The overlap, by drive time
Both footprints routed on the road network. “Both” is the population that can reach a Hardee's and a Burger King within the same drive time.
| Drive time | Hardee's reach | Burger King reach | Both | % of Hardee's | % of Burger King |
|---|---|---|---|---|---|
| 5 min | 14,733,998 | 97,631,916 | 6,958,596 | 47.23% | 7.13% |
| 10 min | 45,220,955 | 219,182,805 | 37,833,085 | 83.66% | 17.26% |
| 15 min | 76,497,142 | 264,928,563 | 70,600,616 | 92.29% | 26.65% |
| 30 min | 147,756,987 | 308,390,721 | 143,772,898 | 97.3% | 46.62% |
| 60 min | 214,272,311 | 326,537,032 | 213,342,484 | 99.57% | 65.33% |
What it means
At 30 minutes, 97.3% of the people Hardee's can reach are also inside a Burger King catchment. 3,984,089 people are Hardee's's alone.
A high shared percentage is not automatically bad. It means the two chains have solved the same geography. It matters when one of them is planning to add units: incremental reach comes from the exclusive population, not the shared one.
Narrative Geo does not sample. Every trade area is routed on the actual road network with OSRM, against full Census/ACS population and a maintained POI set. The drive-time matrix is precomputed at 1.08 billion rows, so a national query across a 20,000-store chain returns in seconds rather than being metered per location.