data.ai (formerly App Annie)

Analyze regional category trends using Market Explorer.

Identify top 5 local competitors by active users.

Analyze their monetization models via Game IQ/App IQ.

Review user sentiment in local languages using Sentiment Analysis.

Navigate to Ad Intel to view competitor creative strategies.

Analyze competitor ad spend share of voice across networks.

Identify high-performing keywords via the ASO module.

Adjust creative assets based on identified visual trends.

Compare the startup's claimed MAU with data.ai's independent estimates.

Look for signs of 'organic' vs 'paid' growth using the download source breakdown.

Assess retention rates compared to the category average.

Check for 'burst' campaign anomalies in historical charts.

Use 'Compare Apps' to overlay feature release dates with active user spikes.

Read through filtered reviews mentioning specific features (e.g., 'offline mode').

Analyze 'Power User' metrics for competitors versus own app.

Review engagement duration (average session length) by genre.

Perform a Keyword Gap analysis against the top 3 competitors.

Identify 'high-win' keywords where competitors are weak.

Optimize app metadata (title, subtitle) using suggested terms.

Track ranking improvements in real-time on the Keyword Tracking dashboard.

Look at 'App Affinity' data to see where churned users go.

Check 'Cross-App Usage' to see if users are migrating to a specific rival.

Analyze the review sentiment for 'stability' or 'bugs' after the last update.

Benchmarking retention curves (Day 1, 7, 30) against the category leader.

Search for apps with a high 'User Overlap' with their fitness app.

Identify apps in the 'Health & Fitness' or 'Food & Drink' categories with high engagement.

Analyze the demographic profile (Age/Gender) to ensure brand alignment.

Reach out to developers of apps with compatible growth trajectories.