Retail and ecommerce

Turn purchases into repeat orders.

Use purchases, returns and product details to recommend what each customer should buy next.

See the workflow Try the ecommerce demo

Saved product preview

Recommend what fits what they kept.

Use kept shoes, running preferences and a supplied catalog match to explain one accessory.

Preview as

Starts when

A shoe order is delivered

Email for Nadia

Morrow Running

A runner following a rocky coastal trail

A match for your running kit

Hi Nadia,

For your Ridge trail shoes and rocky coastal trails, consider the Ridge-compatible gaiter. It fits the Ridge shoe attachment points and helps keep loose grit out.

Explore your matching gear

See current sizes, availability and product details in the store.

More campaign examples

Follow their routine, not a fixed calendar.

Use pack size, the usage customers share and subsequent orders to plan a replenishment reminder.

At the three gels a week you shared, your 12-pack of citrus gels would cover about four weeks. If that routine still fits, you can review a refill before your next long run. Adjust the quantity if your plans have changed.

Make the return part of the relationship.

Match a recorded return reason to an approved replacement, after the refund is complete.

You returned the Pace because it felt too narrow. The Pace Wide is now available in the size you ordered, with the wider fit described in our size guide. Compare the measurements before deciding whether it is the right replacement for you.

A recommendation with a reason.

Owen runs after dark. See what maxinja recommends, then read his saved Adaptyle email.

maxinjaReflective running vest. A reflective vest gives him the high-visibility coverage he's missing for evening safety.

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A runner on a rocky coastal trail — **The reason, in Owen’s email.** Saved Adaptyle copy, in a compact email view.

Recorded customer lookup and separately saved email preview, using Morrow Running demo data.

Check the order before the follow-up.

After a wait, Query updated purchases and returns. Continue only while the offer still fits; let Adaptyle explain the relevant product.

Explore workflows

Example workflowComplete the kit

Otherwise, stop

Query before following up

Read retained purchases, owned gear, running preferences and the accessory match supplied for this customer.

Reuse this context with evaluated attributes

Start with one post-purchase campaign.

Choose a product range. We’ll map customer and order IDs, review recommendation inputs and preview two different shoppers.

Keep purchases, returns and products connected.

Use evaluated attributes to find retained purchases and owned gear. Supply the product matches and details each recommendation needs.

Start with the data you have.

Import customer and product records by CSV; keep orders and availability current through the API. Native Shopify is in development.

See connection options

Keep price and purchase terms fixed.

Adaptyle writes the recommendation. Authored prices, offer terms and store links stay outside its instructions.

Plan your commerce connection

Customer
Order
Return
Product

Customers and marketing preferences
Order items, returns and retained purchases
Product matches, descriptions and availability

Evaluated attribute

Which supplied accessory matches Nadia’s kept shoes and running preference?

Her saved context matches Ridge trail shoes and rocky coastal trails to a Ridge-compatible gaiter. She already owns trail socks.

Start with one campaign, with us.

Meet the founder to map your data, review personal emails and estimate setup and AI costs.

Book a demo

Your first campaign: Complete the kit
Data to connect: Customers, retained purchases, owned gear and supplied accessory matches.
Outcome to evaluate: Accessory purchases and order value in your commerce reports.