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Use case Fuel-to-store conversionFuel and convenience retailer, 52 sites

How a fuel retailer priced fuel to fill the store, not just the tank.

A price war had the team cutting fuel at every site. Cortex showed the cut only paid back where drivers walked inside, and exactly when they did.

Matched where it pays9 siteshigh walk-in, 6–9 AM
Fuel + store gross profit+$1.1Ma year, combined

“Should we keep matching the 6-cent cuts?” → one question to Cortex AI

Matched where it pays9 siteshigh walk-in, 6–9 AM
Held margin43 siteslow walk-in, fleet-heavy
Fuel + store gross profit+$1.1Ma year, combined

01 · The challenge

Six cents off everywhere, for a store that didn’t always benefit.

Two rivals had cut prices across the metro. The team matched at all 52 sites, on the belief that cheaper fuel brings more people into the store.

Fuel volume rose, but fuel margin fell by more. Inside sales barely moved, and no report connected a pump transaction to what happened at the register.

Before Cortex

What the team saw first

  • Fuel volume+8% after the match
  • Fuel margin−6¢ a gallon, every site
  • Inside salesFlat, network-wide
  • InstinctKeep matching to protect traffic

The difference

Same question. Different results.

The question“Where does cheaper fuel actually bring customers into the store, and when?”

Claude / GPT / Public LLMs

Uploaded file

1 sourceThe file you uploadedfuel_sales.xlsx

Answer

Fuel volume rose 8% after the price match. Keep matching to protect traffic.

Just an answer.

Cortex AI

Connected intelligence

Cortex AI
  • Fuel-to-store conversion
  • Hourly street traffic
  • Where customers shop
  • Competitor fuel prices
  • Fleet card mix
  • Basket data
  • Weather
  • Commuter patterns
  • Store sales by hour
  • Mobility data
  • 34% walk in at 9 commuter sites
  • Only 11% at 43 highway sites
  • Peak: 6 to 9 AM

Answer

Match only where drivers walk in. At 9 commuter sites, 34% come inside between 6 and 9 AM and spend $8.40. Hold a 4¢ premium at the other 43. +$1.1M a year.

A decision.

02 · The finding

The store paid for the discount at 9 sites. At 43, nothing did.

Cortex linked fuel transactions to in-store baskets by time and payment, then added traffic, mobility and competitor data. It separated sites where drivers walk in from sites where they pay at the pump and leave.

Fleet cards and long-haul traffic dominated the highway sites. At commuter sites, the morning coffee run made each extra fuel customer worth far more than six cents a gallon.

What Cortex found

Who walks in, and when

9 commuter sites

34%of fuel customers walk in, 6–9 AM$8.40average basket: coffee and breakfast

Match the rival here

43 highway and fleet sites

11%of fuel customers walk in$5.10average basket: drinks and snacks

Hold a 4¢ premium

Walk-in rate by hour, commuter sites

5 AM9 AM1 PM5 PM8 PM
The decision

Price fuel to feed the store where it counts.

  • Matched the rivals at the 9 commuter sites, only during the 6–9 AM window.
  • Held a 4¢ premium at the 43 highway and fleet-heavy sites.
  • Put the coffee and breakfast bundle on the pump screens at the commuter sites.

03 · The impact

What changed.

MeasureBeforeAfter
Sites matching the rivals529
Fuel margin, network average18.2¢23.6¢
Inside sales at the 9 commuter sites—+7%
Walk-in rate at commuter sites, 6–9 AM29%34%
Fuel + store gross profit, annualized—+$1.1M
Leadership takeaway

A fuel price is also a store decision.

We were giving away six cents a gallon to people who never came inside.

The right fuel price depends on who walks in, when, and what they buy. Price the site, not just the pump.

Which of your sites earns its fuel discount back inside?Book a demoSee all use cases
Next use caseHow a regional distributor stopped finding delivery problems at billing
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Leave with a decision.

Target implementation2–4 weeks
EnvironmentPrivate enterprise
Timeline depends on data readiness and integrations.

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