Most Shopify stores have one email list and send campaigns to everyone on it. The stores that generate significantly more revenue from email are the ones that segment — identifying distinct customer groups and communicating with each group differently based on what they've done, what they've bought, and how long they've been a customer.
Native Shopify customer segments
Shopify introduced a native segmentation tool in 2022 (admin - Customers - Segments). It allows you to create dynamic customer groups based on:
- Number of orders placed
- Total amount spent
- Last order date
- Products or collections purchased
- Email subscription status
- Customer tags
- Location
These segments update automatically as customers meet or leave the criteria. You can use them for targeted discounts, specific email campaigns sent from Shopify Email, and to identify which customer groups need attention.
The Shopify native segments are a good starting point but have limitations: they can't do behavioural triggers (email opened, website visited), predictive analytics (likely to churn, predicted LTV), or multi-step flow automation. For those, you need Klaviyo.
The segments that drive revenue
Active customers (purchased in last 90 days). Your warm audience. These are customers who recently bought and are most likely to buy again. Campaigns to this segment should emphasise new products, complementary products to what they bought, and loyalty programme benefits. Don't discount for this group - they bought without a discount and likely will again.
One-time buyers (exactly 1 order, 30+ days ago). The largest revenue opportunity for most stores. These customers bought once, presumably liked the product, but haven't returned. A targeted "We miss you" campaign with a specific product recommendation (based on what they bought) and a clear reason to return (new products, a small incentive) converts at a higher rate than general campaigns. This segment typically represents 40-60% of a store's total customer base.
VIP customers (top 10% by lifetime value). Your most valuable customers. Treat them differently: early access to new products, exclusive offers, personal communication from the founder. The cost of a VIP programme is low relative to the LTV this group represents. Losing a VIP customer to a competitor has an outsized revenue impact.
Lapsed customers (no purchase in 6+ months). Customers who were active but have gone quiet. Win-back campaigns with a meaningful incentive ("We've missed you - here's 20% off") recover a portion of lapsed customers before they're fully churned. Those who don't respond to two or three win-back attempts should be suppressed from general marketing to protect sender reputation.
High-frequency purchasers. Customers who buy monthly or more frequently. For consumable product businesses, this segment identifies natural subscription candidates. A targeted campaign offering these customers a subscribe-and-save arrangement reduces future acquisition friction.
Product-based segmentation
Beyond purchase frequency, segment by what customers bought. A customer who purchased your protein powder but not your creatine is a target for a creatine recommendation. A customer who bought the introductory version of a product is a target for the premium version when they're due to replenish.
In Klaviyo, product-based segments are built using the "Ordered Product" filter. In Shopify's native segments, use the "Product purchased" filter. Either way, the principle is the same: the products someone has bought tell you what they care about, and relevant recommendations convert better than generic bestseller recommendations.
RFM segmentation: the framework
RFM (Recency, Frequency, Monetary) is the standard framework for customer segmentation in ecommerce. It scores each customer on three dimensions:
- Recency: How recently did they buy? (higher = more engaged)
- Frequency: How often do they buy? (higher = more loyal)
- Monetary: How much have they spent? (higher = more valuable)
High R, High F, High M = your VIPs. Low R, Low F, Low M = lapsed customers to suppress or win back. The combinations between these extremes are your targeting opportunities.
Klaviyo's predictive analytics generates RFM-equivalent scores automatically. In Shopify's native segments, approximate RFM by combining last order date, order count, and total spend filters.
Suppression: as important as targeting
Sending campaigns to unengaged subscribers hurts your sender reputation and inflates your list artificially. Build a suppression segment: customers who haven't opened or clicked an email in 6+ months. Remove this group from general campaign sends. Run periodic re-engagement campaigns specifically to this segment, and permanently suppress those who don't respond.
A smaller, highly engaged list consistently outperforms a large unengaged one on deliverability, open rates, and conversion rate.
