Three ad platforms, three sets of definitions, and none of them knew about sales
The agency runs ad accounts for multiple clients on Google, Meta and LINE (the dominant messaging app in Taiwan). Each platform defines spend, conversions and attribution differently, the team switched between three dashboards every day, and clients could only see results by waiting for a manual report. The core problem: the platforms know about clicks, not about sales, so nobody could calculate the real return on each ad (true ROAS).
- Client
- Healthcare advertising agency
- Scope
- Ad data integration
- Key result
- Three platforms, one view · true ROAS
The problems we found
- Spend, conversions and attribution windows are defined differently on each platform, so there is no common basis for comparison
- The team switched between three ad dashboards every day and assembled client reports by hand
- The ad platforms cannot calculate the real return on each ad
What we changed
- Daily automatic data pulls from all three platform APIs (LINE has no official SDK, so we implemented the request signing ourselves)
- A unified metrics layer that standardizes currency, time zone and attribution rules
- Multi-tenant access control: the internal team sees everything, and each client logs in to see only its own data
- Booking and sales data connected to calculate clinic-level true ROAS, with every data layer labeled honestly for how reliable it is
Results
- Three platforms and many client accounts in one view, updated daily with no manual work
- For the first time, ad spend can be matched to actual sales, not to the conversions the platforms report for themselves
Get the data foundation solid first; only then does AI analysis mean anything. If the data can't be trusted, AI just produces wrong conclusions faster.
Can your ad spend be matched to actual sales?
Start with a free 30-minute call about how the work runs today, and we'll judge whether a closer look is worthwhile. Finding where it really gets stuck means looking at the actual workflow.