---
title: UserJournAI Privacy – Privacy-first behavioral intelligence
description: "Discover UserJournAI’s privacy-first approach: understand behavior, generate probabilistic personas and activate qualified audiences without relying on individual identifiers or third-party cookies."
image: https://userjournai.com/hubfs/9.UJ-privacy.jpg
---

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)](https://userjournai.com/en/home?hsLang=en)

- [Platform](https://userjournai.com/en/platform?hsLang=en)
- [How it works](https://userjournai.com/en/how-it-works?hsLang=en)
- [Use cases](https://userjournai.com/en/use-cases?hsLang=en) 
    - [Retail](https://userjournai.com/en/use-cases/retail?hsLang=en)
    - [E-commerce](https://userjournai.com/en/use-cases/e-commerce?hsLang=en)
    - [Media agencies](https://userjournai.com/en/use-cases/media-agencies?hsLang=en)
    - [DOOH](https://userjournai.com/en/use-cases/dooh?hsLang=en)
- [Resources](https://userjournai.com/en/blog?hsLang=en)

[FR](https://userjournai.com/fr/privacy-rgpd) [EN](https://userjournai.com/en/privacy) 

[Platform access](https://platform.userjournai.com) [Request a demo](https://userjournai.com/en/contact?hsLang=en)

[Platform](https://userjournai.com/en/platform?hsLang=en) [How it works](https://userjournai.com/en/how-it-works?hsLang=en)

Use cases

[Overview](https://userjournai.com/en/use-cases?hsLang=en) [Retail](https://userjournai.com/en/use-cases/retail?hsLang=en) [E-commerce](https://userjournai.com/en/use-cases/e-commerce?hsLang=en) [Media agencies](https://userjournai.com/en/use-cases/media-agencies?hsLang=en) [DOOH](https://userjournai.com/en/use-cases/dooh?hsLang=en)

[Resources](https://userjournai.com/en/blog?hsLang=en)

[Request a demo](https://userjournai.com/en/contact?hsLang=en) [Platform access](https://platform.userjournai.com)

Privacy-first intelligence

# Understand behavior without relying on individual identifiers

UserJournAI helps brands, agencies and media owners analyze behavior, generate probabilistic personas and activate qualified audiences from aggregated and anonymized signals, through an approach designed to work in a privacy-first environment.

Privacy-first Aggregated signals Probabilistic personas Without third-party cookies Qualified audiences

[Request a demo](https://userjournai.com/en/contact?hsLang=en) [Discover the platform](https://userjournai.com/en/platform?hsLang=en)

---

New paradigm

## Marketing is entering a new phase

For years, the advertising ecosystem was structured around individual tracking, third-party cookies, persistent identifiers and the massive collection of personal data.

Usage is changing, regulations are becoming stricter, browsers are gradually limiting tracking mechanisms, and users expect greater transparency about how their data is used.

The challenge is no longer simply to target more precisely. It is to keep understanding audiences, testing marketing hypotheses and activating the right segments without relying on individual identification logic.

Less dependence on third-party cookies and persistent identifiers.

More transparency in how behavior is analyzed.

A need to understand audiences without rebuilding individual profiles.

A need for more durable models for marketing activation and measurement.

From individual tracking to behavioral intelligence

Individual profile

→

Probabilistic audience

Third-party cookie

→

Aggregated and anonymized signals

Named history

→

Observable collective behavior

Opaque targeting

→

Explainable audience qualification

UserJournAI approach

## A probabilistic reading of behavior

UserJournAI does not seek to recognize a person. The platform interprets collective signals to qualify audiences, generate personas and test marketing scenarios.

What UserJournAI does

- Analyzes aggregated and anonymized signals.
- Detects observable collective behavior.
- Builds probabilistic audience models.
- Qualifies audiences according to their likely affinities and intent.
- Generates behavioral personas to explore reactions.
- Tests messages, offers and scenarios before activation.

What UserJournAI does not do

- Does not seek to identify a person.
- Does not build nominative profiles.
- Does not rely on third-party cookies as its main foundation.
- Does not reconstruct a real individual.
- Does not turn a persona into a digital copy of a person.
- Does not replace each advertiser’s own compliance rules.

Behavioral digital twins

## Probabilistic models, not copies of individuals

UserJournAI’s behavioral digital twins represent audiences and collective dynamics. They are used to better understand, test and compare marketing hypotheses.

01

### Behavioral signals

The models rely on observable, aggregated and contextualized signals, without nominative identification logic.

02

### Collective dynamics

The analysis focuses on trends, behavior and contexts shared by audiences, not on tracking individuals.

03

### Affinities and contexts

Audiences are qualified according to their likely affinities, interest signals and the environments in which they evolve.

04

### Probabilistic personas

Personas make it possible to explore the likely motivations, barriers and reactions of a given audience.

05

### Marketing tests

Teams can test messages, offers or scenarios with personas before activating a campaign.

06

### Scenario comparison

The platform helps compare several hypotheses to prioritize the most relevant audiences and activations.

Marketing chain

## Why this approach changes the marketing chain

UserJournAI’s privacy-first approach is not limited to a compliance constraint. It transforms the way audiences are understood, tested, activated and measured.

