How a reporting API works
A reporting API answers a query like "installs, spend and revenue by campaign for the last 7 days" with structured data, usually JSON. You authenticate with a key, pass a date range and the dimensions you want, and get back rows that match what the dashboard shows.
A worked example: a growth team posts a morning summary to Slack. A script calls the reporting API at 9 a.m. for yesterday's numbers by campaign, computes ROAS, and flags any campaign where spend rose more than 30% while ROAS fell below 0.5x. Nobody has to open a dashboard to catch the one campaign that went wrong overnight.
Common uses
- BI dashboards that combine MMP numbers with finance and product data.
- Automated alerts on spend, CPI or ROAS thresholds.
- Agency and client reporting across many apps.
- Budget scripts that adjust bids based on recent ROAS.
- Reconciliation of ad network invoices against attributed installs.
Reporting API versus raw data
A reporting API is the right tool when you want the same numbers as the dashboard, in your own system, on a schedule. It is the wrong tool when you need per-user detail, such as joining installs with your order table. That is the job of raw data exports, user-level Data APIs or a warehouse feed. Many teams use both: reporting for the daily view, raw data for deeper analysis.
The Linkrunner Reporting API
Linkrunner's Reporting API returns the campaign analytics shown in the dashboard: clicks, installs, sign-ups, spend, revenue and ROAS, with ad sets, ad creatives and keywords. A separate endpoint covers web campaigns. Requests are authenticated with your project's server key in the linkrunner-key header. The Data APIs add attributed users and attribution lookups, and the MCP server lets AI assistants read the same stats. See APIs and webhooks or the docs.