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Coco Play

Games

Team website
Website
115Apps
4.4Avg Rating
4.4MTotal Ratings
2Categories
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Developer portfolio analysis

Automatically summarizes public App Store metadata such as categories, rating volume, star ratings, release dates, and pricing for competitor research and product planning. The DeepSeek section is generated on demand when the API is configured; otherwise only rule-based analysis is shown.

DeepSeek AI analysis

Runs on demand so the initial page load stays fast.

Review the rule-based cards first, then generate the AI readout. It usually takes 10-40 seconds.

Product direction

Category and portfolio mix

Games is the main category at about 99.1% of apps, while the portfolio spans 2 categories. This is a highly concentrated portfolio strategy.

Games
114 apps · 99.1%
Entertainment
1 apps · 0.9%
  • The primary category Games accounts for 99.1%. The category structure is relatively narrow.
  • The diversification score is about 0.02 (0=highly concentrated, 1=highly diversified), useful for comparing developers.

Portfolio data

Scale and monetization structure

The full portfolio has about 4.4M public ratings, a large public review base. It includes 115 free apps and 0 paid apps.

Apps
115
Total ratings
4.4M
Free / paid
115 / 0
  • By review volume, the leading apps include: "Soap Cutting", "Gymnastics Superstar Gold Girl", "ASMR Slicing".
  • The visible list is free or priced at 0. Monetization may rely on subscriptions, ads, or in-app purchases; verify on the store page.

Ratings and reputation

Weighted average and head effects

Weighted by rating volume, the portfolio averages about 4.62 stars; the simple average is 4.38 stars. The gap shows whether high-volume apps lift or drag the overall reputation.

Weighted avg
4.62 ★
Simple avg
4.38 ★
  • The weighted and simple averages differ meaningfully, indicating that high-review apps strongly shape perception.
  • 1 apps have no public rating data, so long-tail performance is underrepresented.

Reputation risk proxy

Low ratings and thin samples (API has no review text)

The iTunes Search API does not provide review text. This card uses low star ratings with enough review volume as a proxy, and separately highlights apps with thin samples.

  • Low-rating watchlist (at least 80 ratings and below 4.0 stars): "Mia - My New Best Friend" 3.1★; "Star Cheerleader - Go Team Go!" 3.2★; "Ballet Dancer Competition" 3.3★. Use App Store Connect exports or third-party data for semantic review analysis.
  • Thin rating samples (under 50 ratings): "Screwzy", "1 Stroke Brain Puzzles", "Crazy Banana GO!". Star ratings can swing heavily until more feedback arrives.

Release and lifecycle

Listing age span

The earliest listed app is "My High School Dance Game", while the newest or most recent listing signal is "Cats vs Dogs Puzzle Connect". The span is a proxy for long-term iteration capacity.

Span
13 years+
  • Earliest record in this dataset: 2012 (My High School Dance Game).
  • Newer app signal: 2025 (Cats vs Dogs Puzzle Connect).

Reference points for builders

Reusable research angles

These takeaways are based on public metadata and are useful for competitor research or portfolio planning. Deeper conclusions require downloads, revenue, and review text.

  • Study the category mix: 2 categories show whether a main-category plus extension structure matches your resources.
  • Compare reputation structure: weighted 4.62 stars vs. the leading app "Soap Cutting" and its review volume.
  • For similar tools, prioritize review mining on lower-rated apps to find functional gaps; this requires store reviews or third-party data.

Rule-based cards use iTunes Search API data. DeepSeek generates its readout from the same public data and should be treated as directional research.

Team / product news

Runs on demand and avoids external calls by default.

Aggregates news about the team and core products, up to 20 items.