Most marketing teams assume they understand how much data they lose through consent banners. In reality, the consent rate they see on the website rarely reflects what happens inside their paid traffic. The result is a hidden measurement problem that affects attribution, optimisation and ultimately business outcomes.
This issue is known as the consent gap. It describes the difference between what you think you can measure and what your ad platforms are actually able to see.
Why the consent gap exists
Many organisations assume their data loss is the same across all user groups. In practice, this is almost never the case. The consent gap appears because marketers fall into one of three common situations.
Situation 1: Platform bias in reported conversions
Teams assume that performance platforms show the full picture. In reality, these platforms only display data from consenting users or their own modelled estimates. As a result, the numbers you see inside your accounts do not represent the actual number of conversions your website receives.
Situation 2: Misinterpreting overall consent rates
Teams try to correct missing conversions by taking the overall website consent rate and applying it directly to the numbers they see in their advertising platforms.
This creates a simple mathematical extrapolation that looks reasonable but ignores how differently various user segments behave. It is a calculation error based on an incorrect assumption.
Situation 3: Relying on misleading averages
Teams assume that a high average website consent rate means their performance data is reliable. They overlook that users arriving from paid campaigns often have a much lower consent rate and that converters, in particular, are tracked far less consistently. It is not a calculation error but a strategic misinterpretation of what the average actually represents.
In all three cases, budget and optimisation decisions are made on data that does not match reality.
How the consent gap affects decision making
When performance platforms receive fewer real conversion signals, several issues emerge at once.
- Conversion volumes appear lower than they are
- Channels and campaigns look weaker than in reality
- Algorithms lack enough data to optimise bidding
- Budget allocation becomes uncertain
- Scaling becomes harder because signal density is too low
These effects compound during high spend periods such as Black Friday, where even small gaps have a significant impact.
Why data visibility matters for performance
Modern advertising systems need dense, accurate data to work well. When half of your audience becomes invisible, several challenges appear at once:
- Conversions from non consenting users never show up, which makes campaigns look weaker than they are
- Bidding algorithms receive fewer learning signals
- Audience expansion tools have less clarity
- Performance decisions are made on incomplete numbers
Closing the consent gap with Synthetic Users
Synthetic Users addresses these issues by restoring key signals without processing personal data from non-consenting users. This allows advertisers to send complete conversion feedback to Google Ads, Meta, TikTok and other platforms. These systems receive the signals they need to optimise bidding and targeting even when a large portion of the audience opted out of tracking.
What Synthetic Users is
Synthetic Users is an AI-based server side feature using your own first party data to create anonymous, privacy safe representations of users who decline consent. These synthetic profiles are based on real behavioural patterns, not external averages or rough statistical modelling. The aim is straightforward: activate the entire audience, even when users do not allow tracking, while staying fully within consent boundaries.
With more complete conversion feedback flowing into ad platforms, advertisers often see significant performance gains.
The benefits for marketing teams
Synthetic Users provides a clearer, more complete picture of campaign activity. Organisations using the feature report improvements across important metrics. Key advantages include:
- Higher ROAS because platforms receive more conversion feedback
- Lower cost per conversion through better bidding
- Higher conversion rates due to more stable optimisation
- More accurate budgeting based on true campaign impact
- Access to previously unreachable audience segments
- Better insight during high traffic periods
Teams gain a more realistic understanding of their performance and can scale campaigns with greater confidence. Successful adopters like Giesswein and Pixum have seen ROAS uplifts of up to 25% and conversion rate increases of almost 30% thanks to accessing more complete data, stronger audience reach and campaign optimization despite of reduced consent rates.
Read the full Giesswein case study and Pixum case study.
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