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TabTale LTD

Games

Team website
Website
131Apps
4.0Avg Rating
214.1KTotal Ratings
3Categories
Product page (App Store)
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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 76.3% of apps, while the portfolio spans 3 categories. This is a moderately concentrated portfolio strategy.

Games
100 apps · 76.3%
Book
25 apps · 19.1%
Education
6 apps · 4.6%
  • The primary category Games accounts for 76.3%. The category structure is relatively narrow.
  • The diversification score is about 0.38 (0=highly concentrated, 1=highly diversified), useful for comparing developers.

Portfolio data

Scale and monetization structure

The full portfolio has about 214.1K public ratings, a mid-sized public review base. It includes 130 free apps and 1 paid apps.

Apps
131
Total ratings
214.1K
Free / paid
130 / 1
  • By review volume, the leading apps include: "Hotel Transylvania Adventures", "DIY Locker 3D", "DIY Makeup".
  • Free apps dominate, which often points to a utility entry point plus subscription or upgrade model.

Ratings and reputation

Weighted average and head effects

Weighted by rating volume, the portfolio averages about 4.56 stars; the simple average is 3.95 stars. The gap shows whether high-volume apps lift or drag the overall reputation.

Weighted avg
4.56 ★
Simple avg
3.95 ★
  • The weighted and simple averages differ meaningfully, indicating that high-review apps strongly shape perception.
  • 0 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): "Sunnyville Pet Salon" 3.4★; "Spa Birthday Party!" 3.5★; "Babysitter Madness" 3.6★. Use App Store Connect exports or third-party data for semantic review analysis.
  • Thin rating samples (under 50 ratings): "The Fox & the Crow Game Book", "The Four Seasons", "Ethan’s Super Power". Star ratings can swing heavily until more feedback arrives.

Release and lifecycle

Listing age span

The earliest listed app is "Christmas Tale HD", while the newest or most recent listing signal is "DIY Locker 3D". The span is a proxy for long-term iteration capacity.

Span
12 years+
  • Earliest record in this dataset: 2010 (Christmas Tale HD).
  • Newer app signal: 2022 (DIY Locker 3D).

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: 3 categories show whether a main-category plus extension structure matches your resources.
  • Compare reputation structure: weighted 4.56 stars vs. the leading app "Hotel Transylvania Adventures" 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.