5 product recommendations that increase sales for ecommerce

First published on May 4, 2022

 

5 minute read

John Patrick Hinek

Growth

TLDR

Using machine learning and artificial intelligence to integrate product recommendations gives the most accurate predictions for successful advertising, eliminates guesswork in creating campaigns, and creates magical customer experiences. 

Outline

  • Intro

  • 5 ways to implement product recommendations

    1. What people like you bought

    2. Highlighting bestsellers

    3. Discount codes and promos

    4. Bundling

    5. Custom recommendations

  • Call to action

Intro

Product recommendations are essential to boosting revenue and sales for any ecommerce company. Adding product recommendation technology into your systems ensures that relevant products appear as soon as a customer enters your website; maximizing chances of a sale, and minimizing the occurrence of churn. 

While the majority of ecommerce companies have yet to integrate product recommendations into their business, an increase in revenue and sales are common in ones that do. 31% of e-commerce site revenue in 2021 came from product recommendations, per a 2021 

Barilliance

study. 

The most successful product recommendation engines are built with artificial intelligence (AI) and machine learning (ML) technologies that enable brands to get the most out of their data. Once only accessible to billion dollar businesses, new AI/ML and data analytic technologies have made integrating these systems possible for businesses of any size. 

5 ways to implement product recommendations

1. What people like you bought

Using commonalities in crowd data, ecommerce companies can more accurately display relevant products to their customers. 

Advertising products that were purchased by customers of similar demographics (age, region, gender) can increase the likelihood those products will be purchased again. 

95% of customers

read reviews before purchasing a product. Seeing that other customers have purchased a product can make new customers feel more confident in purchasing. 

A system that can segment data is needed to run this process. Intuitive data analytics tools have made it much easier for managers at all levels to organize their data and integrate this system. 

2. Highlighting bestsellers

Prominently advertising best-selling products on ecommerce sites can further boost sales of those products. In business, the 80-20 rule, or pareto’s rule, finds that 80% of revenue comes from only 20% of your profits. While trends and new items may be profitable for a time, continually advertising bestsellers is a way to sustain steady revenue. 

Staying on top of past and current data is all that’s needed to integrate this feature into your website. Data visualization tools make this process incredibly easy for those with or without extensive data knowledge. 

3. Discount codes and promos

Discount codes and promotions are a great way to generate sales. Advertising efforts that highlight discounted products can drive growth to new audiences and renegade old ones.

Sending personalized promo codes through email is an effective way of executing a successful discount campaign.

Experian

found that personalized emails lead to a 27% increase in sales for companies who utilize them; however, only 70% of companies do. 

Using data analysis and AI/ML tools, ecommerce companies can find what discounted items are most relevant to each customer demographic and create personalized messaging for each group. 

4. Bundling

Bundling complementary products encourages customers to spend more than they would otherwise; even if products are offered at a discounted rate, this can boost revenue. 

Executed well, bundles can be extremely successful. 

Shopify

highlights a few bundling case studies in which companies who integrated product bundling increased their average order value by 30% to 111%! 

While data isn’t necessary to implement a bundling strategy, it can help to categorize complementary products based on the demographics who purchased them. This can help teams better create and market product bundles with the highest chance of sale. 

5. Custom recommendations

Amazon and Alibaba’s entire sites are built off of custom product recommendations. Integrating custom recommendations in your own website is a great way to stay competitive. 

With only a few thousand rows of data and AI/ML capabilities, ecommerce companies can customize their product suggestions for every unique customer engagement. 

Ecommerce companies who successfully integrate custom recommendations can expect to see an increase in sales and reduction of churn, as customers find what they’re most likely to look for as soon as they enter your website.

Call to action 

Utilizing product recommendations in ecommerce websites has been shown to increase revenue, sales, and reduce the likelihood of churn. 

Using machine learning and artificial intelligence to integrate product recommendations gives the most accurate predictions for successful advertising, eliminates guesswork in creating campaigns, and creates magical customer experiences. 

Learn more about how to integrate product recommendations with machine learning: 

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