Product Recommendation Emails: How to Set Them Up

Product recommendation emails show shoppers products they may want based on their behavior, purchase history, product interest, or a rule you set. To set them up, you need four things: a synced product catalog, customer behavior data, a recommendation rule, and an email placement where the recommendation makes sense.

The goal isn’t to show random products. It’s to make the next step easier for the shopper.

This guide walks through how to set them up in a practical way for an ecommerce store.

What Are Product Recommendation Emails?

Product recommendation emails are marketing emails that include suggested products for each shopper or customer segment.

Recommendation type	How it works	Best use case
Personalized	Uses behavior like viewed products, cart activity, or purchase history	Browse abandonment, post-purchase, repeat purchase
Rule-based	Uses rules like best sellers, collection, inventory, margin, or price	Welcome emails, campaigns, seasonal promotions
Manual	You choose the products yourself	Product launches, curated edits, small catalogs

Most brands should use a mix. Personalized recommendations are useful when you have enough customer data. Rule-based recommendations are better when the shopper is new or when you want more control.

The test is not whether the block looks personalized. It is whether the products match the customer’s context and help with the next decision.

Where Product Recommendations Fit in Ecommerce Email

Product recommendation emails can be used in both automated flows and campaigns.

Automated emails are often the best first placement because they respond to a known event. The recommendation can reflect what the shopper browsed, left in a cart, or bought instead of relying on a broad campaign theme.

Email placement	Recommendation angle
Welcome series	Best sellers, starter products, category favorites
Browse abandonment	Recently viewed products and related products
Abandoned cart	Cart items, matching products, lower-friction alternatives
Post-purchase	Cross-sells, accessories, refills, next-step products
Replenishment	Products due for refill or reorder
Win-back	New arrivals, popular products, customer favorites
Campaigns	Personalized “you may also like” blocks beneath the main offer

There is no need to rebuild every email at once. Prioritize flows that already have clear buying intent.

Step 1: Sync Your Product Catalog

Your product catalog is the base of every product recommendation email. If the catalog is incomplete, the recommendations will be weak.

At minimum, your email platform should have product name, image, URL, price, category, inventory status, product ID, and variant data.

Depending on the store integration, platforms such as Klaviyo, Omnisend, Mailchimp, Shopify Email, and ActiveCampaign can use catalog data or a custom feed. Klaviyo’s product feed documentation says its recommendations combine catalog and customer behavior data. Klaviyo excludes catalog items without an image, out-of-stock items, products the customer already purchased, and the product tied to the flow-triggering event.

Before building emails, check your catalog quality. Look for broken images, old products, missing prices, duplicate variants, and products that shouldn’t be marketed.

Step 2: Confirm Your Behavior Tracking

Product recommendations get stronger when your email platform can use customer behavior.

The most useful events include viewed product, added to cart, started checkout, placed order, ordered product, viewed category, and email clicks.

Every possible event can wait. Browse-abandonment recommendations do need viewed-product data; cart use cases need add-to-cart or checkout data; and post-purchase recommendations need purchase history.

After tracking is installed, test it with a real browser session. View a product, add it to cart, start checkout, and check whether those events appear on the customer profile.

Don’t skip this. A recommendation block can look fine in the email editor while pulling weak or empty data in real sends.

Step 3: Choose the Recommendation Logic

The recommendation logic is the rule that decides which products appear in the email. The right logic depends on what the customer just did.

If the shopper is new

Use best sellers, top-rated products, or products from the category they signed up for. New subscribers often don’t have enough history for deep personalization.

If the shopper viewed a product

Show the viewed product first, then related products from the same category. This helps the shopper compare options without leaving the email.

If the shopper abandoned a cart

Show the cart item clearly. Then, if it makes sense, include add-ons or alternatives below it. The main CTA should still bring the shopper back to checkout.

If the customer already purchased

Use product pairings, refills, accessories, upgrades, or next-step items.

If the customer has gone quiet

Use new arrivals, best sellers, or products related to the last purchase. Recommendations can help, but they should sit beside a strong message, not replace it.

Step 4: Build Product Feeds or Product Blocks

Most email platforms use feeds, product blocks, or dynamic content areas to place recommendations inside an email. A product feed is a saved set of rules, such as best sellers under $75, products from the same collection, recently viewed items, or in-stock products only. The available rules and default exclusions vary by platform, so check the preview rather than assuming every tool behaves like Klaviyo.

Once the feed is created, add it to an email with a product block. Keep the design simple. A two-product or three-product row is usually enough. Each product should include a clear image, product name, price, short CTA, and product page link.

For mobile, test the block carefully. Rows that look clean on desktop can feel long on a phone.

Step 5: Write Copy That Frames the Recommendation

The product block needs a short line of copy that explains why the products are there. It doesn’t need to be clever. It needs to make the recommendation feel relevant.

Good examples:

• “Picked based on what you viewed”
• “Pairs well with your order”
• “Popular with first-time customers”
• “More from the collection you browsed”
• “You may also like these”

Avoid lines that feel too intense or too personal. A transparent phrase such as “Based on what you viewed” explains the connection; overly specific wording can make an otherwise useful recommendation feel intrusive.

Step 6: Add Guardrails and Fallbacks

Recommendation emails need rules that protect the customer experience.

Key guardrails include excluding out-of-stock products, setting category and inventory rules, limiting discount stacking, and controlling how often a recommendation appears. Exclude previously purchased products when repeat purchase would be irrelevant, but keep them eligible when replenishment or reordering is the point.

Fallbacks are especially important. If the platform doesn’t have enough data, show best sellers, category favorites, or a curated set instead of leaving a blank section.

Step 7: QA Before You Send

Before you launch product recommendation emails, test them like a customer would see them. Preview the email with several customer profiles, check desktop and mobile views, click every product link, confirm images load, and make sure prices match the store.

If the recommendation block pulls attention away from the primary CTA, move it lower or reduce the number of products.

Step 8: Measure Performance

Measure product recommendation emails by the action you want the email to drive. Track click rate, product block click rate, placed order rate, revenue per recipient, average order value, unsubscribe rate, spam complaint rate, and repeat purchase rate.

When traffic permits, run a controlled test with the recommendation module against the same email without it. That is a cleaner way to estimate incremental conversion, order value, and margin than crediting every attributed order to the product block.

Don’t only look at revenue. A recommendation block can increase clicks while reducing checkout completion if it distracts shoppers from the main action. If that happens, move the block lower or show fewer products.

A Simple Setup Plan

If you’re starting from scratch, use this order:

1. Sync and clean your product catalog.
2. Confirm viewed product, cart, checkout, and purchase tracking.
3. Add best sellers to your welcome series.
4. Add viewed products to browse abandonment.
5. Add cart items and careful add-ons to abandoned cart emails.
6. Add cross-sells or replenishment products to post-purchase emails.
7. Review performance every month and adjust the rules.

This approach keeps the work manageable and starts with the emails where intent is strongest.

Conclusion

For a first product recommendation email, audit the catalog, confirm one behavior event, and add one feed to the flow where its intent is clearest. Preview it with new, active, and data-poor customer profiles so you can see both the recommendation and fallback paths. Then compare its product-block clicks, orders, revenue per recipient, and margin with a no-module control before expanding the system.