, or product marketing. At G2, we used this framework and members of our Growth team went on to lead growth at Ramp, Safe, Help Scout, and some of the biggest companies in SaaS.

Establish Lean Ops and Continuous Feedback

4. Adopt Shorter Work Cycles

Transition to a two-week sprint model to enhance team productivity and responsiveness, facilitating rapid iteration and course correction based on real-time feedback. This will also help you identify the capacity and bandwidth of the team but also ensure focus and helps you identify possible blockers that are slowing your team down. Speed is one of the most talked about things in startup culture, and shifting to a sprint model helps the team ship faster.

So how do you actually run a 2 week sprint? It comes down to 3 simple things:

1. Sprint Planning Meetings: At the start of each sprint, conduct a meeting to establish the tasks for the upcoming weeks, prioritize tasks, and set clear goals.

2. Limited Meetings: Instead of daily updates or frequent meetings, the sprint model advocates for one check-in meeting per week. These meetings serve as a platform to discuss progress and resolve issues. Here is the rough agenda for what that looks like: 

   1. Sprint Overview Recap

      • Recap of the sprint goals and key deliverables.

      • Review the sprint timeline and any critical dates coming up.

   2. Progress Updates

      • Update each team member or sub-team on their specific deliverables.

      • Review completed tasks and progress toward sprint goals.

      • Spot any tasks that are behind schedule and discuss how to address them.

   3. Challenges and Blockers

      • Discuss any challenges or blockers encountered since the sprint began.

      • Collaborative problem-solving to address these issues.

      • Adjustments to the sprint plan if necessary to overcome these obstacles.

   4. Resource Allocation

      • Review of resource allocation to ensure it's aligned with sprint's priorities.

      • Reassign of resources if needed to address critical tasks or bottlenecks.

3. Sprint Reviews and Retrospectives: These are conducted at the end of each sprint and focus on evaluating the accomplishments and processes of the team during the sprint.

5. Establish Start-Stop-Continue Retros

Empower team members to identify and eliminate inefficiencies through collaborative retros, where team members can reflect on which activities are impacting the bottom line, fostering a culture of continuous improvement and alignment with strategic objectives.

• Start: Team members brainstorm on practices or activities that they believe should be initiated to increase productivity or help you hit your goals.

• Stop: This segment identifies what is not working—things that hinder productivity or create unnecessary stress or conflict within the team. Campaigns that aren’t working but are still running. These are actions that need to be stopped immediately.

• Continue: This is the affirmation segment, where practices that are working well and contributing to the team's success are acknowledged and agreed to be continued.

This will give your growth team a fresh perspective and a clear understanding of their roles and responsibilities. Everyone on the team will now know what are the most important things they can do to hit growth goals. This meeting should include everyone on the growth team.

One great way to do this is to analyze the projects you have the team working on and suggest cuts there as well.

6. Prioritize Speed & Mental Agility

Why is speed even important for start-ups? Working at a startup is like being an explorer or scout. You are in constant search of finding things. Finding product market fit, optimizing acquisition channels, the right verticals to target, and iterating the right messaging to use.

Startup growth professionals must have a scout mindset. They nurture continuous learning, take calculated risks, and continuously update their map of beliefs about their buyers, channels, and products. Some signals of a scout mindset include:

• Actively admitting when they’re wrong

• Being willing to change their mind on a topic, and be public about it

• Actively seek criticism and challenge from others

• Keeping close to those who challenge your beliefs

You can use these thought experiments to evaluate where your team members are on the scout mindset spectrum.

• Double standard test: are you judging this situation by a different standard than you’d use for another one that you’re less attached to?

• Outsider test: how would you evaluate your situation if it wasn’t your situation?

• Conformity test: if other people (close to you) wouldn’t hold this belief, would you still hold it?

• Selective skeptical test: if this evidence challenged your opinion or beliefs — or your social circle’s — how much would you consider it?

• Status quo test: if your current situation was not the status quo, would you still choose it?

Posing these questions to your team members will put them on the spot and encourage them to develop unbiased and genuine mental agility.

The known and predictable realities of your business are often very small. The unknown however is vast and often where all of the big opportunities lie. And this is why speed is so important. Embracing speed allows great growth leaders and their teams to try things at a faster pace — shipping new campaigns, testing marketing channels, testing messaging variations, designs, etc.

The faster you can get to answers, even when the answer is failure, the closer you are to finding success. To discover the big opportunities for their businesses to grow.

Conclusion

By embracing agility, prioritizing strategic objectives, and leveraging the right cadence and talent, marketing leaders can unlock unprecedented levels of productivity and drive hypergrowth without sacrificing the well-being of their teams. 

If you have followed this model you have now:

• Built a growth-oriented culture with the right people in the right seats

• Identified the key goals you need to hit

• Identified the things you are doing or should be doing to achieve those goals.

• Eliminated every other thing that is a distraction to achieving those goals

• Eliminated countless meetings and check-ins, giving your team 2 full days back a week to just execute.

I have run this exact playbook with every team I have managed and have always been amazed at how much faster teams can execute, without burning them out.

You must reimagine the way growth teams operate and prioritize a growth mindset, efficient processes, and modern leadership. I’ve led growth at companies that have 10x-ed in a single year and those are the biggest keys.

While MQLs are good for summarizing directional growth in high-level reports targeting the C-suite or the members of the boards, it’s quickly becoming just another vanity metric hiding significant operational and decision-making nuances. Nuances which are vital to unpack in our current market landscape, where efficiency and sustainability are more important than ever.

MQLs' inability to distinguish between key lead traits — such as marketing source, intent signals, and buying stage — doesn’t just dilute your marketing channels’ insights, but also affects the sales team's operational efficiency, morale, and hiring plans.

And as serious questions arise about the true drivers of marketing and sales efficiency, a pivotal shift toward metrics that contribute to a faster and more accurate sales cycle is key. What metric can truly align marketing and sales once and for all? 

In this post, we’ll show you our heuristic to define pipeline, show you how your GTM team can prioritize it over MQLs, and why it’s key to foster cross-functional alignment between marketing and sales orgs.

The Inefficacy and Hidden Costs of MQLs

Before we get into the jist of it, let’s put down some definitions:

• Lead: a prospect that has had some interaction with your website or product. This can be just repeated website visits, interaction with your social posts, or content (e.g. downloaded a report, played with your ROI calculator, or reading a blog post).

• Marketing-Qualified Lead (MQL): a prospect that, given some intent signals gathered by the marketing team around your lead scoring (e.g. their company size, location, and industry match your score; plus, they did some significant interaction on your site), has the potential to be passed onto sales.

• Opportunity or Sales-Qualified Lead (SQL): a prospect that, given the intent signals gathered by marketing and the information collected by the sales team on the first meeting, is being marked as an opportunity on the CRM; and will be nurtured by both marketing and sales as it can turn into a customer. Opportunities can have various stages depending on your sales cycle. Also, multiple meetings or email interactions might be required for prospects to pass across each stage. For example:

  • Stage 1 Opportunity (Demo/Handraiser): a prospect that has made it clear that they want to speak to a member of the sales team and learn more about the product. This is a more specific MQL type with higher intent.

  • Stage 2 Opportunity (Requirements): the SDR collects the requirements from the prospect to craft the best proposal that matches their needs and budget.

  • Stage 3 Opportunity (Pricing): the SDR pitches the product and pricing package to the prospect, tailored to their requirements.

  • Stage 4 Opportunity (Negotiation): the prospect and the company negotiate the offer, involving more decision-makers on both sides until the deal is closed or not.

• Pipeline: the value of all the opportunities across all stages logged into the CRM in a given period.

