compare_cohorts
E-commerce platforms vs Retail: the platforms beat the stores
E-commerce platforms outscore retailers on every facet and have more than twice the exemplars. Retail's agent readiness stays near 10.
E-Commerce Platform
Retail
Each sun is drawn from the cohort's averages: six facet rings, the mean Kin Score and mean agent readiness.
Commerce has two sides: the platforms that sell the plumbing, and the retailers who build on it. The 1,669 scored platforms average 21.1 against 17.9 for 1,027 retailers. The platform cohort holds 33 exemplars, including the 94.0 ceiling, against 13 in retail.
Retailers mostly consume APIs rather than publish them, and the facets show it. Retail trails on operational transparency (8.1 against 10.6), developer ergonomics (17.5 against 21.6) and contract quality (9.6 against 13.8). Agent readiness averages 10.1. That matters, because agentic commerce, with agents buying on a shopper’s behalf, will run through retailers’ own catalogs and checkouts.
One adoption rate goes the other way: retail is slightly likelier to publish OAuth scopes (21% against 20%). The delta is depth-confounded, and both cohorts are thinly covered, with medians of eight and seven artifact directories.
The distributions
| E-Commerce Platform | Retail | Delta | |
|---|---|---|---|
| Kin Score, mean | 21.1 | 17.9 | +3.2 |
| Kin Score, median | 15 | 12.4 | +2.6 |
| Kin Score, highest | 94 | 83.9 | |
| Kin Score, std dev | 17.2 | 15.6 | |
| Agent readiness, mean | 12.8 | 10.1 | +2.7 |
| Agent readiness, highest | 72.4 | 63.4 |
Delta is E-Commerce Platform minus Retail, as the tool returns it.
Where the providers sit
E-Commerce Platform
Retail
Facet averages
| Facet | E-Commerce Platform | Retail | Delta |
|---|---|---|---|
| Discoverability | 59.5 | 57.2 | +2.3 |
| Contract Quality | 13.8 | 9.6 | +4.2 |
| Contract Governance | 5.8 | 5.6 | +0.2 |
| Operational Transparency | 10.6 | 8.1 | +2.5 |
| Developer Ergonomics | 21.6 | 17.5 | +4.1 |
| Access Clarity | 24.4 | 20.7 | +3.7 |
What they publish
Share of each cohort's providers publishing each artifact. mcp_pct counts any mcp/ artifact including ones API Evangelist derived from the provider OpenAPI; mcp_first_party_pct counts only servers the provider publishes. Prefer the latter.
| Artifact | E-Commerce Platform | Retail | Delta |
|---|---|---|---|
| First-party MCP server | 11% | 8% | +3 |
| Any MCP artifact (incl. derived) | 23% | 20% | +3 |
| OAuth scopes | 20% | 21% | -1 |
| Spectral rules | 8% | 6% | +2 |
| Arazzo workflows | 1% | 1% | 0 |
| Agent skills | 0% | 0% | 0 |
| Security artifact | 99% | 99% | 0 |
How well we know each cohort
The coverage behind the averages. A cohort with a higher catalog gap and fewer artifact directories has been enriched less, so part of any difference is our coverage rather than the market.
| E-Commerce Platform | Retail | |
|---|---|---|
| Declared members | 1822 | 1118 |
| Scored (in the averages) | 1669 (92%) | 1027 (92%) |
| Thinly covered | 1545 | 977 |
| Median artifact directories | 8 | 7 |
| Mean catalog gap (points we could add) | 79.2 | 81.4 |
The full compare_cohorts response
{"a":{"kind":"industry","slug":"e-commerce-platform","name":"E-Commerce Platform","members":1822,"stats":{"kind":"industry","slug":"e-commerce-platform","name":"E-Commerce Platform","tier":"report","coverage":{"declared_members":1822,"resolved_members":1822,"scored_members":1669,"agent_scored_members":1669,"scored_share_pct":92,"unexamined_members":149,"enrichment_depth":{"mean_catalog_gap":79.2,"median_artifact_dirs":8,"n":1669,"thinly_covered":1545,"thinly_covered_of":1669,"thin_coverage_note":"1545 of 1669 scored members had under half their catalog-attributable points satisfied at all (catalog_earned / catalog_max < 0.5). They are INCLUDED in the mean above. A large share here means the cohort mean is partly a measurement of how far our enrichment reached, not only of how these providers publish.","note":"Rubric points API Evangelist could add to the average member with no action by the providers, and the median count of artifact directories we hold on them. A cohort with a higher gap and thinner artifacts has been enriched less, so part of any difference between its mean and another cohort's is our coverage rather than the market. Compare two cohorts only when this figure is comparable. It is an upper bound on our backlog: it says who CAN close a gap, not who did."},"unexamined_note":"Excluded from the distribution: these carry a catalog-owned needs_work flag (never enriched, or no resolvable host). They are listed as members and keep their own page and score; they do not vote in the averages, because their score measures our coverage rather than their posture."