Match roast, format, and brew method without flattening taste
See how documented origin, roast, tasting notes, and grind options support a useful coffee recommendation while keeping subjective preference visible.
Transparency note: Quiet Current Coffee, Linh, the catalog entries, and the scenario on this page are fictional. They demonstrate ShopDash product logic and do not represent a customer testimonial or measured result.
“I use a V60 and like bright coffee. Which whole-bean option should I try?”
Five coffees list tasting notes but omit recommended brew method or available format, weakening intent-based discovery.
01 · RETRIEVE
Start with evidence the store actually owns.
ShopDash reads the authorized Shopify catalog and assembles the product facts relevant to the question. It does not treat an attractive description as evidence for a missing technical, compatibility, fit, care, or safety attribute.
| Product | Evidence found | Readiness signal |
|---|---|---|
| Kayon Natural | Light roast, whole bean, peach and jasmine notes, filter guidance | Strong documented match |
| Sierra House | Medium roast, whole bean, chocolate and almond notes | Available; different taste direction |
| Nadi Decaf | Decaf process and cocoa notes; brew guidance absent | Needs a brew-method fact |
02 · REASON
Make the reasoning legible.
Connect preference to documented attributes
Brew method, roast, format, process, and tasting notes each answer a different part of the request.
Keep taste subjective
A tasting note is useful evidence, but not a promise that every palate or recipe produces the same result.
Surface discovery gaps
Missing brew guidance becomes a merchandising task that can improve future category exploration.
03 · ANSWER
Be useful without filling gaps with confidence.
“Kayon Natural is the strongest documented match: it is a light roast, available as whole bean, and the catalog recommends it for filter brewing with peach and jasmine tasting notes. Taste is subjective, so those notes describe the roaster's profile rather than a guaranteed experience.”
Grounded example · not shown to a live shopper04 · ACTIVATE CAREFULLY
Start read-only. Expand when the evidence earns it.
Scan, prioritize, test
- Catalog scan
- Preference retrieval
- Variant availability
- Agent Lab testing
- Read-only controls
Activate, learn, act
- Merchant-approved brew facts
- Storefront preference capture
- Recommendation attribution
- Approval workflows
THE SYSTEM BEHIND THE PLAYBOOK