What Are Klaviyo’s Product Recommendations?
Klaviyo is a marketing automation platform used by ecommerce brands to send emails, SMS, and on‑site messages that are personalized for each shopper.
Product Recommendations in Klaviyo dynamically show customers tailored product suggestions based on their behavior and data — like what they browsed, added to cart, or bought before — instead of static, one‑size‑fits‑all product blocks.
This helps ensure every user sees products that are relevant and compelling, boosting engagement and sales.
How Dynamic Product Recommendations Work
Klaviyo generates personalized product suggestions by using:
1. Behavioral Data
- What customers view on your site
- What they add to cart
- What they purchase
Klaviyo analyses this behavior to predict products each person is most likely to engage with.
2. Machine Learning Signals
Klaviyo’s system learns over time — the more data it sees, the more accurate recommendations become.
Recommendation logic can include:
- “People who viewed this also viewed…”
- “Frequently bought together”
- “Recommended for you based on your browsing history”
3. Integration With Your Store
Product recommendation features work with ecommerce platforms like:
- Shopify
- BigCommerce
- Magento
- WooCommerce
Once connected, Klaviyo can access product catalogs and customer events to feed recommendations.
Where You Can Use Klaviyo’s Product Recommendations
1. Email Campaigns
Insert personalized product blocks into:
- Cart abandonment emails
- Browse abandonment emails
- Post‑purchase follow‑ups
- “We miss you” win‑back campaigns
Each recipient sees different products based on their data.
2. SMS Messages
Boost relevance in SMS promotions by including:
- Product links tailored to each user
- Quick recommendations based on recent activity
3. On‑Site (Popups & Blocks)
Klaviyo can also display recommendations directly on your website:
- As part of popups
- Inline on product detail pages
- In recommendation widgets on home or collection pages
This increases onsite engagement by showing what customers are most likely to buy next.
Key Recommendation Types
Klaviyo supports several recommendation strategies:
| Recommendation Type | Purpose |
|---|---|
| Also Viewed | Shows products viewed by other customers after this product |
| Related Products | Items similar to what the customer is browsing |
| Bought Together | Products frequently purchased with the one being viewed |
| Recommended for You | Tailored suggestions based on customer history |
| Best Sellers | Popular products overall |
| New Arrivals | Latest items added to your catalog |
Benefits of Dynamic Personalization
1. Higher Conversion Rates
Customers are more likely to buy when they see products that match their interests.
2. Increased Average Order Value
Including “bought together” suggestions encourages customers to add more items to their cart.
3. Better Engagement
Personalization improves:
- Email open rates
- Click‑through rates
- Repeat purchases
4. Automation & Scale
Once set up, this runs automatically for all customers — no manual product selection required.
How to Set Up in Klaviyo
Step 1: Connect Your Store
- Integrate Klaviyo with your ecommerce platform
- Sync your product catalog
Step 2: Define Your Recommendation Blocks
- Choose where recommendations should appear (email, SMS, on‑site)
- Select recommendation logic (e.g., “bought together”)
Step 3: Add to Campaigns and Flows
- Insert blocks into automated flows or one‑off campaigns
- Use Klaviyo’s editor to style and preview products
Step 4: Monitor Performance
Look at metrics like:
- Clicks on product recommendations
- Sales generated from recommendations
- Conversion rates per recommendation block
Use this data to optimize display logic and placement.
Best Practices
Keep It Relevant
Use customer behavior to tailor recommendations — avoid generic suggestions.
Use Multiple Recommendation Types
Combine “bought together”, “also viewed” and “recommended for you” for impact.
Align With Campaign Goals
Use product recommendations to support:
- Seasonal promotions
- Customer retention flows
- Win‑back emails
Test & Iterate
A/B test recommendation placements and types to see what resonates most with your audience.
Summary
Klaviyo’s product recommendations help ecommerce brands:
Personalize content dynamically
Improve engagement and conversions
Boost average order value
Automate relevant product suggestions across emails, SMS, and onsite
Here are case studies and expert commentary showing how companies use Klaviyo’s dynamic product recommendations to personalise content, drive revenue, and improve customer experience.
