Use marketplace benchmarks to compare sponsored placements, listing conversion efficiency, and retail-media performance without forcing them into generic ecommerce targets. Marketplace CTR, CPC, ROAS, listing conversion rate, and review-driven conversion support.
Top-level marketplace marketing benchmarks for Amazon, Walmart Marketplace, Etsy, Instacart, DoorDash Marketplace, and other in-market catalog environments.
| Context | Median | Top Quartile | Best For |
|---|---|---|---|
| Sponsored Product CTR | 0.7% | 1.2% | Capturing in-market shopper demand on category or product queries |
| Listing Conversion Rate | 9.8% | 14.6% | Product-detail-page efficiency and retail readiness |
| Brand Store Traffic-to-Order | 5.1% | 8.4% | Bundling, cross-sell, and brand-store merchandising |
| Marketplace ROAS | 4.3x | 6.8x | Retail-media spend efficiency in high-intent catalog demand |
| Review-Led Conversion Lift | 12% | 21% | Trust-sensitive products where rating and proof change purchase confidence |
These top-level pages work best when they explain why benchmark ranges shift before a user drills into the narrower benchmark route.
| Driver | Impact |
|---|---|
| Marketplace algorithm behavior, listing quality, and retail readiness on the PDP | Marketplace CTR, CPC, ROAS, listing conversion rate, and review-driven conversion support. |
| Review volume, rating quality, and price competitiveness inside the category | Marketplace CTR, CPC, ROAS, listing conversion rate, and review-driven conversion support. |
| Sponsored vs organic placement mix and how much demand the listing can convert on its own | Marketplace CTR, CPC, ROAS, listing conversion rate, and review-driven conversion support. |
| Catalog structure, inventory reliability, and buy-box or fulfillment competitiveness | Marketplace CTR, CPC, ROAS, listing conversion rate, and review-driven conversion support. |
Top-level marketplace marketing benchmarks for Amazon, Walmart Marketplace, Etsy, Instacart, DoorDash Marketplace, and other in-market catalog environments.
Use marketplace benchmarks to compare sponsored placements, listing conversion efficiency, and retail-media performance without forcing them into generic ecommerce targets.
Use marketplace benchmarks to compare sponsored placements, listing conversion efficiency, and retail-media performance without forcing them into generic ecommerce targets.
Use marketplace benchmarks to compare sponsored placements, listing conversion efficiency, and retail-media performance without forcing them into generic ecommerce targets.
Use marketplace benchmarks to compare sponsored placements, listing conversion efficiency, and retail-media performance without forcing them into generic ecommerce 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 different from generic ecommerce benchmarks because the platform owns the shopping environment, search behavior, and many parts of the conversion path.
They explain both retail-media performance and listing conversion strength, since weak PDPs can distort otherwise healthy ad efficiency.