Mar 25, 2024Düsseldorf / Germany

Leveraging generative AI to boost efficiency and personalization

Henkel Expands Partnership with Adobe to Deliver Personalization at Scale Through Generative AI
  • Henkel will train Adobe Firefly using its own assets through Custom Models in a pilot that enables teams to rapidly produce personalized content that is safe for commercial use while adhering to brand standards.
  • The expanded partnership will advance Henkel's content supply chain by scaling content production with generative AI, helping drive efficiencies and agile workflows across digital marketing campaigns.
  • Generative AI capabilities in Adobe Experience Cloud and Adobe Firefly will reduce campaign costs and time by allowing teams to quickly create, deliver, and optimize personalized experiences at scale.

Henkel and Adobe have expanded their partnership to advance Henkel's content supply chain with the power of generative AI and deliver personalization at scale across the company's global brand portfolio. For this purpose, the Adobe Firefly and Adobe Experience Cloud solutions will be used in Henkel's digital business platform RAQN.

Henkel has seen exponential growth in the demand for high quality and personalized content that meets the needs of digital marketing and omnichannel campaigns and product launches. With Adobe Firefly Custom Models, Henkel will be able to train and fine-tune Firefly generative AI models using its own assets to create on-brand content, accelerating content production and streamlining repetitive tasks. For example, it will allow teams behind Henkel's hair care brand Schwarzkopf to create a variety of visual assets to support true one-to-one personalization around product recommendations, based on a consumer's hair color, style or length.

"Generative AI is disrupting economy and society similar to the internet - but at lightspeed. We must adopt to and capture these new technologies early on to drive innovation and open up new opportunities for Henkel," said Michael Nilles, Chief Digital & Information Officer at Henkel. "Together with our strong partner Adobe, we will significantly advance our content and marketing workflows using responsible generative AI, innovating how we produce assets at scale and deliver personalized, omnichannel experiences."

"Generative AI is reshaping what we thought possible to deliver personalization at scale across data, content and customer journeys," said Luc Dammann, President of EMEA at Adobe. "With Adobe Firefly and Adobe Experience Cloud, Henkel is leveraging natively integrated generative AI capabilities to power its digital strategy and set a new standard around efficiency, reshaping how its iconic brands approach content production, campaign optimization, and personalized customer experiences."

Committed to deliver personalized experiences to its consumers through its existing digital business platform RAQN - powered by Adobe enterprise applications including Adobe Experience Platform and Adobe Real-Time Customer Data Platform - Henkel has a single, unified view of its consumers and customers. With that, Henkel will be able to leverage other generative AI capabilities embedded in Adobe's product landscape to orchestrate journeys with auto-generated message variations that drive consumer engagement. When combined with visual assets created in Adobe Firefly, Henkel can quickly deliver personalized marketing campaigns, website creative, and mobile experiences that strengthen consumer loyalty and prevent messaging fatigue.

In the past, digital marketing campaigns were often restricted to limited variations of assets and copy variations. With the power of generative AI, Henkel can combine and tailor content for different channels and increase the volume of tailored messages. Content production tasks that would have taken hours or days, can be brought down to minutes, helping Henkel quickly create consistent, on-brand, compliant, and commercially-safe content.

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Henkel AG & Co. KGaA published this content on 25 March 2024 and is solely responsible for the information contained therein. Distributed by Public, unedited and unaltered, on 25 March 2024 08:02:04 UTC.