--- title: UserJournAI for retail – Real behavior, drive-to-store and impact measurement description: UserJournAI helps retailers, store networks and retail media players understand real behavior, validate audiences before activation, activate the right segments and measure drive-to-store impact. image: https://userjournai.com/hubfs/5.UJ-retail.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/cas-dusage/retail) [EN](https://userjournai.com/en/use-cases/retail) [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) Retail use case # Generate in-store traffic by targeting real behavior UserJournAI helps retailers, store networks and retail media players identify the most relevant audiences: those who can actually travel, visit the right areas and show a concrete affinity with the offer, qualify real intent and activate more effective local campaigns based on observable behavior. Catchment areas Drive-to-store Retail media Validation before activation Local activation [Request a demo](https://userjournai.com/en/contact?hsLang=en) [See how it works](https://userjournai.com/en/how-it-works?hsLang=en) --- Retail challenges ## The limits of traditional retail targeting Retail has many marketing signals, but still struggles to connect real behavior, physical footfall, intent and media performance. Activation decisions still too often rely on theoretical segments, declared targeting or poorly contextualized data. The result: local campaigns that can lack precision, budgets that are poorly allocated and difficulty proving the real impact on traffic and footfall. UserJournAI makes it possible to move beyond this logic by starting from observable behavior: mobility areas, territorial dynamics, interest signals, affinities and exposure contexts. Segments that are too generic to finely arbitrate local activations. An incomplete reading of catchment areas and mobility basins. Difficulty testing messages before media investment. Measurement still too often limited to delivery, not real-world impact. Retail: moving from assumed targeting to qualified audiences Generic socio-demographic profile → Audience built on observable behavior Theoretical area → Real mobility and footfall basin Message chosen by intuition → Message tested with behavioral personas Isolated media performance → Impact analyzed on behavior and field indicators Approach ## A behavioral reading of retail audiences UserJournAI turns aggregated behavioral signals into activatable audiences to help retail teams understand, test, activate and measure more precisely. 01 ### Identify areas and mobility basins Identify the most relevant territories, catchment areas and mobility dynamics around points of sale. 02 ### Understand behavior around stores Analyze routines, contexts, affinities and interest signals linked to audiences that can actually be exposed. 03 ### Qualify intent before activation Prioritize the audiences most likely to react to a local campaign, offer or commercial moment. 04 ### Test personas and marketing scenarios Generate behavioral personas, interact with them and test messages before committing media budget. 05 ### Activate qualified audiences Move from analysis to activation across compatible channels, with a local, national or drive-to-store logic. 06 ### Measure real impact Connect campaigns to field indicators: exposure, visits, observable behavior and business performance. Retail applications ## Examples of use in retail Concrete use cases to better prioritize your campaigns, qualify your audiences and connect activations to real-world behavior. 01 · Catchment area ### Catchment area optimization Identify real footfall basins around a store network. - Understand flows and mobility routines - Compare potential between areas - Prioritize activation territories ⇒ A more operational view of the areas to address. 02 · Audience ### Audience validation before a local campaign Test different segments before media activation to reduce delivery risk. - Qualify the highest-potential audiences - Compare several targeting hypotheses - Reduce uncertainty before investment ⇒ Better-oriented budgets from launch. 03 · Retail media ### Retail media & geolocated activation Activate high-potential audiences around specific commercial areas. - Build activatable local segments - Align audience, context and exposure area - Adapt campaigns to field realities ⇒ More precise and more coherent local activation. 04 · Drive-to-store ### Drive-to-store impact measurement Measure campaign impact on footfall and observable behavior. - Track traffic and visit indicators - Compare activated scenarios or segments - Connect media activation and field performance ⇒ Measurement closer to real business impact. 05 · Store opening ### Store opening launch or local highlight Identify priority local audiences before an opening, relaunch or commercial operation. - Analyze the potential of an area - Test messages before delivery - Activate the most relevant segments ⇒ A better-prepared local ramp-up. 06 · Territory ### Territorial competitive analysis Compare footfall dynamics and behavioral profiles between areas. - Identify behavior differences by territory - Understand footfall contexts - Adapt activations by area ⇒ A more territorialized media and commercial strategy. Personas & testing ## Test audiences and personas before activation UserJournAI makes it possible to generate probabilistic behavioral personas from real signals, then test messages, offers and scenarios before delivery. 