AB InBev
retail media network on a B2B super app: automated auction and AI personalization of sponsored placements based on the retailer's profile, self-service for third-party brands
AB InBev turned its B2B ordering super app BEES (3.9 million monthly active users, $52.5 billion in GMV in 2025, 29 markets) into a retail media network, BEES Ads, built on Topsort's infrastructure: each sponsored placement is auctioned and targeted on the retailer's profile and purchase history, with third-party brands running their campaigns self-service.
Key points
- AB InBev turns its BEES ordering super app (3.9M monthly active users) into a retail media network with Topsort.
- Each ad is targeted on the retailer's profile and purchase history; brands manage their campaigns self-service.
- Automated auction: the advertiser pays only for the ads actually displayed.
- Foundation at scale: BEES generated $52.5B in GMV in 2025 (+12%), live in 29 markets, 72% of group revenue through B2B digital platforms.
Objective
Monetize the captive retailer audience of the BEES super app by turning it into a retail media network. AB InBev, a manufacturer and distributor, becomes a seller of advertising space on its own ordering channel: brands (its own and third parties) buy sponsored placements targeted at the retailers already reordering on the platform. Monetization is added on top of existing GMV, with no extra audience acquisition cost.
The deployment
BEES is AB InBev's B2B super app: retailers (grocery stores, bars, points of sale) use it to order and restock. AB InBev grafted a retail media network onto this channel, BEES Ads, built on Topsort's advertising infrastructure. Sponsored placements are inserted into the app's purchase journey. Each ad is targeted on the retailer's profile and purchase history, so brands reach the most relevant buyers. Booking works as an auction: the advertiser pays only for the ads that are actually displayed. Brands, including third parties, build, run, and track their campaigns self-service from the Be Ads platform, with real-time performance monitoring. The business model: AB InBev, which already owns the channel and the purchase data, sells audience on its own distribution network. The foundation is large and public: BEES generated $52.5 billion in GMV in 2025 (up 12%), was live in 29 markets as of December 31, with 72% of group revenue captured through B2B digital platforms, and an audience of 3.9 million monthly active users on which the network relies. The honest caveat: no advertising revenue specific to BEES Ads is broken out publicly, and the network's mechanics are described only by the vendor Topsort.
Results Proof B
The BEES Ads mechanics (automated auction, AI personalization based on the retailer's profile and purchase history, self-service for brands, 3.9 million monthly active users) are documented by a quantified case study from the vendor Topsort, which corresponds to level B (quantified platform/vendor case study). The scale of the foundation is corroborated by an established press source (Digital Commerce 360) reporting AB InBev's 2025 annual results: $52.5B in GMV (+12%), 29 markets, 72% of revenue through B2B digital platforms. The caveat that prevents a higher rating: no advertising revenue specific to BEES Ads is broken out in a financial document, no precise launch date is published, and the description of the advertising setup rests on the vendor alone. The official AB InBev page consulted does not mention BEES Ads.
How it works
Documented architectureThe stack in detail
- plateforme BEES AB InBev's B2B super app through which retailers order and restock. Serves as both the channel and the data source (profile and purchase history) for the BEES Ads network.
- plateforme Topsort Auction-based retail media infrastructure that powers BEES Ads: targeting of sponsored placements, automated auction, self-service interface, and real-time campaign tracking.
How it runs, concretely
For ops teams-
1Making inventory available AI
AB InBev opens sponsored placements in the BEES app's purchase journey, backed by Topsort's infrastructure.
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2Self-service campaign creation marketing
The advertising brand builds its campaign, sets its budget and targets directly on the Be Ads platform.
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3Targeting and auction AI
On each display, the most relevant ad for the retailer is selected by auction based on its profile and purchase history; the advertiser pays only for the ads displayed.
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4Tracking and management marketing
The brand tracks performance in real time and adjusts, activates, or pauses its campaign.
The retailer's profile and purchase history on BEES: this is what targets each ad toward the relevant buyers. Without this first-party ordering data, personalization and the value of the inventory collapse.