So why is MQLs poison for marketing and sales teams alike?

This reporting mechanism impacts significantly the insights gathered by marketing teams, who feed their lookalike audiences and targeting algos contradicting intent signals; which will return lower conversion rates and shrinking ROI on channel performance. In the medium term, this can also lead to misleading channel optimization and/or budget allocation decisions.

The poisonous MQL reporting has serious repercussions on also the sales team, which similarly is not able to distinguish between leads with high or low opportunity potential. When you are just given MQLs, it becomes harder to distinguish between hand-raisers — prospects who actively want to see your product in action with a demo — and broader “sales meetings”. Hence, SDRs will scramble to find time to hop on a call with both, reducing their efficiency. In the medium term, this problem leads to critical friction and trust issues with marketing, ultimately dragging down the whole GTM and stifling growth altogether.

On an ops level, this can even lead to the false belief that, given the growing number of MQLs, more SDRs need to be hired to evaluate them, or more marketing budget needs to be deployed to compensate for the low MQL-to-opportunity conversion rate; significantly impacting hiring, CAPEX, and burn rate.

Moreover, MQL reporting and optimization usually come with cumbersome lead scoring and routing processes, which can further detract focus from sales efficiency by delaying lead activation and contributing to higher friction between marketing and sales. At HyperGrowth, we’ve seen this firsthand, when one of our clients was requiring more than 24 hours to ingest, score, and route leads to the sales team.

Benefits of Prioritizing Pipeline over MQLs

However, with fewer, higher-quality opportunities, and no more minutiae of sifting through low-intent leads, response rate and sales efficiency go up, and the need to expand your GTM team decreases. This is what happens when both sales and marketing focus on the value of the opportunities generated, also known as pipeline.

Ultimately, the definition of pipeline can vary between companies; above, we’ve considered it as a stage 1-2 opportunity beyond the first demo; a conversation that the sales team can confidently add to their CRM as an opportunity with the potential to be turned into a deal.

All these reasons make it paramount to define lead lifecycle metrics — as we did above — and accurately map the customer journey from initial contact down to conversion. 

Optimizing for pipeline metrics rather than MQLs gets leads scored and assigned more quickly, giving the right priority to activating hand-raisers. When time-to-score is low, it reflects the team is focusing on quality vs. quantity of leads. 

By repurposing our clients’ ops to focus more on pipeline, we’ve not only cut down the lead scoring, routing, and activation from 24 hours to 20 minutes, but we’ve also seen:

• More predictable conversion rates for both marketing and sales.

• Handed-off leads have an agreed-upon threshold to move to pipeline, and then to revenue.

• Which turns into significant cultural alignment and morale improvement on the GTM org.

When focusing on pipeline metrics, lead scoring serves also as a leading indicator, which aligns marketing and sales on what good and great leads look like. This overall leaner deal flow and opportunity activation, a more efficient budget allocation, and ultimately the opportunity to reinvest cost savings into meaningful distribution efforts like brand, product marketing, and compounding top-of-funnel activities.

Closing Thoughts — Redefining the Marketing-Sales Relationship

As B2B marketers, our goal is to feed the sales team with valuable opportunities and empower them to make an impact on the organization's bottom line.

MQLs distort that because it puts more work on the sales team’s plate instead of giving them value. Also, when focusing on MQLs, marketing's role in supporting sales is underscored, which creates dynamics of arrogance, frustration, and lower morale.

But with a focus on pipeline, marketing, and sales are finally aligned on the same definition of success. Marketing can optimize their budget, targeting, and lookalike for it brings to sales and its tangible impact on the company’s growth. Your sales team can focus on nurturing only higher-quality opportunities with the potential to convert.

How do you shift from MQL to pipeline?

1. Define all your lead lifecycle stages based on your sales cycle and customer journey. Combine qualitative and quantitative definitions, and strive to align sales and marketing.

2. Set shared goals across sales and marketing to focus on pipeline generation.

3. Optimize conversion events, lead scoring, and hand-off process for pipeline generation.

How does that look in practice?

We’ve put together a simple report where you can compare different campaigns and their impact on pipeline.

Get your template report

In the medium-to-long term, this alignment will have a significant impact not just in terms of net revenue growth, but also in terms of conversion rates, ROI, and team size; contributing to a much leaner and sustainable growth trajectory.

Yet, most teams are rushing to market without spending proper time and resources creating a proper ICP, let alone thinking through how to craft a targeting strategy and invest in related data. 

And few serious issues are coming out of this shallow approach.

• Inefficient Allocation: Without precise targeting, your marketing unit costs like Cost per Thousand Impressions (CPM), Cost per Lead (CPL), and Customer Acquisition Cost (CAC) will suffer. Essentially, you'll be spending more to reach less relevant audiences.

• Internal Trust Erosion: Ineffective targeting results in low-quality leads, breeding discontent and mistrust among your sales and revenue teams, who are going to complain you’re driving shitty or not enough leads like if it was 2015 (when you didn’t have targeting data).

• Losing Market Share: While you grapple with targeting inefficiencies, your competitors are likely eating significant portions of your Share of (SOM), Serviceable (SAM), and Total Addressable Market (TAM), leaving you with limited opportunities. And before you know it, you’re left with almost no one to target.

So how do you craft a targeting strategy that’ll keep your CAC low while driving high growth? And what are the targeting data and sources that will empower you to outcompete other players, and drive high-quality pipeline and conversations to your revenue team? And last but not least, once you do have all the right targeting data, how do you personalize your messaging and demand gen distribution to maximize revenue?

Read on to find out.

Formulating an Effective Targeting Strategy

To develop an effective targeting strategy, it's key to understand that commonly available targeting data might not suffice. Targeting data that you can buy on the main data platforms is not good enough because all your competitors can access it, and that data hardly scales. 

1. Start with Your ICP

But before getting into all the fun data stuff though, you must build a strong understanding of your ideal customer. A thorough ICP exercise involves pinpointing and validating the following traits.

1. Firmographics. This is the easy part. You need to list and segment in a table all the possible properties for the following traits — geographic location, industry, company size (by team, revenue, funding, user base), and business model of the companies you’re targeting. This is the initial “filter”.

2. Buyer Personas: This is where things get more interesting, and you need to narrow down your target.

   • Teams: First, understand which functional areas your ICP is working in — is it product, design, engineering, sales, finance, operations, or multiple teams? 

   • Roles: Then, you need to figure out the main roles. For each of these, you should write down their job title, seniority level, years of experience, average yearly budget, and sales cycle (eg. how long it takes for them to purchase and adopt a new SaaS).

     • Champion. Who uses your product daily, usually an individual contributor or mid-level manager.

     • Economic Buyer. Those who approve the decision to purchase your product and hold the budget for it. The larger your target organization, the more people might be involved in the decision — usually, the head of your target department, the VP of Finance/Operations, and/or even the CEO.

     • Technical buyer. Those who make a technical analysis of your product and will decide whether it’s compatible with the technical architecture of the organization stack, and release the engineering resources for the necessary integration (eg. via API, where applicable). This is usually an Engineering Manager, Tech Lead, or CTO.

3. Technographics. Then, you should identify which technology these companies are using that aligns with or complements your product. You should run this exercise from two points of view:

   • Org-wide technographics. These can be general work productivity tools that have cross-functional or org-wide use cases. For example, Slack or MS Teams for chat, JIRA for project management, or Notion and Google Workspace for documentation.

   • Team-specific technographics. These are specialized tools used by 1-2 teams maximum to carry out specific JTBDs at a team level. For example, product teams use Amplitude for product analytics; marketing teams use Mutiny for website personalization; HR/Ops teams use Remote.com for hiring and payroll management; and engineering teams use Vercel to streamline their development process.

