How to Steal Your Competitor's App Strategy (Legally)
TL;DR
Most app developers make decisions by guessing — wrong audience, wrong keywords, wrong visuals. This session walks through a structured framework for reverse-engineering any competitor's strategy using public and aggregated data, then applying those insights to downloads, revenue, targeting, and retention. ---
Key Concepts
Competitive intelligence
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Systematically analyzing competitors' public-facing and inferred data to inform your own strategy
Hyper-targeting
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Showing each user exactly what they want to see — matching screenshots, keywords, and messaging to specific user intent
Custom Product Pages (CPP)
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App Store feature allowing up to 70 alternate screenshot sets, each tied to specific paid or organic keywords
Long-tail keywords
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Highly specific, lower-popularity search terms that are cheaper to bid on and less contested by large apps
SDK analysis
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Examining which third-party libraries an app uses to infer their marketing stack, engagement strategy, and feature roadmap
Audience demographics
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Age and gender breakdown of an app's actual users, used to sharpen ad targeting
Notes
§Step 1 — Validate the Competitor Is Worth Studying
- Check current performance: last 30 days of downloads and revenue
- Ask: does this app meet the revenue threshold you need to justify the category?
- Check trends: is performance growing, declining, or plateauing?
- A high current number that peaked months ago is a warning sign
- Year-over-year view reveals structural problems vs. seasonal spikes
- Check competitive position: is this app large or small relative to the category?
- A small but profitable app in a large market signals room for new entrants
- A dominant app declining may signal category saturation
§Step 2 — Understand the Audience
- Demographics (age + gender):
- Don't assume — actual splits often differ from intuition
- PicsArt: largest segment is 18–24, split roughly 50/50 male/female; older segments skew more male
- Targeting based only on aggregate demographic averages misses segment-level nuance
- Geography:
- PicsArt: 31% of downloads from India, only 6% from US
- If you ignore India-level ASO and paid targeting in this category, you cede the largest growth market
- Cross-app usage (what else their users have installed):
- Reveals whether users are loyal or sampling multiple competing apps
- PicsArt users also use: Prequel, VSCO, AirBrush, FaceTune, Funimate, Motion Leap — highly promiscuous audience
- High cross-app usage = high churn risk; retention must be a priority
§Step 3 — Assess User Satisfaction
- Look at rating trends over time, not just the average
- A rating drop at a specific date points to a triggered event (price change, feature removal, AI rollout)
- PicsArt ratings fell sharply after summer — reviews cite pricing and AI feature complaints
- Read negative reviews to find unmet needs
- Unhappy users who stay anyway are primed to switch to a competitor that solves their complaint
- If you offer a better price or the missing feature, downloads convert more easily
§Step 4 — Reverse-Engineer User Acquisition
- Large apps rank for thousands of keywords — PicsArt: ~10,000
- Sort competitor keywords by rank to find where they dominate
- Use competitor keyword gap analysis to find terms they rank for that you don't
- Don't try to clone their full keyword list; find overlapping intent keywords that fit your app
- PicsArt bids on ~2,500 keywords
- Find keywords where they hold the highest share of impressions ("the crown") — avoid those unless budget is very large; they are actively outspending all rivals
- Target keywords with even impression distribution across competitors — lower cost, more realistic to win
- Example opportunity found: "magic eraser," "background eraser," "AI eraser" — moderate popularity, PicsArt not dominating share → viable targets
- Once a user lands on your page via a specific keyword, your default screenshots may not match their intent
- CPPs solve this: serve a screenshot set built around the exact feature the user searched for
- PicsArt CPP example: users searching background removal see screenshots only about background removal — no clutter, no unrelated features
- Steps to replicate:
§Step 5 — Analyze Activity & Tech Stack
- Track name and subtitle changes by language and date
- PicsArt: actively changing names across multiple locales, adding "AI" consistently → AI positioning is intentional strategy, not coincidence
- Apps that rarely update ASO = opportunity to outrank them with active optimization
- PicsArt: 675 updates over 11 years, 16 recent metadata updates
- High update frequency in a category means you cannot "set and forget" — you must keep shipping
- Native: faster access to new OS features, slightly slower cross-platform iteration
- Non-native (React Native, KMP): easier cross-platform, faster shipping cycles
- PicsArt: primarily Swift/native, experimented with React Native and Kotlin Multiplatform
- Know what your competitor uses to estimate their speed advantage or disadvantage
- PicsArt (selected findings):
- Adjust + AppsFlyer: running paid campaigns at scale and measuring attribution
- Braze + CleverTap: active push notification and engagement campaigns to fight churn
- Firebase: analytics baseline
- User Voice / live chat tool: in-app customer support — reduces friction from dissatisfied users
- ARKit: AR features in development or deployed
- Newly added permissions or SDKs can signal upcoming unreleased features
- PicsArt collects: audio, coarse location, crash data, device ID, email, customer support data
- Breadth of collection correlates with sophistication of engagement/re-engagement campaigns
- If a competitor collects more behavioral data, they can personalize retention more effectively
Actionable Takeaways
- Check trends before copying — a competitor's current numbers may mask a declining trajectory; don't inherit a failing strategy
- Pull demographic splits by age group, not just overall — the 18–24 cohort may be 50/50 gender even if aggregate skews male
- Target geography your competitors dominate — if 31% of a category's downloads come from India, your ASO and paid campaigns need India-specific coverage
- Read negative reviews with a purpose — complaints about price or missing features are your conversion opportunity
- Find paid keywords where no one holds the crown — even impression distribution = cheaper CPIs and realistic wins
- Build at least one Custom Product Page per major use case — match screenshots to the exact search intent that brought the user there
- Audit competitor SDKs — if they're using Braze/CleverTap and you're not doing push engagement, you're losing the retention battle
- Watch for new permissions in competitor updates — microphone or camera access without a new visible feature = something is being built
Quotes Worth Keeping
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Guessing equals wasting time equals bad.
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Always hyper-target. Really always hyper-target. If you take one thing from this entire live stream, it's always hyper-target.
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Find all the crowns and stay away from them — unless you really want to take over a keyword, and then know that it's going to be costly.
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Those young females are unhappy about the price. If you have a competing app with a more competitive price, as long as you get them to download your app, you have a real potential of converting them.