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Dhameliya Infotech private limited

Shopping

Team website
Website
147Apps
4.4Avg Rating
55Total Ratings
5Categories
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

Shopping is the main category at about 93.2% of apps, while the portfolio spans 5 categories. This is a highly concentrated portfolio strategy.

Shopping
137 apps · 93.2%
Business
5 apps · 3.4%
Productivity
2 apps · 1.4%
Lifestyle
2 apps · 1.4%
Travel
1 apps · 0.7%
  • The primary category Shopping accounts for 93.2%. Long-tail categories can reduce single-category risk.
  • The diversification score is about 0.13 (0=highly concentrated, 1=highly diversified), useful for comparing developers.

Portfolio data

Scale and monetization structure

The full portfolio has about 55 public ratings, a small public review base. It includes 147 free apps and 0 paid apps.

Apps
147
Total ratings
55
Free / paid
147 / 0
  • By review volume, the leading apps include: "Lollicup-Store", "Lilii ليلي", "Chic Chubby Cherub".
  • 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 3.98 stars; the simple average is 4.45 stars. The gap shows whether high-volume apps lift or drag the overall reputation.

Weighted avg
3.98 ★
Simple avg
4.45 ★
  • The weighted and simple averages differ meaningfully, indicating that high-review apps strongly shape perception.
  • 122 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): "NEW CREDIT INC", "JewelryFresh", "Bradshaw Blanks". Star ratings can swing heavily until more feedback arrives.

Release and lifecycle

Listing age span

The earliest listed app is "Name Sign", while the newest or most recent listing signal is "Renaissance Jewel". The span is a proxy for long-term iteration capacity.

Span
4 years+
  • Earliest record in this dataset: 2021 (Name Sign).
  • Newer app signal: 2026 (Renaissance Jewel).

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: 5 categories show whether a main-category plus extension structure matches your resources.
  • Compare reputation structure: weighted 3.98 stars vs. the leading app "Lollicup-Store" 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.