How your customers perceive this type of use
Sourced studiesLe pricing algorithmique est le terrain le plus inflammable : 68% des consommateurs disent se sentir leses quand les marques utilisent le pricing dynamique et 80% jugent plus dignes de confiance les marques aux prix constants (Gartner, 2024). L'equite percue varie selon le secteur : le pricing dynamique n'est juge juste que par 33% a 40% des repondants selon qu'il s'agit de concerts ou de cinemas (YouGov, 17 marches). Le prix personnalise par les donnees individuelles est le plus rejete : 47% des Americains s'y opposent fermement (Consumer Reports, 2024).
Acceptance conditions
- La constance des prix comme signal de confiance : 80% jugent plus fiables les marques aux prix stables (Gartner 2024)
- Le secteur conditionne l'equite percue : le pricing dynamique est mieux tolere pour les cinemas (40% le jugent juste) que pour les concerts (33%) (YouGov 2024)
Red lines
- Le pricing dynamique percu comme abus : 68% se sentent leses (Gartner 2024)
- Le prix individualise a partir des donnees personnelles : 47% d'opposition ferme (Consumer Reports 2024)
- Les frais caches et hausses imprevues, vecus par 79% des consommateurs sur un an et associes a la perte de confiance (Gartner 2024)
Sources: Gartner 2024 · YouGov 2024 · Consumer Reports 2024
How to replicate
Inference, not sourcedData prerequisites
- A proprietary digital channel with a captive audience (app, marketplace, portal) that a population returns to regularly
- First-party behavioral and purchase data per user, suited to targeting placements
- An identifiable inventory of placements across the journey (home, search, product page, cart)
Org prerequisites
- A dedicated retail media / ad sales team, separate from brand marketing, to sell the inventory and hold the advertiser relationship
- A compliance framework for the use of targeting data (GDPR if EU audience, information for business users)
- Clear governance between in-house brands and third-party brands that will buy the same inventory
Possible stack
- A turnkey auction-based retail media infrastructure (Topsort type) plugged into the existing app
- A self-service interface for brands to build and track their campaigns
- A targeting/personalization layer backed by first-party purchase data
- A measurement and per-display billing module
The plan, step by step
- Step 1Qualify the audience of the proprietary channel (return frequency, volume, purchase data per user) and estimate the value of a targeted advertising inventory.Deliverable: Diagnostic of the monetizable audience and the available targeting data.
- Step 2Plug an auction-based retail media infrastructure into the app, with targeting backed by the retailer's profile and purchase history.Deliverable: Targeted sponsored placements, awarded by auction, in the journey.
- Step 3Open a self-service interface for brands to build, run, and track their campaigns.Deliverable: Autonomous advertiser journey, from creation to real-time reporting.
- Step 4Bill per display (payment for the ads displayed) and measure advertiser performance to retain demand.Deliverable: Monetization loop with advertiser ROI measurement.
- Step 5Expand the inventory and open it to third-party brands, framing data compliance and in-house/third-party governance.Deliverable: Retail media network open beyond the group's brands.
First step: Map the captive audience of the proprietary channel and the available purchase data, then identify a first pocket of sponsorable placements in the journey, before opening an auction pilot to a small panel of brands.
The same pattern, proven in other industries
Airbnb
dynamic price suggestion to sellers (host pricing)
Delta Air Lines
AI dynamic pricing (yield management)
Kuaishou
ad monetization through generative models: generative recommendation and intelligent bidding, plus creative generation and rebuilt merchant search
Sources
- S1 BEES Launches BEES Ads Powered by Topsort Interested party archive pending
- S2 AB InBev expands BEES B2B platform as volumes decline Established press archive pending
- S3 BEES (Topsort customer story) Interested party archive pending
An error, newer info, a source?
This page lives on its accuracy. If a figure has moved, if the deployment has changed, or if you have a higher-quality source, tell us. Every sourced correction is verified before publication.