How do I compare call handling across locations without the comparison being unfair?
Compare within call type, not across totals. Locations differ in demand mix, service area density, seasonality and staffing model, so raw booking rate rankings mostly measure market, not skill. Rank on booking rate for bookable new-demand calls inside the same category, and treat each location's own trend as the primary signal. Cross-location ranking is a conversation starter, not a scorecard.
Why raw rankings mislead
One location sits in a dense metro with heavy emergency demand and books almost everything it answers. Another covers a rural territory where half the calls are outside the drive radius. A third runs a call center that also fields billing questions for the whole group. Their headline booking rates are not comparable in any useful sense.
Ranking them anyway produces the worst outcome available: the strongest team looks weak, everyone learns the metric is unfair, and the data stops influencing behavior at all.
The normalizations that matter most
- Call mix. Compare new-demand calls to new-demand calls. Service and billing traffic varies enormously by location and swamps everything else.
- Bookability. Apply the same service-area and services-offered rules per location, using that location's real boundary.
- Hours and coverage model. A location with live evening coverage and one using an answering service are running different experiments.
- Capacity. Booking rate is capped by available appointment slots. A booked-out location cannot book, and that is a scheduling fact, not a phone failure.
- Seasonality offset. Markets do not enter season on the same week, so a single group-wide month comparison distorts the ones that started later.
Trend beats rank
The most defensible multi-location metric is each location compared to itself over time, with the group median shown as context rather than as a target. That framing removes almost all of the fairness objections and still surfaces the location that slipped.
When a location does move, the diagnostic sequence is the same one you would run for a single business: volume, answer rate, bookable share, then booking rate. Running that automatically for every location and rolling it up is exactly what multi-location briefs are for, because no regional manager has time to do it by hand across eight markets.
What to do with the outlier
When one location genuinely outperforms after normalization, the value is not in the ranking. It is in the calls. Pull the recordings and find the specific behaviors, then use them as coaching material everywhere else. That transfer of practice is the only real return on cross-location measurement.
Doing it well requires consistent evaluation criteria across every market, which is the practical case for a shared rubric rather than each manager grading by feel. It is also where a group-level view of revenue by market stops being a report and starts being an operating tool.
Topics: multi-location · benchmarking · booking rate · normalization
Have a version of this question about your own business?
The useful answer usually depends on which systems you run and how they're connected. That's a conversation, not a blog post.