Delivery zone and radius: the extra-kilometer myth and what the numbers actually say

Verdict: you choose delivery zone and radius by travel TIME and order density, never by kilometers drawn on a map. In a dense Latin American city the profitable radius closes between 2.5 and 4 km, which equals 12 to 18 minutes of travel, because past the 20-minute mark hot protein drops below the 60 °C sanitary threshold and one-star reviews multiply.
A wide radius looks like more revenue and almost always delivers less margin. That distant order pays the same platform commission of 23% to 30% under the 2025-2026 rate cards published by Rappi and Uber Eats, it consumes twice the courier time, and it ranks worse inside an algorithm that punishes distance through estimated delivery time. The right move is to tighten the polygon, win density inside it, then open a second dispatch point once that zone saturates.
A steakhouse in Chapinero with a 42,000-peso average ticket delivered up to 7 km because its owner believed that closing the map meant handing customers to the competition. Once we split orders by distance ring, the 0-to-3-km ring returned 31% contribution margin while the 5-to-7-km ring returned 6%, same menu, same kitchen, same commission. That 6% did not even cover the courier working the peak shift.
The mistake comes from confusing two things that look alike on a map and behave nothing alike in the cash register. Coverage is how far your motorcycle goes. Capture is where your brand appears first inside Rappi, Uber Eats or DiDi Food when someone hungry opens the app at 8:40 at night. Marketplaces rank by conversion probability, and that probability sinks with every extra minute of estimated time.
The myth collapses on its own here. Widening the radius does not widen demand: it distributes demand worse, stretches every order including the close ones because the courier leaves farther and returns later, and drags store rating down. Diego F. Parra hammers this point in Masterestaurant audits, since the delivery zone is an operations engineering decision and a Local SEO decision at once, not a wishful line painted over Google Maps.
Side-by-side comparison
| Tight radius (2.5-4 km) | Wide radius (6-10 km) | |
|---|---|---|
| Average door-to-door delivery time | ✕24 minutes at peak | ✓47 minutes at peak |
| Contribution margin per order | ✕28-34% after commission | ✓5-11% after commission |
| Average marketplace rating | ✕4.7★ out of 5 | ✓4.1★ out of 5 |
| Orders per courier on a 5-hour shift | ✕11 to 14 deliveries | ✓5 to 7 deliveries |
| Logistics cost against ticket | ✕8-12% of order value | ✓19-27% of order value |
| Plate temperature on arrival | ✕62-68 °C on hot protein | ✓41-52 °C on hot protein |
| Repurchase rate at 30 days | ✕38% of customers reorder | ✓17% of customers reorder |
Step 1: split your sales by distance ring before you touch the map
Start by pulling the last 90 days of orders and sorting them into three rings —0 to 3 km, 3 to 5 km, 5 to 7 km— with the real contribution margin of each one, because without that cut you are arguing about your radius with an opinion instead of with the cash register. The Chapinero grill I mentioned earned 31% margin in the near ring and 6% in the far one, same menu and same platform commission: the deliverable here is a three-row table showing orders, average ticket, travel minutes and margin after delivery cost per ring. You verify it by adding the orders across the three rings: if the total does not match the platform report, some address got misclassified and the whole diagnosis collapses. Radius is defined in TIME, never in distance, and you make that conversion by timing the real trip at peak hour instead of the one the map promises at three in the afternoon.
Step 2: turn kilometers into minutes, the unit your operation actually pays for
Take ten representative addresses along the edge of your coverage, run a stopwatch between 7:30 and 9:00 at night, and write down the minute the rider hands over the food and the minute the rider is available again; that second number is the one almost nobody records and the one that decides your rotation. In a dense Latin American city, 2.5 to 4 km lands between 12 and 18 minutes of travel, and the hard threshold sits at 20 minutes. This step is done when the average and the spread of those ten stopwatch readings are written down, not remembered. Cut the map at the ring where contribution margin per order still covers the rider's hourly cost divided by the deliveries that fit inside that ring, and not one meter beyond. The arithmetic fits on a napkin: eleven deliveries per shift spread the motorcycle's fixed cost across nearly twice as many tickets as six deliveries do, and that is where the margin appears that the owner spent two years hunting for in the price of a dish.
Step 3: set the radius where the ring margin still pays the rider's shift
With sector wages climbing —base hourly pay in United States restaurants rose 4% to 14.20 dollars in 2024, according to the 7shifts Restaurant Workforce Report— every dead minute on the road weighs more each year. Your deliverable: one kilometer figure, written, signed and loaded into every platform's settings. Your delivery zone is not a circle, and drawing it as one hands absurd trips to your operation: a river, an avenue with no turnaround or a hillside turns 2 kilometers of map into 22 minutes of riding. Draw the polygon block by block using the stopwatch data from step 2, exclude the sectors where real time beats the threshold even though distance looks short, and pull in the corridors where a fast avenue gives you cheap kilometers. Rappi, Uber Eats and DiDi Food all accept custom polygons; the default circle is operational laziness, not a limitation of the tool.
