Product recommendations can help your customers find what they’re looking for
On a basic level, product recommendations are where you offer your visitors additional items which you believe may be of interest to them based on their own buying/browsing history, or that of a similar customer browsing profile. Or a combination of both of these. The intent being to increase your sales and/or average order value (AOV).
Product recommendations are now so commonplace that they are used by many of us every single day. And not just in our online purchases. Choosing what to watch on Netflix or listen to on Spotify; which news article to read next, as well as which jeans, TV, or coffee to buy. It’s so embedded into our expectations that we pretty much take it as a given to be offered alternative products as part of the user experience, on almost any website or digital application we use.
The most important thing in making product recommendations engines effective is the data. Data can be collected as users interact with your website, as well as through importing historical information.
This could be weeks, months or even years of purchase data – the sky really is the limit! The more data the algorithm has access to, to filter and inform its decisions, the more accurate the product recommendations will be for your visitors.
The most common examples you will see across many websites and digital services are things such as:
These are all available via Webtrends Optimize, however, almost any insights which your data can provide can then be utilised and filtered to promote your products, increase your average order value and enhance the user experience of your website. You don’t just need to stick with the crowd.
At its core the Webtrends Optimize product recommendations engine utilises your own customer data, applying different algorithms to suggest the most relevant items as highlighted above.
However, if that feels too much like you’re relinquishing full control to the AI bots, then don’t worry, filtering can also take into account any business-driven rules you choose to apply – such as recommending a product by a specific brand, only recommending a product between X and Y selling price, or taking stock control into account, to ensure the automated data filtering compliments your overall business strategy.
When used alongside AB testing and Multivariate testing, you can maximise the placement, positioning and messaging of your product recommendations, as well as testing which of the above examples (or others) are the most effective on your own site.
As stated above the common uses of product recommendations can be very effective, however the key here is to see what works on your website, for your customers, and for your products. For example, in a previous test, one client found that using People who bought this also bought… performed much better for them on Womenswear, whereas People who viewed this also viewed… was more effective for Menswear.
As with any website optimisation and personalisation strategy it is the use of tactical combinations of different elements that allow you to fully maximise the potential of your website or mobile application. And the great thing is that with Webtrends Optimize you get access to all of these tools. As standard. With no additional cost.View Pricing
Want to know more about product recommendations, or how Webtrends Optimize can help you increase your conversion? Click below to send us a message or call us on 0333 444 5502.Send message