Benetton Group: Enhancing Customer Experience with AI and Cloud-Based Analytics
- Analytics & Modeling - Real Time Analytics
- Automation & Control - Human Machine Interface (HMI)
- Consumer Goods
- Retail
- Sales & Marketing
- Real-Time Location System (RTLS)
- Track & Trace of Assets
- Cloud Planning, Design & Implementation Services
Benetton Group, a globally recognized fashion company with a network of 4,000 stores, was faced with the challenge of improving its online customer experience during the COVID-19 pandemic when physical stores were shut. The company had already digitized its shopping experience and built a marketing data lake to understand its customers better. However, it sought to enhance its recommendation tool for online customers and provide a more personalized, real-time shopping experience. The existing content management solution had a built-in recommendation tool, but it lacked sophistication. Benetton Group wanted to leverage advanced analytics and AI to gain detailed insights into shopping patterns, store performance in a multichannel environment, and how to localize recommendations for a global customer base.
Benetton Group is one of the best-known fashion companies in the world, operating in key global markets with a network of 4,000 stores. Founded in 1965, the Group has distinguished itself with its sense of style, bold use of color, and inclusive messaging. It is committed to the environment, human dignity, and societal transformation. During the COVID-19 pandemic, Benetton Group successfully digitized its shopping experience and built a marketing data lake to better understand its customers and their preferences. The Group is continuously planning for the future while living in the present.
Benetton Group turned to Google Cloud and used BigQuery and Discovery AI Solutions to build a data-driven omnichannel experience. The company adopted a multi-site approach, grouping different countries by language type to create customized recommendation models for each user. It took 90 to 120 days of data for each country from Google Analytics and BigQuery and imported it into Recommendations AI, which became the heart of real-time recommendations made to users on digital channels. After a successful proof of concept with one model trained in Recommendations AI, the Group rolled out its new solution within three months. It trained its models to show recommendations in various context-specific sections of the web, such as 'Frequently Bought Together' on product detail pages or 'Recommended for you' and 'Others you may like' on the checkout page. Benetton Group also redesigned its user experience, focusing on the recommendations panel to increase time on the site and reduce friction in the sales funnel.