How to Win Back Lapsed Shopify Customers With Personalized Product Recommendations

Your store has customers who used to buy regularly and then stopped. They already know your products, your shipping and your quality. Bringing even a few of them back is often easier than finding new buyers, but only if you give them a reason that's about them.

A generic "We miss you, here's 10% off" email doesn't do that. This guide covers how to find lapsed customers in Shopify, decide who to contact first, and build a win-back offer from what each customer already bought.

What "Lapsed" Means for Your Store

There's no universal cut-off. A customer who buys coffee every five weeks is lapsed after three months. A customer who bought a sofa may not need anything for a year.

Start from your own order history:

• For repeat buyers, compare the time since their last order with the gap they usually leave between orders. A customer who ordered every 6 weeks and hasn't ordered in 5 months has clearly changed pattern. Our guide to purchase timing explains how to read those gaps.
• For one-time buyers, use your store's typical buying cycle for the product they bought.

Write your definition down, so everyone on the team means the same thing by "lapsed".

How to Find Lapsed Customers in Shopify

Shopify gives you two useful tools for this, both in customer segments.

Last order date

The last_order_date filter "Includes customers who placed their last order on the date specified," and it accepts relative dates such as the last week or the last eight months. Combine it with number_of_orders to separate customers who bought several times from customers who bought once. Shopify notes that date values "depend on which time zone your store is in."

RFM groups

Shopify's RFM customer analysis scores customers from 1 to 5 on recency, frequency and monetary value, and "RFM scores are based only on data from your store." Four of its 11 groups describe customers who haven't bought recently:

You can use these groups directly with the rfm_group filter in Shopify's segment editor. Our guide to customer segmentation covers the other filters.

Decide Who to Contact First

A segment tells you who has gone quiet. It doesn't tell you who is worth a personal offer. Start with the customers where you have the most to work with:

1. Previously loyal and At risk customers. They have a strong history, so you have the most purchase data to base a recommendation on.
2. Repeat buyers of replenishable products who are well past their usual reorder time.
3. One-time buyers whose first product has a natural next step.

Leave Dormant customers with a single small order for later or for a general newsletter. A personal basket takes time, so spend it where the history gives you a clear reason. Our guide to identifying high-value customers explains why value and opportunity aren't the same thing.

Five Reasons a Lapsed Customer Might Come Back

A win-back offer works best when it answers "why now?" for that customer. Their purchase history usually suggests one of these:

1. They probably ran out

A customer who bought skincare, coffee or pet food regularly and then stopped may have run out and bought elsewhere. Recommend the refill they used to buy, plus one useful addition.

2. What they bought may need replacing

Running shoes, razor blades, filters and phone cases wear out. If enough time has passed, a replacement of what they had is a natural reason to return.

3. They never bought the natural complement

A customer who bought a camera but never a spare battery or memory card still has a gap. Our guide to complementary products covers how to find those relationships.

4. You have something new in their category

New arrivals in a category they bought from are a reason to look again, as long as they genuinely fit what the customer bought before.

5. The season fits

Holiday gifting, a change of season or an event can make a past purchase relevant again. A customer who bought a gift set last December may be shopping for gifts again now.

Check Before You Send

Before contacting a lapsed customer, check four things:

• Consent. Only customers who agreed to marketing should get a promotional email. Filter with email_subscription_status = 'SUBSCRIBED', and see our guide to email marketing consent before BFCM.
• Why they stopped. A customer whose last order was returned or who contacted support with a complaint needs a different approach. See recommending products after a returned order.
• Gift orders. If their last order went to someone else, it may say little about their own needs. See recommending products after a gift purchase.
• What they already own. Don't recommend the product they already have unless it's a refill or a replacement. Our guide to choosing the right products for each customer covers these filters.

Should You Add a Discount?

A discount can lower the barrier, but it isn't the reason to come back. A relevant product is. If a customer receives 15% off with nothing they need, the discount does very little.

If you do add one:

• Tie it to the offer, not to everything in the store.
• Keep it modest, so you don't teach customers that waiting pays.
• Give it an end date, so it reads as a personal offer rather than a standing discount.
• Be careful around BFCM, when customers already see many storewide discounts.

A Simple Win-Back Workflow

1. Define "lapsed" for each main product type.
2. Build the segment with last_order_date, number_of_orders and, if useful, rfm_group.
3. Filter for consent with email_subscription_status.
4. Prioritize Previously loyal and At risk customers first.
5. Read each customer's history for one clear reason to return.
6. Build a small basket, two or three products, with nothing they already own.
7. Decide on an offer, with or without a discount.
8. Send it once, with a short personal message and a link that goes straight to checkout.
9. Measure who came back.

Where Curivo Fits

Curivo is built for step 6, the part that takes the most time.

For a win-back offer, the workflow is manual from start to finish:

1. Open the customer you chose from your Shopify segment. Curivo shows their purchase history.
2. Build the basket by hand, or choose from four AI-generated options.
3. Review and edit the products, and add a discount if you want one.
4. Set the link options. A checkout link can be single-use or multi-use, and you can give it an optional expiry date and time. For a win-back offer to one customer, a single-use link with an expiry keeps the offer personal and time-limited.
5. Select Generate Link to create the checkout link.
6. Share it yourself, through the channel you choose.

Generating a link doesn't create a Shopify draft order. Creating a draft order is a separate option, and Curivo creates one only when you select it. For how Shopify's own checkout links and draft order invoices compare, see our guide to sending a Shopify checkout link.

A few limits matter for win-back:

• Win-back is manual. Curivo's automated offers on the Starter and Growth plans are a separate feature. They start when an order is created or delivered, so they don't reach customers who haven't ordered in a while, and Curivo doesn't reactivate lapsed customers automatically.
• Plan limits apply. The Free plan includes 10 AI generations and 20 checkout links a month, with unlimited baskets built by hand. Starter and Growth add more AI generations and unlimited checkout links.
• You choose who to contact. Curivo doesn't build segments. Use Shopify segments to decide who is lapsed, then build their basket in Curivo.

Curivo is available on the Shopify App Store.

How to Measure a Win-Back Effort

Keep it simple:

• Reactivation rate: lapsed customers who placed an order within a set window, such as 30 days, divided by the lapsed customers you contacted.
• Revenue from reactivated customers in that window.
• What they bought: the recommended products or something else.

Compare against a similar group you didn't contact, if you can, since some customers return on their own. Our guide to measuring recommendation revenue covers attribution in more detail.

Common Mistakes

• Sending the same discount to every lapsed customer, with no reason that's about them.
• Contacting customers who didn't agree to marketing.
• Recommending what they already own.
• Ignoring why they left, such as a return or a complaint.
• Following up too often after a customer doesn't respond.

The Bottom Line

Lapsed customers aren't lost causes. They're customers whose history tells you what they might need next. Find them with Shopify segments, start with the ones who bought most, and send each one a short, relevant reason to come back.