Aeon Retail shared how AI personalization boosts purchase rates.
They assign 170 attribute scores per customer.
One case showed purchase rates improved 5.5-6 times.
What happened
Aeon Retail uses AI to assign 170 attribute scores to customers and dynamically match them with product characteristics, improving purchase rates by 5.5 to 6 times in one case study.
Why it matters
The company integrates this with a mid- to long-term PDCA process, pre-analyzing purchase data to segment non-buyers and customers. It also involves about 110,000 store employees nationwide in the operation design.
What to watch
The video details co-creation examples with manufacturers, such as Asahi Super Dry with crab, Nescafe bread and coffee for breakfast scenes, and Coca-Cola Ayataka developing a special onigiri with the deli team.
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Aeon Retail's presentation, delivered by retail media promotion department head Kaori Tanaka, illustrates how the company leverages data and AI to enhance marketing precision. By pre-analyzing purchase data to segment customers and using AI to assign 170 attribute scores, the company can dynamically match products to consumer preferences. The improvement in purchase rates by 5.5-6 times in a specific case underscores the potential of this approach.
The company's strategy also emphasizes organizational collaboration, such as the 'double ownership system' with the merchandise division and weekly meetings for rapid decisions. Additionally, including approximately 110,000 store employees in operations ensures that strategies are executed consistently at the store level. Co-creation with manufacturers, like Asahi Super Dry with crab and Nescafe for breakfast scenes, highlights how data-driven insights can lead to innovative cross-merchandising.
The video, part of a series, offers practical insights for retailers and marketers looking to adopt similar AI-driven personalization and PDCA frameworks.
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