01

### Understand

Identify observable behavior, interest signals and collective dynamics that structure audiences.

02

### Test

Generate probabilistic personas to simulate reactions, compare messages and reduce uncertainty before launch.

03

### Activate & measure

Build qualified segments, activate them on compatible channels and connect campaigns to observable behavior.

Privacy by design

## A platform designed for a privacy-first environment

UserJournAI is designed to operate in an environment where individual identification is becoming less central, less durable and less acceptable.

01

### Aggregated signals

Analyses rely on collective, contextualized and anonymized signals.

02

### Probabilistic models

Personas represent likely behavior, not real individuals.

03

### Reduced dependence

The platform does not rely on third-party cookies as its main foundation for understanding.

04

### Durable approach

A logic designed for regulatory and technological changes in marketing.

05

### Activation control

Scenarios can be tested before launch to limit blind decisions.

[Product **Platform** Discover how UserJournAI turns aggregated signals into audiences, personas, activations and measurements. Discover →](https://userjournai.com/en/platform?hsLang=en) [Method **How it works** Understand the full chain: data, models, personas, tests, activation and measurement. Understand →](https://userjournai.com/en/how-it-works?hsLang=en) [Applications **Use cases** Explore retail, e-commerce, media agency and DOOH use cases. Explore →](https://userjournai.com/en/use-cases?hsLang=en)

Frequently asked questions

## Frequently asked questions about the privacy-first approach

Does UserJournAI use third-party cookies?

UserJournAI does not rely on third-party cookies as its main foundation for understanding. The platform prioritizes a reading based on aggregated, anonymized and probabilistic signals to qualify audiences.

How are personas generated?

Personas are generated from probabilistic audience models. They represent likely behavior, motivations and reactions of a group, not the real profile of an identifiable person.

What is a behavioral digital twin?

A behavioral digital twin is a probabilistic audience model built from collective signals, contexts and observable behavior. It is not a digital copy of a real individual.

Does UserJournAI identify individuals?

No. The platform’s objective is not to identify a person, but to understand audience dynamics from aggregated and anonymized signals.

Can audiences be activated without individual tracking?

Yes, depending on compatible channels. UserJournAI makes it possible to qualify audiences, build segments and activate scenarios without relying on individual recognition logic.

Is the data anonymized?

The platform works with aggregated and anonymized signals to produce a collective reading of behavior and audiences, without building individual nominative profiles.

Why is the probabilistic approach important?

It makes it possible to understand likely trends and behavior at audience scale, without claiming to know or track a specific person. It is an approach better suited to a privacy-first environment.

What is the difference with a traditional DMP or CDP?

A DMP or CDP generally organizes customer or media data around profiles and segments. UserJournAI focuses on probabilistic understanding of behavior, persona generation, scenario testing and activation of qualified audiences.

## Understand audiences in a *post-cookie world*

Request a demo to discover how UserJournAI helps understand, test, activate and measure audiences through a privacy-first approach.

[Request a demo](https://userjournai.com/en/contact?hsLang=en) [Discover the platform](https://userjournai.com/en/platform?hsLang=en)

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)](https://userjournai.com/en/home?hsLang=en)

UserJournAI helps teams understand real behavior, validate marketing decisions and activate higher-performing campaigns from launch.

[YouTube](https://www.youtube.com/@UserJournAI)[Facebook](https://www.facebook.com/Userjournai)[LinkedIn](https://www.linkedin.com/company/userjournai/)[Instagram](https://www.instagram.com/userjournai/)[X](https://x.com/UserJournAI)

Member of the collective [Hub&Up](https://www.hubandup.com)

### Company

- [About](https://userjournai.com/en/about?hsLang=en)
- [Manifesto](https://userjournai.com/en/manifesto?hsLang=en)

### Resources

- [Blog](https://userjournai.com/en/blog?hsLang=en)
- [Privacy](https://userjournai.com/en/privacy?hsLang=en)
- [FAQ](https://userjournai.com/en/faq?hsLang=en)

[Legal notice](https://userjournai.com/en/legal-notice?hsLang=en) — Copyright © 2026, User JournAI

```json
{
  "@context" : "https://schema.org",
  "@type" : "WebPage",
  "description" : "Understand real behavior, generate probabilistic personas and activate qualified audiences without relying on individual identifiers.",
  "isPartOf" : {
    "@type" : "WebSite",
    "name" : "UserJournAI",
    "url" : "https://userjournai.com"
  },
  "name" : "UserJournAI Privacy",
  "url" : "https://userjournai.com/en/privacy"
}
```

```json
{
  "@context" : "https://schema.org",
  "@type" : "Organization",
  "description" : "Understand real behavior, generate probabilistic personas and activate qualified audiences without relying on individual identifiers.",
  "name" : "UserJournAI Privacy",
  "sameAs" : [ "https://www.youtube.com/@UserJournAI", "https://www.facebook.com/Userjournai", "https://www.linkedin.com/company/userjournai/", "https://www.instagram.com/userjournai/", "https://x.com/UserJournAI" ],
  "url" : "https://userjournai.com/en/privacy"
}
```