},"sufficient":true,"kin_score":{"mean":21.1,"median":15,"min":0,"max":94,"stdev":17.2},"agent_readiness":{"mean":12.8,"median":4.5,"min":0,"max":72.4,"stdev":15.6},"band_distribution":{"exemplar":33,"strong":68,"developing":161,"thin":257,"emerging":556,"minimal":594},"facet_averages":{"discoverability":{"mean":59.5,"n":1669},"contract_quality":{"mean":13.8,"n":1669},"contract_governance":{"mean":5.8,"n":1669},"operational_transparency":{"mean":10.6,"n":1669},"developer_ergonomics":{"mean":21.6,"n":1669},"access_clarity":{"mean":24.4,"n":1669}},"adoption":{"mcp_pct":23,"mcp_first_party_pct":11,"mcp_note":"mcp_pct counts any mcp/ artifact including ones API Evangelist derived from the provider OpenAPI; mcp_first_party_pct counts only servers the provider publishes. Prefer the latter.","skills_pct":0,"scopes_pct":20,"security_pct":99,"arazzo_pct":1,"rules_pct":8}}},"b":{"kind":"industry","slug":"retail","name":"Retail","members":1118,"stats":{"kind":"industry","slug":"retail","name":"Retail","tier":"report","coverage":{"declared_members":1118,"resolved_members":1118,"scored_members":1027,"agent_scored_members":1027,"scored_share_pct":92,"unexamined_members":87,"enrichment_depth":{"mean_catalog_gap":81.4,"median_artifact_dirs":7,"n":1027,"thinly_covered":977,"thinly_covered_of":1027,"thin_coverage_note":"977 of 1027 scored members had under half their catalog-attributable points satisfied at all (catalog_earned / catalog_max < 0.5). They are INCLUDED in the mean above. A large share here means the cohort mean is partly a measurement of how far our enrichment reached, not only of how these providers publish.","note":"Rubric points API Evangelist could add to the average member with no action by the providers, and the median count of artifact directories we hold on them. A cohort with a higher gap and thinner artifacts has been enriched less, so part of any difference between its mean and another cohort's is our coverage rather than the market. Compare two cohorts only when this figure is comparable. It is an upper bound on our backlog: it says who CAN close a gap, not who did."},"unexamined_note":"Excluded from the distribution: these carry a catalog-owned needs_work flag (never enriched, or no resolvable host). They are listed as members and keep their own page and score; they do not vote in the averages, because their score measures our coverage rather than their posture."},"sufficient":true,"kin_score":{"mean":17.9,"median":12.4,"min":0,"max":83.9,"stdev":15.6},"agent_readiness":{"mean":10.1,"median":0.6,"min":0,"max":63.4,"stdev":13.8},"band_distribution":{"exemplar":13,"strong":26,"developing":73,"thin":142,"emerging":318,"minimal":455},"facet_averages":{"discoverability":{"mean":57.2,"n":1027},"contract_quality":{"mean":9.6,"n":1027},"contract_governance":{"mean":5.6,"n":1027},"operational_transparency":{"mean":8.1,"n":1027},"developer_ergonomics":{"mean":17.5,"n":1027},"access_clarity":{"mean":20.7,"n":1027}},"adoption":{"mcp_pct":20,"mcp_first_party_pct":8,"mcp_note":"mcp_pct counts any mcp/ artifact including ones API Evangelist derived from the provider OpenAPI; mcp_first_party_pct counts only servers the provider publishes. Prefer the latter.","skills_pct":0,"scopes_pct":21,"security_pct":99,"arazzo_pct":1,"rules_pct":6}}},"comparable":true,"delta":{"kin_score_mean":3.2,"kin_score_median":2.6,"agent_readiness_mean":2.7,"facets":{"discoverability":2.3,"contract_quality":4.2,"contract_governance":0.2,"operational_transparency":2.5,"developer_ergonomics":4.1,"access_clarity":3.7},"adoption":{"mcp_pct":3,"mcp_first_party_pct":3,"mcp_note":null,"skills_pct":0,"scopes_pct":-1,"security_pct":0,"arazzo_pct":0,"rules_pct":2},"enrichment_depth":{"mean_catalog_gap":-2.2,"median_artifact_dirs":1}},"depth_confounded":true,"depth_note":"E-Commerce Platform scores 3.2 points higher than Retail AND is the better-enriched cohort: 2.2 points less catalog_gap and 1 more artifact directories on the median member. The market difference and our coverage difference point the same way, so this delta cannot be attributed to the markets on its own. Close the enrichment gap, or report both figures together."}
Result read 2026-10-27. E-Commerce Platform and Retail each have their own page with the full roster and leaderboard.
Run this comparison yourself
Everything above came from one call to compare_cohorts. Swap in any two tags, industries, regions, areas or VC portfolios and you get the same answer for your own shortlist. It is an Understanding tool, included in the Understanding and Influence plans, or pay per call.
https://apis.io/mcp:
{"name": "compare_cohorts", "arguments": {"a": "industry:e-commerce-platform", "b": "industry:retail"}}
Over the REST API:
curl "https://apis.io/api/v1/cohorts/compare?a=industry:e-commerce-platform&b=industry:retail" \
-H "X-API-Key: $APIS_IO_KEY"
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