Shopify is building agentic checkout. ChatGPT and Perplexity now recommend products. Your catalog decides whether you show up. Founder-led. Fixed scope. Two weeks.
When a buyer lands on your store, they scan images and headlines. When an AI agent reads your store, it parses structured data: product titles, metafields, schema markup, and feed attributes. The agent builds a machine-readable picture of what you sell, who it is for, and whether it matches a query. Visuals do not factor in.
Most Shopify stores were built for human browsers. Missing schema. Weak metafields. Titles written for eyes, not parsers. When Shopify Sidekick, ChatGPT Shopping, or Perplexity queries your catalog, they surface what they can read. Stores with poor data structure get skipped or misrepresented regardless of product quality.
This is a catalog problem. The fix is structural. Rebuild the schema, metafields, and taxonomy, and agents can read and recommend your products accurately. Two weeks is enough time to do it right. The ACR Score tells you exactly where to start.
Each dimension maps directly to the signals AI shopping agents use to parse, match, and recommend products. Most stores score under 40 out of 100. The kit shows you exactly which checkpoints to fix.
JSON-LD product schema, schema type accuracy, GTIN and MPN fields, brand markup, pricing and availability data. Agents parse schema before any visible content. Most stores score under 8 on this dimension alone.
Title format and length, description structure, specification completeness, material and size data, benefit statements. Agents match products to buyer queries through text precision. Vague descriptions fail the match and the recommendation.
Collection logic, metafield completeness, Shopify taxonomy alignment, variant naming consistency, product type accuracy. Agents need logical product relationships to surface the right item for a specific query.
Google Merchant Feed accuracy, alt text completeness, handle format, canonical URL structure, sitemap coverage, image spec compliance. Feeds are how ChatGPT Shopping and Perplexity ingest your catalog at scale.
Subscription app presence, pricing tier clarity, offer structure, retention flow completeness. Agentic checkout surfaces subscription options as first-class purchase paths. Stores without clear subscription signals miss the placement.
Self-guided. 20 checkpoints. Fix guides included.
Fixed scope. Fixed price. Work starts within 24 hours of kickoff.
Product titles, descriptions, metafields, and taxonomy rebuilt for machine readability. Every SKU structured so agents can parse, match, and recommend accurately. Covers up to 100 products.
Schema markup, structured data, feed quality, and machine-readability across the full catalog. The structural foundation that determines whether agents surface your products at all.
Product pages rewritten to convert buyers and satisfy agents simultaneously. Benefit-driven, spec-complete, structured for both audiences without compromise. Up to 50 PDPs.
Subscription offer architecture, pricing tier structure, and retention flows built from scratch. Agentic checkout weights stores with clear subscription paths. This sprint gets you there.
Collections, taxonomy, automations, and internal SOPs built as a complete operating layer. The full infrastructure that makes your store run cleanly and scale without manual overhead. Best for stores that need catalog, ops, and systems work done together.
Structora is run by Stanley Mburu. There are no account managers, no junior staff, no hand-off between the person who sold you the sprint and the person who runs it. When you message Structora, you get the person doing the work.
The sprint model keeps scope tight. Two weeks, a fixed deliverable list, and a clean handover. Structora takes on a small number of sprints at a time. That concentration is deliberate: your store gets full attention, not divided time across ten clients.
Every sprint has a fixed price agreed before work starts. No hourly billing, no scope creep, no invoice surprises. The work ends with a walkthrough, a handover document, and everything owned by you. There is no lock-in, ever.
Agent surfaces change. Shopify updates its taxonomy. New schema requirements appear. The ACR Monitor keeps your catalog optimized after the sprint ends.
Monthly re-score, quarterly catalog audit, Slack access.
Everything in ACR Monitor, plus monthly implementation hours.
Download the $47 ACR Audit Kit and score your store across all five dimensions. 20 checkpoints. Fix guides included. Takes under an hour.
Bring your score to a 30-minute call. We look at the gaps together and agree on which sprint closes them fastest.
Fixed scope, fixed price, work starts within 24 hours of kickoff. Two weeks later, the catalog is rebuilt and your ACR score moves.
We reply within 1 business day.
Common questions
Straight answers. No pitch.
/api/mcp that AI agents use to read your catalog. You control your visibility by controlling your product data — titles, descriptions, metafields, taxonomy categories, and image alt text. No app installs, no code changes required for the basics.