Once you have a compelling understanding of the above, you can move on to crafting your value proposition messaging, which translates into a set of copy assets that span across:

• Jobs To Be Done. Your customer's Jobs-To-Be-Done (what they’re trying to achieve at work within the specific problem you’re solving), how they’re currently solving for this goal (eg. by employing other market alternatives), and the related challenges that stem from their current way, as well as the impact on their goals.

• Value Proposition. Mirroring the JTBD messaging, clearly articulate your product's capabilities (eg. what your product does to help them solve the current way’s challenges and achieve their JTBD), its differentiation (why it’s better and/or different than current alternatives), and the benefits (eg. the positive reasons why it impacts your JTBD).

If you have a hard time coming up with, or confirming the above, check out Wynter; it’s a great resource to capture nuanced insights about who your ICP is, their pain points and solution messaging, as well as how they approach the buying process.

2. Access Targeting Data

Once you laid out all your ICP traits, you can move on to purchasing various targeting data to effectively distribute your demand generation campaigns. Each data source offers unique insights that, when combined, can effectively enable you to target your ICP.

Firmographics & Buyer Personas Data: Zoominfo, Apollo, Clearbit, and Cognism

Platforms like Zoominfo, Apollo, Clearbit, Metadata, and Cognism are great market intelligence platforms offering a wealth of firmographics and buyer personas data. By tapping into their huge database, you can mine contacts that fit your company's industry, size, and roles, and even purchase detailed intent analysis over the sales cycle. You can then use these actionable insights to:

• Prospect, enrich, and score your web visitors and CRM contacts. These tools will automatically inject targeting data to help you define and create a list of contacts in your TAM, reveal your website visitors, enrich your CRM contacts, and even score your prospects. So you can identify and capture the best leads and drive only the highest-quality conversations.

• Personalize ads, forms, emails, landing pages, and chat experiences. You can also plug these traits into your demand gen channels to personalize their cross-channel experiences and make them highly relevant. So you can drive higher conversions at low costs.

Alternatively, you can also use Waterfall or Clay as an aggregator that will display most of the data from the vendors above at a fraction of the cost.

Technographics Data: HG Insights, Builtwith, 6sense, and Clearbit

Firmographic data are extremely accessible, that’s why you need to combine them with technographic data. This data provides insights into the technology and tools used by your target accounts, including information on when a customer started using specific software, sales cycles, contract renewal dates, and an overview of a company's tech stack. 

This data — accessible from platforms like HG Insights, Builtwith, 6sense, and Clearbit becomes extremely useful to refine your segmentation and competitor analysis and optimize your ABM and demand gen efforts. It’s instrumental in identifying customers who might be receptive to your solution and in understanding the challenges they work to solve​​​​​​​​.

Intent Data: G2, Bombora, and 6sense

Last but not least, intent data uncovers what your prospects are researching online, which products and services they are interested in, and the web content they consume, based on specific keywords or topics relevant to your products. Demand gen teams can use intent data to further pinpoint those prospects that are down in the conversion funnel and ready to buy, and as a result, avoid wasting budget on those that are not. 

You can split intent data into:

• First-party intent data. Data points you collect yourself through the product (eg. in-app actions) marketing (eg. website actions, social, surveys, forms, etc.), and sales (eg. CRM)

• Third-party intent data. Data collected outside of your owned properties. Think actions and interests publicly shared across online publishers, websites, and apps, like site visits purchasing history, and more.

G2's, Bombora, and 6sense are great third-party intent data platforms that leverage account identification technology to nearly double the match rate of buyer intent. These platforms enable you to create dynamic audiences and ad-targeting workflows that match your ICP and are triggered by specific buyer behaviors on platforms like G2. It helps in uncovering prospective accounts, automating high-quality pipeline creation, and targeting high-intent accounts, thereby facilitating highly efficient revenue growth.

Scraping data to create your own signals: Keyplay

Third-party data like firmographics, technographics, and intent data will get you only to a point. Remember, this data is also accessible to your competitors and hardly scales, so you won’t make targeting your competitive advantage with just this. 

To go the extra mile, you have to add your own first-party data. And unless you have a dedicated customer research team and extensive data collection, you need to get creative and brainstorm which first-party data you need that fit your unique ICP. You can then use custom your scraping setup through public APIs (eg. via ScrapingBee, Simplescraper, or ScrapeHero) or through one of my favorites, Keyplay, where you can leverage both existing and custom first-party data signals to further enrich your target account list. I’m a big fan of Keyplay and use it extensively with my clients.

Connecting everything together: Clay

Once you have everything laid out, you can connect all your targeting data together. This is where the magic happens. Clay is an all-new fantastic SaaS that lets you aggregate a plethora of data from different sources together while enabling a very novel way of getting at data that would normally not be accessible.

3. Personalizing Demand Gen Campaigns with Data

To effectively reach your best ICP, you should connect your targeting data, and inject it across your demand gen channels like LinkedIn, Meta, Google, display, landing pages, and email. Combining firmographics, technographic, and intent data, you’ll get the clearest, most complete picture of your ideal customer, empowering your demand gen teams to drive higher revenue at lower costs.

To help you in the process, you can use SaaS like:

• Metadata to enrich and orchestrate your campaigns across multiple advertising channels — both for prospecting and retargeting. Their Metamatch targeting platform is unlike any other in the industry and is very reasonably priced.

• Apollo or Clay to craft highly personalized outbound emails that generate responses

• Mutiny to personalize your landing page messaging and content based on your ICP

• Drift to display and customize chat messaging to route visitors depending on their interactions

Closing Thoughts

To grow conversations and pipeline effectively while managing CAC and outpacing competitors, investing in unique targeting data becomes paramount. By taking the time to delve into your ICP and brainstorm creative, untapped data sources, you position your demand gen campaigns to show up to the right audience at the right time.

Leveraging these diverse data sources provides a rich tapestry of insights essential for B2B SaaS. It enables more targeted and effective demand gen and demand capture strategies, leading to better customer engagement, higher conversion rates, and ultimately, business growth.

Whereas the community is mostly aligned on the importance of lifecycle marketing, things might get hairier when it comes to execution. From our own experience owning lifecycle marketing at several early-stage startups but also at scale-ups such as Opendoor and MasterClass, we’ve learned most teams fail to realize that a successful lifecycle must align engineering and marketing. To properly execute lifecycle marketing, you don’t just need a full-fledged plan, you also need the right tooling, data, and fit within the broader software architecture to bring it to life.

Our advisory experience shows many startups under index on making the right Lifecycle Marketing Software (LMS) investment, and that has a serious impact, even on your path to PMF and early scale.

• User experience. Emails, push, and retargeting define most of your out-of-product experience, actively building your habit loops. Failing to select a platform that effectively delivers on that means failing to build half of the retention you need to reach PMF.

• Financial investment and lock-in. Most sophisticated LMS platforms are sizable investments starting from $10-15,000/year for enterprise-grade solutions, mostly priced around the number of customer contacts you can store within them. If you lock yourself into the wrong platform or make too big of an investment, you might regret it. This is especially hard as you’ll need to estimate how much, and how fast, your contact list is going to grow; but also when you’re migrating across LMS platforms there is lots of customer and performance campaign data that is hard to migrate and you can’t just replay post-migration. All of this adds to the financial investment and trade-off.

