Use local marketing benchmarks to judge call, booking, map, and in-market discovery performance without blending local service intent into national acquisition targets. Calls, bookings, store visits, Google Business Profile actions, and geography-weighted intent.
Top-level local marketing benchmarks for maps, Google Business Profile, local service ads, click-to-call, store-visit, and geography-sensitive conversion actions.
| Context | Median | Top Quartile | Best For |
|---|---|---|---|
| Google Business Profile Actions | 7.4% | 12.8% | Map-driven discovery and near-me demand |
| Local Service Ads Lead Rate | 16% | 24% | Urgent service intent and booked-call efficiency |
| Click-to-Call Campaigns | 11.2% | 18.6% | Mobile-first lead capture with low friction |
| Store Visit Objectives | 5.5% | 9.1% | Retail and multi-location foot-traffic goals |
| Review / Reputation Pages | 3.2% | 6.4% | Trust-driven conversion support near decision time |
These top-level pages work best when they explain why benchmark ranges shift before a user drills into the narrower benchmark route.
| Driver | Impact |
|---|---|
| Geography, competition density, and how local demand behaves inside one metro or service radius | Calls, bookings, store visits, Google Business Profile actions, and geography-weighted intent. |
| Mobile intent and the speed of actions like calling, routing, or booking from map surfaces | Calls, bookings, store visits, Google Business Profile actions, and geography-weighted intent. |
| Operational follow-through, especially answer rate, scheduling coverage, and location reputation | Calls, bookings, store visits, Google Business Profile actions, and geography-weighted intent. |
| Platform differences between maps, local ads, and website-driven local landing pages | Calls, bookings, store visits, Google Business Profile actions, and geography-weighted intent. |
Top-level local marketing benchmarks for maps, Google Business Profile, local service ads, click-to-call, store-visit, and geography-sensitive conversion actions.
Use local marketing benchmarks to judge call, booking, map, and in-market discovery performance without blending local service intent into national acquisition targets.
Use local marketing benchmarks to judge call, booking, map, and in-market discovery performance without blending local service intent into national acquisition targets.
Use local marketing benchmarks to judge call, booking, map, and in-market discovery performance without blending local service intent into national acquisition targets.
Use local marketing benchmarks to judge call, booking, map, and in-market discovery performance without blending local service intent into national acquisition targets.
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 unusually sensitive to geography, device behavior, and business operations, which makes local pages poor candidates for one-size-fits-all performance targets.
They should connect maps, calls, bookings, and reputation signals because the local conversion path is rarely one channel deep.