Restaurants & Food · Scenario 05

Ramen Shop

Delivery orders grow but margins shrink the further the driver goes — and the shop can’t see where its real demand lives. We map it and redraw the radius around profit, not optimism.

Method · Geospatial analytics

The situation

Third-party delivery made the ramen shop busier and, oddly, not much richer. Long-distance orders arrive cold, earn complaints, and cost more in driver time and platform fees than they bring in. Meanwhile clusters of nearby demand go under-served because marketing is spread evenly across a city that doesn’t order evenly.

The owner has no map of where orders come from, how far is too far, or which neighbourhoods would respond to a targeted push. Every postcode is treated the same.

7.2 km
avg delivery distance
31%
orders losing money
1 zone
flat delivery radius
No map
of demand density

Where we dig for the truth

We geocode every order and overlay cost, delivery time and margin to see where ramen actually pays — and where it quietly doesn’t.

Geocoded order historyDelivery time & distanceDriver & platform costMargin per orderNeighbourhood densityCompetitor locations
Where the orders come fromOrder volume by distance band0531061592121800-2 km1402-4904-6456-8208 km+

Orders thin out fast with distance — and past about 6 km each one loses money once driver time and platform fees are counted.

Our approach — Geospatial Demand & Delivery-Radius Optimization

We map demand density and compute true contribution per order by zone, factoring driver time and platform fees. The flat city-wide radius becomes a profit-aware one: a tight, well-served core, a mid-band kept only where it pays, and the loss-making long-haul fringe dropped.

Marketing spend is then redirected from ‘everywhere’ to the dense, profitable blocks — and to the gaps between the shop and the nearest competitor, where a nudge converts cheaply.

From a flat radius to a profit map1Geocode demandPlot every historicalorder and overlayneighbourhood density.2Cost each orderAttribute driver timeand platform fees tofind true margin byzone.3Redraw the zoneSet a profit-awareradius; drop thelong-haul orders thatlose money.4Aim the spendConcentrate promos ondense, profitable,winnable blocks.
Weekly delivery profitAfter re-drawing the zone and focusing spend$0k$2k$3k$5k$6kW1W2W3W4W5W6W7W8S&I starts

Cutting the money-losing long hauls and concentrating promos in dense, nearby blocks lifts profit even as total order count dips slightly.

What changes

Same kitchen, a smaller but smarter delivery map. Representative for a shop with heavy third-party delivery.

Representative 90-day movementOrders losing money31%7%▼ -24 ptsAvg. distance7.2 km4.1 km▼ -43%Delivery margin9%21%▲ +12 ptsMonthly profit$14k$23k▲ +64%
Where the gain comes from+$9kmonthly profitDropped loss-making zone38%Focused local promos34%Lower delivery cost28%
Why this is not "social media management"
We didn't buy this shop more delivery ads across the whole city. We mapped where ramen actually pays, stopped subsidising cold bowls driven across town, and aimed the marketing at blocks that respond. Geography is data — we used it.

Frequently asked questions

How do you make restaurant delivery profitable?
We geocode every order and attribute driver time and platform fees to each one, revealing where delivery actually pays. We then redraw the radius — dropping money-losing long hauls — and aim promotions at dense, nearby, winnable blocks.
What is geospatial demand analysis?
It is mapping where your orders physically come from and overlaying cost and margin by area, so you can see which neighbourhoods are profitable to serve and market to, and which quietly lose money.
How is this different from buying more delivery ads?
Rather than spending across a whole city that does not order evenly, we use the geography of your own order data to focus on profitable demand — and stop subsidising cold bowls driven across town. Book a marketing audit.

Want this run on your numbers?

Send your delivery order history and we’ll map where you’re making and losing money.