Franchise benchmark pages need geography, brand, and local-operator context because corporate marketing and local execution both influence performance. Lead cost, booked rate, local conversion efficiency, and location-level variance.
Use these labeled KPIs together instead of judging franchise performance from one headline number. Conversion-sensitive metrics update when you change the conversion type above.
| Metric | Median | Top Quartile | What It Tells You |
|---|---|---|---|
| CTR | 2.4% | 4.1% | Creative and message-to-audience fit |
| CPC | $2.80 | $1.65 | Click acquisition efficiency |
| CVR | 3.4% | 6.2% | Landing-page and offer effectiveness |
| CPA | $82 | $45 | Cost to generate the selected conversion |
| CPM | $12.40 | $7.80 | Auction pressure and reach efficiency |
| ROAS | 3.1x | 5.2x | Revenue efficiency where purchase value is tracked |
Lead cost, booked rate, local conversion efficiency, and location-level variance. Benchmarks should be interpreted with contextual commentary, not as standalone averages.
| Business Type | Average | Median | Top Quartile | Bottom Quartile |
|---|---|---|---|---|
| Franchise | $57 | $46 | $28 | $91 |
These are the main drivers that typically explain why the same headline metric changes across channels, industries, and conversion contexts.
| Factor | Why It Matters |
|---|---|
| Location-level operational consistency | Changes how lead cost, booked rate, local conversion efficiency, and location-level variance. |
| Brand strength vs local competition | Changes how lead cost, booked rate, local conversion efficiency, and location-level variance. |
| Centralized vs local marketing execution | Changes how lead cost, booked rate, local conversion efficiency, and location-level variance. |
Franchise benchmark pages need geography, brand, and local-operator context because corporate marketing and local execution both influence performance.
Franchise benchmarks should surface local variance and operational consistency instead of presenting one blended average across locations.
Franchise benchmarks should surface local variance and operational consistency instead of presenting one blended average across locations.
Franchise benchmarks should surface local variance and operational consistency instead of presenting one blended average across locations.
The Benchmarketing 4-Band Method. The Benchmarketing 4-Band Method reads every marketing metric against four percentile bands — P25 (bottom quartile), median, P75 (top quartile), and elite (top ~10%) — for a specific industry and channel, instead of a single cross-industry average. Averages blend brand and non-brand campaigns, $500/month and $500,000/month accounts, and unrelated industries into a number almost nobody actually has.
Where the numbers come from. The figures on this page come from the Benchmarketing benchmark dataset — thousands of curated benchmark observations across channels, industries, and US metro areas. Every statistic traces to a named source: WordStream Google Ads Benchmarks (2024), Meta Business Insights (2024), HubSpot Email Marketing Report (2024), Unbounce Conversion Benchmark Report (2024), Databox Marketing Benchmark Report (2024), Benchmarketing Platform Data (2023–2024). Benchmarketing does not publish anonymous "studies show" figures.
The Benchmarketing position. Beating the cross-industry average is a vanity milestone, not a target. Compare your number to the P25–P75 band for your specific industry and channel; if you are above average but below your industry's P75, you are leaving performance on the table.
They particularly sensitive to geography because the same brand can perform very differently across markets and operators.
Use both blended brand benchmarks and location-level operational benchmarks so weak local execution is not hidden.