Why Personalise?

It’s widely accepted that visitors who engage with personalized product recommendations on a website convert more, buy more and have a higher average order value than those who don’t. Click through rates of 8-25% are not unusual.

At its simplest level, a good recommendation engine will select and display personalized product recommendations that are the most relevant to each individual whilst they are browsing.

This enhances the findability of products by automatically showing products that the user didn’t realize they were interested in until they were actually shown them. This “discovery” aspect is particularly useful for sites with large product catalogues and for sites such as apparel sites where the user may have only a vague idea of what they are looking for.

Increasing incremental sales

For the user, recommendation engines offer a richer customer journey which will ultimately improve loyalty and customer lifetime value. For the retailer, it offers measurable, incremental sales.

However, extensive research shows that retailers are only using personalization tools in approximately 40% of all their onsite shopping sessions. For those retailers who have invested more heavily, and now feature some element of personalization in more than 80% of all shopping sessions, incremental sales have increased on average by over 10% and up to 20% in some cases.

Shortcoming of segmentation

Some companies create behavior profiles by placing individuals into simple segments. Product recommendations and personalization tools are then organized according to each segment. But a segmented model is not likely to deliver the best results because targeting still remains imprecise.

Multivariate testing suffers under the same constraint, showing products with multiple variations to eventually work out what the best product to serve is at any given point. However, it is not able to deliver a personalized experience for each visitor.

Individualizing the experience

To be most effective, it’s essential that individual profiles are created for each individual visitor who visits a website. Each profile should be unique to each visitor.

In order to refine the relevancy of products recommended there also needs to be a mechanism for capturing and learning visitor actions and responses to products recommended to them. Only in this way can a precise 1-to-1 targeting of the right product in front of the right person at the right time be enabled.

It's all about generating extra sales

Personalization is an important navigation tool. After all, it helps customers to find more quickly the products they want to buy which makes for a good customer experience which in turn supports conversion and retention objectives.

However, the focus has to be squarely on its ability to increase sales. Key performance indicators should be applied to monitor the ongoing sales results achieved by each page and by each recommendation widget on the page if more than one are used.

Behavior data is constantly evolving so it’s essential to keep validating how well each page type is performing in generating sales.

Keeping an eye on engagement

While monitoring the sales achieved, it is also important to monitor the level of engagement each visitor is demonstrating with respect to the products that are being served. A high click through rate of products recommended will give a clear indication of the relevancy of the products served to each visitor.

The click to purchase (CTP) metric indicates how well a product sells. If this is less than 10% it may indicate that there is something else such as price that is inhibiting the sale.

True 1-to-1 personalization

Personalization has been around for awhile, but how it works and what it can achieve varies enormously. Often the difference in performance is due to the technology itself.

Many vendors claim personalization capabilities, but few are actually able to deliver truly 1-to-1 personalization. This means they never achieve the best return on investment possible.

Precise 1-to-1 targeting, for example, displays the right product to the right person at the right time. In other examples it may be that the technology is not sufficiently well deployed nor is it configured and customized to accommodate the browsing behavior of individual sites.