What in-store data does merchandising personalisation use?
Merchandising personalisation draws on real-time selling data at store level, which lets merchandising teams build bespoke assortments for each location by allocating more of a certain colour, fit or size, along with new products and collections, to a specific store's inventory 1. That same data can inform how retailers optimise assortment against local demand, profitability and inventory management efficiency 1.
Customer data used in store
- Customer preferences and purchasing habits, tracked so that promotions, discounts and recommendations can be tailored to individual shoppers 2.
- Customer behaviour and preferences, used for targeted promotions and recommendations 3.
- Customer profiling data that supports real-time personalised rewards delivered at impactful moments in store, and that helps retailers understand behaviours and journeys well enough to improve store layouts 4.
- First-party data from each touchpoint, which the Retail Spotlight material frames as the basis for making the next customer interaction faster and easier 5.
- Qualified data attached to identifiers such as email address, name, address or customer ID, according to IAB Europe 6.
How the data is brought together
Customer data platforms consolidate customer data from multiple in-house and third-party sources to give a holistic view of customer behaviour for targeted marketing and product recommendations 7. In the Prada Group and Adobe partnership, customers who have opted in allow sales assistants to know when they visit a store and what their preferences are, and follow-up recommendations combine the purchase, the in-store experience and the online profile 8. Morrisons personalises forecasting to every single store in the UK, using each store's performance to predict demand and supply 9.