• Technical dependencies. When approaching lifecycle marketing, you think you just need to send your customers some emails. In reality, LMS implementations eventually include a nontrivial technical component.  We recommend thinking through key lifecycle marketing use cases and doing a proof-of-concept implementation as part of vendor evaluation. At a minimum, this will ensure that your core retargeting campaigns will be fully supported by your vendor. At Opendoor we nearly canceled our LMS platform after discovering particular promised features were underbaked and ensured we had adequate workarounds before proceeding.

In this post, we’ll guide you through HyperGrowth Partners' very own framework to select, implement, and manage your Lifecycle Marketing SaaS Platform, as this is one of those investments you don’t want to regret.

1. Defining the core lifecycle marketing use cases

To pick the right LMS we need to first define what a successful lifecycle marketing operation is supposed to do. In concrete, lifecycle marketing should trigger this set of campaigns. 

Each campaign consists of a sequence of one or more emails and push notifications that aim at getting users back into the product on a recurring basis. How to structure these campaigns in detail might be a story for another day, however, the table below might provide some food for thought.

At Opendoor, one of our key campaigns was the abandoned cart to keep users up to date on the value of their houses, which we'd send every week. To make that happen, we had to tailor it based on who got which email when and pipe the pricing data into the email pulled from our DB. 

Or take our MasterClass weekly recommendations email, where we suggest what other courses you may want to check out, based on event requirements tailored based on an internal data science model.

2. Dissecting the LMS core capabilities 

Once you have an overview of your lifecycle marketing campaigns, it’s essential to define the core use cases of an LMS — what it does and when to use it. For the purpose of this exercise, we’ll distinguish between:

1. Table stakes features. Basic, indispensable capabilities are required to carry out a successful lifecycle marketing operation. These entail:

   • Design & messaging. Writing, designing, hosting, sending, and tracking messages — across at least 1-2 channels across email, push notifications, and SMS — depending on your business.

   • Automated workflows. Create automated messaging sequences, depending on the actions and behaviors that you want to encourage throughout the lifecycle (eg. activation, engagement, retention).

2. Advanced features. Capabilities that can sensibly enhance not just the user experience, but also the robustness of the backend and the effectiveness of your marketing team. These include things like:

   • Advanced segmentation. A more sophisticated messaging journey builder that lets you target users based on advanced customer event triggers, including things like event frequency, advanced delays, and channel filtering. For example: “Send this only to people who started checkout twice, on two different days, from two different channels”.

   • Advanced design templates. Think reusable email template components like headers, footers, etc. to reduce custom design iterations and streamline UI consistency across your journeys.

   • Sophisticated A/B testing. Not just for testing subject lines or email copy, but entire journeys in a way that optimizes for true business metrics such as average basket value or revenue.

   • Data and tooling integrations. Connecting arbitrary API endpoints in the middle of specific journeys to capture event data and feed them, for example, into Meta Ads retargeting audiences.

   • Data governance. Tooling that allows you to see which data fields are used in which journeys and mark certain events or user traits as deprecated, increasing the efficacy and reliance of the autocomplete process.

   • Permissions & approvals. Enterprise-grade granular permissions to manage team access and GitHub-like review workflow to approve changes before they get deployed.

   • Cross-channel support. Broader messaging capabilities across additional channels where you can re-engage your customers, such as in-app modals, Slack, or other OTT platforms (eg. WhatsApp, Telegram, Messenger, etc.), direct mail, etc.

Working back from your requirements is key to making the appropriate investment. Again, the below list might not be exhaustive, but we’ve found this to define the lay of the land. Also, one thing to notice is that:

As market competition increases in both pace and intensity, the pressure to deliver an above-average lifecycle marketing experience is high, pushing advanced features to table stakes quicker.

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3. Picking the right LMS based on your company stage

Pre-seed stage — code + email delivery vendors

In the early stages of your organization, the attention is normally on building an MVP and getting initial customers; email is on nobody’s radar when you have a product to build. However, as we’ve seen above, some emails and pushes are part of the core user experience even at the MVP stage!

Because these emails must be sent, the scrappiest (quick, easy, and convenient) solution might be to have your emails triggered directly from your back end through some minimal engineering work that connects directly to your software architecture. In our experience, Django, Rails, or Node all do a perfectly reasonable job of creating and hosting HTML email templates directly in your code base. You could then connect your templates to a simple email-sending service like Postmark (our favorite!), Twilio’s Sendgrid (also great!), Mailgun, or AWS’ Simple Email Service. 

This option should give you baseline capabilities such as email firing and basic and domain health reporting; however, everything that relates to subscriber list segmentation and email sequencing, as well as any email template design update, will need to be executed through engineering work, which could also slow initial product marketing efforts down. 

Seed stage — lean LMS platforms

As you start releasing your product for beta, email becomes one of your first channels to activate and nurture your waiting list.

Building a relationship with your early customers is key, and email will be your primary channel for that — ensure you don’t get bogged down by technical dependencies!

When the need of product (marketing) teams to repeatedly iterate on email template design or start more articulated email sequencing, you know it’s time to move on to the next phase.

At this stage, we recommend signing up for a proper LMS platform, which is ultimately the go-to solution for ensuring flexibility in design and marketing, as well as pace of execution. Keep deferring to manual engineering work, or even teaching a non-technical person to do the manual job, are typically net negative resource allocations.

Before we dive into the details, a clarification on the category naming and its use case.

• LMSs are not CRMs. As outlined above, these SaaS include email list segmentation and subscriber management capabilities, but that doesn’t make them CRMs. CRMs like Salesforce, Hubspo, or Attio are platforms geared for B2B, high-touch customers, which provide much more tailored comms capabilities compared to LMS which are more designed for automated, one-to-many messaging. 

• LMSs are not for outbound. Also, LMS heavily differs from outbound email outreach SaaS like Apollo, reply.io, or SalesLoft, which are usually used by B2B sales and revenue teams to scrape and generate business leads and pipelines. On the contrary, the LMS job starts when the customer is already in the ‘customer’ lifecycle, which usually starts post-signup.

Our favorite vendors include customer.io (our top choice by far!), Drip, and Ortto, as well as newcomers such as Loops or Dittofeed. These solutions are usually priced more flexibly with monthly plans starting in the region of $100/mo — their pricing model works by the number of customer contacts with a threshold starting at 5,000 contacts; hence affordable up to series A.

Implementing these solutions requires a little bit more thinking, but it’s important to start small, keep it lean, and don’t over-engineer it. The key things to focus on are:

• Track customer events. Ensure you track all critical customer lifecycle conversion events (eg. what customers do in your product) through your Customer Data Platform (CDP) like Segment — they include `Signup Started`, `Account Created`, `Feature Used`, `Checkout Started`, or `Purchase Completed`, etc. Again, don’t over-engineer your events — ensure your event tracking plan is as lean as possible especially if you’re just starting out. You might already be tracking these through your product analytics tool like Amplitude or June; if so, they should appear on your LMS as soon as you connect it with your CDP.

• Build user profiles. Sending the right emails doesn’t just require knowing about what customers do with your product, but also who they are. Don’t forget to capture critical customer dimensions like:

  • Full name. Include a function that helps you split first and last names so you can address customers just with their first name (we’re not in the 1800s anymore!).

  • Email preferences. Another must-have is to ensure you get consent for sending marketing emails and allow them to manage the related preferences on a dedicated page of your LMS (all of the above should provide an out-of-the-box one). 

  • Created at. The timestamp of when the customer profile was first seen in the product (eg. signup date).

  • Key demographics. If you’re in B2C, you might want to capture and store traits like gender, age group, income bracket, etc. 

  • Key firmographics. If you’re in B2B, you might be more interested in capturing their job title, department, seniority level, or company-related information like industry, number of employees, revenue, etc.

