Since its expansion, asambeauty has been presenting a dream world with over 500 high-quality beauty articles exclusively from its own brands in its online shop. In order to guide customers through the new product jungle, the beauty platform relies on the recommendation of possibly suitable products – on the product detail page, the add to basket page and in the shopping basket. Based on the interests of historical customers who had viewed or bought similar products to the current user, these were played out by a classic RECO tool before the project began. However, this meant that they were of little relevance to many visitors: Because their actual interests and preferences can differ greatly from those of the comparison group, so that they were often ignored. The beauty platform was therefore looking for a solution to suggest the most suitable products to each individual user.
For this, asambeauty relies on the next generation of recommendations: situation-related recommendations by ODOSCOPE. This approach enables the beauty platform to tailor product suggestions to the individual needs and current shopping situation of each user. These are determined with the help of an Operational Intelligence Platform (SaaS) based on the surfing behaviour of historical users who resemble the current visitor both in terms of personal interests (e.g. skin, hair or body care) and