---
title: UserJournAI – Behavioral AI to understand, validate and activate audiences
description: UserJournAI is a behavioral AI platform that helps brands, agencies and media owners identify, understand and activate audiences based on real behavior, with pre-activation validation and a privacy-first approach.
image: https://userjournai.com/hubfs/1.UJ-Home-2.jpg
---

[![UserJournAI](data:image/png;base64,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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/accueil) [EN](https://userjournai.com/en/home) 

[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)

Behavioral AI to understand, validate and activate audiences

# Understand, validate and activate your audiences *based on real behavior.*

UserJournAI helps brands, agencies and media owners move from targeting based on assumed profiles to activation built on real behavior. The platform helps teams understand audiences, validate marketing decisions and activate the right segments before media investment.

Real behavior Decisions validated before activation Activation without third-party cookie dependency GDPR-ready privacy-first approach

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

---

The problem

## You target profiles. You measure results. Between the two, real behavior remains invisible.

Advertising platforms optimize after delivery. Campaigns are therefore launched before they are truly understood, creating a structural gap between targeting, message and performance.

Most marketing decisions still rely on assumptions: interests, lookalike audiences or socio-demographic targeting. These approaches describe profiles, but they do not reflect how consumers actually behave.

Approximate audiences built on weak signals

Messages delivered without real upfront validation

Performance that varies across campaigns and periods

Media budgets partly wasted due to limited upfront confidence

Changing the marketing logic · Before → After UserJournAI

Assumed profiles→Observable behavior

Testing in production→Validation before delivery

Broad targeting→Audiences that can actually be activated

Uncertain performance→More predictable decisions

Intuition alone→Understanding based on real signals

The shift

## Understand before activating

UserJournAI reverses the logic of marketing targeting: before investing, you understand; before activating, you validate. The platform models real behavior and turns aggregated signals into measurable marketing decisions.

Today’s market

UserJournAI

Declared profiles

Real behavior

Optimization after launch

Validation before activation

Intuition-led decisions

Decisions based on observable signals

Budget exposed to uncertainty

Budget committed with greater confidence

How it works

## From raw signal to activation

The platform turns aggregated behavioral signals into activatable segments, consumer insights and validated marketing decisions through a six-step sequence. The models do not invent: they interpret real, cross-referenced and contextualized signals.

01

### Signal collection

Aggregated data from anonymized physical mobility, digital signals, socio-demographic data, consumer panels and media environments.

Aggregated data

02

### Behavioral modeling

Behavioral AI cross-references signals to detect correlations: movements, life rhythms, visited areas, affinities and consumption patterns.

Behavioral AI

03

### Audience building

Segments are built from observable behavior to represent probabilistic audiences that can actually be activated, without individual identification.

Segmentation

04

### Insight understanding

The platform helps understand who audiences are, where they are, what motivates them, what holds them back and why they act.

Insights

05

### Decision validation

Audiences and messages are tested before delivery to reduce marketing risk and strengthen relevance.

Pre-activation

06

### Activation and measurement

Campaigns are activated across key media environments and continuously measured through to visits, leads or sales depending on the use case.

Continuous activation

Data sources

## Where do the signals come from?

UserJournAI combines several families of complementary signals to build a probabilistic understanding of audiences. The goal is not to identify a person, but to understand collective, anonymized and activatable dynamics.

**Anonymized physical mobility**Flows, high-traffic areas and mobility catchment zones

**Aggregated socio-demographic data**Territorial context, IRIS/INSEE data and area characteristics

**Consumer panels**Affinities, intentions and structured declared behavior

**Contextual signals**Trends, media environments and interest signals

Use cases

## Built for your challenges

Store networks, e-commerce teams, media agencies and DOOH media owners use UserJournAI to reduce uncertainty, refine targeting and better manage performance.

