How INFOnline Makes Digital Reach Fully Visible
Why extrapolation methods matter – and how we deliver valid results without consent-related data gaps
In a world where cookies are disappearing, consent rates are fluctuating, and ad blockers have become the norm, one question stands at the core of digital media analytics:
- How can reach be measured accurately, even when not all user actions can be directly tracked?
The answer lies in a transparent and privacy-compliant extrapolation method, which INFOnline has been using since 2023.
Why is extrapolation necessary?
Since the introduction of the EU GDPR and the TTDSG, obtaining explicit user consent has been a legal requirement for many forms of data measurement. But consent is dynamic — some users agree, others don’t. This inevitably leads to data gaps.
If these gaps were left unaddressed, they would distort the true picture of actual reach — which is why they must be closed through a robust methodology.
How our extrapolation works
INFOnline uses two complementary measurement systems and calculates key metrics by comparing them:
Example:
If the pseudonymous measurement (with consent) shows an average of 2 Page Impressions per Visit, this factor can be applied to the fully collected Page Impressions from the census-based measurement (without consent).
- This allows us to statistically estimate the expected number of Visits, even without consent — based on real usage patterns.
The result: Qualified, comprehensive metrics
- Visitors
- Visits
- Clients
These values are derived through clearly defined methods — even when only partial data is available.
Privacy-Compliant. Transparent. Future-Proof.
100% GDPR & TTDSG compliant
Not a black box — but a documented, verifiable mathematical model
High data validity while fully honoring user privacy preferences
Ready for real insights?
Get started now – with a reliable measurement system designed for professional use in the media market and flexible enough to adapt to your needs.