Unraveling the Mystery of Stalled App Growth
The Early Warning Signs of App Failure
In the world of app development and growth, failure rarely comes as a surprise. It's a gradual process, often signaled by subtle patterns that experienced professionals can identify long before a project crashes and burns. The challenge lies not in recognizing these signs, but in acknowledging them while there's still momentum.
A Diagnostic Approach to App Growth
During a recent App Talk session at Business of Apps Berlin 2025, Samet Durgun, the renowned Growth Therapist, offered a unique perspective on app growth. Instead of focusing solely on tactical optimizations, Durgun emphasized the importance of understanding the underlying system and its impact on long-term success. He highlighted the recurring conditions that separate leading apps from those that lag behind, regardless of category, business model, or maturity stage.
This article is not a quick fix checklist, but a comprehensive guide to identifying structural issues that can lead to app growth stagnation.
Cash Flow: A Structural Constraint
One of the earliest indicators of potential issues is timing. Particularly for subscription-based app businesses, there's a significant delay between revenue generation and actual payout, often stretching to six weeks through app stores. This lag can turn scaling into a risky endeavor if not properly accounted for.
"You're essentially spending money you haven't received yet," Durgun pointed out. Growth decisions made without a reliable understanding of LTV (Lifetime Value) can deplete future resources. The danger lies not in ignorance, but in optimism - teams often assume the next payout will arrive on time, until it doesn't.
In this context, cash flow discipline is about visibility, not austerity. Growth requires bridging gaps, and those gaps need clear definitions, numbers, and contingency plans, not blind faith.
Retention: The Key to Long-Term Success
Retention is often discussed as a post-install metric, something to optimize once acquisition is stable. However, this approach misses the bigger picture. Retention is shaped from the very first interaction with the app, influenced by onboarding friction, paywall clarity, perceived value, and the overall initial experience.
"It's not just about day seven or day thirty," Durgun emphasized. "It's about every second from the moment a user opens the app to whether they still care about it months later."
Instead of chasing absolute benchmarks, Durgun advocated for working within healthy retention ranges, guided by credible industry medians and top-quartile data. Retention, when viewed this way, becomes a continuous diagnostic tool, not just a single KPI.
Instrumentation: A Strategic Decision
Event setup is often seen as a technical prerequisite, but it's actually a strategic decision that determines what a growth system can learn. Many apps optimize around convenient signals, like a trial start, which may indicate progress but mask immediate cancellation behavior. More predictive signals often lie a step later in the user journey, requiring deliberate definition and consistent transmission across analytics, attribution, and media platforms.
Instrumentation failures often manifest indirectly. Teams struggle to explain performance differences between channels, reconcile app store data with MMP reports, or adjust campaigns without understanding which behaviors actually correlate with revenue. These issues rarely stem from media buying; they originate upstream, in decisions about what the system is allowed to measure.
Attribution: An Organizing System
Attribution problems are often subtle and accumulate through small inconsistencies - delayed signals, missing parameters, or revenue visible in one system but not another. Even at scale, these gaps can persist.
"I still see companies doing millions," Durgun said, "but they don't really know which channel is driving what."
The issue is rarely the tools themselves; most stacks already contain the necessary components. The failure lies in orchestration - deciding when and how data moves between product, MMPs, and acquisition platforms. Without a clear map, optimization becomes a guessing game disguised as analysis.
Creative Scale and the Cost of AI
The increasing availability of AI-generated creative has shifted the conversation from scarcity to abundance. Achieving volume is no longer the challenge; the true cost of producing a winning creative asset is often overlooked.
Creative production carries an opportunity cost, whether the labor is human or machine-assisted. Prompting, iteration, testing, and interpretation all require time and attention. Measuring success solely by output count obscures the more important question: how much total effort was required to create a creative that actually performs?
A more useful metric is cost per winning asset, which helps teams avoid optimizing for throughput at the expense of emotional resonance, mistaking speed for effectiveness.
Learning from Spend: The Key to True Scale
Statistically significant data requires investment, but feeding algorithms without clear hypotheses can lead to waste. Spend that isn't designed to generate learning is indistinguishable from spend that simply fails. The warning sign is activity that increases complexity without increasing clarity - more campaigns, creatives, and channels, but diminishing insight into what actually works. Growth becomes louder, but less informed.
Product-Market Fit: An Ongoing Test
Product-market fit is often treated as a milestone achieved early on, assumed to be permanent. In reality, it's a fragile balance that requires constant maintenance. Markets evolve, expectations rise, and user tolerance narrows.
Apps built from genuine personal friction tend to recalibrate faster because their creators feel the problem directly. "If you wouldn't use your own app," Durgun said, "it's hard to know when it stops helping."
Focus: A Powerful Growth Strategy
Instead of chasing new tactics, channels, or formats, the recommendation for the year ahead is focus. Focus on what already works, on the strongest product, and on signals that matter. As Jeff Bezos famously said, what matters most is what will not change - relevance, clarity, and value remain resilient against trend cycles.
In growth, as in therapy, progress often starts with understanding what's undermining the existing system, not by adding something new.
If these questions resonate with your work, Business of Apps London is the place to delve deeper into these topics, live and unscripted.
