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叶 李

Health & Fitness

Team website
Website
27Apps
4.7Avg Rating
18.0KTotal Ratings
6Categories
Product page (App Store)
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

Health & Fitness is the main category at about 40.7% of apps, while the portfolio spans 6 categories. This is a relatively diversified portfolio strategy.

Health & Fitness
11 apps · 40.7%
Education
7 apps · 25.9%
Sports
3 apps · 11.1%
Music
2 apps · 7.4%
Productivity
2 apps · 7.4%
  • The primary category Health & Fitness accounts for 40.7%. Long-tail categories can reduce single-category risk.
  • The diversification score is about 0.74 (0=highly concentrated, 1=highly diversified), useful for comparing developers.

Portfolio data

Scale and monetization structure

The full portfolio has about 18.0K public ratings, a small public review base. It includes 27 free apps and 0 paid apps.

Apps
27
Total ratings
18.0K
Free / paid
27 / 0
  • By review volume, the leading apps include: "Yoga Workout-Do Yoga At Home", "WeightLoss Workout-HomeFitness", "Pilates Workouts-Home Fitness".
  • 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 4.71 stars; the simple average is 4.68 stars. The gap shows whether high-volume apps lift or drag the overall reputation.

Weighted avg
4.71 ★
Simple avg
4.68 ★
  • The weighted and simple averages are close, suggesting reputation is relatively balanced across apps.
  • 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.

  • No app triggered the low-rating plus sufficient-sample threshold.
  • Thin rating samples (under 50 ratings): "腹肌撕裂者-腹部肌肉锻炼", "马甲线教程-女士减肥瘦身减脂", "Chinese Lessons-Learn Mandarin". Star ratings can swing heavily until more feedback arrives.

Release and lifecycle

Listing age span

The earliest listed app is "韩语学习-轻松学韩语视频教程", while the newest or most recent listing signal is "Saxophone Master - Sax Lessons". The span is a proxy for long-term iteration capacity.

Span
9 years+
  • Earliest record in this dataset: 2016 (韩语学习-轻松学韩语视频教程).
  • Newer app signal: 2025 (Saxophone Master - Sax Lessons).

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: 6 categories show whether a main-category plus extension structure matches your resources.
  • Compare reputation structure: weighted 4.71 stars vs. the leading app "Yoga Workout-Do Yoga At Home" 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.