Benchmarks / Apparel / v2.0.4
Apparel agentic commerce benchmark v2.0.4
This is version v2.0.4, issued 9 October 2026. The current version is v2.0.8.
Across 58 apparel stores Ottom measured at every stage in the 90 days to 9 October 2026, the median agentic readiness score was 97 out of 100. 84% of them let an AI shopping agent reach the payment step.
n = 58 of 60 stores · 11 July 2026 to 9 October 2026 · v2.0.4 · bench-v5 · methodology
Scores come from the 58 stores Ottom measured at every stage. A further 2 were scanned but stopped before checkout, usually at bot protection or a robots.txt rule, so they have no comparable score. All 60 are still counted in the stalls below, because what was found on a store does not depend on how it was scored.
A store enters Ottom’s survey only if a catalogue of at least ten products can be read from it in one request, which in practice means Shopify and WooCommerce storefronts. These figures therefore describe the storefronts Ottom can read in bulk rather than apparel as a whole. The methodology sets out what that excludes.
Readiness score
The median of the 58 apparel stores Ottom measured at every stage in the 90 days to 9 October 2026 scored 97 out of 100, and a quarter of them scored 92 or below.
The spread of overall readiness scores across the category. We publish quartiles rather than a best and worst store, because the best and the worst are each one identifiable merchant.
Where agents stall
Of the 58 apparel stores Ottom measured at every stage, 71% scored 80 or better at the discover stage, against 95% at the compare stage.
Each stage of the journey, and the share of apparel stores whose score at that stage was 80 or better.
| Stage | Median score | Stores passing | Stores measured |
|---|---|---|---|
| Discover | 100 | 71% | 58 |
| Evaluate | 88 | 86% | 58 |
| Compare | 100 | 95% | 58 |
| Buy | 100 | 84% | 58 |
Reaching the payment step
84% of the 58 apparel stores Ottom measured let an AI shopping agent reach the payment step. Ottom stops there and never submits payment.
What stops them
The most common stall on apparel stores is products have no GTIN or MPN to match against, found on 65% of the 60 stores Ottom scanned in the category in the 90 days to 9 October 2026.
The most common stalls in this category, as a share of all 60 stores scanned. A stall found on fewer than 5 stores is withheld, because at that count it points at a merchant rather than at a category.
- No sitemap18%
- No product structured data8%
- No product identifier65%
- Variants undescribed13%
None common
None common
| Stall | Stage | Severity | Share of stores |
|---|---|---|---|
| Products have no GTIN or MPN to match againstEvaluate | Evaluate | Medium | |
| No sitemap for agents to crawlDiscover | Discover | High | |
| Variants are not described in structured dataEvaluate | Evaluate | High | |
| Product pages have no schema.org markupDiscover | Discover | High |
What to change first
- No product identifier
Populate the barcode field (GTIN, EAN or UPC) on each variant, which most platforms already have a field for.
- No sitemap
Publish /sitemap.xml covering product, collection and policy URLs. Most platforms generate this for you once it is enabled.
- Variants undescribed
Add hasVariant entries to the Product markup, one per purchasable combination, each with its own offer carrying price and availability.
6 further stalls were found in this category but withheld: too few stores showed them to report a share without pointing at an individual store.
Citing this benchmark
These figures are published under CC BY 4.0. Quote them freely, with this attribution:
Ottom, Apparel agentic commerce benchmark v2.0.4, 11 July 2026 to 9 October 2026, methodology bench-v5. https://ottom.io/benchmarks/apparel/v2.0.4. Licensed CC BY 4.0.
The same figures as JSON.