Fiscal data operators process receipt information. Permitted anonymised signals may help define category, brand or competitor-buyer audiences and assess purchase recency and frequency. Activation and measurement use an agreed partner matching process. Advertisers should not receive individual receipts; data fields, minimum group sizes and permitted use depend on suppliers and applicable rules.
How it works
- 01Define category and purchase criteria
- 02Confirm permission and availability
- 03Build an anonymised segment
- 04Activate and measure
From an available receipt to an audience
- 01EventPurchase in an available category
- 02RulesPermitted use and anonymisation
- 03SegmentCategory, brand, recency and frequency
- 04ActivationPartner matching and media
Different purchase audiences
Category, brand and competitor buyers represent different marketing hypotheses. Recency and frequency only make sense against the product's purchase cycle.
Matching and activation
The partner workflow maps permitted purchase signals into an addressable segment. Matching rules, minimum scale and available fields must be agreed before launch.
A role in Sales Lift
Available purchase data can support exposed versus control comparisons. A matched ad exposure and purchase alone does not establish causality.
The same source answers two different questions
- find category buyers
- consider recency and frequency
- check segment scale
- match available purchases
- compare test and control
- report outcomes and limits
What purchase data can solve
Fiscal signals can identify category or brand buyers, purchase recency and frequency within available coverage. They are especially valuable when the final transaction happens in an offline pharmacy and web analytics cannot observe it.
Designing a buyer segment
A purchase-segment brief needs the category, brand list, purchase period and exclusions. For a switching test, decide whether to include own-brand buyers who also bought a competitor. Then check scale and activation within the available partner environment. Tighter criteria may leave too few observations; extending the window requires another check of recency and relevance.
From purchase signal to measurement
Purchase data can inform the audience before launch and support Sales Lift after exposure. Targeting asks whom to reach; the study asks how buying behaviour differed between exposed and control groups. Design and purchase window are set before launch.
Value for the brand
Purchase data helps select groups with buying experience in the category. In the Radevit Active case, receipt-based profiling informed targeting; the ALMAG case compared purchases in a Sales Lift study. Segment composition, scale and the chosen measure are assessed separately for each new project.
Purchase frequency and recency
Interpret purchase recency and frequency in relation to pack size, the category cycle and data coverage. No new receipt in the source does not prove that a person stopped buying: the purchase may fall outside available coverage. For repeat communication, agree what counts as recent and when the observation stops being useful. There is no universal window for every medicine.
Limitations
Fiscal data do not cover every sale. Availability depends on partners, lawful use, match quality and minimum group size.
Questions
Can competitor buyers be reached?
Yes, where permitted anonymised fiscal signals and sufficient segment scale exist. Brands, lookback period and exclusions are agreed before launch.
Does the brand receive individual receipts?
No. The brand receives permitted segments and aggregated results, not identifiable buyer records or receipts.
Do fiscal signals cover every market sale?
No. They represent available partner coverage, so market-level claims must reflect that coverage.
Can purchases after advertising be measured?
Yes, if data and scale support a Sales Lift study. Test and control groups, purchase window and KPI must be set before the campaign.
How is the purchase lookback window selected?
It follows the category's buying cycle and the campaign goal. We check signal volume and frequency before setting the window.