Google Cloud Platform Case Studies Benetton Group: Enhancing Customer Experience with AI and Cloud-Based Analytics
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Benetton Group: Enhancing Customer Experience with AI and Cloud-Based Analytics

Google Cloud Platform
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.

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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.

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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.

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The implementation of Recommendations AI and the redesign of the user experience have significantly improved Benetton Group's online customer engagement. The company found that users who clicked on the recommendations panel had a conversion rate six times higher than those who didn't. The sales from these interactions were also 7% higher on average than sales that hadn't come through the recommendations panel. Furthermore, customers who engaged with the panel stayed on the site almost three times longer than those who didn't. The successful rollout of the redesigned user experience, including the release of Recommendations AI panels across its top five markets, has led Benetton Group to work on extending it to the rest of its territories. The Group is also working to improve its recommendations tool by adding automation for even more responsive engagement with customers.

Increased conversion rate by 6 times when customers interacted with the panels generated by Recommendations AI

Boosted sales by 7% by reducing friction in the sales funnel

Increased customer engagement and time spent on the website by almost 3 times

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