Reviews: stars over a window, per review page
The reviews a keyword collects (App Store, Google Play, Trustpilot, Google Maps): count, average stars, distribution, replies and open 1-2 star reviews, for the workspace and per review page with a series of average stars per `bucket`, plus the tags the unhappy reviews carry. A review matched by two keywords counts once. The window is `range` (7d, 30d, 90d, 365d, ending today) or `from` and `to`, cut into days in `timezone` (UTC by default); `keywordIds` and `platforms` narrow it; `compare=true` adds the period of the same length right before it. Time axis is the publish date.
API key minted via POST /v1/api-keys (format mk_live_...)
In: header
Query Parameters
Preset window ending today. Ignored when from or to is given. Default 30d.
"7d" | "30d" | "90d" | "365d"First day, YYYY-MM-DD, inclusive, in timezone.
^\d{4}-\d{2}-\d{2}$Last day, YYYY-MM-DD, inclusive, in timezone. Default today.
^\d{4}-\d{2}-\d{2}$Only these keyword ids. Repeatable, or comma-separated; omit for every keyword.
items <= 50Only these platforms. Repeatable, or comma-separated; omit for every platform.
items <= 20true adds the period of the same length right before the window as previous.
IANA zone the days are cut in (Europe/Madrid). Default UTC. One offset, the zone's at the end of the window, applies to the whole window.
length <= 64Series bucket: day (default up to 90 days) or week.
"day" | "week"Response Body
application/json
application/json
application/json
curl -X GET "https://api.mentio.dev/v1/analytics/reviews"{
"window": {
"from": "string",
"to": "string",
"days": 0,
"timezone": "string",
"bucket": "day"
},
"totals": {
"reviews": 0,
"averageRating": 1,
"distribution": {
"1": 0,
"2": 0,
"3": 0,
"4": 0,
"5": 0
},
"responded": 0,
"openNegative": 0
},
"tags": [
{
"tag": "string",
"count": 0
}
],
"pages": [
{
"reviews": 0,
"averageRating": 1,
"distribution": {
"1": 0,
"2": 0,
"3": 0,
"4": 0,
"5": 0
},
"responded": 0,
"openNegative": 0,
"platform": "appstore",
"id": "string",
"url": "string",
"series": [
{
"date": "string",
"reviews": 0,
"averageRating": 1
}
],
"previous": {
"reviews": 0,
"averageRating": 1
}
}
],
"previous": {
"reviews": 0,
"averageRating": 1,
"distribution": {
"1": 0,
"2": 0,
"3": 0,
"4": 0,
"5": 0
},
"responded": 0,
"openNegative": 0
}
}{
"error": {
"code": "unauthorized",
"message": "string",
"requestId": "string",
"retryAfterSeconds": 0
}
}{
"error": {
"code": "unauthorized",
"message": "string",
"requestId": "string",
"retryAfterSeconds": 0
}
}Headline counts for a window GET
Matched and relevant mentions, distinct posts and people, sentiment, buying intent and questions, estimated reach, and where the matches stand in triage. The window is `range` (7d, 30d, 90d, 365d, ending today) or `from` and `to`, cut into days in `timezone` (UTC by default); `keywordIds` and `platforms` narrow it; `compare=true` adds the period of the same length right before it. Time axis is the publish date.
Brand against competitors GET
Every keyword matched in the window with its counts and its share of brand plus competitor matches; topic keywords are counted but stay out of the split. The window is `range` (7d, 30d, 90d, 365d, ending today) or `from` and `to`, cut into days in `timezone` (UTC by default); `keywordIds` and `platforms` narrow it; `compare=true` adds the period of the same length right before it. Time axis is the publish date.