Enhance your store analytics with customer data

Connect purchase data to customer profiles at the store level and gain new insights to optimise your inventory, offers, marketing campaigns and overall performance.

How it works

Customer-centric store analytics

We are integrated at the POS – every store transaction runs through refive

Every in-store customer is identified and matched with purchase data

This combined data allows us to create a “store profile” – helping you understand store performance as a whole as well as in the context of customer segments and individual shoppers

How it works

Use store-level insights to grow sales

Why refive?

A new perspective on store performance

View your stores through the customer lens

Most store analytics focus on the shopping basket or footfall. On the other hand, marketing analytics is centered on the customers – their characteristics and preferences. refive brings together customer data and POS data and thus allows for a whole new way of analysing store performance in the context of the customers shopping in that store. You can gain new insights on popular products, customer feedback, purchase behaviour, discount usage by customer segment and by store.

Democratise store insights

Store insights are often locked away in ERP / BI systems that aren’t accessible to marketing teams and store members. The refive merchant dashboard empowers teams to find and utilise store and customer data to improve store performance, improve customer experience and grow sales.

Get to know and delight your customers

Generate e-commerce level insights into in-store customer behaviour, increase engagement and customer retention via smart digital receipts

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Digital in-store touchpoints

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SME

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The Future of Enhancing Brand Narratives With In-Store Touchpoints

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Enhance your store analytics with customer data

Customer-centric store analytics

Use store-level insights to grow sales

Find out if your in-store customers are new or returning shoppers to optimise layouts and offers accordingly

Monitor the loyalty of a specific store’s customers

Discover how customer satisfaction in the store varies throughout the day

Understand the baskets of store customers right down to micro-segments

Identify how price-sensitive customers of this store are and use that to inform local pricing strategy

Determine which products do well with which customers in which stores and use that insight to inform merchandising decisions