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Store results tell you where to look. Teams can explain how stock, service, training and incentives shape those numbers
Pick a store result you want to understand
Ask OREY AI voice agents to investigate what helps or hinders sales in each store
Try a promising routine and compare the result across stores
Compare stores on a KPI, then look at the routines that may explain the difference
Understand which barriers explain a difference between stores
Find a routine from another store and check it fits locally
Choose a store to test the change and review it with store data
Ask staff about the moment behind the number, whether it is an empty shelf or a missed sale
Typical KPI for grocery stores as a starting pointOn-shelf availability
Stock may be in the building but no one owns the move from backroom to shelf
Think of a shelf that stayed empty. Where did replenishment break down?
Clarify who refills the shelf, then watch on-shelf availability
Typical KPI for fashion stores as a starting pointConversion rate
Customers may leave when fitting rooms are busy or staff cannot step in to help
Tell us about a customer who left without buying. What help was missing?
Try a better fitting-room routine in a few stores and compare conversion
Typical KPI for hair salons as a starting pointShampoo upselling rate
Stylists may lack product knowledge, a visible display or a reason to make the recommendation
When does a shampoo recommendation feel useful to a client, and what gets in the way?
Test better onboarding and product placement, then track shampoo upselling
Typical KPI for hotels as a starting pointRoom turnaround time
Late linen and unclear handovers can leave room attendants waiting to start
Think of a room that was ready late. What held up the team?
Try a clearer handover with reception, then track rooms ready by noon