Case Studies
Case Study 1: Ecommerce Apparel Brand — Boosting Cross‑Sell Revenue
Company: Mid‑sized fashion retailer on Shopify
Challenge: Customers tended to buy a single item and leave — low average order value (AOV)
Strategy
- Added “Frequently Bought Together” and “Recommended for You” product recommendation blocks to:
- Post‑purchase emails
- Browse abandonment campaigns
- Cart abandonment emails
Results
- AOV increased by 15–25% within 3 months
- Customers who clicked on recommended products had 35% higher conversion rates
- Repeat purchases increased as personalised recommendations surfaced relevant products
Insight: Dynamic suggestions helped turn one‑item baskets into multi‑item purchases by exposing customers to complementary products.
Case Study 2: Direct‑to‑Consumer (DTC) Home Goods Brand — Personalised On‑Site Experience
Company: Homewares brand with both online store and newsletter audience
Challenge: High bounce rate on product pages
Strategy
- Displayed “Also Viewed” recommendations on product detail pages
- Added “Best Sellers for You” on the homepage
- Integrated tailored product blocks into email campaigns for abandoned browse and cart flows
Results
- Time on site increased by up to 40%
- Page views per session increased significantly
- Email click‑through rates (CTRs) for campaigns with product recommendations were 2× higher than static campaigns
Insight: Personalisation not only boosted sales metrics but improved customer engagement and discovery.
Case Study 3: Subscription Box Brand — Win‑Back and Re‑Engagement
Company: Subscription snack box retailer
Challenge: Customers churned after initial subscription
Strategy
- Sent personalised “Recommended for You” product suggestions based on past subscription profile and browsing history as part of lapsed subscriber win‑back campaigns
Results
- Win‑back email open rates reached 22% (above industry average)
- Clicks on recommended products converted at double the rate of generic emails
- Re‑activated subscribers returned at higher lifetime value (LTV) than first‑time buyers
Insight: Using behavioural data to inform product suggestions gave lapsed customers a reason to return — with relevant offers.
Case Study 4: Multi‑Vertical Retailer — Cart Recovery Strategy
Company: Large online store offering fashion, accessories, and gifts
Challenge: High cart abandonment rates
Strategy
- Added “Recommended for You” products tailored to items left in the cart
- Included recommendations in cart abandonment flows sent via email and SMS
Results
- Cart recovery rate improved by 10–18%
- SMS flows with recommendations outperformed plain text recovery messages
- Cross‑sell products recommended in abandoned cart emails accounted for 30% of conversions from the flow
Insight: Dynamic recommendations can revive abandoned carts by showing alternatives or complementary items, reducing lost sales.
Expert Commentary
1. On Behaviour‑Driven Personalisation
Marketing experts emphasise that Klaviyo’s real strength is in using actual customer behaviour, not rules‑based static placements.
Comment: “Personalisation based on what customers have actually browsed or bought delivers relevance that generic suggestions simply can’t match.”
2. On Impact Across Channels
Analysts note that leveraging product recommendations in email, SMS, and on‑site blocks creates a seamless cross‑channel experience.
Comment: “Consistent personalised messaging across touchpoints increases trust and keeps customers engaged longer.”
3. On Average Order Value (AOV) Growth
Conversion specialists report that product recommendations frequently unlock significant incremental revenue.
Comment: “When customers discover products they didn’t know they wanted, they buy more — and effective dynamic recommendations make that discovery easier.”
4. On Customer Retention
Customer lifecycle strategists highlight recommendations’ role in retention and repeat purchase.
Comment: “It’s not just about one transaction — it’s about building a habit. Relevant suggestions keep customers coming back.”
Key Takeaways
- Behavioural personalisation matters — show what’s relevant
- Cross‑channel deployment multiplies impact
- AOV, CTR, and retention are the biggest beneficiaries
- Product recommendations help with discovery, conversion, and loyalty
Bottom Line
Brands using Klaviyo’s dynamic product recommendations see measurable improvements in engagement, sales and customer loyalty because they are not just showing products — they’re showing the right ones to each customer at the right time.