Store-visit benchmarks matter for retail, restaurants, healthcare, and multi-location brands where the real outcome is foot traffic or a location-level visit rather than an online form fill. Visit rate, cost per visit, post-click directions rate, and location-level lift.
Use these labeled KPIs together instead of judging store visit 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 |
Visit rate, cost per visit, post-click directions rate, and location-level lift. Benchmarks should be interpreted with contextual commentary, not as standalone averages.
| Conversion Type | Average | Median | Top Quartile | Bottom Quartile |
|---|---|---|---|---|
| Store Visit | 7.3% | 5.9% | 11.1% | 2.6% |
These are the main drivers that typically explain why the same headline metric changes across channels, industries, and conversion contexts.
| Factor | Why It Matters |
|---|---|
| Distance and local intent between the user and the location | Changes how visit rate, cost per visit, post-click directions rate, and location-level lift. |
| Map visibility, review quality, and offer relevance | Changes how visit rate, cost per visit, post-click directions rate, and location-level lift. |
| Location convenience, hours, and operational follow-through | Changes how visit rate, cost per visit, post-click directions rate, and location-level lift. |
Store-visit benchmarks matter for retail, restaurants, healthcare, and multi-location brands where the real outcome is foot traffic or a location-level visit rather than an online form fill.
Store-visit pages should be benchmarked with market density, mobile behavior, and location operations because the same media can perform very differently across markets.
Store-visit pages should be benchmarked with market density, mobile behavior, and location operations because the same media can perform very differently across markets.
Store-visit pages should be benchmarked with market density, mobile behavior, and location operations because the same media can perform very differently across markets.
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.
Use visit rate, cost per visit, direction intent, and market context together so the benchmark reflects actual local demand quality.
They need their own benchmark logic because the outcome is offline, geography-sensitive, and strongly affected by location-level execution.