Customer Stickiness by Location
Share of customers with 2+ orders at a location in the window. A base-wide repeat measure every customer ever seen in Jan–Jun is the denominator.
Stickiness by Location
Brick & mortar stores ranked by repeat behavior. Food trucks shown separately they serve rotating locations and events, so one-time foot traffic dominates and the metric is not comparable.
| Location | Customers | Repeats | Stickiness | Rate |
|---|---|---|---|---|
La Jolla High stickiness at scale (20K base) | 20,296 | 4,063 | 20.0% | |
Palo Alto Top of the corporate set | 4,730 | 869 | 18.4% | |
San Jose | 8,835 | 1,323 | 15.0% | |
Oakland | 2,142 | 308 | 14.4% | |
San Francisco | 8,630 | 1,235 | 14.3% | |
San Mateo Lags pack, win-back opportunity | 7,550 | 853 | 11.3% |
| Location | Customers | Repeats | Stickiness | Rate |
|---|---|---|---|---|
SF Food Truck 2 | 9,477 | 659 | 7.0% | |
SF Food Truck 1 | 3,784 | 164 | 4.3% |
What This Tells Us
Three reads a CFO would highlight to investors.
Largest customer base in the system (20.3K) and still posting 20.0% stickiness. That combination depth and rate is the single most durable signal in the dataset.
Top of the tracked corporate set on a 4.7K customer base. Confirms the concept earns the repeat when the operation is clean.
11.3% on 7.6K customers meaningful traffic but the weakest conversion to repeat. Win-back and CRM testing here has the largest absolute upside.
SF Truck 2 (7.0%) and SF Truck 1 (4.3%) serve rotating locations and events mostly one-time foot traffic. Compare trucks to trucks, not to brick & mortar.
Stickiness = % of customers with 2+ orders at the location in the period. Customers = distinct purchasers (proxy). First-party only third-party delivery excluded per the retention rule; catering and voided orders excluded. Window covers Jan–Jun, so newer customers have less time to return; this is a base-wide repeat rate, not a fixed-window cohort retention.