Ecommerce growth · conversion path
Stop discounting first. Send the product path that already converts.
A shopper emails, searches the site, views page A, checks delivery, and needs a recommendation that is better than a generic discount.
A high-intent shopper is one email away from buying — or going cold forever. The team’s default is a generic 10% code. Comparable journeys say that wastes margin and misses the real move.
Purchase path
Primary outcome
Ranked converted_purchase first from comparable sets
High
Confidence
Evidence-supported match band from runtime scoring
Minutes
Decision speed
Ops gets one brief instead of a six-tool war room
Protected
Margin posture
Discount is demoted until the specific path fails
The situation
What the team was living with
A shopper emails about a waterproof trail jacket, searches the site, lands on the hero product page, checks delivery and returns, then pauses.
CRM shows a new enquiry. Web analytics shows commercial intent. Merchandising sees stock. Nobody has one ordered trail that says what worked last time.
Growth wants conversion this week. Finance does not want another blanket discount. Support does not want a sizing ticket after a rushed push to checkout.
Revenue pressure
Basket recovery windows close in hours, not days.
Margin risk
Default discounts train customers to wait for codes.
Fragmented signals
Email, search, page view, and delivery intent live in different tools.
The trail
Signals that formed the path
Not a dashboard dump — the ordered evidence that made the next task defendable.
Data examples
- Email enquiry with product-fit intent
- Website search for waterproof trail jacket
- Page A product view and delivery/returns page view
- Synthetic prior purchase, page C, support, and account-registration outcomes
Event path
- 01email_received
- 02website_search
- 03page_view: page-a
- 04page_view: delivery-returns
- 05purchase_completed in comparable paths
The recommendation
The money move
Primary action · High · score 0.6499
Send a specific product email with stock reassurance and direct checkout link.
Expected outcome: converted_purchase
High-confidence match to previous converted journeys. The action is narrow, evidence-backed, and reviewable: send the product email with stock proof and a clean path to buy — not a campaign spray.
Relationship analysis ranked a specific product follow-up — stock reassurance plus direct checkout — above discount, page-C diversion, or premature account push. Comparable converted paths shared the same email → search → product page pattern.
Alternative 1 · Medium
Send a comparison link to page C because similar visitors bought after reading compatibility guidance.
If outcome tilts toward: returned_to_page_c
Alternative 2 · Medium
Reply with support resolution first, then send the product link; pushing checkout first reduced conversion in comparable paths.
If outcome tilts toward: retained_after_support
Alternative 3 · Low
Ask them to create an account so saved preferences and restock alerts can be used before discounting.
If outcome tilts toward: account_registered
Want this shape on your workflow?
Before
Generic discount blast. Hope. Margin leakage. No memory of which path actually converted.
After
One specific email, stock reassurance, direct checkout. Path evidence attached. Outcome recorded for the next match.
The operator moment
The growth lead opens one brief: what to send, why similar paths converted, what to try if this one stalls, and what outcome to record so the next shopper is smarter.
Leadership brief
What the room hears
Plain-language explanation generated from the checked packet — for operators and sponsors who need the why, not a raw dump.
Recommended action: Send a specific product email with stock reassurance and direct checkout link.
Why this is supported: Fortress ranked converted_purchase first with score 0.6499 and high confidence. Comparable relationship sets ended in converted_purchase and share signals such as email_enquiry, page_a, commercial_intent_page, purchase, website_search. The supporting relationship sets are set-87feb2cff218, set-f71fc9ea58fe, set-fa8baf718b14, set-68a546a52b3e, set-97e49a56bf80.
What to do now: brief the growth lead with the runtime query, the shared signals (email_enquiry, page_a, commercial_intent_page, purchase, website_search), and the exact action. Keep the action specific to this scenario rather than turning it into a generic campaign or workflow rule.
When to choose an alternative: switch if the live evidence is closer to returned_to_page_c (Send a comparison link to page C because similar visitors bought after reading compatibility guidance.); retained_after_support (Reply with support resolution first, then send the product link; pushing checkout first reduced conversion in comparable paths.); account_registered (Ask them to create an account so saved preferences and restock alerts can be used before discounting.).
Outcome to capture: record the action taken, the reviewed outcome, and any contradictory signal so the next Scout/Fortress comparison has stronger evidence.
Recommended action: Send a specific product email with stock reassurance and direct checkout link.
Evidence: Comparable relationship sets ended in converted_purchase and share signals such as email_enquiry, page_a, commercial_intent_page, purchase, website_search.
Primary action: Send a specific product email with stock reassurance and direct checkout link.
Primary expected outcome: converted_purchase
Alternatives: returned_to_page_c: Send a comparison link to page C because similar visitors bought after reading compatibility guidance. | retained_after_support: Reply with support resolution first, then send the product link; pushing checkout first reduced conversion in comparable paths. | account_registered: Ask them to create an account so saved preferences and restock alerts can be used before discounting.
Capture the reviewed outcome and feed it back into the relationship-set evidence.
Runtime evidence
Technical trail for diligence
Query, Scout path memory, Fortress ranking, and outcome loop from the synthetic run.
Run 2026-06-17-base-run · ecommerce-d2c/query-results/email-search-page-a.json
Runtime query
A person emails in, searches the website, views page A for waterproof jackets, then looks at the product fit and delivery page. What should we do to get them to buy?
Scout outputs
- Runtime generated Scout-shaped data items for the domain.
- Runtime generated Scout relationships and ordered attribution paths.
- Domain manifest cross-checks the journey, event, and relationship-set counts.
Fortress outputs
- Runtime generated comparable relationship sets.
- Runtime returned ranked action options with scores, confidence labels, outcomes, and supporting relationship-set IDs.
- Runtime preserved synthetic-only and customer-data false caveats.
Outcome loop
- → Capture which ranked action was taken.
- → Record whether the expected outcome happened.
- → Feed the reviewed outcome back into the next relationship-set comparison.
Want this shape on your workflow?
Synthetic proof first. Scoped pilot next. Start with the library, proof boundaries, or a short technical discussion.