The CatalogIQ Index

One number for catalog quality.

A single 0 to 100 score across 13 dimensions in two sub-indices, measured against published commerce and classification standards. One read on whether your catalog can compete where buyers actually look.

Request your assessment → Read the methodology
52/ 100
CatalogIQ Index
DEVELOPING
ACatalog Quality & Discoverability54
BAI Commerce Readiness49
Return Risk signalElevatedWeight 0
Structure · one number

One number, two sub-indices, thirteen dimensions.

The Index resolves to two weighted sub-indices across twelve weighted dimensions. The thirteenth, Return Risk, is a signal reported beside the Index at weight zero, never folded into it.

0 to 100
A single score anyone can read at a glance, comparable across catalogs scored the same way.
2
Sub-indices: A, Catalog Quality and Discoverability (the data and how it is found), and B, AI Commerce Readiness (how machines transact with it).
13
Dimensions, 12 weighted plus Return Risk reported beside the Index at weight 0.
CatalogIQ Index0 to 100 · 13 dimensions Sub-index A · Quality & Discoverability8 weighted dimensions · 60% of Index Sub-index B · AI Commerce Readiness4 weighted dimensions · 40% of Index Attr Completeness 20 Value Consistency 18 Classification 15 Findability 15 Spec Accuracy 14 Technical Docs 8 Descriptions 6 Imagery 4 Structured Data 30 Agent Attributes 28 Feed Protocol 24 NL Parseability 18 Return Risk signalweight 0 · reported beside the Index not folded into the score
Dimensions carry their v8.0 weight (shown as % within each sub-index); the split is 60% A / 40% B. Return Risk is reported beside the Index at weight 0.
A

Catalog Quality and Discoverability

8 weighted dimensions

The structural and content quality of your data: completeness, accuracy, identifiers, structure, categorization, media, descriptions, and customer experience. The half a human can partly see.

Completeness71
Accuracy58
Identifiers (GTIN/UPC)29
B

AI Commerce Readiness

4 weighted dimensions

How findable and machine-readable your products are: agent reachability, semantic richness, structured attributes, and taxonomy mapping. The half only a measurement built for machines can see.

Agent reachability38
Structured attributes44
Taxonomy mapping61
The independence proof

Measured against the standards, not a random opinion.

Because the standards are public and the weights are published, you can see exactly why your catalog scored the way it did and take real action to make it competitive. ECLASS and ETIM are the leading technical classification standards for B2B and industrial product caalogs; Google, Amazon, and GS1 provide the guidance for many CPG and arry consumer catalogs.

See the framework →Read the methodology →
ETIMETIM ECLASSECLASS UNSPSCUNSPSC GS1GS1 GoogleGoogle AmazonAmazon
What you get back

The number, then the work behind it.

Top gaps by impact, sample
1
Missing GTIN / UPC identifiers
Sub-index A · Identifiers · critical
4,820SKUs
2
No structured attributes for agents
Sub-index B · Agent reachability · critical
3,107SKUs
3
Thin or duplicated descriptions
Sub-index A · Content quality · high
2,540SKUs
Peer benchmark, sample distribution
0-19
20-29
30-39
You · 52
40-59
60-79
80-100
Peer median 37Your score 52Top decile 78+
From score to fixed

The score points to the work. The re-score confirms it.

Closing a gap does not count because someone marked it done. It counts because a fresh measurement proves it. That is the loop, and it is why remediation never compromises the score.

Voltage rating on Eaton XTCE009B10 Contactor• Re-score confirmed
Baseline
not present
score 40
→
Current
24V AC coil
score 61+21

Questions about the Index.

What does CatalogIQ measure?

CatalogIQ measures the quality of your product catalog data and produces a single score from 0 to 100. It reads your catalog the way AI shopping agents, marketplaces, and search engines read it, then grades it across 13 dimensions organized into two sub-indices: A, Catalog Quality and Discoverability, which covers the structural and content quality of your data and how findable it is, and B, AI Commerce Readiness, which covers how ready your products are to be read and transacted by machines.

Is CatalogIQ a PIM?

No. A PIM stores and manages your catalog data. CatalogIQ measures its quality independently. The two are complementary: a PIM is where your data lives, and CatalogIQ is the independent score that tells you whether what is in it is good enough to compete. We do not replace your PIM and we are not trying to.

How is the CatalogIQ Index calculated?

The Index is a weighted score across 12 of the 13 dimensions, split between the two sub-indices, A Catalog Quality and Discoverability and B AI Commerce Readiness, plus a separate Return Risk signal that is reported alongside the Index for information rather than folded into it. The full weighting and method are published openly on the Methodology page, which is part of what makes the score independent and auditable.

What standards does CatalogIQ score against?

Published, recognized standards, not our private opinion. The active set includes ETIM, ECLASS, UNSPSC, GS1, the Google Product Taxonomy, and Amazon's requirements. Because the standards are public and the weights are published, you can see exactly why your catalog scored the way it did.

Can I get a free score?

Yes. The free Snapshot tier is an assisted assessment that runs on a sample of your catalog and gives you your number, with a walkthrough of the gaps that cost you the most. The paid tiers extend that to your full catalog, track it over time, and tell you what is behind the number.

How is my score benchmarked against competitors?

Paid tiers place your score against a peer benchmark for your category, so you see not just your number but where you stand relative to others measured the same way. The benchmark is built from catalogs scored on the identical methodology, which is what makes the comparison fair.

See where your catalog stands on the Index.

Your number, your sub-indices, and the gaps that matter most.

Request your assessment → Read the methodology