Sena Decision AI shows grocery teams empty shelves, rival prices, and why shoppers switch. Every figure traces to a store photo, a shopper answer, or the team's own files.
Grocery analytics from checkout and loyalty data shows the sale that stayed in the store. A missing item, a lower price nearby, or a thin assortment sends the rest of the basket to a rival.
Replenishment files show what each store ordered and received. The shelf shows what the shopper found.
Sena: Sena captures geo-verified photos store by store and flags each planned product missing from the shelf.
The price file shows what each store should charge. Shoppers judge that price against the nearest rival.
Sena: Sena reads the shelf price in the chain's stores and named rival stores side by side.
Loyalty data shows a member's spend falling. The reason sits with the shopper.
Sena: Sena captures consented input from shoppers on why they chose a store and what would make them switch by segment and market.
Grocery analytics pays off in four calls that decide whether the weekly shopper stays.
Shoppers in Sena's consumer network state which store they shop most often, which stores they compared, and what would make them switch.
Decides: Which price, assortment, or service fix wins back the weekly basket.
See perception measurement and tracking →Sena reads the price tag in each store photo, across the chain's stores and nearby rival stores, and sets each price beside the price plan.
Decides: Where to match a rival's price and where to hold margin, store by store, within the chain's supermarket pricing strategies.
See retail price monitoring →Sena flags the planned products missing from each shelf, then matches each gap to the chain's supplier delivery files for the same store and date.
Decides: Which fix goes to the supplier and which to store operations.
See on-shelf availability →Sena reads the chain's sales files by product and store, and shoppers state what they would buy if an item left the shelf.
Decides: Which products leave the assortment and which stay to hold the basket.
See SKU rationalization analysis →Sena ties every figure to its capture, so a team checks any store against its own grocery point of sale data.
Each shelf and price reading carries its photo, location, and date. An availability figure counts only products a photo confirms.
Every photo and shopper answer clears a multi-level QA flow. Sena declines a capture that misses the check, and the decline stays visible.
Grocery store analytics on availability starts with two counts: the products on a store's assortment plan and the products a photo confirms on the shelf. Sena captures the second count and splits the gap by category, format, and supplier.
The availability gap calculator shows the products a store is missing and the weekly sales at stake.
A walkthrough runs Sena on one grocery category in one market, from store photo to assortment decision.
Pick the closest fit, and the walkthrough starts from that team's question.
Grocery analytics on assortment, availability, and what shoppers would buy in place of a cut item.
Book a category walkthrough →Supermarket pricing strategies checked against shelf prices in the nearest rival stores.
Book a pricing walkthrough →Planned products missing from the shelf, each matched to its supplier delivery.
Book an operations walkthrough →Grocery customer retention, from why shoppers choose the chain to what would make them switch.
Book a marketing walkthrough →A Sena reading for one grocery category across a set of stores, with the shelf photos and shopper answers visible behind every figure.
A store reading puts availability, price, and the switching reason on one page.
Sena captures geo-verified photos and consumer activity in the markets a question names, when the question needs it.
Sena reads those captures beside the files and systems already in use, across 250+ integrations.
Sena compares the market against the plan and shows each gap, with every figure traced to its source.
| Area | Common method | Sena |
|---|---|---|
| Shelf availability | Gap scans by store staff, logged store by store | Geo-verified photos confirm each planned product on the shelf |
| Rival prices | Staff price checks in rival stores, entered by hand | The price tag in the rival store, read from a dated photo |
| Switching reasons | Loyalty card spend, read for a drop in frequency | Shoppers state why they switched and what would bring them back |
| Assortment reviews | Products ranked by sales and margin | Sales files read beside the products shoppers would buy in their place |
| Auditing | Gap scans, price checks, and loyalty reports matched by hand | Each shelf figure opens its dated photo or shopper answer |
Talk to the Rwazi team about one grocery category, one market, and the decision on the table this quarter.