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Orderhouse Blog

4 Ways Product Recommendation Engines Grow eCommerce Business

Online Shopping_ Girl on Mobile.jpg 

Forrester study shows that 73 percent of customers surveyed stated they preferred a personalized shopping experience

35 percent of what consumers purchase on Amazon and 75 percent of what they watch on Netflix come from product recommendations.  McKinsey 

Increasing order size. Greater shopper engagement. Converting shoppers into customers.

These are everyday challenges that every ecommerce business faces. Personalization improves the metrics in all of these areas, and Product Recommendation Engines are a key ecommerce personalization strategy. 

In an effort to reach more consumers and build stronger customer relationships, a manufacturer decides to sell their products DTC (Direct-to-Consumer) and launches a branded ecommerce site.  The site is getting plenty of traffic but many visitors are leaving without making purchases, and when they do buy the average order value isn’t meeting expectations.  As a company with several lines of complementary products, this is puzzling. 

Management has data showing that the average order value for their brand is much higher in bricks and mortar retail.  They know that training their retailers on the product line and cross sell has made a difference in converting customers and increasing average purchase amounts.

Their dilemma:  without the face to face interaction of traditional retail, how can they engage shoppers and boost the average order size of their online sales? 

“Recommended for You…” 

What if there was a virtual personal shopper that knows what your customers bought in the past and what type of products they’re interested in? Even better, this personal shopper also has an encyclopedic knowledge of what other people with similar customer profiles are interested in. And uses this knowledge to make recommendations that match your customers’ interests while they are on your site.  And when they are not on your site, knows which customers to notify about new products or special offers that are a fit for them. 

That is just what a product recommendation engine can do. 

Based on a customer’s browsing and buying history it will determine how each customer navigates your website, pointing them toward categories and products based on algorithms in the recommendation engine software.

It can also predict what a customer might buy in the future based on the buying behavior of others, enabling you to make more recommendations.

Most importantly, it provides a layer of personalization to the buyer journey. 

Key Benefits

Getting back to our manufacturer, let’s take a look at some of the ways a recommendation engine can help their grow their online business:

  1. Increase Average Order Value – When the customer is shown other products that meet his interest, the number of items per order increases and so will the average order value.  This cross sell solves our manufacturer’s main problem
  2. Increased Conversion Rate – The personalized experience created by the recommendation engine turns browsers into buyers
  3. More Customer Loyalty – Analytics enable personalized marketing tailored to customer preferences and facilitates more repeat business and customer loyalty
  4. Better Engagement – Visitors engage with recommendations and stay on your site longer without having to perform searches

It’s easy to see that a personalization engine provides benefits that capture new customers, increase retention, and build brand relationships.

Here are some other benefits:

  • Analytics and Reporting on customer behavior and the buyer journey
  • Saves Time & Labor – the software automatically adds recommendations, up sells, cross sells, etc.

For Everybody?

We’ve seen that market leaders like Amazon and Netflix have reaped huge benefits from recommendation engines.  Can you realize the same benefits in your efforts to increase personalization and grow ecommerce sales?

Recommendation engines need a critical mass of user data in order to make useful suggestions to customers. It may not be a good investment if you fit any of the following: 

  • Early stage company
  • Small number of products
  • Light traffic volume
  • Small order volume

But if you’re off the launching pad, have a large number of SKUs, and drive a lot of traffic to your site, a product recommendation engine should be part of your personalization strategy.

Here’s a few useful links if you’re ready to start considering solutions: 

5 Top Recommendation Engines

Personalization Software

For more insight on end to end eCommerce strategy visit this resources page.


Topics: ecommerce ecommerce trends direct to consumer