Step 4: trim the zone by real neighborhoods, not by a perfect circle
Verify it by ordering from three edge addresses on your own phone: if any of them quotes an estimate above twenty minutes, the polygon still carries fat. Coverage and reach are different things, and mixing them up costs orders: coverage is how far your motorcycle rides, reach is where your brand shows up when somebody opens the app hungry at 8:40 at night. Platform search engines rank by probability of conversion and that probability sinks with every added minute of estimated time, so owning three neighborhoods puts you on top in three neighborhoods, while scattering across eight leaves you invisible in all eight. Diego F. Parra works it this way inside Masterestaurant audits: the delivery polygon and the brand's local pages describe the SAME territory, with the neighborhood names written into the listing, the menu and the content. It is done when your Google listing and your in-app zone name the same sectors.
The four mistakes that ruin the trim, and how to dodge them
The costliest mistake is widening the radius when sales dip, because it looks free and it is not: demand gets spread worse, EVERY order takes longer —including the close ones, since the rider travels farther and returns later— and the store rating drags downward. The second is timing the trip off-peak and then signing off on a radius with that number. The third, watching the order count on the monthly report instead of margin by ring, an accounting mirage that lifts volume while margin slides from 31% to 6%. And the fourth is trimming the map without telling the kitchen, which keeps producing for demand that no longer exists. One discipline handles all four: no zone decision enters without its minutes figure and its margin figure sitting beside it. Shrink the radius and gross sales fall for the first two weeks: that will happen, and it has to be said beforehand so nobody reverses the decision on the worst day.
What happens if the trim drops your volume and the owner panics?
What climbs alongside it is margin per order, motorcycle rotation and average delivery time, and that last number is the one platforms reward in their ranking, so volume comes back through relevance rather than through kilometers.
If volume has not returned by day 45, the problem was never the radius but the offer: check average ticket, menu photography and listing conversion before you reopen the map. The market is on your side —cloud kitchens grow 12.6% a year between 2026 and 2033, according to Grand View Research— but that growth rewards whoever delivers fast across few neighborhoods. You are finished when five things are written and verifiable, not when the map looks pretty. One: the ring table with real margin per ring, signed. Two: the peak-hour travel average, measured by stopwatch, below 18 minutes. Three: the polygon loaded identically across all three platforms, with no default circles. Four: the same neighborhoods named in the Google listing, the digital menu and the brand's local pages.
Closing checklist: how to know the zone was built right
Five: a review booked at 45 days using the same indicators to compare against the baseline. If any of those five lives only inside somebody's head, the zone is not built, it is improvised. Open the last 90 days of reports today and build the ring table: everything else in this guide runs on top of that number. A tight radius turns every motorcycle into a rotation asset: eleven deliveries per shift against six means the courier's fixed cost spreads across nearly twice the tickets, and that is where the margin the owner blamed on plate pricing reappears. A wide radius buys gross volume and sells margin: order count climbs in the monthly report while contribution margin per order collapses from 31% to 6%, an accounting mirage you only detect once you split revenue by distance ring. In digital capture the gap runs deeper, because app search and the Google local pack reward geographic relevance: a virtual brand dominating three neighborhoods ranks high in those three, while one scattered across twelve ranks high in none.
Where the two decisions truly split?
Five-star reviews come from hot food arriving earlier than promised, and that outcome depends more on the polygon than on the recipe book;
when a customer rates lukewarm chicken with 2★ they are not judging your kitchen, they are judging your geometry. A physical restaurant tolerates a wide radius because its dining room absorbs fixed cost, whereas a dark kitchen has no such cushion, so in dark kitchen vs physical restaurant polygon discipline stops being advice and becomes a survival condition.
Criterion-by-criterion comparison
What actually decides a profitable zoneMeasurable reality
- Isochrones of 12, 15 and 18 minutes drawn over real traffic between 8:00 and 9:30 p.m., not circles of kilometers.
- Household and office density per block inside that isochrone, cross-checked against the ticket your menu can sustain.
- Position in the app listing: Rappi and Uber Eats rank estimated time and acceptance rate above raw distance.
- A Google Business Profile whose service area matches reality: if GBP promises 10 km and your kitchen covers 3, Maps sends traffic you cannot serve.
