Recommendations AI: Google’s new eCommerce recommendation system

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Recommendations AI

16/12/2020

Profile picture for user Ángela de la Vieja

Ángela de la Vieja

Finding the perfect formula to build the recommended products list for your eCommerce business is now easier thanks to Recommendations AI, the new Google tool that always offers users the best products related to their purchase. Do you want to improve cross-selling in your eCommerce business? Add Recommendations AI to your price intelligence package and boost your sales.

What exactly is Recommendations AI?

Recommendations AI is a tool created by Google that aims to find the best products in your eCommerce business to cross-sell in each product sheet. For this, it uses an algorithm, based on machine learning, that’s able to conclude what these products are, based on each user’s shopping history and tastes as well as on similar users.

The truly revolutionary aspect of this new system comes from the use of automation in the process, which significantly lightens the workload of eCommerce managers and has a direct effect on an increase in profits. This is what those who’ve already been able to test it have commented, including the manager of testing at Sephora.

How can Recommendations AI help your eCommerce business?

At the heart of Google’s launch of Recommendations AI as a tool is the ability to offer a much more personalised shopping experience to each and every one of your users. If you’ve already put customised pricing strategies in place, for example, this will be the icing on the cake that can make your eCommerce business offer users an experience that is 100% adapted to them.

Of all the possibilities out there, there are two key benefits to using Recommendations AI in your eCommerce business:

1. Offer items that are related to the user’s search history. These aren’t only the products that the brand believes should be sold together or that make sense as such. This knowledge of the user goes deeper and the system can make its proposal based on its analysis of their previous search behaviour. 

2. Read the purchase process horizontally. When it comes to cross-selling and seeing which products end up selling together more often, you can extract all the deepest knowledge about your audience. What do they buy before and after? Even though this doesn’t have a direct relationship, apparently. This will help you to better select the elements to compare in A/B testing or to make a successful sales pitch in formats like newsletters, for example.

Recommendations AI

How to get the most out of Recommendations AI

In itself, implementing artificial intelligence, like that from Google Shopping’s Recommendations AI, is a key, differentiating element for your business. However, there are some elements that you should take more care with to achieve the desired effectiveness.

The first of these elements is the environment in which the user encounters the product proposal. How is the cross-selling module designed? What message is delivered to the user as a catalyst for purchase?

The second element to keep in mind is the place that the user goes when they access the purchase. In both the main and the target product sheets, there should be a clear thread connecting the two items. The path must be organic and comfortable for the user. Moving from the pre-purchase step to the new, related product sheet should be completely smooth, only offering improvement.

And, last but not least, check how the pricing module works within your product highlights. Recommendations AI will give you the formula to find the best product on offer, but the presentation is up to you. Are you already ready to achieve the highest level of success?

Find out how Minderest can take your business to the next level.

Contact our pricing experts to see the platform in action.

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