Sena Decision AI shows restaurant and foodservice teams where to open, what to sell, and why guests switch. Every figure traces to a guest answer, a site photo, or the team's own files.
Multi-location restaurant analytics usually starts at the POS: what was sold, when, and at what check. The reason a guest picks one restaurant over another sits outside the POS.
Site files describe a district's income and traffic. The block shows who already sells food there.
Sena:Sena captures geo-verified photos of the rival restaurants around each candidate site.
Item sales show the answer once a new item is live. Guests can say beforehand what they would pay and what it would replace.
Sena:Sena captures what guests in the target market would pay for a new item by segment and market.
QSR analytics shows fewer orders at a location. The reason sits with the guest: price, speed, menu, or a new rival.
Sena:Sena captures why guests chose a rival and what would bring them back by segment and market.
These four decisions add the guest's reason to restaurant data analytics.
Sena captures geo-verified photos of the rival restaurants around each candidate site, and residents state which food the area still misses.
Decides:Which address gets the lease, and which format fits it.
See restaurant site selection analysis →Sena reads item sales from the team's files beside the items guests say brought them in and what else they order, by segment and market.
Decides:Which low-margin items stay on the menu because they bring guests in.
See entry point products →Guests in the target market state what they would pay for a new item and which item it would replace.
Decides:Which item rolls out, at what price, and in which market first.
See innovation decisions →Guests state where they eat most, which restaurants they compared, and what would bring them back, by segment and market.
Decides:Which price, menu, or service fix wins back the lost guest.
See growth decisions →Sena ties every figure to the answer or photo behind it, so QSR analytics teams check each one against their own sales files.
Each site reading carries its photo, location, and date.
Each reason comes from a guest who chose to share it. Every capture clears a multi-level QA flow. Sena declines a capture that misses the check, and the decline stays visible.
Restaurant guest analytics on switching starts with two counts: the guests a restaurant serves each week and the share who names a rival as their main choice. The team enters both and checks that share against guest answers in the market, by segment, with the rival in each segment named.
The guests at risk calculator shows the guests a rival can win and the weekly sales at risk.
A walkthrough runs Sena on one restaurant format in one market, from guest answer to the site or menu decision.
Pick the closest fit, and the walkthrough starts from that team's question.
Restaurant site selection, scored on the rivals around each address and what residents want.
Book a site walkthrough →Which new item guests would order, at what price, and which item it would replace.
Book a menu walkthrough →Restaurant guest analytics on why guests choose a rival and what would bring them back.
Book a marketing walkthrough →Why one location trails another, read across every site in the chain.
Book an operations walkthrough →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 |
|---|---|---|
| Sales | Restaurant data analytics solutions built on POS sales | Guests state why they ordered, switched, or came back |
| New sites | Restaurant industry analysis and traffic counts for the district | Photos of the rival restaurants on the block, beside what residents want |
| Menu tests | Item sales after rollout | What guests in the target market would pay before rollout |
| Value items | Margin rank by item | The items guests say brought them in |
| Auditing | Sales, guest comment, and site reports matched by hand | Each site figure carries its guest answer or site photo |
Talk to the Rwazi team about one restaurant format, one market, and the decision on the table this quarter.