Product Recommendation Research – What we learnt

Data is the lifeblood of the internet. Every online activity generates data that businesses can use to build an agile approach to marketing. E-commerce is no exception and, according to a recent study by Barilliance, almost a third of e-commerce revenue is a direct result of personalised product recommendations (see more:


From past purchases to product wish lists to abandoned transactions, e-commerce activities generate a wealth of usable data. Product recommendations can leverage this data for the purposes of upselling, increasing customer satisfaction and more.


Which Product Recommendation Generates the Most Revenue?

There are many different product recommendation techniques, and some online stores use more than one to optimise performance. However, the report by Barilliance in 2015 revealed that one method outshines all others: “Visitors who viewed this product also viewed…”.


Before online shopping became the most popular way to purchase, consumers often enjoyed window shopping without having any intention of buying a specific item. Nowadays, people shop online in much the same way, sometimes browsing relentlessly for something that interests them before making a purchase.


By automatically suggesting products that other would-be buyers have been viewing (rather than actually purchased), you’re tapping into a potential goldmine. Most importantly, this technique illustrates the perceived popularity of a product from the perspective of other customers, rather than that of the store itself.


How Can Retailers Use Product Recommendations to Increase Revenue?

It pays to understand the psychology of buyers. The Barilliance study also revealed that the popular ‘customers also brought’ method is not nearly as effective, for example. The reason for this is that people are looking for guidance rather than distractions, and this technique tends to lead people away from what they might already be intent on purchasing. In other words, people want suggestions rather than orders, implied or otherwise.


Understanding the buyer journey is the key to success with personalised product recommendations. Sometimes, there’s a fine line between guiding customers through the buyer journey and just distracting them. Aggressive upselling, for example, tends to distract and annoy customers. By contrast, simply suggesting products in an unobtrusive way can encourage them to add more to their shopping baskets or perhaps add products to a wish list for returning to later.


Why Personalisation Is the Key to Successful Product Recommendations

The studies show that providing too many options confuses people while also damaging the credibility of the recommendations. Rather than displaying lots of products early on during the customer journey, it’s often better to learn more about the customer so that you can better personalise the product suggestions.


Most importantly, e-commerce stores should avoid trying to cross-sell on the product description page, since doing so distracts rather than guides your customers. Instead, it’s better to list similar products, hence the effectiveness of the ‘Visitors who viewed this product also viewed…’ method.


It’s important to remember that, while a customer is reading a product description page, they’re still in the research phase of the buyer journey. By contrast, once a buyer has reached the shopping cart, they’re almost at the point of making a purchase. As such, you want to avoid taking the customer back a step at this stage by recommending other products. Instead, the shopping cart is a better place for upselling.


Customers use data to help them make a choice. Personalised product recommendations are one of the most effective ways to provide guidance, but it’s crucial that they don’t distract your customers.







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