Haynechi
Haynechi Index Understand where you stand in AI Search before competitors own the prompt map.

Commerce

Control how products appear in AI shopping journeys

Measure SKU-level inclusion, attribute accuracy, review sentiment, and retailer citation quality in AI shopping answers.

Map this surface Platform model
Capture: SKU promptNormalize: Retailer sourceRoute: Fix queueProve: Shelf movement

Shopping Shelf

Which products appear in AI shopping answers, what is wrong, and who can fix it?

Commerce teams need SKU-level answer visibility across inclusion, retailer citations, attributes, reviews, and launch timing.

Map this surface
Capture SKU prompt

category, retailer, comparison, season

Normalize Retailer source

URL, freshness, detail quality

Route Fix queue

PDP, catalog, review, PR

Prove Shelf movement

inclusion, attribute, citation

Operating LoopSKU
01 Track prompts

Monitor category, product, comparison, gift, problem-solution, and seasonal shopping prompts.

02 Audit shelf

Record SKU inclusion, competitor displacement, attributes, retailer sources, and review language.

03 Assign fixes

Route PDP, catalog, retailer, review, and PR actions to the correct owner.

04 Watch peaks

Review answer movement around launches, promotions, and seasonal demand spikes.

Tracked ObjectsShopping Shelf
SKU row

included, absent, displaced, miscategorized

monitored
Attribute claim

spec, price, availability, positioning

checked
Retailer source

URL, freshness, detail quality, conversion path

scored
Review signal

positive, negative, recurring language

mined
ControlsOperator safe
Truth source

Compare AI answer claims against approved product and retailer data.

Seasonal watch

Increase review cadence for launch, promotion, and Black Friday windows.

Owner routing

Separate catalog fixes, retailer corrections, PDP work, and earned-source requirements.

Readoutsproduct inclusion, attributes, and retailer citations
AI shopping shelf

SKU presence, competitor position, and answer quality

Attribute queue

wrong, stale, missing, or unsupported claims

Retailer plan

sources most likely to influence future recommendations

Signal Console

A command center for zero-click marketing.

The product surface is built around the work: prompts become clusters, clusters become actions, actions become measured answer movement.

  • Prompt clusters scored by demand, visibility, sentiment, and conversion intent.
  • Citation source maps that separate trusted mentions from narrative drift.
  • Agent workflows that create briefs and campaigns with approval gates.
Haynechi Command Sample category: fintech SaaS
Visibility72.8+8.4
Share18.6%+2.1
Citations4,892+18%
Risk11-4

Recommended actions

Refresh the comparison page cited by Claude and Perplexity.

Publish a source-backed glossary for the highest intent prompt family.

Engine coverage

Start with the map

Start with one market map.

Request the pilot