Choose a task.
Follow the evidence.

Make product data usable

Resolve identity, measurements, compatibility, and purchase conditions, then verify the destination record.

1. Product data an agent can use without guessing. ↗

   A practical product-data contract for variants, dimensions, availability, provenance, and unknown values, with a downloadable JSON example.

2. SKU vs GTIN: differences, barcodes, and variant IDs ↗

   Learn the difference between SKU and GTIN, map Shopify variant IDs, and keep product groups separate. Includes a worked example and downloadable identity ledger.

3. Product data ownership: resolve a price conflict ↗

   A field-ownership register for PIM, ERP, storefront, and feed data, with a worked correction and explicit release checks.

4. Product dimensions vs package dimensions: compare units safely ↗

   Compare product or package dimensions in your browser. Convert inches, cm, mm, and metres; inspect differences and download the result with your source records.

5. Comparing product dimensions across country pages: a 30-listing audit ↗

   Eight complete comparisons, twenty retrieval gaps and two axis gaps: a reproducible audit of displayed product dimensions on sampled IKEA US and GB pages.

6. Product compatibility data: prove the exact accessory match ↗

   Separate compatible products from related products. Use exact model pairs, revisions, adapters, and source evidence, with a downloadable decision ledger.

7. Shipping and return policy data for shopping agents ↗

   Compare delivery charges, handling time, return windows, and policy exceptions in one scoped record. Includes fictional offers and a reusable JSON worksheet.

8. Product feed specification: Shopify, Google, and ChatGPT ↗

   Map 20 product feed fields across Shopify, Google Merchant Center, and ChatGPT. Compare IDs, price, stock, and variants; download the JSON reference.

9. Can you copy a product feed unchanged? A 12-case test ↗

   Inspect twelve synthetic product records or check your own JSON locally. Review explicit mappings, unresolved fields, and supplied evidence; download reproducible results.

10. ChatGPT product feeds: sale prices, stock changes, and stale-data checks ↗

    Check current price and stock evidence against a ChatGPT product-feed snapshot. Includes a local checker, six fictional cases, and explicit timestamp rules.

11. Why a product feed check can pass while the records disagree ↗

    Five reproducible synthetic source/feed pairs separate single-record checks from price agreement, exact identity and fresh evidence. Includes inputs, results and runner.

12. Does the product page match the variant you submitted? ↗

    A six-case acceptance test for variant identity, price, availability, and missing facts, with reusable JSON fixtures.

Check the commercial decision

Reconcile the revenue, account for returns, and test whether stock supports more advertising.

1. ROAS calculator: break-even and contribution ↗

   Calculate ROAS, contribution after advertising, and the break-even return for your margin. Includes worked examples and a margin comparison.

2. Why retail-media revenue and settled orders disagree ↗

   Bridge ad-attributed sales to a defined order ledger, preserve unresolved differences, and keep bank payouts separate. Includes a worked USD example and CSV/JSON worksheet.

3. Is the campaign still profitable after returns? ↗

   A worked order-cohort reconciliation for refunds, recovered inventory, return costs, and ad spend, with a reusable review template.

4. Can your stock support more ad spend? ↗

   An inventory and ad-spend calculator with daily stock checks, a delayed-delivery example, and a downloadable decision worksheet.

Release agent-assisted work

Choose a bounded workflow, define acceptance, and count the effort needed to deliver it.

1. Agentic commerce starts with an operating model. ↗

   A practical framework for choosing agent-assisted commerce work, setting decision rights, and proving that the result is worth the cost.

2. From request to release: a supervised commerce workflow. ↗

   An original seven-stage operating checklist for turning agent-assisted commerce work into an inspectable, authorized, verified release.

3. How do you check AI product copy before publishing? ↗

   A claim-by-claim review method, six failure cases, and a reusable evaluation brief for AI-assisted product descriptions.

4. Did AI save time after review and rework? ↗

   Compare the full cost of accepted work, including preparation, supervision, review, and corrections. Includes a local calculator and a reusable time ledger.

Measure visibility, attribution, and visits

Check access first, then separate exposure, visits, and outcomes before choosing an improvement.

1. Make a website easy for agents to find, read, and use. ↗

   An evidence-based guide to crawler access, HTML, structured data, Markdown, llms.txt, feeds, and real tool descriptions.

2. AI visibility metrics: impressions, citations, referrals, and outcomes ↗

   A source-linked metric dictionary for people and agents building AI visibility reports. Includes units, formulas, interpretation limits, and a versioned JSON download.

3. How to read Search Console’s generative AI report ↗

   Measure Google AI Overviews and AI Mode exposure, avoid double counting, and turn an impression report into a useful content decision. Includes a review worksheet.

4. How to measure AI citations and visible brand attribution ↗

   A repeatable rubric for checking whether an AI answer consulted, linked, displayed, or named your source. Includes a blank ledger and calibration examples.

5. How to find referral traffic in GA4, including AI ↗

   Find referring sites in GA4, separate Referral from AI Assistant, and check Google AI traffic. Includes report steps and a downloadable review worksheet.

6. Why Search Console, GA4, and Vercel show different traffic numbers ↗

   Compare clicks, sessions, and page views without forcing the totals to match. Includes a worked example and a reusable reconciliation worksheet.

7. Search impressions but no clicks: a diagnostic and planning calculator ↗

   Work backward from a click target, test CTR assumptions, and choose a useful response to search exposure with few visits. Includes a local calculator and worked scenarios.

8. Measure AI visibility without confusing it with traffic. ↗

   A measurement framework that separates crawler access, answer citations, referral visits, and qualified commercial outcomes.

Open the focused measurement collection ↗