Marketing Personalization
Bosch China wanted to improve pre-sales support by connecting offline and online consumer behavior, increasing product awareness, improving customer experience, and enabling more effective cross-selling across product groups.
Reported impact
Bosch launched a knowledge graph algorithm on an online Bosch China e-commerce platform and deployed an onsite toolkit for the Bosch Home Appliances Brand Experience Center, giving the business a more digitalized and personalized pre-sales engagement model that can reach a large member and customer base.
Bosch China’s IoT-020 project uses the Bosch Consumer Data Center as the shared data foundation for pre-sales personalization across business units including Bosch Home Comfort, BSH Home Appliances, Bosch Power Tools, and Bosch Mobility Aftermarket. In physical stores, a store digitalization toolkit with sensors, embedded IoT, QR codes, and WeChat interactions captures offline browsing behavior and links it to member actions such as saving digital product flyers, so offline engagement can be analyzed alongside online activity. The recommendation system then applies AI techniques including a knowledge graph algorithm to build scenario-based user tags and personalized marketing strategies. These recommendations are delivered through MyBoschClub 3.0, SMS, and Bosch China’s e-commerce channels. Large Language Models (LLM) are also used in the AI generated content workflow to enrich user features for the recommendation model and help create personalized marketing text and images.
Consumer data from multiple Bosch business units is consolidated in the Bosch Consumer Data Center. In stores, the store digitalization toolkit collects offline interaction signals through sensors, embedded IoT, QR codes, and WeChat-linked actions. These data feed the recommendation system and knowledge graph algorithm, which create user tags and personalized strategies that are delivered through MyBoschClub 3.0, SMS, and Bosch China e-commerce channels.
"A key milestone was achieved by launching a knowledge graph algorithm to an online Bosch China e-commerce platform and launching an onsite toolkit for the Bosch Home Appliances Brand Experience Center of Bosch China."
"Bosch China will use AI techniques such as knowledge graphs to create scenario-based user tags and personalized marketing strategies for the business units."
"Large Language Models (LLM for short) are used, for example, to add user features and then embed them in the recommendation model to improve its performance."
"The project is based on the Bosch Consumer Data Center operated by RBCN/BUD."
"The recommendation system will be integrated into the new version of MyBoschClub, which will be launched this year: MyBoschClub 3.0 is the next generation of Bosch loyalty and membership applications in WeChat."
"The results of the project can impact around 6 million Bosch members and 10 million Bosch customers on the e-commerce platform and offline business."
"With the help of sensors and embedded IoT, users' online shopping behaviour can be emulated to offline shopping to improve the customer experience offline as well."
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