Smart Points Ltd

Food & Drink is the main category at about 73.5% of apps, while the portfolio spans 8 categories. This is a moderately concentrated portfolio strategy.

Food & Drink

36 apps · 73.5%

Finance

3 apps · 6.1%

Entertainment

3 apps · 6.1%

Business

2 apps · 4.1%

Shopping

2 apps · 4.1%

• The primary category Food & Drink accounts for 73.5%. Long-tail categories can reduce single-category risk.
• The diversification score is about 0.45 (0=highly concentrated, 1=highly diversified), useful for comparing developers.

The full portfolio has about 1.2K public ratings, a small public review base. It includes 49 free apps and 0 paid apps.

Apps

49

Total ratings

1.2K

Free / paid

49 / 0

• By review volume, the leading apps include: "Florence Coffee Co", "LoyLap", "Ready Fit Go!".
• The visible list is free or priced at 0. Monetization may rely on subscriptions, ads, or in-app purchases; verify on the store page.

Weighted by rating volume, the portfolio averages about 4.78 stars; the simple average is 4.36 stars. The gap shows whether high-volume apps lift or drag the overall reputation.

Weighted avg

4.78 ★

Simple avg

4.36 ★

• The weighted and simple averages differ meaningfully, indicating that high-review apps strongly shape perception.
• 38 apps have no public rating data, so long-tail performance is underrepresented.

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): "LoyLap Merchant", "BRTC Grill", "Tealicious Blend". Star ratings can swing heavily until more feedback arrives.

The earliest listed app is "LoyLap", while the newest or most recent listing signal is "FACILIPAY Merchant". The span is a proxy for long-term iteration capacity.

Span

13 years+

• Earliest record in this dataset: 2013 (LoyLap).
• Newer app signal: 2026 (FACILIPAY Merchant).

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: 8 categories show whether a main-category plus extension structure matches your resources.
• Compare reputation structure: weighted 4.78 stars vs. the leading app "Florence Coffee Co" 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.