A Product Recommendation Guide

November 14, 2022
A Product Recommendation Guide

You're probably familiar with product recommendations if you shop online. Every time you visit your favourite brand's website, you'll see a list of products tailored specifically to you based on your search history, previous purchases, and a plethora of other data points. These numbers are crunched behind the scenes by artificial intelligence (AI) and machine learning algorithms, which are attempting to determine exactly what you want to see in real-time.

Product recommendations have played a significant role in e-commerce's increased growth. Amazon and Netflix were early adopters of artificial intelligence-powered product recommendations, investing millions to develop and test their own proprietary solutions. This strategy, of course, paid off, and a growing number of businesses have made product recommendations central to their digital business models.

According to research, whether you sell to consumers or businesses, this is a winning proposition. Product recommendations, when used correctly, can increase the average number of items in online shopping carts by 68% — and conversion rates by an incredible 320%. Product recommendations could account for up to 31% of total eCommerce revenue.

What exactly are product recommendations, and why are they significant?

Product recommendations are product listings tailored to individual website visitors based on information about them, their behaviour and preferences, or the behaviour and preferences of similar shoppers. You can make product recommendations to customers who do not have a profile or account with your company.

The following are examples of common types of recommendations:

  • Bestsellers
  • Currently popular
  • Suggestions for you
  • You might also be interested in Products like this

10 Product Recommendation Strategies That Work

Product recommendations can be used to connect with customers and encourage them to buy in almost any location on your website. The following are ten of the most effective product recommendation strategies from Ingold Solutions as an Adobe Commerce Bronze Partner:

1. Emphasising best-sellers

One of the simplest and most effective forms of product recommendation is to promote your best-selling products. If your existing customers like them, chances are your new customers will as well.

2. Concentrate on popular items

During certain seasons or holidays, emphasising products that customers are likely to be looking for can be extremely effective. Customers also enjoy new arrivals. Returning customers see something they haven't seen before. New customers notice that your inventory is constantly changing, and it's worth checking back frequently.

3. Putting sales and discounts in the spotlight

Customers are constantly looking for a good deal. You'll give them a reason to buy if you recommend discounted products. You can also suggest a sale page (rather than a single item) or simply display a pop-up with your current offer.

4. Ratings and social proof

Showing social proof in the form of quotes and ratings is an excellent way to establish trust and demonstrate value to a customer. This tactic, like many previous ones, offers customers products that other customers are already pleased with, encouraging the customer not to miss out on a great item.

5. Make your recommendations even more personalised

Personalised recommendations start with suggestions based on what customers like. Personalization begins once you've made progress in developing individual customer profiles. Personalisation that is effective is based on transactional and behavioural data, as well as financial, operational, and third-party data. This data provides the most relevant, tailored product recommendations, increasing sales.

Starting with product recommendations

Personalised product recommendations are rapidly becoming an inevitable part of everyone's customer experience. And advances in eCommerce technology have brought them within reach of almost any business, including yours.

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