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JENTIS Synthetic Users

JENTIS Synthetic Users is a must-have tool for data-driven Marketing professionals. With this exclusive technology, you can make the most of your compliantly captured real data and use machine learning models to replace information lost to lack of consent, adblockers, and ITPs. For the first time, you can compliantly share with third-party tools unique identifier parameters, such as GCLID and FBCLID, connected to an audience segment without singling out or exposing personal identifiers of specific users.

In this article, we will explain the concept of JENTIS Synthetic Users, how it works, and how it can help your business make better data-driven decisions and improve your marketing results.

The Data Challenge for Marketing Strategies

Ad blockers, browser anti-tracking features, and lack of user consent are causing a noticeable drop in the quantity and quality of data available for marketing.

The stricter regulation of cookie banners by EU data protection authorities are leading to a trend of consent rates below 50% in some regions. Combined with other anti-tracking features and ad blockers, this can result in only 30% of correct data being available.

The question arises: How do marketers enable data-driven marketing in such conditions? How can continuous business growth be guaranteed when the customer journey is not completely visible?

With JENTIS Essential Mode, it is already possible to capture website data from non-consented users for analytical purposes using fully compliant methods. Now, with JENTIS Synthetic Users, you can also compliantly recover and activate up to 100% of conversions that couldn't be tracked. For the first time, it’s possible to compliantly share with third-party tools unique identifier parameters, such as GCLID and FBCLID, connected to an audience segment without singling out or exposing personal identifiers of specific users.

Introducing JENTIS Synthetic Users

JENTIS Synthetic Users is a technology developed in collaboration with leading data protection lawyers - check our Legal Memorandum here - mathematicians and experts of the global measurement community. 

With this new technology, you can make the most of your first-party data and use machine-learning models to replace lost information with actionable synthetic data while protecting your users' privacy.

How it works:

  1. Use your real data captured with consent and create a machine-learning model to identify segments of users with similar characteristics. These segments will be used as predictors.

  1. Apply the model to your non-consented data captured with Essential Mode and predict which segment each user on your website belongs to. By placing non-consenting users into the appropriate segments, we can model their behavior based on consenting user data. Through machine learning, we can transform non-consenting users into synthetic users.

    Once predicted, all non-consented real data is deleted. It is important to remember that no PII is used in this process.

  1. During this process, all click IDs from each segment are combined into a pool, and the reference to an individual person is dissolved. Whenever a conversion happens in a segment, a random ID from that group is selected and shared with the advertising tool. This means that, for the first time, you can compliantly share with third-party tools unique identifier parameters, such as GCLID and FBCLID, connected to an audience segment without singling out or exposing personal identifiers of specific users.

What are the benefits?

With your conversions recovered, you can improve your marketing campaigns, have complete customer journeys, and make better data-driven decisions:

  • Increase your Conversion Rate and Return on Ad Spend by uncovering conversions previously lost due to no-consent and tracking preventions

  • Feed richer data to ad network algorithms to optimize your bids and campaign performance, helping you stay ahead of the competition.

  • Neutral and GDPR-compliant, with no reliance on third-party cookies, no transfer of personal data, and no need for dark patterns.

Read next:

JENTIS & Privacy: Synthetic Users

JENTIS Synthetic Users: How to create your Model

JENTIS Synthetic Users: How to set up your advertising tools


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