Data analysis and personalized recommendations in print and on the Web can generate more sales from your existing customers.
According to a recent article on VentureBeat, an online venture capital news site, Amazon.com attributes 35% of its product sales to recommendations. While that may be quite a number to fathom, even small businesses can take advantage of the technology and tools used by an 800-pound gorilla like Amazon. It’s not as difficult or expensive as you might think. Data-driven marketing applications are now practical, affordable and something your must consider as part of your marketing mix.
What does your customer data say? In order to create personalized recommendations and maximize the value of your current customers, you must perform a thorough analysis of your existing database.
Organize and review your current customer list and perform additional analysis to predict customer tendencies in terms of clusters, and other data modeled groupings. This will help you to determine the type of message or offer to send to each group based on their past behavior. Then you’re ready to leverage your data and analysis in order to move your best customers to higher purchase levels. This might take the form of making a specific set of cross-sell or up-sell recommendations to individual sets or cluster of customers.
If your current customer files are not in the condition necessary to take advantage of some of these types of analyses, make it a priority to clean up your data so you can maximize your ability to harvest your own greatest asset.
What about recommendation systems? The idea is that customers are not all the same so why would you treat them that way? Amazon was the first to really utilize the, “Customers who purchased this also were interested in the following items”, technique. But you can use the same approach (and even improve on it, as Amazon clearly does not always get it right) for your own Web site.
In the movie rental arena, Netflix, Blockbuster and FamilyVideo.com have used recommendation systems successfully, and Netflix is even running a $1 million contest offering programmers the chance to beat the current Netflix system by more than 10% and win the big prize. They are doing this because a better system will drive incremental sales well above $1 million over the life of its implementation.
Personalized recommendation systems can cost well over $100,000 for companies with a large number of product offerings. But for companies with a smaller amount of products costs can be less than $50,000 for set-up, and monthly maintenance charges can be tied to performance.
An added benefit is that creating a truly personal shopping experience for your customers engenders increased customer loyalty. Even though its suggestions may not always be on the mark, we return to Amazon again and again when looking for items for ourselves and gifts for friends and relatives. The friendly service seems to know us — it certainly recognizes us — and it appears to have been waiting patiently for our return. Why not create a “My-store,” “wish-list,” e-mail alert, or an intelligent search function on your site and make your customers’ shopping experience truly unique? Today’s shoppers want to feel that they are in control of their shopping “experience” and affording them choices to make (but not too many) is a key to success.
So whether it is in print, on your Web site, or both, data-driven applications offer your precious customers new products, destinations and experiences — and provide you with stronger income opportunities.