  The goal is to create a single user profile serializer — a JSON code that captures and stores interesting customer traits that can be used for segmentation and targeting purposes. 

• Bulk update your LMS user profiles. Once you have your profile done, you can run a bulk update of your LMS user profiles, especially when:

  • Users perform critical events like creating an account or making a purchase — hardcode these critical events in the user profile as properties

  • Or every night, for all users in bulk. This alternative is easier than the above, and you can eventually move it to your data warehouse.

• Keep transactional emails in your codebase. You might get tempted to also move transactional, product-related emails (eg. password reset, receipts, etc.) to your LMS. At this stage, we recommend to keep them separate. Because these are critical UX elements that require fewer updates and/or iteration, it’s important to retain control over them and avoid migration efforts.

Growth stage — enterprise-grade LMS

Eventually, you’ll run into the limitations of your first system. Typically, this will feel like dealing with:

• The kitchen sync. Your LMS will become clogged with duplicate and redundant user events and traits, creating confusion, and dependencies, and slowing things down. Marketers won’t know which fields to trust, which turns into buggy emails like “Hello f_name” being sent.

• Too many cooks. Another common issue is having too many cooks in the kitchen, where everyone has access to emails and related code. Email template breaks, messaging, and design guidelines aren’t followed, and lines get crossed. Startup life, hey!

• Very sophisticated recipes. Your marketing team starts asking things like: “Let’s send a maximum of one email per day based on their time zone, prioritizing campaigns based on custom user traits,” or “Let’s include tailored product recommendations in our emails that are based on previous purchase history”, or even better “Let’s trigger this resurrection email with a custom incentive that is fired based on the data science team’s churn model”.

When requirements like this start landing on your table, you know you’ve graduated to the big leagues, which is spoiled for options; we love the most modern solutions like Iterable, Braze, and Klaviyo (for e-commerce companies), but there’s also a handful of more legacy providers that do an enterprise-grade job like Market, Pardot, Salesforce Marketing Cloud, and obviously Hubspot Marketing Hub.

Some of our recommendations that no SDR of these companies will ever tell you when pitching your products are:

• Ensure you’ve hired a Head of Lifecycle Marketing. At this stage, lifecycle marketing becomes a team with a capital T — a structured organization with 3+ people who need proper tooling to get their job done.

• Minimize LMS access. Remove access to the LMS SaaS for everybody except for the lifecycle marketing team members. Until things are more organized, everything is going through them.

• Plan for the migration. When graduating for a better and bigger LMS, you need to factor in a migration process — involving user profiles, design templates, campaign workflows, related data, and everything in between — and ensure that data, engineering, and design support will be provided in the transition.

Implementing or migrating to this type of LMS is no easy fit. As mentioned before, it’s a cross-functional effort that can require up to a quarter.

Upgrading to an enterprise-grade LMS will require you to clean up the events data kitchen sink. Because this cleanup work is hardly prioritized, you’ll need to be able to point to previous incidents and related negative effects on the business (eg. churn). This might require you to introduce data governance tooling like Segment Protocols or Avo that will enable you to enforce pre-agreed events and properties data schemas and proactively trash events outside of it. Specifically:

• Customer events. Start proactively filtering the ones that explicitly go to your LMS

• User profile updates. It’s time to move these to an external data warehouse Job, or use a dedicated reverse ETL tool like Census or HighTouch) 

Upgrading to these systems is not just a good excuse to reorganize your data strategy, but also to migrate your lifecycle marketing assets email-by-email and workflow-by-workflow. These migrations are often a fraught and risky process that many companies avoid especially if their existing tool is enterprise-friendly.

Late stage — open core / open source

Congratulations! If you’re reading this paragraph, you might be a decacorn! Are you someone from Uber, Airbnb, Doordash, or Pinterest? Eventually, you’ll run into a degree of workflow customization that even enterprise-grade LMS can’t natively support. And even if you’re a decacorn, you can’t get them to build it for you!  

At this stage, when companies typically get to 500+ engineers, more and more capabilities start being brought back in-house to cater to a more advanced degree of security, scale, and personalization, so they more cleanly fit within the broader software architecture made of analytics, experimentation, compliance, etc.

In this context, you might have an even more structured lifecycle marketing organization, with very specific requirements that span well beyond data-driven journey personalization and touch upon content and messaging localization and transcreation, with incentives and sequences that are highly aligned to the multiple regions you operate in.

Depending on these tailored requirements, what most lifecycle marketing organizations do is rebuild specific modules of LMS capabilities as custom in-house software, even with the dedicated support of an internal Marketing Tools Engineering team.

Some focus areas to keep in mind here are to align your cross-regional and -cultural lifecycle marketing organization to deeply understand which capabilities need to be customized and rebuilt in-house, and which ones can stay off-the-shelf on the current LMS.

In 2023, some companies have been pursuing an open core/open source strategy, building LMS  platforms that can be forked into both hosted modules of capabilities and some others that are fully hosted and outsourced. This is still a recent development, but we believe it’s a great starting point for a future where LMS software becomes less proprietary and easier to iterate on based on specific company requirements.

Closing thoughts

Selecting a Lifecycle Marketing SaaS should be a thoughtful process, echoing the company’s stage, needs, and goals. Starting with foundational platforms and moving through to more advanced systems as the company evolves, enables sustainable growth and efficiency. 

Whether the company is at pre-seed, growth- or late-stage, the essence is to align with the company’s requirements and structure and grow from there. The right LMS acts as a catalyst for habit-building, retention, and growth, so don’t under-index its impact, but neither its implementation nuances and dependencies.

In a world where we’re overwhelmed with SaaS choices, it’s not about having a myriad of features but about having the right ones, aligned with your company’s stage.

The current market downturn is making fundraising and growth more challenging than ever for consumer businesses. The main reason? Arguably, a lack of differentiation, not only in terms of product and positioning but also in distribution.

Starting with the usual suspects, performance marketing, especially paid social, is not as economically sustainable as in the 2010s. Channel saturation and competition have increased CAC beyond financially sustainable levels, desensitizing users to every kind of messaging. What’s worse is that the race to advertise on emerging channels like TikTok is getting frantic, shortening the channel’s lifecycle, compounding saturation, and favoring winner-take-all dynamics where incumbents with bigger budgets win.

Talking about content & SEO, these are traditionally expensive channels to scale without  UGC dynamics. Yes, AI is about to unlock massive cost savings on content creation. Still, until we solve issues like content hallucinations, we’re yet to see the potential of this medium to emerge as a new growth standard.

Last but not least, referral programs do not apply to every product. If your product doesn’t have high LTV, is not intrinsically shareable, or doesn’t have network effects, it might be hard to engineer this type of distribution. Even when you have the above, it’s hard to scale referrals beyond the early stages of a company. Take Dropbox or PayPal as examples, products whose early consumer growth revolved around sharing features, turbocharged by their referral programs. Referrals are great for early growth but less so at the scale stage when virality makes the referral incentive less ‘appealing.’ 

These limits are affecting consumer growth marketing and VCs' appetite, who in recent years fundamentally refocused on profitability as a quasi-requirement for signing term sheets for both early- and growth-stage investments.

The PLG miracle — only a B2B thing?

At the other end of the industry, B2B gained a significant leg up with product-led growth. In this motion, cross-functional teams use product, content, outbound, and community strategies to empower leads to self-qualify, drive virality (internally and externally), and scale acquisition at low CACs.

PLG has been a game changer for companies like Figma, Slack, and Notion, who grew their top-of-the-funnel in a true “consumerized SaaS” fashion with a robust B2C-like traffic engine that feeds into their B2B machines.

