Henkel
genAI content supply chain for one-to-one personalization at scale
In March 2024 Henkel expanded its Adobe partnership to move its content supply chain to genAI (Firefly Custom Models inside the RAQN platform), bringing production tasks that took hours or days down to minutes and delivering one-to-one personalization at scale, illustrated by Schwarzkopf recommendations based on hair.
Objective
Industrialize the content supply chain to deliver one-to-one personalization at scale across the brand portfolio, cutting time and cost without stepping outside brand and commercial-safety rules.
The deployment
In March 2024 Henkel expanded its partnership with Adobe to move its content supply chain to genAI and deliver personalization at scale across its global portfolio. Adobe Firefly and Experience Cloud are integrated into RAQN, Henkel's digital platform built in 2021 for consumer and retail insights. With Firefly Custom Models, teams train and fine-tune generative models on Henkel's own assets to produce on-brand, compliant, commercially safe content. Cited example: the hair care brand Schwarzkopf can generate visuals for one-to-one personalization of product recommendations based on a consumer's hair color, style, or length. Henkel says production tasks that would have taken hours or days can be brought down to minutes, which speeds up production and smooths digital campaign workflows while increasing the volume of personalized messages.
Results Proof C
Official Henkel press release (subject brand, T1) detailing the rollout and platform, corroborated by trade press. Gains stated in orders of magnitude rather than as an isolated financial figure, hence C.
How it works
Documented architectureThe stack in detail
- llm Adobe Firefly Custom Models Generative image models trained and fine-tuned on Henkel's own assets to produce on-brand, commercially safe content
- plateforme Adobe Experience Cloud Campaign and experience orchestration suite integrated into the Henkel platform
- plateforme Adobe Real-Time Customer Data Platform CDP that unifies consumer data and provides the one-to-one personalization signal (e.g. Schwarzkopf recommendations based on hair)
- infra RAQN Henkel's in-house digital platform, built in 2021 for consumer and retail insights, into which the Adobe building blocks are integrated
How it runs, concretely
For ops teams-
1Brand model training data team / Adobe
Firefly Custom Models fine-tuned on Henkel assets to produce on-brand, commercially safe content.
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2Content generation AI / marketing
Production of visuals and variations in minutes, integrated into RAQN.
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3Personalization marketing / CDP
Assembly of one-to-one personalized messages (e.g. Schwarzkopf recommendations) via the CDP.
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4Multichannel delivery marketing
Delivery of personalized experiences across digital campaigns and e-commerce.
The unified consumer data in Adobe Real-Time CDP and the quality of the Firefly Custom Models trained on brand assets. Without a proprietary brand corpus, the generated content drifts from the guidelines and commercial safety.
How your customers perceive this type of use
Sourced studiesLe paradoxe est documente des deux cotes : 71% des consommateurs attendent des interactions personnalisees et 76% sont frustres quand elles manquent (McKinsey, 2021), mais 75% declarent ne pas acheter aupres d'organisations auxquelles ils ne confient pas leurs donnees (Cisco, 2024). La « creepy line » est localisee : messages recus quelques secondes apres une recherche et suivi de localisation sont les pratiques qui mettent le plus mal a l'aise (Periscope by McKinsey, 2019).
Acceptance conditions
- La confiance dans le traitement des donnees precede l'achat : 75% ne achetent pas sans elle (Cisco 2024)
- Un cadre legal protecteur rassure : 59% des consommateurs disent que des lois fortes sur la vie privee les rendent plus a l'aise pour partager des informations dans des applications IA (Cisco 2024)
- La personnalisation elle-meme est attendue quand elle est consentie : environ la moitie des consommateurs (US 55%, UK 52%) disent s'inscrire souvent ou parfois a des services personnalises (Periscope by McKinsey 2019)
Red lines
- Le message declenche quelques secondes apres une recherche ou un achat : deuxieme ou troisieme cause de malaise selon les pays (Periscope by McKinsey 2019)
- Le suivi de localisation percu comme de la surveillance : 40% de malaise en Allemagne et au Royaume-Uni (Periscope by McKinsey 2019)
- Le mesusage des donnees personnelles par l'IA, devenu la premiere inquietude des consommateurs, a 53% et en hausse (Qualtrics 2025)
Sources: McKinsey & Company 2021 · Periscope by McKinsey 2019 · Cisco 2024 · Qualtrics 2025
How to replicate
Inference, not sourcedData prerequisites
- corpus of brand assets to train custom models
- unified consumer data (CDP)
- brand and commercial safety rules
Org prerequisites
- tooled content supply chain
- brand-safety governance of the custom models
- legal basis for one-to-one personalization
Possible stack
- custom generative models (Adobe Firefly type)
- real-time CDP
- content orchestration platform
The plan, step by step
- Step 1Gather the asset corpus of a pilot brand (visuals, packshots, guidelines) and set the brand-safety and commercial-safety rules with legal.Deliverable: Qualified training corpus and approved governance rules
- Step 2Train and fine-tune a custom model (Firefly Custom Models type) on those assets, with creative review of the outputs.Deliverable: Brand model producing on-brand visuals approved by the studio
- Step 3Connect the CDP for a first one-to-one personalization case on a segment (e.g. variations based on a consumer attribute), with the legal basis verified.Deliverable: First personalized content flow in production on a channel
- Step 4Integrate generation into campaign workflows so marketing teams produce the variations themselves.Deliverable: End-to-end tooled content supply chain workflow
- Step 5Measure production time, volume of personalized messages, and cost per campaign, then extend to other brands in the portfolio.Deliverable: Quantified review and portfolio expansion plan
First step: Train a custom model on a brand's assets and connect the CDP for a first personalization use case.
The same pattern, proven in other industries
Taobao
Real-time product recommendation with deep learning, served across hundreds of scenarios in the app
Amazon
Item-to-item collaborative filtering product recommendation engine, served across every touchpoint
ASOS
catalog-scale deep learning product recommendation, plus a conversational style assistant
Sources
- S1 Henkel Expands Partnership with Adobe to Deliver Personalization at Scale Through Generative AI Primary archive pending
- S2 How Henkel Plans To Stay On Brand With Generative AI Secondary archive pending
An error, newer info, a source?
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