Customer, sales and stock data that works across every brand and channel
Retail groups and hospitality operators often run many brands, each with its own POS, loyalty and e-commerce stack. We create one consistent data layer so forecasting, loyalty and AI work across the group.
Focus markets: UAE · UK
The problems that come up most
Every brand measures differently
Sales, margin and footfall are defined differently across brands, so group reporting takes weeks.
Loyalty data is underused
Customer and loyalty data sits in separate programmes and is rarely joined to sales and stock.
Forecasts miss demand swings
Seasonal peaks, events and tourism flows make demand volatile, and forecasts rely on spreadsheets.
Promotions are hard to evaluate
Nobody can say with confidence which promotions actually drove incremental sales.
What we do about it
- A group-wide data model and semantic layer for sales, margin, stock and customers
- Demand forecasting on governed data, by store, channel and season
- Loyalty and customer data joined to transactions, with consent respected
- Natural-language reporting for brand, store and category managers
Regulation we design for: UAE PDPL and UK GDPR for customer and loyalty data, including consent.
Questions your teams could ask
- Which stores are likely to run out of top sellers before the weekend?
- How did the last promotion perform against a normal week, by brand?
- What share of sales came from loyalty members in each mall last month?
Illustrative. Answered from your governed data, in Slack, Teams or your own tools.
Find out how ready your data is
Start with the free scorecard, or book a call to talk through a specific use case.