Challenge

### Store networks

Attract consumers who actually move

- Identify real catchment areas based on flows
- Target the audiences most likely to visit points of sale
- Understand physical journeys and local dynamics
- Measure campaign impact on visits and valuable traffic

⇒ More qualified traffic, less waste

[Optimize in-store traffic](https://userjournai.com/en/use-cases/retail?hsLang=en)

Challenge

### E-commerce

Target more concrete purchase intent

- Identify audiences with strong real affinity with the offer
- Better understand offline signals that influence online purchases
- Validate messages before delivery to limit unnecessary testing
- Improve conversion through more precise decisions

⇒ More conversion, less uncertainty

[Understand e-commerce challenges](https://userjournai.com/en/use-cases/e-commerce?hsLang=en)

Challenge

### Media agencies

Strengthen performance and differentiation

- Bring clients more precise audience intelligence
- Support media recommendations with behavioral signals
- Reduce the gap between strategy, targeting and results
- Create more value through a better reading of behavior

⇒ More performance, more credibility

[Improve client performance](https://userjournai.com/en/use-cases/media-agencies?hsLang=en)

Challenge

### DOOH media owners

Measure real impact on physical flows

- Understand the audiences actually exposed to screens
- Qualify flows based on behavior and affinities
- Better value inventory with a more useful field-level reading
- Demonstrate campaign impact beyond raw exposure

⇒ More proven value, more measured impact

[Measure real impact](https://userjournai.com/en/use-cases/dooh?hsLang=en)

Privacy & compliance

## Designed to work without individual personal data

UserJournAI works from aggregated and anonymized data. The platform was designed to improve marketing performance without relying on individual identifiers, without third-party cookies and with a GDPR-ready privacy-first approach. It does not seek to recognize people: it models collective behavior to produce probabilistic representations of audiences.

No individual personal data

Marketing decisions built from aggregated and anonymized data

Privacy-first approach

Compliance is not an added layer; it is part of the architecture

Compatible with your existing stack

The platform integrates with your media environments and existing tools

Performance without compromise

Better understand and activate audiences without compromising privacy

Frequently asked questions

## Essential answers to understand UserJournAI

A clear summary to understand the platform’s positioning, how it works, its use cases and its privacy-first logic.

What is UserJournAI?

UserJournAI is a marketing intelligence platform based on behavioral AI. It enables brands, agencies and media owners to identify, understand and activate audiences based on real behavior by cross-referencing physical mobility and behavioral signals, without using individual personal data.

How is UserJournAI different from traditional advertising platforms?

Traditional platforms mainly target profiles, declared interests or lookalike audiences. UserJournAI targets real behavior and makes it possible to validate audiences and messages before media activation, reducing uncertainty and improving performance from launch.

How does the platform work?

The platform collects aggregated signals, applies behavioral AI models, builds activatable audiences, validates marketing decisions before delivery, then activates and measures campaigns in a continuous improvement loop.

Where does the data come from?

UserJournAI combines anonymized mobility signals, aggregated socio-demographic data, consumer panels and contextual signals. These sources are used to build a probabilistic understanding of audiences, without individual identification.

What does “behavioral digital twins” mean?

They are not digital copies of individuals. They are probabilistic representations of audiences, built from collective, anonymized and contextualized signals, to understand behavior, test hypotheses and qualify intent before activation.

Who is UserJournAI designed for?

UserJournAI is designed for store networks, e-commerce teams, media agencies and DOOH media owners that want to better understand their audiences, reduce marketing risk and improve campaign precision.

Is UserJournAI GDPR-compliant?

Yes. UserJournAI works from aggregated and anonymized data, without using individual personal data. Its architecture is privacy-first by design and built for GDPR-compliant use.

## Stop guessing, start *understanding*

Request a demo to discover how UserJournAI helps your teams make more reliable decisions, target audiences more precisely and improve campaign performance.

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

[![UserJournAI](data:image/png;base64,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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" : "Organization",
  "name" : "UserJournAI",
  "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"
}
```