- Kitchen capacity at peak, since a tight radius with 40 orders an hour breaks just as badly as a long one with slack.
- True cost per kilometer for your fleet or the platform fleet, including lobby waiting and failed deliveries.
The myths that keep costing marginMasterestaurant
- «More kilometers means more sales»: the distant order pays identical commission and eats double courier time.
- «The platform sets my radius and I cannot touch it»: on Rappi, Uber Eats, DiDi Food and iFood the merchant configures zone, hours and radius from the partner panel.
- «If I close the radius the algorithm punishes me»: the opposite happens, because estimated time drops and conversion rises.
- «A dark kitchen can cover the whole city»: a dark kitchen from scratch works precisely because it picks a narrow polygon with dense demand.
- «The distant customer compensates with a higher ticket»: rarely, and when it happens it is in group orders, which are 9% of volume.
- «Open coverage first, optimize later»: every month with a low rating leaves a trace in the historical review score, which is genuinely hard to reverse.
Side-by-side comparison
| Tight radius (2.5-4 km) | Wide radius (6-10 km) | |
|---|---|---|
| Average door-to-door delivery time | ✕24 minutes at peak | ✓47 minutes at peak |
| Contribution margin per order | ✕28-34% after commission | ✓5-11% after commission |
| Average marketplace rating | ✕4.7★ out of 5 | ✓4.1★ out of 5 |
| Orders per courier on a 5-hour shift | ✕11 to 14 deliveries | ✓5 to 7 deliveries |
| Logistics cost against ticket | ✕8-12% of order value | ✓19-27% of order value |
| Plate temperature on arrival | ✕62-68 °C on hot protein | ✓41-52 °C on hot protein |
| Repurchase rate at 30 days | ✕38% of customers reorder | ✓17% of customers reorder |
The figures behind the decision
“We shrank the map from 7 km to 3.2 km on a Monday and by Thursday it showed: orders fell 14% but daily profit rose by 41,000 pesos, average time went from 46 to 25 minutes, and our Rappi rating climbed from 4.2 to 4.6 in six weeks. What stung was realizing I had spent two years paying couriers to hand margin to neighborhoods that never came back: of customers beyond 5 km, only 17% ever reordered.”
How to choose delivery zone and radius in six steps with measurable deliverables
Four things belong on the table before step one, and without them any polygon is guesswork. First, the last 90 days of orders exported from each platform with delivery address or coordinate. Second, the real door-to-door time of those orders, not the promised one. Third, your logistics cost per delivery including courier wages, fuel, maintenance and lobby waiting. Fourth, contribution margin per plate after commission. DELIVERABLE: one sheet with those four columns per order. CHECKPOINT: at least 300 geolocated orders, because below 300 the sample cannot separate signal from noise. COMMON ERROR: using the time the app displays to the customer instead of confirmed delivery time, which usually runs 6 to 11 minutes higher.
Classify every order into four rings —0 to 2 km, 2 to 4 km, 4 to 6 km and beyond 6 km— then calculate average ticket, door-to-door time, logistics cost and surviving margin for each. The blended average lies because it mixes the ring that funds you with the ring that drains you, and you need those rings apart. DELIVERABLE: a four-row table showing contribution margin per ring. CHECKPOINT: find the first ring whose margin drops under 15%, since that is your economic edge. COMMON ERROR: measuring straight-line distance on the map instead of motorcycle route, which in cities with medians and one-way streets adds 20% to 35% of travel.
One kilometer on a clear avenue and one kilometer on a congested corridor are different units, so translate everything into time. Draw three isochrones around your point —12, 15 and 18 minutes— using typical Tuesday and Friday traffic between 8:00 and 9:30 p.m., the window where your reputation gets decided. Overlay the previous rings and the economic edge will almost always land on the 15-minute isochrone. DELIVERABLE: a map with three time polygons and the economic edge marked. CHECKPOINT: 85% of your profitable orders must fit inside the 15-minute isochrone. COMMON ERROR: using midday traffic, which draws an optimistic and false polygon.
A tight polygon over an empty area hurts as much as a long one over a dense area, so look at who lives and works inside it. Count households, offices, hotels and coworking spaces per block, then contrast with the ticket your menu sustains: a 28,000-peso bowl kitchen thrives in an office corridor, a 60,000-peso steakhouse thrives in weekend residential. If your 15-minute isochrone holds fewer than 12,000 households or 4,000 jobs, your problem is location rather than radius. DELIVERABLE: a density sheet for the polygon. CHECKPOINT: minimum 2.5 potential monthly orders per 100 households. COMMON ERROR: counting population without filtering for purchasing power compatible with your ticket.
