Customer Commitment through Digital Fashion Insights
The goal was to better understand the purchasing behavior of customers in the online store: How do they navigate through the store? Which products do they prefer? And what keeps them from buying? Based on these findings, the online product range was to be optimized and the way customers are addressed was to be personalized.
Another goal was to increase customer commitment and thus achieve a significant increase in sales and turnover.
Key Benefits of the Solutions
All master and transaction data is available in real time and continuously.
A personalized search engine provides the customer with an optimal shopping experience and an outstanding user experience.
Smart algorithms open up comprehensive cross- and upselling potentials.
- The numerous channels and touchpoints that customers use in part in parallel in the purchasing process must be comprehensible to the customer journey.
- Optimizing the cost-benefit ratio of campaigns despite highly diversified and segmented target groups.
- Addressing target groups with individualized information and offers.
- Establishment of a generic search engine that delivers accurate and relevant results and recommendations.
The amentis DXS platform serves as a central hub where all transactional data - from page visits to shopping cart activities - is collected and then combined with product master data, customer master data and order history.
With its machine learning algorithms, the amentis DXS Add-on "ML Classification" analyzes the data and uncovers patterns in customers' purchasing behavior. Relevant target group clusters are automatically formed from this data, for which suitable cross- and upselling recommendations are generated.
A modern personalized product search engine is also based on the data collected in the hub, which enriches the pure product search with additional content. The relevance of the search results is individually weighted for each visitor to the online store to ensure the optimal shopping experience.