Transparent by design
How Bright App Data turns public signals into an app report.
Every conclusion must be traceable to visible store evidence. Missing private information stays missing.
1. Collect the public listing
We record the app title, descriptions, category, creative assets, rating volume, available install estimates, release history, update date, pricing and public developer links.
2. Sample reviews and classify repeated problems
Rule-based detection groups recurring complaint language and preserves short excerpts. One angry review is not presented as a widespread defect, and a small sample is labelled as a sample.
3. Score twelve ASO signal groups
The audit covers title use, short and long descriptions, screenshots, icon, video, rating, review volume and velocity, developer replies, update cadence, privacy and localization evidence.
4. Estimate a bounded public-signal range
Audience proxies, rating quality, maintenance recency, maturity, monetization badges, ASO strength, sampled-review risk and detected issue pressure produce a transparent range. Every multiplier is shown on the report.
5. Keep the permanent report current
Each app has one canonical report URL. A re-audit refreshes its evidence instead of creating a competing duplicate page.
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Methodology questions
What public data does Bright App Data use?
Store listing copy, media coverage, rating and review signals, developer replies, release and update dates, privacy links, localization checks and other publicly observable metadata.
Does Bright App Data know an app's revenue or retention?
No. Revenue, conversion, retention, verified profit and source-code condition are private inputs. Public reports label them unavailable instead of guessing.
Is the app value estimate a sale price?
No. It is a public-signal screening range for comparison and prioritization. Transaction pricing requires financial, legal, security and source-code due diligence.
How are review issues detected?
A deterministic, rule-based classifier groups recurring complaint language such as crashes, login, payments and performance. Reports show counts and available public excerpts as evidence.
How many reviews does an audit read?
Up to 100 recent public reviews per app, which is what the stores expose reliably. A complaint cluster requires at least two independent reviews rated one to three stars describing the same kind of problem, so a single outlier never creates a finding.
Does every audited app get a public page?
No, deliberately. A report is published only when it clears a quality gate: enough reviews analysed, at least two distinct complaint clusters, review excerpts as evidence, substantial listing copy and a composite quality score of 70 or higher. Reports that fail stay unpublished rather than becoming thin pages.
How often is a report refreshed?
Every report shows the date its evidence was collected. Listings change, so a report older than about six weeks is flagged internally for a refresh, and the visible date always reflects the real audit rather than the last deploy.
What if a report about my app is wrong?
Contact us and we re-run the audit against the current listing, correct any demonstrated factual error and show the refreshed date. Owners can also request removal. The full corrections policy is on the disclaimer page.