Switching back to B2C, we can observe early applications of this logic. Think Duolingo’ ‘world-class gamification —  a great combo of cutting-edge content, social incentives to share, and rituals to gather around in a community —  or NerdWallet’s content& SEO strategy, which created a meaningful edge over their competitors. 

We say early applications because, despite these innovations, these orgs haven’t leveraged the full potential of high-scale, low-CAC channels, as B2B did with PLG. At HyperGrowth Partners, we believe they can — and we believe this approach can effectively overcome the limitations of traditional growth channels.

Introducing PCC — the PLG of B2C

What would happen if consumer growth teams intentionally leveraged all three pillars — product, content, and community — in tandem?

How? At a high level, these three pillars constitute a compelling full-funnel growth strategy across acquisition, engagement, and retention, where each pillar creates its specific growth loop that augments each other.

1. Content

The first step to embracing the PCC model is to set up a content acquisition loop that grabs your audience's attention by entertaining and educating your audience about your value prop with an authentic, unique narrative. Earlier in this post, we mentioned the limits of traditional consumer content. To effectively stand out and overcome these bottlenecks, your content must have:

• Bit-sized formats. You should optimize for short, hyper-consumable content formats like 15- to 30-second videos or shareable quotes. This should sensibly decrease production costs and increase scalability.

• ‘Surprising’ buckets. To effectively stand out from the crowd, your content buckets should optimize for novelty, which triggers a neurochemical reward for the audience. For simplicity, your content buckets can be grouped into:

  • Funny: something that makes your audience smile. This can work with any consumer brand and product, no matter how serious or fun your use case is.

  • Interesting: something that makes your audience curious and provides a snippet of valuable knowledge that will educate them on topics adjacent to your use case. This is especially relevant for personal development products like health and fitness and wealth-related products like fintech.

• Memetic message. Bonus points to nail your surprise level; tap into the memetic culture of your audience. Every generation shares cultural “touchstones” of pop culture. Think movies, songs, fashion, trending news, and the people starring in them, like characters, actors, singers, producers, politicians, and entrepreneurs. Look for characters and scenes that recently went viral in your audience, and adapt them to your own set of problems you’re solving, use cases, or larger industry topics.

• Native production. Most brands still invest so much time and resources in writing pristine, engineered copy and videos with strong brand aesthetics, only to realize that this is what gets mostly scrolled through on social feeds — massively increase your creative ROAS! The reality is that UGC-produced ads in TikTok, Reels, and podcasts are becoming much stronger formats for audiences to discover and buy consumer products. Why? At a high level, because people buy from people, not from brands — even the average consumer doesn’t like to be sold directly. At a deeper level, it’s because of:

  • Problem mapping: users better understand what products do and how they can help them when the direct language that they understand and use.

  • Identity signaling: users can relate to who explains the product to them either because their peers to them (eg. nano or micro creator) or because they aspire to be like them (eg. macro creator or influencer).

  • Familiar context: when users browse Reels and TikTok, all they see is cute dogs, hot models, breathtaking holiday views, (aspiring) influencers, and movie memes — 90% of them shot with a selfie. Great content means leveraging this familiarity — fit in to stand out.

    

2. Product

Once users are drawn in with the content, the product UX/UI must quickly confirm their expectations by providing a delightful, seamless, and intuitive experience that leads them to the Aha moment as quickly as possible. 

This means the NUX — the New User Experience — has minimal taps for people to sign up, understand the benefits, and get to the first key outcome. Regarding NUX, it’s not a joke that “speed is everything.” However, it’s important to balance it with empathy, understanding, and the outcome of the aha moment.

Making a good impression is not enough; consumer apps must be built for strong retention and engagement to survive the growing competition of apps on our devices. 

To do so effectively, it’s critical to inject game-like mechanics across your single- and multi-player use cases to give users a sense of continuous progress, accomplishment, and healthy competition, which helps to keep them engaged and coming back for more. In 2023, gamification is non-negotiable.

• Streaks to remind users of progress made for continued product use. 

• Quests as mission-driven tasks to encourage specific feature activation and retention.

• Levels, badges, and achievements to nurture retention breadth (eg. daily tasks to come back daily) and engagement depth (eg. earn badges to level up to graduate from casual, to core, to power user).

• Points and in-app currency to redeem continued usage against benefits related to the aha moment or game-like mechanics (eg. streak freeze, XP boost, etc.).

• Profiles, leagues, and leaderboards to drive users against each other in a healthy, competitive environment, engage socially, and display their achievements.

• Completion sounds and haptic feedback to complement the individual and social with physical feedback that cements their habits.

Needless to say, Duolingo is among the leaders in gamification in consumer apps. But also consumer giants like Headspace, Waze, Spotify, and Airbnb are incorporating similar elements to gamify their experience.

3. Community

Gamification doesn’t just drive engagement and retention across demographics and use cases but can also help build community. At the middle and bottom of the funnel, a community loop can cement belonging and habit loops that further nurture engagement, amplify word of mouth, and even reduce customer support costs.

When you provide your users with a space and a set of incentives to connect, share tips and tricks, and solve problems together, you create a sense of belonging and shared identity, effectively increasing switching costs for competitive alternatives. Remember, as community expert Greg Isenberg mentioned: 

Community-based or community-enhanced products are machines that compound tremendous growth with the aforementioned channels. 

1. Content. Build a (free) audience to grab people’s attention.

   • Social (eg. Twitter, Instagram, TikTok, etc.)

   • Blog, Newsletter & Podcast

2. Product. Drive the audience to your product/app or alternatively to adjacent free community features.

• Job board (eg. Pallet). Great for professional or personal development apps.

• Store (eg. merchandising), ideal for monetizing fandom.

• Info products (eg. books, tools, checklists). Think longer-form educational content.

• Q&As (eg. Zoom, WhatsApp) to give product feedback or just hang with other users

• Live performances (eg. companies-hosted gigs, webinars, or other sessions)

3. Community. Convert your free community members into product users or more active members. Most of these can be layered or are part of the aforementioned gamification strategy and can be baked directly into the product features.

   • Identity: usernames, avatars, memes, and shared aesthetics

   • Community board: Reddit, Discord, FB Group, Skool, WhatsApp

   • Quests & incentives: missions, tasks, and referrals

   • Reputation system: roles, levels, badging, and memberships

   • Loyalty program: rewards, incentives, and special access

   • Online/IRL meetups: 1:1s, workshops, Q&As, AMAs, office hours, etc.

   • Happy hours (eg. Notion class notes, Loom recorded sessions)

Keep in mind that building community is one of the hardest endeavors in tech and is not a straight line. The CMX Engagement Cycle is a great framework to get started.

1. Define community identity (eg. handles, avatars, vocabulary, roles)

2. Earn community trust (eg. by providing value upfront, for free)

3. Encourage participation (eg. games, challenges, quests, promise of rewards)

4. Give recurring rewards (eg. social, financial, knowledge, time, mastery, joy, etc.)

Closing thoughts

Does the current market downturn mark the end of performance marketing? Of course not, but paid ads can no longer serve as a primary growth driver to scale consumer businesses, nor a competitive moat.

What B2B has done with PLG is admirable — growth teams are slowly but surely, breaking down their silos and blending their skills into coordinated product, marketing, and sales efforts that resulted in high-scale, low-CAC growth machines. 

Truth be told, these strategies don’t have to be just a B2B thing. Using the PCC model, consumer businesses can be more intentional about aligning their product, content, and community efforts to drive high-scale, low-CAC growth, which creates a competitive moat and draws in funding, particularly for use cases that revolve around personal development, like fitness, wellness, fintech, and collectibles.

