Top quartile refers to the top 25% of benchmark observations in a dataset.
| Field | Detail |
|---|---|
| In plain English | It shows what stronger-performing programs look like, without only focusing on the single best outlier. |
| Why it matters | Top-quartile benchmarks help teams set ambitious but still realistic improvement targets. |
| Good benchmark context | Top quartile should be used with median and bottom quartile so users can understand the full distribution, not just the aspirational number. |
Where interpretation of Top Quartile most often goes wrong.
| Common mistake |
|---|
| Treating top quartile like the default target for every team. |
| Using top-quartile figures without showing the median for context. |
| Ignoring whether the comparison set is truly similar enough. |
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), AdLiftr Snapchat Ads Cost Benchmarks (2026), Ad Badger Amazon Advertising Benchmarks (2026). 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.
It shows what stronger-performing programs look like, without only focusing on the single best outlier.
Top quartile should be used with median and bottom quartile so users can understand the full distribution, not just the aspirational number.