Case studies

Three shops, three agent breaks, fixed.

Product selection, policy trust, and AI search are where agent purchases break first. Here is what changed when each one got fixed.

ExampleB2B supply · 30-day sprint01

Cartpilot: 38% fewer agent drop-offs in 30 days.

Cartpilot converted well for humans, but AI agents could not compare variants, service levels, and bundle rules. We rebuilt the product evidence, clarified checkout, and left a repeatable agent-readiness test.

IndustryB2B industrial supply
Catalog12,400 SKUs
Timeline30 days

Services

Agent Journey MappingStructured Commerce UXCheckout Readiness

"We didn't have a conversion problem. We had an agent-trust problem. In 30 days it was gone."

Head of ProductCartpilot

38%fewer agent drop-offs
61%more product evidence live
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ExampleDTC beauty · 6-week sprint02

Verity Goods: 42% fewer policy escalations in 6 weeks.

Verity's product pages convinced people, but delivery, returns, and warranty resolved three different ways. Agents bailed to support. We made every promise one citable value across all surfaces.

IndustryDTC beauty / skincare
Catalog240 SKUs
Timeline6 weeks

Services

Trust SystemsPolicy VisibilityAI Search Readiness

"Our pages were strong — but only for humans. Now they're strong for agents too, without any loss for customers."

COOVerity Goods

42%fewer policy escalations
2.4×clearer answer coverage
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ExampleSpecialty retail · 8-week sprint03

Northstar: 74% more answerable product questions in 8 weeks.

Northstar's edge was expert advice locked in chat logs and PDFs. AI search couldn't cite it. We turned the buying logic into structured criteria and compatibility data agents could quote.

IndustrySpecialty outdoor retail
Catalog3,800 SKUs
Timeline8 weeks

Services

Product EvidenceComparison UXAgent QA

"AI search now cites us where competitors used to be. The recommendation logic became part of the product."

FounderNorthstar Goods

74%answerable product questions
31%fewer agent dead ends
View analysis
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