Bangaly Kaba joined Instagram’s growth team in 2016, when the platform had roughly 400 million users. By the time he left, Instagram had crossed one billion. The insight that drove much of that expansion wasn’t a new feature, a viral loop, or an ad campaign. It was a question the team kept asking: who are the people that already know about us, already downloaded the app, and still didn’t stick around?
Kaba calls them adjacent users. They sit in the ring just outside your active user base. They’re aware. They’ve tried. They left. And most product teams never study them because the loudest feedback comes from the power users who already love the product.
That blind spot is where product strategy quietly breaks down.
Power Users Distort the Signal
Every product team gravitates toward its most engaged users. These are the people filling out NPS surveys, joining beta programs, posting in community forums, filing feature requests with screenshots attached. Their input feels like signal because it arrives with specificity and conviction.
The distortion: power users represent a shrinking percentage of your addressable market as your product matures. Andrew Chen, general partner at Andreessen Horowitz and former growth lead at Uber, describes the dynamic clearly. At Uber, many employees who were heavy riders assumed they understood what would push growth forward. They were almost always wrong. The changes that mattered to power users had little overlap with the changes that would unlock the next cohort.
I’ve watched the same pattern repeat in enterprise settings during fractional COO work. A company builds an internal operations platform optimized for the engineering team that designed it. When product, marketing, or customer success tries to adopt the same platform, the onboarding is confusing, the terminology is foreign, and the workflows assume context that only the original builders carry. The tool works beautifully for its creators. Everyone else bounces.
That’s the adjacent user problem at enterprise scale. And it happens in product discovery just as often as it happens in product design.
What Adjacent Users Actually Look Like
Kaba’s framework maps users into concentric rings: power users at the center, then core users, casual users, signed-up-but-inactive users, and visitors at the outer edge. Growth happens when people move inward from one ring to the next.
The critical point: the barriers between each ring are different. A visitor needs awareness. A signed-up user needs activation. A casual user needs a reason to return. Each transition has its own friction, and power user feedback tells you almost nothing about these transitions. Power users crossed those thresholds so long ago that they’ve forgotten the barriers existed.
Instagram’s data illustrated this precisely. New users who gained more than 10 followers within their first seven days had a 65% probability of becoming active, long-term users. That metric pointed to a specific adjacent user barrier: people signed up, couldn’t build an audience quickly enough, and left. The fix was better follow suggestions and onboarding flows, not a new filter or editing feature for existing photographers.
The Numbers Behind the Stall
Growth research from Sequoia frames the stakes in stark terms: once a product reaches its S-curve inflection point and growth stalls, the recovery rate is below 10%. Companies that avoid stalling are the ones that shift strategic attention outward before the plateau arrives.
Product-led growth benchmarks tell the same story from a different angle. Across PLG companies, only 9% of free accounts convert to paid. But companies that actively identify and reduce activation barriers for adjacent user segments see conversion rates between 25% and 30% for product-qualified leads. That gap represents the difference between building for the users you have and building for the users you almost had.
The risk is subtle because your existing metrics look healthy. Engagement among core users stays strong. Revenue per user might even climb. But the top of the funnel leaks, and the leak accelerates as the product becomes increasingly optimized for experts. If you’ve ever noticed the pattern of strong retention paired with flat acquisition, this is often the cause. Survivorship bias in your data makes the problem invisible until growth stalls outright.
Finding Them in Your Own Data
Adjacent users leave real traces. They’re not hypothetical personas:
Trial users who never activated. They signed up, poked around, and left. Your analytics tool knows exactly who they are. Segment them. Study what they did (and didn’t do) before the drop-off.
Single-feature users. They found enough value in one capability to stay but never expanded. Something about the broader product feels too complex or too irrelevant to explore.
Unadopted teams in enterprise accounts. In B2B, adjacent users are often entire departments. Slack, Notion, and Figma all grew team by team inside organizations. Each new team was an adjacent user group with its own activation barriers, its own vocabulary, its own workflow expectations.
Churned users who match your ideal customer profile. Not every churned user is equally informative. The ones who look like they should have succeeded, and didn’t, are the signal.
Building Outward Instead of Inward
Serving adjacent users requires a different kind of product thinking than optimizing for your core. A few principles from teams that do this consistently:
Assign ownership. Kaba’s central argument is that without a dedicated team studying and building for adjacent users, the work never happens. Core product teams naturally optimize for the people they hear from. Adjacent user work needs its own mandate, its own metrics, and its own roadmap.
Remove barriers before adding features. When Notion wanted to grow beyond technical early adopters, they didn’t add more developer-centric features. They added integrations with Google Docs, Slack, and Sheets so new users could try Notion without abandoning their existing tools. That’s a barrier-removal strategy. It looks nothing like a traditional feature roadmap.
Track activation, not satisfaction. Power user satisfaction scores can climb while adjacent user activation rates drop. Both numbers are real. Only one predicts where your next phase of growth will come from.
Accept targeted simplification. Serving adjacent users sometimes means reducing complexity in areas where power users have learned to navigate it. That feels like regression if your feedback loop only includes experts. It’s strategic investment if you’re watching the full funnel.
When This Lens Doesn’t Apply
Not every product needs to chase adjacent users. If you’re building specialized software for a finite professional audience (actuarial modeling, seismic analysis), your addressable market has a natural ceiling and deepening value for current users is likely the right strategy.
The adjacent user lens matters most when your product targets a large potential market, when growth is slowing despite strong engagement among current users, and when your analytics show meaningful sign-up-to-activation drop-off. For most SaaS products, collaboration tools, and consumer applications, that describes the situation precisely.
The Question Worth Asking
The adjacent user framework reframes a strategic question that every product manager eventually faces: who are we building for next?
The instinct is to answer by listening to the users who speak up. The data says the answer lives with the users who tried your product, found it lacking, and left without filing a single ticket. They didn’t complain. They just disappeared.
Your job is to find out why they left, and then decide whether removing that barrier is worth more than the next feature your power users requested.
For most products, the math is not even close.