But why is that? And now that AI has pervasively entered our lives, how will this affect growth strategies like personalization and the stacks and teams used to execute them? To make it worse, Martech is exploding. Thousands of alternatives and continuous bundling and unbundling of products make selecting, building, and maintaining a growth stack impossible.

So where is the market headed next? What strategies, stacks, and team setups will make the winners of the next cycle led by AI? At HyperGrowth Partners, we’ve operated at the epicenter of B2B SaaS, growth, and MarTech for the last two decades.

This two-post series will unpack which growth strategies, teams, and stacks will make the next generation of hyper-growth companies. 

The Cyclical Evolution of Growth Marketing

To understand how the next market cycle affects growth strategies, teams, and stacks, let’s walk down memory lane and explore the last four growth marketing cycles. Each lasts approximately 7-8 years and is driven by disruptive technologies that define the period's strategies, teams, and stacks. Please note the cycles identified here reflect our take on the market and might not be exhaustive (chart inspired by chiefmartech.com).

• 2000-2007: Cloud Computing, Single-use-case SaaS. Cloud computing revolutionized how software was delivered to businesses, dismantling on-premise (I still remember selling business software in…boxes 🥲). Most companies were providing single-use-case solutions, with Salesforce and Hubspot leading the way. Back then, there were mostly top-down sales teams focused on SDR-led outreach and digital marketers operating the newly launched Adwords (I was one of them at Apple!). There were no such things as automation or personalization, as each integration needed to go through the infamous IT.

• 2007-2015: Mobile, Social & SaaS Bundling. The following cycle saw the rise of smartphones, mobile apps, and social. Single-use-cases SaaS slowly evolved into platforms that bundled multiple products ‘all-in-one’ — Hubspot did it for marketing automation, Zendesk for customer service, and Salesforce for sales. Inbound marketing, developed by Hubspot, and digital advertising, led by Google and Facebook, became new popular growth strategies on top of outbound and SEO, growing the roster of go-to-market channels. Also, despite seeing the first cross-functional growth teams at Facebook,  Hubspot, and Uber, marketing technologists were still the standard in this period.

• 2016-2022: Data Analytics & SaaS Unbundling. Mobile and social enabled businesses to track various data points across devices and apps, paving the way for data analytics disruption. Segment, Amplitude, and DataBricks emerged to help businesses manage and analyze large datasets. Especially CDPs like Segment enabled data to flow across a myriad of micro-SaaS — each handling a specific use case — igniting the explosion of MarTech unbundling (which grew 429,000% over the previous cycle!!!) and modern growth stacks as we know them today. According to Gartner, software spending was up to $4,800 per employee per year in 2020! These modular data-powered growth stacks enabled advanced and automated growth strategies like personalized outbound at scale. And with the birth of Reforge, growth marketing became a popularized practice and an in-demand mindset in any organization.

Why data? We need to know our customers!

Before stepping into the future and seeing what growth marketing will look like in the age of AI, someone might ask: Why all of this in the first place? Why would every hypergrowth startup want sophisticated growth stacks and tons of customer data points to deliver personalization at scale?

As marketers, we aim to engage buyers, capture attention, and drive action. But with the growing volume of messages generated by growth automation, our poor buyers became increasingly desensitized, eventually disregarding ~96% of their ads.

I often propose this thought experiment. Think of your physical mailbox. You get mail SO frequently that out of ten letters, nine are likely ads you will trash without reading them. Now imagine the tenth envelope. It has a handwritten return address and a clumsily stuck stamp. These features utterly convince you it’s from another person. How likely are you to trash that one without thinking of opening it? Take a second to think about it. 

Zero. If you are convinced it is from a human and not an ad, you will open it every single time. People buy from people, not from businesses, even in B2B.

Why is that? It’s because of the powerful combination of curiosity — ”Who sent me this letter?” —  and reciprocity — ”If someone went through the effort of handwriting me a letter, I should probably at least return the favor and read it”.

Before being buyers, we are all people. And as a deeply social species, we crave empathy, reciprocity, and social liking. And that’s what you feel when you find a hand-written email that stands out.

As marketers, we’ve been using technology all along — cloud, mobile, social, data, and now AI — to cut through the noise and deliver personalized reciprocity at scale because that’s what drives your conversion rates. The data analytics market cycle made it clear — the SaaS stacks and tools we use are all in service of creating a one-to-one connection with our buyers. Otherwise, why collect customer data at all?

However, what goes up must come down. Like every cycle, successful growth tactics become obsolete because they get overused, and buyers get annoyed and ignored. It happened with retargeting, and now it’s happening with enriched emails. AI is adding a leg up in this cycle.

And that’s where the true top 1% of growth teams stand out. They’re at the bleeding edge of the growth strategy/stack lifecycle. They create the bleeding edge of growth strategies by creatively experimenting with new combinations of tactics and technologies to unlock new levels of personalization and reciprocity. The goal is to build a competitive moat before these tactics get saturated.

2023-2030: The AI-powered cycle

Growth strategies: AI-powered, hyper-realistic personalization

So what will happen in the next cycle? AI makes one-to-one relationship-building not only hyper-personalized but also hyper-realistic. In the previous cycle, customer data and CDPs powered tactics like enriched emails, custom retargeting, or Loom videos with buyer’s names written on a board. These worked for that time, but the most tuned-in buyers could discern they were not ‘real’. Thus the desired reciprocity effect quickly disappeared.

ChatGPT and Bard will be able to gather many more data points than current CDPs, scouring the web to find contextual information and deliver messaging that matches people's demographics, psychographics, firmographics, and more — all in real-time and at scale. This is where the true 10x growth strategy opportunity is and where the top 1% of growth marketers should invest.

In the near future, we might see buyers getting so many AI-generated messages that ’push marketing channels’ might decay in favor of ‘pull’ ones, where buyers discover and evaluate products via centralized chat UIs à la ChatGPT. But we’re not there yet, and growth teams should invest in the next big opportunity before thinking too ahead of the curve!

If you’re ready to drive hyper-realistic personalization, contact us at HyperGrowth Partners. We have decades of experience implementing growth strategies at the bleeding edge of the growth tactic lifecycle.

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Growth stacks: AI-generated, Ambient Stacks

Which stacks will enable these bleeding-edge levels of hyper-realistic personalization? The ones that will:

• Centralize and orchestrate data upstream. The explosion of data and touchpoints is forcing the bundling of customer data upstream in the value chain. Data governance and orchestration companies like Census, Segment, and HighTouch drive this trend via their CPDs and (reverse) ETL products. Successful stacks must be able to track and analyze tons of data points from disparate sources and enrich them with third-party data by default. Also, observability must ensure data is clean and reliable at all times. Because clean and proprietary data will make the biggest impact in training AI, it’ll become a marketing channel per se and one of the most important in building a competitive moat.

• Unbundle tooling downstream with AI. The MarTech unbundling will likely continue as generative AI will give birth to a long tail of AI-powered micro-SaaS automating downstream use cases like ads, emails, chats, content, SEO, and more! CDPs and APIs will feed data to AI, which, thanks to composability, will progressively take control of connecting the dots among these tools at the point that new campaigns and tactics will be first suggested, then created automatically in the background, without teams even realizing it. But we’re not there yet. In the short term, we’ll still be using CDPs and Zapier to drive custom downstream personalization — this is where growth teams should invest now.

Growth Teams: AI-powered Growth Ops Generalists

Since the rise of the first cross-functional growth teams at Facebook, Hubspot, and Uber, the lines between core company functions — marketing, sales, product, and engineering — have been increasingly blurring. No code has democratized engineering to non-technical users, and buyers' complex demands have forced teams to collaborate closely and at faster rates.

