How Improved Product Recommendations Equal More Clicks and Sales for Your Business

Just because a shopper landed on your website, it doesn’t mean they always find exactly what they’re looking for on the first visit.

That’s why product recommendations are an effective way to personalize your marketing communications while increasing your return on investment (ROI) and customer lifetime value (LTV).

But product recommendations can make or break your sale.

Putting the right product recommendation in front of someone can influence a purchase they might not have otherwise considered. On the other hand, poor recommendations will, at best, result in a wasted opportunity, and at worst, they can make your brand come off impersonal.

So how do you make accurate recommendations to customers who are shopping with you?

The best way to create relevant recommendations is to factor in the products that customers and prospects view and purchase, not just the ones you think they should buy.

Shoppers are constantly sharing data surrounding the types of products they’re interested in through their onsite activity. What if you could take that data and use it to put the right product in front of the right person at key moments in their customer journey?

Unfortunately, there aren’t enough hours in the day for you to give personalized recommendations to each customer individually—but that’s where technology can help.

Introducing Klaviyo’s Personalized Recommendation Engine

No matter the size of your business, you can use Klaviyo’s Personalized Recommendation Engine to make more relevant product recommendations to your customers.

To use the Personalized Recommendation Engine, simply build a product feed by selecting the categories from your ecommerce store you want to include and exclude, then choose whether you want to base the recommendations from those included categories on products ordered, products viewed, or a blend of both.

Once a product feed is set up, just add it (via a product block) to any campaign or flow to start adding personalized recommendations to your messages.

Previously, order history was the only metric you could factor in when making product recommendations. This is effective for customers who have shopped at your store multiple times and have a rich order history, but what about shoppers who haven’t made a purchase with your brand yet?

Now you can reference the products a shopper has viewed in addition to the products they’ve ordered. This ensures that you can make accurate product recommendations for current and potential customers alike.

product recommendation engine

Product recommendation metrics

When should you use ordered product, viewed product, or a blend? Here’s more information on the Product Recommendations Engine metrics and how to use each.

Ordered Product

The ordered product metric allows you to make recommendations based on an individual’s previous purchases and similar customers’ purchases. If you choose this metric, I recommend using it on customer profiles that have made at least two purchases. 

A few places to use the Ordered Product metric include your thank you, anniversary, loyalty program, cross-sell, and winback flows.

Viewed Product 

The viewed product metric makes recommendations based on products an individual has browsed the product detail page for. 

Consider using the Viewed Product metric in your welcome series, when recommending new or high-priced items, and if you’re a new or smaller brand who doesn’t yet have customers with a rich purchase history.


The blended metric makes recommendations based on a combination of the Viewed and Ordered Product metrics. 

Consider using the Blended metric when communicating to a broader audience. For example, you could add blended recommendations as a secondary call to action (CTA) in flows that include content like blogs, new products, or seasonal sales.

Provide more relevant recommendations to your customers

Product recommendations are a crucial tool in your efforts to personalize at scale and effectively communicate with your customers. Skip the black box approach and use shopper data to your advantage with Klaviyo’s Product Recommendation Engine for more relevant recommendations.

Learn more about how to use product feeds and recommendations.

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