This tailor-made approach to the shop visitor also works for first-time visitors or guest users, because they also provide some information such as location, operating system or referrer (visit source, e.g. social media). By analyzing the totality of all customer histories, statistical siblings (peer groups) can be determined for the unknown user. The products with the highest conversion probability are then automatically offered to the customer in real time.
In addition, analytics or intelligence teams can save a lot of time through such automation. A Gartner survey found that in most companies, data scientists spend most of their time visualizing data, preparing data for analysis, charting, dashboards and statistics. Through our situationalization platform, Data Scientists have more time for analysis and knowledge gains.
With a situation-related personalization, every visitor receives an individually equipped online shop with what is relevant in his particular situation. This improves his shopping experience, which makes him happy to come back and keeps him as a customer in the long term. Companies win additional customers and users can shop more efficiently and comfortably – a real win-win situation!