Case Study — Ecommerce & Retail

A large catalog with thin, inconsistent product content.

An illustrative scenario showing how we'd approach this challenge in Ecommerce & Retail — not a claim about a specific past client.

The Situation

Hundreds of SKUs carry generic, inconsistent descriptions written by different people over several years. There's no email lifecycle program capturing existing traffic, and Google Shopping feed errors are quietly suppressing visibility on the best-margin products without anyone noticing.

Expert Diagnosis

Catalog content problems compound silently. A single missing GTIN or mismatched category doesn't just hurt one listing, it can suppress feed approval for adjacent products too. Feed health is diagnosed before any content rewrite begins, since rewriting descriptions on a broken feed wastes the work.

Our Approach, Phase by Phase

01 / Audit

Full feed health check across Google Merchant Center and any marketplace channels in use.

02 / Fix Feed Errors

Resolve rejections and warnings suppressing visibility on the highest-margin SKUs first.

03 / AI Content Pass

Generate and human-review descriptions catalog-wide, prioritized by revenue contribution.

04 / Capture Existing Traffic

Launch an Email Growth Engine in parallel so current visitors aren't leaving without ever being captured.

Capabilities Applied

AI for Commerce, Marketing & Email, Digital Commerce

Typical Timeline

4–6 weeks for initial catalog and feed fixes

See the AI for Commerce Capability →
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