How to Increase Repeat Purchases with Personalized Product Recommendations

August 29, 2025

A Strategic Framework for Segmenting and Re-Engaging Customers Through Smart Suggestions

Too many brands treat personalization like a buzzword. They show “Best Sellers” to everyone. They automate product blocks with no logic. And then they wonder why their repeat purchase rate is flat.

But when personalization is intentional—when recommendations are based on real purchase behavior, lifecycle stage, or product affinities—it becomes one of the most powerful tools in your retention strategy.

That’s why we created the Personalized Recommendations Framework—a one-page planning system designed to help Shopify and DTC brands deliver smarter product suggestions that actually convert.

Download the Personalized Recommendations Framework

What Is the Personalized Recommendations Framework?

This framework is a simple but powerful worksheet built by the team at Sticky Digital. It gives ecommerce teams a clear structure for:

Segmenting customers based on past purchase or browsing behavior
Planning product or content recommendations for each segment
Mapping personalized messages across email, SMS, and site experiences

It’s designed to plug directly into your Klaviyo, Attentive, or Yotpo flows, and help your team increase repeat purchases without relying on discounting or guesswork.

Why Personalized Recommendations Matter

Personalization isn’t optional anymore. According to McKinsey, 71% of consumers expect personalized interactions—and 76% get frustrated when they don’t receive them.

Done right, product recommendations can:

Increase repeat purchase rate by 20–40%
Lift email and SMS conversion rates
Reduce time-to-second-purchase
Improve customer satisfaction and brand affinity

But the key is segmentation. Showing random products doesn’t work. Showing the right products to the right people at the right time—that’s what drives retention.

How to Use the Personalized Recommendations Framework

1. Segment Your Customers

The framework includes templates for grouping customers based on:

Last product purchased
Product category affinity
Cart size or AOV
Subscription status or loyalty tier
Browse abandonment data

Using Klaviyo, Attentive, or your ESP, you can dynamically tag these segments and serve different flows or product blocks based on behavior. For example:

Customers who bought your hero product → Recommend complementary accessories
Customers who browsed skincare but didn’t buy → Recommend entry-level or travel-size SKUs
Repeat buyers who only purchase bundles → Recommend subscriptions or limited edition kits

2. Plan Your Recommendations

The worksheet provides space to map 1–3 recommended products or content assets per segment. This planning phase allows your team to align on:

Which SKUs are most relevant
Which SKUs have the highest margin
Which product education or use-case content supports the next purchase

For example, a customer who just purchased a probiotic may not be ready for a refill—but might benefit from a blog post on gut health and a suggested complementary product.

3. Apply It Across Channels

Once segments and recommendations are mapped, implement them across:

Email: Add personalized product blocks to post-purchase, winback, and loyalty flows
SMS: Send targeted follow-up with direct-to-product links and urgency framing
Site: Use Rebuy, Digioh, or Shopify logic to serve dynamic PDP or cart recommendations

The result? A consistent, strategic experience that feels personalized at every touchpoint—not random.

Examples of Smart Personalized Recommendations

A supplement brand uses the framework to recommend complementary SKUs in their post-purchase flow based on the type of health goal (e.g., energy vs. immunity)
A beauty brand segments based on skincare routine step—then recommends what's missing from the routine (e.g., cleanser → moisturizer → SPF)
A food brand triggers a “refill or try something new” SMS based on last purchase date + AOV

These aren’t guesswork—they’re mapped in advance and grounded in behavioral logic.

Benefits of the Personalized Recommendations Framework

Brands that use this worksheet typically see:

Higher click-through and conversion rates in flows
Faster movement from first to second order
Increased LTV from curated bundles and product education
Lower opt-out rates from better-targeted content

Personalization, when rooted in segmentation and mapped intentionally, becomes a powerful lever for retention—not just another automation.

Download the Framework and Start Personalizing Smarter

Generic product suggestions are a thing of the past. With the Personalized Recommendations Framework, you can structure your personalization strategy around what your customers actually want—based on their own behavior and preferences.