Markin + Shopify integration
Orders, catalogue and margin as decision inputs.
What is a Shopify AI agent?
A Markin and Shopify setup reads orders, customers and catalogue data to decide the next offer for each shopper, then activates it through email, ads or an on-site surface. Nothing about the storefront build changes.
Optimising for conversion alone reliably grows unprofitable orders. With margin in the input, Markin can decline a discount that would have converted and still lost money.
What Markin reads
- Order and refund history
- Catalogue, price and margin
- Cart and checkout events
What Markin writes back
- Decision events for downstream lifecycle tools
How the connection works
| Pattern | What it means here |
|---|---|
| Read only | Markin reads signal from this system. Nothing is written back and no schema is changed. |
| Triggered event | Markin emits an event that starts or advances a journey. Near-immediate, and the channel keeps its own governance. |
What can you ask Markin to do in Shopify?
- How do I increase repeat purchase rate on Shopify?
- How do I recommend the next product without cannibalising margin?
- How do I win back one-time Shopify buyers?
- How do I test offers on Shopify against a holdout?
What Markin does in Shopify
- 01Read orders, line items, discounts and refunds.
- 02Read customer records, tags and lifetime value.
- 03Read catalogue and inventory constraints.
- 04Model repeat purchase timing per customer.
- 05Choose the next offer with margin and cannibalisation accounted for.
- 06Activate through Klaviyo, ads or an on-site surface.
- 07Keep a randomised holdout out of every offer.
- 08Report incremental margin, not just incremental revenue.
Scope of work
The growth work behind Shopify
The list above is what Markin touches in Shopify. A connector is only the surface. Below is the work itself: what an analyst, a lifecycle manager, a data scientist and an experimentation lead would do between them, running continuously against your own data.
Read the estate
Normally a data engineer, once, then never refreshed.
- Flag data quality breaks that would make a decision unsafe.
- Map every customer, account, subscription and plan in the systems you already run.
Find where revenue is leaking
Normally a quarterly analyst deep dive.
- Spot channels and campaigns spending into audiences that would have converted anyway.
- Size every finding in revenue, not in percentage points.
Explain why
Normally a two-week investigation pulled off the roadmap.
- Separate mix effects from real behaviour change.
- Rank drivers by how much of the movement each one accounts for.
Write hypotheses worth funding
Normally a workshop, limited to the ideas in the room.
- Attach the evidence and the assumption each one depends on.
- Rank the portfolio by expected value, not by seniority.
Decide per customer
Normally segment rules refreshed when someone has time.
- Respect eligibility, consent, locale and channel preference.
- Pick the channel, timing and incentive level, not only the message.
Execute in the tools you already run
Normally a ticket, then a slot in next month's calendar.
- Update audiences, lists and segments without hand-built rules.
- Route offers, retention plays and save flows to the right surface.
Prove it caused the revenue
Normally argued about, rarely measured.
- Report retention, ARPU, margin and contact pressure side by side.
- Detect and discount cannibalisation between competing actions.
Retire, govern and hand over
Normally nobody's job, so nothing is ever switched off.
- Retire programmes automatically when they stop beating control.
- Re-test assumptions that decay, such as price sensitivity and seasonality.
Shopify questions
- How does Markin connect to Shopify?
- Read only, Triggered event. Markin reads signal from this system. Nothing is written back and no schema is changed.
- What does Markin read from Shopify?
- Order and refund history; Catalogue, price and margin; Cart and checkout events.
- What does Markin write back into Shopify?
- Decision events for downstream lifecycle tools
- Do we have to move our data to Markin?
- No. Markin reads from your warehouse, product events and operational systems in place, on your compute, under the access rules your data team already set. Nothing is copied into a separate customer base and there is no vendor-side profile store to migrate off later.
- Does Markin replace our engagement platform or CDP?
- No, and it should not. Your engagement platform keeps the channel, the templates, the deliverability and the governance. Your CDP keeps identity and consent. Markin adds the layer neither has: deciding which action deserves to exist for each customer, and proving it against a holdout.
- What if the system we use is not listed?
- The four activation patterns cover almost everything: attribute write-back, triggered event, decision API and direct surface rendering. Any system that exposes an API, accepts a table, or can read a warehouse column can receive decisions. New connectors are built during deployment, typically in days.