Thanks to Google Cloud, Lucky Cart can now processes very large volumes of data and performs the complex calculations required to set up ultra-personalized marketing operations for its customers.<\/p>\n\n\n\n
Lucky Cart analyzes receipt data collected in real time to predict shopper consumption and optimize brand presences for their partners. They use the data to gain a better understanding of shoppers’ individualized purchasing profiles, to enable an ultra-personalized e-retail and increase profits.<\/p>\n\n\n\n
Retailers are always searching for new ways to increase consumer engagement online, and one way to do this successfully is through gamification. In one study, introducing an element of competition or challenge helped content and media companies increase online customer interactions by 30-40%<\/a>, and the potential applications of this approach are endless.<\/p>\n\n\n\n This is one of French marketing technology company Lucky Cart\u2019s key strategies and it\u2019s transforming the way fast-moving consumer goods (FMCG) brands and distributors are leveraging data to increase customer engagement. With access from between 10 to 20 million lines of purchase receipts a day through its network of brands and distributors, Lucky Cart uses artificial intelligence to create ultra-personalized marketing campaigns, in which shoppers can try their luck at a promotional game to win back the total value of their shopping cart. It works with 85% of the FMCG market in France, and is the only player in ecommerce media with this level of distribution.<\/p>\n\n\n\n “Shoppers see an integrated banner on the distributor’s platform encouraging them to purchase multiple goods from a certain brand, and if they fulfill the purchasing criteria, they are invited to play the game,” explains Nicolas Trannoy, Marketing Director at Lucky Cart. “As well as broad and static targeting, our solution enables ultra-personalized and dynamic profiling, so each shopper is treated as an individual. For the distributors, that means a 20% increase in value of the average basket.”<\/p>\n\n\n\n To deliver this level of ultra-personalization, Lucky Cart handles large volumes of complex first-party data, creating profiles using sophisticated algorithms and then handling browsing data in close to real time. This data is then fed back into the system, to refine and improve future predictions. With the goal of improving its capacity for handling very large volumes of data, Lucky Cart decided to migrate its infrastructure to Google Cloud<\/a>.<\/p>\n\n\n\n “What enables us to stay ahead of our competitors is the work of our data science team,” says Trannoy. “The added value we offer is the capacity to generate ultra-personalized profiles, and that’s why we chose Google Cloud for our data infrastructure.”<\/p>\n\n\n\n To deliver a high level of personalization based on constantly refining its knowledge of consumer habits, Lucky Cart analyzes its distributors’ data to create shopper profiles, always in compliance with GDPR regulations. As this includes three years of historic sales data, the volumes involved are very large, and its previous system was not able to provide sufficient computational power to carry out the necessary requests.<\/p>\n\n\n\n “Our previous system was not sufficiently scalable, in terms of the machine learning and deep learning capabilities we require,” explains Julien Guitard, Chief Data and Science Officer at Lucky Cart. “The infrastructure was not very intuitive to use, and the lack of scalability was holding back both our data engineers, and our data scientists.”<\/p>\n\n\n\n To enable it to access the power it required to carry out complex calculations for every shopper, across hundreds of categories, two years ago Lucky Cart switched both its application services infrastructure, and its data analysis infrastructure to Google Cloud.<\/p>\n\n\n\n\tChoosing a cloud provider to support big data analyses:<\/h2>\n\n\n\n