For operators

The answer key for profitable store decisions.

Chains like yours have already figured out what works, by doing it: breakfast hours, the remodel order, the loyalty fix. We measure what those changes actually caused in their POS data, using causal math of the kind Google open-sourced, and hand you the answer key: do this, it's worth this much at your stores, this sure. Then we grade our own answers on the record.

The big chains build digital twins with cameras and sensors. Seurat builds a twin of every store from the sales data you already have.

Every surface stays readable by a general manager without translation: what to do, what it's worth, how sure, what status.

A note on benchmarks

The industry benchmark isn't built for a chain your size.

The convenience channel's standard financial benchmark reports averages across firms that volunteer their data, and the store count behind those averages is dominated by the largest chains in the country. Measure a 40-store operation against it and you are measuring yourself against companies with a different format, a different foodservice program, and a different cost of capital.

It also publishes firm averages and no store-level spread at all. That is the harder limit. A benchmark built from company means can describe a good operator. It cannot locate a good store, and it cannot tell you which of yours is the problem.

That is the question this board answers, and it answers it from your own tape.

Types of questions we answer

You ran a loyalty relaunch, a fresh-food reset and a price change in the same quarter, and sales went up. Which of the 3 did it, and which one cost you margin?Which of your stores are well run once location is taken out of the picture?Is your made-to-order food program bringing in new customers, or rearranging the basket you already had?

Have a different question?Ask it →

Two stores your reports get wrong

A store on a busy corner can beat its peer benchmark every month while running a mediocre operation, because the location is doing the work.
Another store can slip 1% in the year a competitor opens nearby. Every standard metric calls that a decline. We call it the best-run site in the chain, because its twin, facing the same new competitor, lost 10%.

Both stores are illustrations.

Where this sits

Four questions, in the order they usually get asked. Start wherever yours is.

Which of my stores are underperforming, and what are customers saying about them?Answered by: Store-to-Store ReadTakes from you: Nothing What did the changes we already made actually do?Answered by: Calibration ReadTakes from you: One data export What should we do next, and what is each lever worth?Answered by: Lever BoardTakes from you: 2 years of sales data Is it working, and is it still being done?Answered by: MonitoringTakes from you: Nothing new

Where we've pointed it

QuestionEvidence so farWhich read answers it

What is my fresh case earning per foot, against what it could earn?The fresh case readReviewsReview reads at 2 regional chainsFieldStore walks at the same 2 chainsCalibration Read

Are the franchise brands inside my stores earning the share of the ticket they take?Return on brandReviews3,109 reviews classified at an operator hosting franchise brandsFieldStore walks at the same operatorThe Lever Board

Proof

Two-Strike winback after a second bad visitHalf the shoppers who quit a store were gone within 2 bad visitsIn our survey of 1,200 shoppers, 29% have quit a location of their go-to chain, and half of them were gone within 2 bad visits. Heavier shoppers are more likely to quit a location, but they don't leave any faster.SurveySame Brand, Different Store ExperienceA national survey of 1,200 U.S. shoppers on why the same chain performs so differently store to store.

Running designed tests today?No test design, no held-out stores →

Need the store-level view first?Store-to-Store Read →

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