Also, the explosion of data, APIs, and automated tooling has been driving progressive operationalization of each function to the point that each one has an ‘ops’ team — marketing ops, sales ops, rev ops, dev ops, and so on and so forth. 

These two forces, operationalization, and cross-collaboration, coupled with AI, call for a more holistic approach to lead the growth of the business. One where a small, nimble team has the big picture of the whole funnel, strategy, and stack.

Because AI-powered stacks will be full funnel — closing the loop from acquisition to won deal, feeding back to the top of the funnel, marketers in the medium term will become more and more system operators. We’ll respectively see:

• Fewer specialists. We’re already seeing large specialist teams shrinking due to the recent tech layoffs. AI will likely push this trend forward, reducing the number of full-time marketing specialists in each area and relying more on ad-hoc expert advisors to drive channel-specific strategies. Organizations are also moving away from channel-specific marketers like paid and SEO because, as a result of AI, they’re becoming more and more algorithmic and automated. This makes it easier to justify investing in an AI-powered SaaS platform to do the job instead of a full-time team. If anything, it’s worth investing in specialists with no SaaS-based algorithmic solutions yet, like in PLG or outbound.

• More cross-functional generalist. As a result, there will be a convergence of small teams of growth operators. These are not mere generalists but “Internet plumbers” that deeply understand each stage of the entire funnel, know the latest technology that can be plugged into each of these and can stack and connect each block together. Like plumbers, they understand how to pipe data into different SaaS tools to unlock personalization and reciprocity each step of the way. These people will have a specific mindset, strong business sense, notions of product, engineering, marketing, sales, and deep-rooted culture of data and ops. Their focus? Set up the strategy to deliver hyper-realistic personalization through AI and orchestrate large, modular growth stacks.

However, we’re not there yet! In the short term, winning growth teams will hire talent to use data to creatively feed AI to power the hyper-realistic personalization that makes buyers tick. These growth operators are empowered by AI to craft & test infinite variations of personalized experiments. As a practitioner, I’ve been working very hard to get there, doing things like:

• Consistently check the MarTech section of Product Hunt

• Talk with founders and work with MarTech companies

• Scour and contributing to MarTech Slack communities

• Constantly ask mentees about new growth stacks and tactics they’ve been using and their results of course!

And then recycle what works in early-stage into later-stage organizations.

Zooming out, it’s clear that AI is not the first technology that brought disruption and significant change. However, the order of magnitude of this cycle will be unprecedented, and the changes affecting VC-backed startups will be much more abrupt.

You don’t have to face all of these challenges on your own. At HyperGrowth Partners, we’re experts in designing growth strategies, stacks, and teams. Hit us up if you want to join the next generation of hypergrowth B2B SaaS.

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In the next post of this series, we’ll deep dive into the next-gen B2B SaaS growth stack. Subscribe to stay in the loop.

Editor’s Note: This article was written in collaboration with , who assisted in bringing to life ’s experience and insights through his writing.

‍Most practitioners think growth marketing is about hacks, namely finding one silver bullet that generates that hockey stick. Yes, effective growth marketing results in unpopular solutions that deliver disproportionate results, which one could call hacks. But that’s not all of it.

‍Experienced practitioners know that what worked for others might not work for you, so hacks can’t always be replicated. Also, finding one hack is not enough to win the market in the long run. You need a process to repeatedly and sustainably identify these improbable wins. 

‍And to implement this process, you not only need different tactics, but you also need a different mindset, one where you understand the probabilities of success vs. risk of failure. And that’s exactly where most practitioners fail. They don’t realize that you must change your mindset to achieve disproportionate results. But you can’t change your mindset without the right process.

‍At HyperGrowth Partners, we’ve managed to help companies like Ramp scale from $10M to $100M in just over a year because we helped them set up the right growth process right from the start. This process enabled them to develop the right mindset to identify outliers and yield disproportionate results systematically.

‍In this post, we’ll reveal the effective growth framework we have deployed at tens of companies and how you can implement the process and mindset shift with your team and reliably build that hockey stick growth.‍

Core Mindset vs. Growth Mindset

Growth professionals are not more intelligent or skilled than core PMs or marketers; they have different approaches and mindsets.

The core mindset has its merits when the benefits outweigh the risks, just like when investing in an already-established late-stage venture. On the other hand, the growth mindset is like angel investing — because you have limited knowledge, outlier effects can happen more often. But you’ll also need to experiment more to find them!‍

‍Founders are realizing the core mindset applied to early-stage sets too high expectations, which makes core teams move too carefully, committing full-blown resources to customer interviews to create fine-grained products and marketing them for the long term.

‍In early-stage, this mindset stifles chances to discover outlier effects. And if the product doesn't succeed, the cost of failure can be excruciating, particularly in the early stage when VCs pressure to bring products to market quickly.

‍This was more likely back in 2021 when fundraising was much easier, and whoever had the most funding had more fuel to implement these core marketing strategies end-to-end and with a fine-grained level of detail. But for this cycle, this can’t be done anymore.

‍Simply put, core product and marketing strategies have a high upfront cost, decreasing the marginal efficiency of capital allocated to these initiatives. And in the current macroeconomic landscape, where fundraising is more challenging and boards are pushing for lower burns, these strategies will get you only so far and nowhere near the top.

The funny thing is that most startups focus on building disruptive products and experiences but fail to do the same within their marketing. That’s why a new, radically different approach is needed.

Growth and Angel Investing

The growth process solves this similarly to angel investing. According to Angel List, angel investing has the highest yield when investing in every deal. As soon as you start cherry-picking your investments, you miss out on the highest yield of the outliers.

When investing in early-stage startups, angels have limited information to predict whether their investment will be profitable. However, as they invest in more deals, they better understand what makes a successful investment. Growth has the same mindset.

‍Growth teams work with limited data and continually run tests to prove their hypotheses. The more experiments they run, the more they learn what strategies are successful and quickly feed the learnings back into the process.

‍Like in angel investing, the key to success for growth teams is not having the highest success rate (typically between 30-70%, just a 2x factor) but rather the highest rate of experimentation. This helps them quickly identify more levers and outliers, reducing their operating costs (which can take 1-10 days — a 10x factor!).

‍The secret to successful growth is finding that lever, the variable that slashes the cost of learning. For example, if the goal is to increase revenue by 10x in the next two years, growth teams must find a lever to reach this goal at a lower cost or in less time. If a growth team focuses too much on a few experiments, they trade the low learning cost for a high failure cost and start operating more like a core product or marketing team.‍

‍Similarly, if they know the outcome of an experiment will be successful (a sure bet), it’s no longer a growth experiment but a core product feature requiring the commitment of end-to-end resources. This mindset helps learning and shipping faster and builds focus, cross-functional knowledge, and flexibility to adapt to a fast-paced market.

‍In conclusion, you’ll need to apply the angel investing mindset of experimentation and high-risk tolerance to marketing problems to achieve disproportionate results. To do it systematically, you’ll need a clear framework and process, which most people fail to implement. They’re too focused on the hacks, distracting them from following the process consistently and ultimately learning the mindset.

Scaling from $1M to $10M ARR in one year instead of five requires building this process and mindset right from the start. At HyperGrowth Partners, we’ve put years of craft, experience, and results to perfect this process so your team, too, can join Ramp, Vercel, Maze, and many others on the path to hyper-growth.

Editor’s Note: This article was written in collaboration with , who assisted in bringing to life ’s experience and insights through his writing.