Sales drive online businesses. Successful online businesses depend upon relevant recommendation technology that offers personalized product recommendations to their customer at multiple touch points. Often, businesses implement mediocre recommendation technology that seems like it will work; yet, these businesses fail to monitor the technology’s performance. With personalization becoming just as much of a competitive aspect as price in today’s online economy, businesses must be sure that their recommendation technology successfully promotes their online operations in order to experience the success they desire.
The best recommendation systems combine a shopper’s historical profile (if one exists) with his or her in-session activity to offer relevant recommendations in real-time. If no historical data exists for a given user, then superior recommendation engines will refer to the user’s most recent search in order to provide personalized recommendations. Recommendation systems that feature direct integration with a customer database and email marketing and that employ algorithms covering multiple scenarios (from first-time visitor to high-value registered customers) are also preferable.
First and foremost, an organization’s recommendation technology should be able to recognize the search terms that bring the customer to that organization’s site. For instance, if a user conducts a Google search using the word “tennis shoes,” then when that user clicks on Google’s link to that organization’s site, he or she better see an assortment of tennis shoes for sale. If the user does not immediately find what he or she is looking for on that business’s site – such as an array of tennis shoes under the heading “Customers who searched for ‘tennis shoes’ liked these products” – then he or she will leave that site to find shoes elsewhere. In cases like these, the recommendation software in use absolutely fails. In order to ensure that your organization’s recommendation engine is as successful as possible, you must ensure that your technology will be able to recognize both off-site and on-site search terms and that, furthermore, it will be able to consistently return relevant results to your customers based on those search terms.
Businesses should also use their recommendation software to make relevant contact with their customers as frequently as possible. Throughout the online shopping experience, sidebars and page modules should alert the customer of related products under headings such as “Customers Who Like This Also Like.” Follow-up emails and marketing materials, both online and offline, should use customer data to make intelligent offers. A well monitored and thoroughly connected (i.e., to customer databases and other marketing efforts) recommendation engine that consistently returns relevant results to your business’s customers can have a dramatic, positive effect on your online presence.