Market context
Market datamethodology
How we collect and present Google Trends, search interest, growth, internal popularity, and competitive market data — and why none of it changes structured product scores.
Google Trends data
We track Google Trends interest for product names and related search terms. Trends data shows relative search popularity over time — useful context for how much attention an app receives compared to rivals, not how well it performs in hands-on testing.
Search interest over time
Search interest charts plot normalized query volume across weeks and months. Spikes often follow product launches, viral moments, or major feature updates. We present this as market context alongside reviews, not as a quality signal.
Twelve-month growth
We calculate approximate year-over-year or trailing-twelve-month growth in search interest where data is available. Growth indicates rising or falling demand; it does not measure conversation quality, image accuracy, or privacy practices.
Internal popularity and ranking data
We aggregate anonymized on-site signals — page views, compare usage, directory clicks, and outbound referral patterns — to understand which apps readers research most. Internal popularity reflects audience interest on AI Girlfriend Expert, not an endorsement or performance score.
Competitive market comparisons
Market comparison panels place an app next to category peers on search interest, pricing position, and internal popularity. These comparisons help readers see competitive context; they do not feed into category or overall performance scores.
Pricing position against the market
We compare subscription price, real monthly cost estimates, and per-use charges against the apps in our database. Market pricing context appears in reviews and roundups for value comparison. Structured pricing scores come only from our Pricing category tests.
Data sources
Primary sources include Google Trends (public search interest), our internal analytics, published pricing pages, and our structured test database. We document the source for each market data point shown on a review.
Update frequency
Google Trends and search interest data refresh monthly or when a review is substantially updated. Internal popularity metrics update on a rolling basis. Pricing market position updates when we retest or when competitors change prices.
Calculation methods
Search interest uses Google Trends normalized indices (0–100 scale). Growth percentages compare current and prior twelve-month averages. Internal popularity ranks apps by relative on-site engagement within the same period. All calculations are documented in review footnotes where shown.
Limitations
Google Trends reflects search behavior, not user satisfaction. Internal popularity skews toward apps we cover most prominently. Market data can lag real-world events. We treat all market metrics as directional context with known blind spots.
Why market data does not affect scores
Product scores measure hands-on performance through structured tests. Popularity, search demand, and competitive buzz do not make an app remember context better, generate cleaner images, or protect privacy more effectively. Keeping market data separate preserves score integrity.
Popularity and search demand provide useful context. They do not measure how well an app performs in hands-on testing and do not affect the overall performance score.Back to how we test
