This audit was generated on March 7, 2026
The data may no longer be up to date.
How your app performs across different visibility factors
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Start tracking for freeYour app's position for key search terms
10
Keywords analyzed
1
Ranked in top 100
1
In top 10
| Keyword | Rank | Traffic | Difficulty | Ahead | Behind | Top 5 |
|---|---|---|---|---|---|---|
| wikisprint | #3 | |||||
| wikipedia game | Not ranked | — | — | |||
| speed game | Not ranked | — | — | |||
| logic game | Not ranked | — | — | |||
| casual game | Not ranked | — | — | |||
| daily challenge | Not ranked | — | — | |||
| puzzle game | Not ranked | — | — | |||
| link game | Not ranked | — | — | |||
| word game | Not ranked | — | — | |||
| brain game | Not ranked | — | — |
Apps positioned directly before or after yours on keywords
Education
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Occurrence count shows how many keywords each competitor appears on
Games chart position
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Improve your ratings and downloads to climb the category charts.
Personalized insights generated by our AI
WikiSprint has a decent foothold with its brand keyword ranking #3, but overall ASO is weak: only 1 of 10 target keywords ranks, no user ratings, and a low quality score, resulting in a visibility score of 12/100. Immediate focus should be on expanding keyword coverage, boosting app quality signals, and driving user reviews.
The app’s own name "wikisprint" ranks #3 with 34 traffic units and a relatively low difficulty (28), giving a solid base to build upon. Leverage this by keeping the name unchanged and reinforcing it in the subtitle and keyword field.
Only 1 of 10 analyzed keywords is ranked; high‑traffic terms like "puzzle game" (traffic 66, difficulty 72) and "speed game" (traffic 79, difficulty 48) are missing. Expand the 100‑character keyword field and use the subtitle to capture these missed opportunities.
The app shows a 0.0 rating with no reviews, which heavily penalizes quality score (50%) and conversion rate. Implement an in‑app prompt after a successful game round to solicit 4‑star reviews and consider a small incentive for feedback.
The subtitle can hold additional high‑traffic keywords (e.g., "Puzzle, Speed & Logic Game"). Adding 2‑3 of the unranked but relevant terms can improve discoverability without sacrificing character limits.
A quality score of 50% suggests under‑optimized screenshots/video. Introduce 5‑6 high‑resolution screenshots showing gameplay, daily challenges, and VS mode, plus a 15‑second preview video highlighting the fast‑paced nature to raise conversion and ranking.
Actionable recommendations to improve your visibility
Your app was updated recently, signaling active maintenance to users and stores.
You have 3 screenshots. Adding more (8-10) helps showcase features and increases conversion.
Not ranking in top 50 for generic keywords. Consider optimizing title and description with relevant search terms.
Score of 12/100 suggests room for ASO optimization. Focus on keywords and category ranking.
Improving ratings and downloads can help reach category top charts.
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Common questions about this ASO audit.
WikiSprint has a visibility score of 12 out of 100 on the Apple App Store (US). The score combines keyword rankings, top charts presence, and listing quality signals like rating and update recency. This audit was generated on March 7, 2026.
WikiSprint is tracked on 10 keywords in this audit. It currently ranks in the top 100 for 1 keyword, with 1 keyword reaching the top 10. Ranking in the top 10 is where most discovery traffic happens.
Based on shared keyword rankings, the most frequent competitors of WikiSprint are R Discovery: Academic Research, ResearchGate. These apps appear next to WikiSprint on the keywords it ranks for, which makes them the most direct opportunities for ASO benchmarking.
WikiSprint is listed in the Games category on the Apple App Store.
Based on this audit, WikiSprint should focus on the keywords where it ranks 11 to 50 (closest to the top 10), benchmark its title and subtitle against the most frequent competitors, and refresh its listing regularly to maintain quality signals. The full audit lists specific weaknesses, opportunities, and AI-generated suggestions tailored to WikiSprint.
This audit was generated automatically by Applyra by scraping public Apple App Store data: app metadata, keyword rankings, category positions, and competitor listings. Visibility, keyword and listing quality scores are computed from those signals. Audits are free and do not require an Applyra account.