How to Use
- Click a score (1-5) for each dimension based on your current capabilities
- Your total score updates automatically as you go
- Once complete, share your results or download your scorecard
- Use the action checklist below to plan your next 30 days
Scoring Guide
| Score | What It Means |
|---|---|
| 1 | Ad-hoc / missing / inconsistent |
| 2 | Basic coverage, manual processes |
| 3 | Operational, repeatable, measured |
| 4 | Strong coverage + automation + governance |
| 5 | Agent-optimized, continuously improved |
The Five Dimensions
1 Data Completeness
- Do we have comprehensive, structured data for every product (specs, compatibility, use cases)?
- Is our product data consistent across channels and platforms?
- When was the data last audited for accuracy?
Your Score
2 Technical Accessibility
- Do we expose APIs for real-time inventory and pricing?
- Can external systems query product availability and fulfillment options?
- Is checkout accessible to agent-initiated transactions and emerging auth standards?
Your Score
3 Reputation Signals
- Do we have sufficient review volume and recency (not just average rating)?
- Are we present in expert sources and comparison resources agents consult?
- Do merchant-level signals (returns, service, shipping reliability) support trust?
Your Score
4 Product Differentiation
- Can we describe who our product is best for, and why, in data-friendly terms?
- Do we have clear, testable advantages for specific use cases/segments?
- Can an agent match our product to a need without extra context?
Your Score
5 Organizational Readiness
- Is there executive ownership of agent optimization?
- Do we have capabilities for data engineering, APIs, and structured content?
- Are metrics, incentives, and budget aligned to agent commerce success?
Your Score
Your Results
| Band | What To Do Next |
|---|---|
| 5-10 | Early — fundamentals missing. Focus on structured product data and reviews first. |
| 11-17 | Developing — you can win specific categories by tightening data + APIs + differentiation. |
| 18-22 | Prepared — shift attention to distribution, real-time capabilities, and AEO measurement. |
| 23-25 | Leading — build continuous improvement loops and defend share of model. |
The Data Stack (What Most Teams Should Build First)
For agent commerce, data infrastructure is usually the biggest gap. Use this 3-layer stack as your build order:
- Layer 1 — Product Information: structured attributes, specs, use cases, media metadata, and relationships
- Layer 2 — Distribution: ensure data appears consistently across databases and platforms agents query
- Layer 3 — Real-time Capabilities: APIs for live inventory, pricing, and fulfillment options
Pick Your Top 3 Actions (Next 30 Days)
- Run a product data completeness audit on your top 20 SKUs and fix the top 10 missing fields
- Ship schema markup and a product feed that includes specs, compatibility, and use cases
- Expose or document an inventory/pricing endpoint (even if internal first)
- Launch a review volume sprint (post-purchase emails, in-box inserts, CS outreach)
- Write a 'best for' positioning doc per hero product with use-case tags and segment criteria
- Assign an exec owner + a weekly 30-minute cadence for agent readiness
Go Deeper
This scorecard is from Instant Checkout: How AI Agents Are Quietly Replacing the Way We Buy