Use Cases

The statistics API is very powerful and can be used for many different purposes. Here are a few common applications that we would like to highlight

  • Unifying attribution data with in-house analytics and BI tools
    It is common for larger games to create custom dashboards to track key performance indicators at a glance. Integration with the stats api enables you to include your user acquisition data alongside your other key metrics. Additionally, with Gamesight statistics warehoused you can perform deeper analysis and enhance your learning.
  • Tagging users by attribution source in-game
    Gamesight strives to provide meaningful information about which sources are providing your most valuable users, but sometimes there are metrics that you wish to use to determine player quality that Gamesight doesn't have access to. In these scenarios, the stats API can be used to provide information on attributed source by user_id. This will enable you to attach attribution data to your users so you can run custom user scoring by campaign.
  • Evaluating campaign performance using custom metrics
    Similar to tagging users by attributed source, you may want to use automated methods for evaluating your campaign performance. The stats api's real-time data enables you to react quickly to changes in campaign performance so you can most effectively spend your marketing budgets.


The following fields are supported.

  "fields": [
    "goals", // Breakdown of all attributed goals
    "network_reported_performance", // Includes impression, click, and cost data as reported by your ad network (Facebook, Google, etc)
    "launches", // Total game launches recorded by attributed users
    "retention", // will add fields for 1,3,7,14,30 day retention
    "custom_events", // includes a breakdown of events that attributed users triggered


The following fields can be included in the grouping for the report. If you request a field in the grouping it will also be returned as one of the fields in the results.

  "groups": [

Note if you group by user_id all other groupings will be applied automatically since each value is unique on a per-user basis (except for created_at_date, please include this grouping separately if desired). We recommend using the user_id grouping when you want to pull attach source data about your users in your BI system.

Additionally, the clicked_at_date group will group your statistics on the date of the attributed click, not the date that events occurred.


Each of the following fields may be used to filter the results of a stats request.

  "filters": {
    "user_ids": ["user1", "user2"],
    "team_ids": [12345],
    "networks": ["facebook"],
    "campaigns": ["test_campaign"],
    "ad_groups": ["ad-grou-1"],
    "ads": ["my-ad"],
    "sub1": ["arbitrary"],
    "sub2": ["arbitrary"],
    "sub3": ["arbitrary"],
    "sub4": ["arbitrary"],
    "sub5": ["arbitrary"],
    "countries": ["CA", "DE"], // ISO 3166-1 alpha-2
    "start_created_at_date": "2000-01-01",
    "end_created_at_date": "2001-01-01",

    "start_date": "2000-01-01",
    "end_date": "2001-01-01",

Note that the start_date/end_date filters use the date of the attributed click, not events themselves to filter results. Only use these filters if you are also grouping by clicked_at_date.

Click Try It! to start a request and see the response here!