01 ### Creative validation Compare several creative angles before launch to identify the most relevant ones for the target audience. 02 ### Message testing Evaluate promises, commercial mechanics or wording before committing media budget. 03 ### Express studies Launch a simulated study in minutes to collect structured feedback on an audience. 04 ### Intent qualification Understand what motivates or prevents store visits according to behavioral profiles. 05 ### Audience reaction simulation Interact one-to-one with personas to explore objections, expectations and potential reactions. Activation & measurement ## From analysis to media activation UserJournAI goes beyond insight. The platform also makes it possible to activate qualified audiences and measure real campaign performance. 01 ### Activation Deliver qualified segments on compatible media platforms: DOOH, social ads, open web, CTV or drive-to-store campaigns. 02 ### Management Track performance, compare activated audiences and adjust scenarios based on observed feedback. 03 ### Measurement Analyze impact on behavior and field indicators: exposure, visits, engagement, conversion or incremental sales. Retail benefits ## An approach to move faster from insight to action UserJournAI helps retail teams reduce uncertainty, improve local activations and better demonstrate field impact. Benefit 01 ### Reduce uncertainty before activation Make decisions based on observable behavior, not only on assumptions or theoretical profiles. Benefit 02 ### Improve the relevance of local activations Qualify audiences that can actually be exposed according to areas, contexts and mobility dynamics. Benefit 03 ### Connect marketing and field performance Measure the real impact of campaigns on observed behavior and business indicators. Benefit 04 ### Accelerate decision-making Move faster from analysis to activation thanks to personas, tests and activatable segments. [Method **How it works** Understand the complete data processing logic. Discover →](https://userjournai.com/en/how-it-works?hsLang=en) [Use cases **All use cases** Explore the other business applications of UserJournAI. Explore →](https://userjournai.com/en/use-cases?hsLang=en) [Compliance **Privacy** Understand the approach without individual personal data. Understand →](https://userjournai.com/en/privacy?hsLang=en) Frequently asked questions ## Frequently asked questions about retail How does UserJournAI help retail brands? UserJournAI helps retailers understand real behavior around points of sale, qualify the highest-potential audiences, test messages before delivery, activate relevant segments and measure campaign impact on real-world behavior. Can it work at local or national scale? Yes. The platform can be used to analyze a national network, compare several areas, work around a specific point of sale or prepare a local activation linked to an opening, commercial operation or key store moment. How are catchment areas analyzed? The analysis relies on aggregated and anonymized signals to understand mobility basins, footfall dynamics, territorial contexts and audience affinities. The objective is to move beyond a theoretical area and identify truly observable behavior. Can audiences be activated directly? Yes, on channels compatible with the platform. Qualified audiences can be used in DOOH, social ads, open web, CTV or drive-to-store campaigns, depending on objectives and available media environments. Can campaigns be tested before delivery? Yes. UserJournAI makes it possible to generate behavioral personas, interact with them, test several messages or scenarios and compare reactions before committing media investment. Which indicators can be measured? Indicators depend on the setup: exposure, engagement, store traffic, incremental visits, conversion, sales or drive-to-store performance. The goal is to connect activation to observable behavior and results. Is UserJournAI compatible with a privacy-first approach? Yes. The platform works from aggregated and anonymized signals. Analyses and personas represent audiences and collective dynamics, without seeking to identify individuals. How is drive-to-store impact measured? Drive-to-store impact can be analyzed by comparing activated audiences, areas or scenarios with observable behavior after exposure: footfall, incremental visits, movement intensity or commercial performance depending on available data. ## Want to improve your *drive-to-store* ? Request a demo to understand how UserJournAI can help your retail teams qualify audiences, test messages, activate the right segments and measure field impact. [Request a demo](https://userjournai.com/en/contact?hsLang=en) [Understand the method](https://userjournai.com/en/how-it-works?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, qualify retail audiences, activate the right segments and measure drive-to-store impact.", "isPartOf" : { "@type" : "WebSite", "name" : "UserJournAI", "url" : "https://userjournai.com" }, "name" : "UserJournAI for retail", "url" : "https://userjournai.com/en/use-cases/retail" } ``` ```json { "@context" : "https://schema.org", "@type" : "Organization", "description" : "Understand real behavior, qualify retail audiences, activate the right segments and measure drive-to-store impact.", "name" : "UserJournAI for retail", "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/use-cases/retail" } ```