Mechanism

How Burnish works.

An always-on instrument with four jobs. This page is the whole mechanism.

Dashboard

How AI assistants answer for Threshold Footwear

Measured against your real buyer questions, every day, across the assistants your customers actually ask. Reflecting the last 7 days · updated 19d ago.

68/100
AI Commerce Index
▲ 4 · 7d
Seen · mention rate41%29 of 71 answers · ▲ 5 pts
Did · this week3123 fixes · 8 articles
Earned · AI revenue$486.004 orders
Products indexed12050 buyer questions tracked
ManifestoActivePowering every product, article, and visibility check in your brand's voice.View manifesto ↗
Engine performance
Today's sampling · 34 of 50 questions
ChatGPT · visibility score▲ 5 this weekComposite weight 0.6
Discovery58

how often ChatGPT surfaces your store in category answers

Reputation79

what ChatGPT answers when buyers ask about you directly

This week's read

Strong on brand questions · weakest on “best waterproof sneakers” category asks

72 answers · 21d · gpt-5.2View ChatGPT answers
Index trend
Last 7 days
Last 30 days
Last 90 days
Mention rate — % of AI answers that name your store
ArticlesView all →
18Gaps found12Published7Measuring3Won
Up next✦ How to break in canvas sneakers · Wed, Jul 8
Latest winCited by Perplexity
Smart postingOff · drafts wait in the pool
AI Readiness
81/100▲ 3 · 7d
12 fixes awaiting your approval
AutopilotOn · 23 fixes shipped this week, review-first
Activity
1 need youView all →
ActionCatalog · Rewrote 6 product descriptions · waffle-sole collectionExecuted2h ago
MonitorVisibility · Perplexity began citing /guides/sizing in 3 answersDetected6h ago
ActionCatalog · 12 bold rewrites awaiting approvalNeeds you1d ago
ActionArticles · Article published: “How to break in canvas sneakers”Executed1d ago
FoundationsThe machine-readable groundwork every other system runs on.Manage →
Brand Manifesto
Active

Six systems read from it. Rewritten as your store changes.

Review →
Structured data
Product & Article schema — specs, author & date
FAQ schema — answers can surface as direct AI answers
Breadcrumbs — Home → Blog → Article
AI crawler access
Open to all 8 AI crawlers — Checking your robots.txt…
Internal links AI can follow — Not measured
Burnish Web Pixel
Connected

Ties AI traffic to the orders it earned.

SetupEverything is running.4 of 4 done
Burnish app embedOn

Burnish is publishing structured data and open crawler access on your storefront.

Specialist session

Sit down with an AEO specialist

Half an hour on your store’s answers: which buyer questions you are losing, which competitor is taking them, and the order worth fixing them in.

30 minutes · we read your manifesto and engine scores before you join.

Book a session ↗

Questions about a number?How Burnish measures

Two judges read every answer.

The twelve-question battery fires in a continuous round-robin; these grade what comes back.

Recognition judge

A closed question · you or not you

The question it asks
Is this answer about you, a namesake, or a guess?
What it reads
The engine’s answer alone.
What it refuses
Wrong-store answers never score as yours.
Scores only Your store

Accuracy judge

An open grading · claim against page

The question it asks
Is what the engine claimed actually true?
What it reads
Your live policy pages, fetched fresh, beside the claim.
What it refuses
A claim is graded against your own pages, not taken at its word.
Grades against Your live pages

The brand brain.

Before Burnish says a word about your brand, it builds the manifesto.

[01]

A fact spine, with sources attached

Extracted from your store, invention forbidden. Nothing enters that cannot be pointed at.

[02]

A narrative pass you approve

You approve and can regenerate it. Every engine-facing word traces back — discovery queries, battery tokens, articles, rewrites, schema.

Four jobs, on a loop.

Each one hands its output to the next, and the last one starts it again.

  1. Measure

    What five assistants say about your store, sampled continuously rather than once.

  2. Diagnose

    Every gap comes with a why — which field, which product, which question.

  3. Fix, with your approval

    Twenty-nine of the forty-one fix types wait for you. The rest sit behind floors.

  4. Prove

    What the work earned, measured on the same instrument and labelled with its limits.

Representative demo · Threshold Footwear

Burnish design sandbox

Living Loop · Concept A

Open log
01Research
Catalog mapped47 prompts tracked
02Monitor
Sampling now4 engines · 1 min agoView log →
03Action
ResolvedLast autopilot run · 9:43 PM · 4 fixes appliedQueue →
04Measure
Tracking lift+$1,240 · 9 fixesSee lift →
Representative demo · Threshold Footwear
The loop, running — 03 Action · Threshold Footwear fixture

Earned autonomy.

Never assumed. Each level is unlocked by a record, not by a plan.

L1 · Review everything

Burnish proposes. Nothing is written until you say so.

L2 · 20 approvals

Half the queue starts auto-publishing. The other half still waits.

L3 · 50 approvals

The widest lane, and it still needs explicit consent.

How the proof works.

Four signals, and one sentence about what the result is not.

SignalWhat it is
First-party pixelConsent-gated and zero-PII. Classifies AI-referred sessions and ties them to orders inside a 60-day window.
Shopify order journeysCorroborate the pixel. First and last visit source only — no customer data.
GA4Optional cross-validation. Never a requirement.
Per-action liftShips with bootstrap 95% confidence intervals.
What it is notDirectional, not a controlled trial. The product labels it that way wherever it appears.

Four guardrails, always on.

They do not switch off at the higher autonomy levels.

Start with the reading.

The free audit runs the instrument against your store and shows you what came back, engine by engine.