Query Parameters
| Name | Type | Default | Description |
|---|---|---|---|
| country | string | us | ISO country code (e.g. us, gb, de) |
| days | number | 7 | Trend window in days (1-30) |
| limit | number | 50 | Max keywords to return (1-100) |
Examples
Response
Response Fields
Top Level
| Field | Type | Description |
|---|---|---|
country | string | ISO country code |
period | string | Trend window (e.g. 7d, 14d, 30d) |
keywords | TrendingKeyword[] | Keywords sorted by growth percentage (descending) |
total | number | Total trending keywords found (before limit) |
TrendingKeyword
| Field | Type | Description |
|---|---|---|
keyword | string | The keyword |
growthPercent | number | Percentage growth in reach over the period |
maxReach | number | Maximum reach (top app review count) in current window |
currentReach | number | Most recent reach value |
volumeScore | number|null | Estimated search volume (0-100) |
resultCount | number | Number of apps returned by iTunes Search for this keyword |
difficulty | number|null | Ranking difficulty score (0-100) |
How It Works
The trending algorithm compares keyword reach between two time windows:- Current window: Last
daysdays - Previous window: The
daysbefore that
top_app_reviews — the review count of the #1 ranking app for each keyword. This is a strong proxy for keyword popularity because high-traffic keywords attract apps with large user bases.
A keyword is “trending” when its max reach in the current window exceeds the previous window. The growth percentage is: (current - previous) / previous × 100.
This endpoint requires background scraping data. Keywords are scraped daily via the
scrape:keywords worker. New keywords can be added to the pipeline via POST /v1/keywords/track.Caching
Results are cached for 30 minutes.Errors
| Status | Code | When |
|---|---|---|
| 500 | INTERNAL_ERROR | Failed to compute trends |