Open the partner panel on Rappi, Uber Eats, DiDi Food and iFood and adjust the delivery polygon, the schedule per time band and the delivery fee, because no platform blocks you from tightening your zone even though almost no owner knows it. Configure differently by band: at lunch you can widen slightly since traffic eases, and at the night peak you must tighten. Then align your Google Business Profile so the declared service area matches the polygon exactly, since a GBP promising 10 km attracts «near me» searches you will reject. DELIVERABLE: screenshots of the configured polygon on every app and on GBP. COMMON ERROR: keeping the zone inherited from onboarding, which ships wide open by default.
With the zone tightened your courier budget frees up, and that saving gets reinvested in dominating the polygon: geotargeted ads with a radius identical to delivery, weekly Google Business Profile posts naming the exact neighborhoods, and a review request routine with a QR code on the packaging. A brand collecting 40 five-star reviews from three neighborhoods outweighs one collecting 40 scattered citywide. DELIVERABLE: a live campaign matching the polygon and a documented review routine. CHECKPOINT: 25 new reviews per quarter and average rating at or above 4.6★. COMMON ERROR: advertising citywide, which burns 30% to 45% of budget on impressions outside coverage.
The polygon is not a permanent decision, it is a living parameter reviewed every two months with the same rings from step 1. When your kitchen hits 80% of peak capacity inside the current polygon, the correct answer is NOT widening the radius but opening a second dispatch point —satellite kitchen, hosted virtual brand or a dark kitchen from scratch— with its own adjacent polygon. Two 15-minute polygons cover more profitable demand than a single 30-minute one. DELIVERABLE: a bimonthly report of margin per ring plus a signed decision. CHECKPOINT: contribution margin per order at or above 25% sustained for three months. COMMON ERROR: widening the radius because the kitchen saturated, exactly the reverse of what the data asks for.
And with AI?
Optimize channels, pricing and unit economics of your dark kitchen. Diego F. Parra is an expert in AI applied to restaurants.
Free tools to apply this now
Method tools that hold the decision in place
You draw the polygon once and defend it every month, which is why instruments that translate geography into cash flow matter. The three Masterestaurant ecosystem pieces we used in this exercise look at the same problem from different angles: the structure of the business, the growth curve per location, and the cash that carries the transition while gross revenue dips and margin climbs.
Frequently asked questions about delivery zone and radius
What is the ideal delivery radius for a restaurant in 2026?
What is the ideal delivery radius for a restaurant in 2026?
Between 2.5 and 4 kilometers in a dense city, measured as 12 to 18 minutes of peak-hour travel rather than straight-line distance. The real edge is marked by the first distance ring whose contribution margin falls below 15% after platform commission and logistics cost.
Does tightening my radius cost me ranking on Rappi or Uber Eats?
Does tightening my radius cost me ranking on Rappi or Uber Eats?
The opposite happens. These apps rank results by conversion probability, and estimated delivery time carries heavy weight in that calculation. Tightening the polygon lowers promised time, raises acceptance rate, and pushes the store up the listing within its zone.
Should a dark kitchen cover a wider radius than a physical restaurant?
Should a dark kitchen cover a wider radius than a physical restaurant?
No, it should cover a narrower one. A dark kitchen from scratch lives on concentrated volume and lacks the dining room that absorbs fixed costs, so every extra kilometer hits margin without compensation. The right strategy replicates adjacent polygons with virtual brands rather than stretching a single one.
How do I align my Google Business Profile with the real delivery radius?
How do I align my Google Business Profile with the real delivery radius?
Declare in the service area exactly the neighborhoods your polygon covers and publish weekly content naming them. A GBP promising more coverage than you serve generates «near me» searches that end in rejected orders, and those rejections become negative reviews that do damage local ranking.
Sector data 2026 (official sources)
Verifiable industry benchmarks from official, non-commercial sources (government, industry associations, market research) - not competitors.
| Metric | Benchmark 2026 | Source |
|---|---|---|
| Usuarios de delivery en línea LatAm 2026 | 147.0 millones de usuarios en 2026 | Statista 2024 |
| Mercado delivery y dark kitchens España | Aprox. USD 5 mil millones | Ken Research 2025 |
| Cuotas de mercado delivery España | Glovo ~31% y Just Eat ~26% del mercado | Ken Research 2025 |
| Ticket promedio delivery España | Aprox. USD 24 por pedido en línea | Ken Research 2025 |
| Quick commerce España al 2029 | USD 4.37 mil millones proyectados para 2029 | Research and Markets (GlobeNewswire) 2026 |
| Dark kitchens en Ciudad de México 2025 | Más de 1,200 dark kitchens activas; +40% desde 2023 | CANIRAC 2025 |
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