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Product recommendations

Increase your conversion rate with personal recommendations

What are product recommendations?

There are many types of recommendations – you probably already know "abandoned basket", "other users also bought" or "bestsellers in the category". In addition to different types of recommendations, you can also use recommendations on different platforms such as on your website, in emails or on social media. In the following sections, we delve into different ways to use product recommendations.

With product recommendations you can:

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    Increase the number of conversions

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    User experience

    Improve the user experience

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    Provide real-time personalisation

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    Basket size

    Increase the average basket size

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    Customer loyalty

    Improve customer loyalty

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    Automate email dispatch according to user behaviour

How do I get started?

There are several providers of platforms to implement personalised product recommendations – whether in emails, on the website or in the search results on Google. One aspect that is the same for all providers is that you must install a script on the site, which starts tracking the user and their purchasing behaviour.

Depending on the type of product recommendation you want, you must connect your data to your website, email platform or SEM tools. Likewise, your product feed must be configured so that it can be read by the chosen platform. At Novicell, we specialise in the implementation of product recommendations, and are happy to help you get started - from choosing a platform, to technical implementation and utilisation of the platform.


Personalise the user experience on the website

A good place to start using product recommendations is on your website. There are several ways in which you can automatically present the user with relevant products, such as: • "Recommendations for you" • "Other users also looked at" • "Most popular items in the category" See, for example, how Ilva uses product recommendations on its front page to recommend selected products based on the user's behaviour on the site - of course based on real-time data.


This type of "product band" can be implemented in several places on the website. By presenting the user with more relevant and personalised products, for example based on behaviour or previous purchases, you increase the chance of a conversion on the site. You can also use recommendations in your check-out flow to increase the basket size through cross- and up-selling. An old saying is "Other users also bought" or "Related products". For example, Hatting Agro uses a ribbon with related products to increase basket size based on purchase history from other users. The recommendation is displayed when the user places an item in the basket.


Increase the conversion rate from your newsletters

Most email and automation systems can be relatively easily integrated with a product recommendation platform – and there can be many benefits to be gained, including: • Save time on manually setting up emails • Send personalised and relevant offers instead of mass mailings • Automate the sending of abandoned basket and weekly offers for example By using the data you have collected about each individual customer, you can expect a boost in both click-through rates and conversion rates in the email channel. This is of course because your email will now be far more relevant to the individual recipient, as it will contain exactly the products that person is interested in. You can also free up resources that were previously used on setting up offer emails for different segments, and instead, automate these right down to the user level.

Selected companies we have helped with commerce

Take recommendations into the search engine

Wouldn't you like to show the most relevant products when a user searches for your products on the search engine? More and more of the recommendation platforms now have built-in functions to link recommendations with your SEM work. By using the users' behavioural data, you can therefore link purchase behaviour and purchase intentions with display and Google shopping advertising.

It gives you the opportunity to work with omnichannel marketing and align your targeting of messages across channels.

Multiple systems also allow you to build segments and target groups in systems based on their interests and buying behaviour. These target groups can then be exported and used in, for example, Google Ads or on Facebook.