Customer engagement--it’s a known gold standard for driving conversions and loyalty.  Finding the right formula to create scalable and consistent results has been a hot topic for quite some time in both digital and brick and mortar channels.  As the amount of customer data we collect increases, the challenge of making sense of that information in terms of relevant customer engagement often becomes more complicated.  In today’s ultra-competitive world, I think the competitive advantage will go to retailers who are able to leverage their data to create personalized experiences that are truly relevant to their customers. 

In the digital world, personalization can be defined as providing each customer with a web experience made more relevant or customized to the customer based on data derived from the individual user, group of users, or some combination of the two.  In theory, web sites that are personalized to individual customer tastes and sensibilities should see greater engagement and higher conversion rates than “one size fits all” presentations. 

A perfect example of this is Netflix.  By paying close attention to the content each subscriber views and factoring the subscriber’s subjective ratings (one to five stars) into their algorithms, Netflix is able to create highly personalized and relevant experiences for each customer.  This process increases the amount of time each user spends on watching programs based on known tastes.  The personalized engagement Netflix subscribers experience results in higher conversion rates, measured by Netflix as subscription renewals. 

Obtaining the Right Customer Data

Netflix is well positioned to develop relevant personalization because most of its customers are regular consumers of its product.  So purchase history and subjective user ratings are great starting points to build meaningful profiles.  But what if you are selling something that people don’t purchase often?  There are third party data suppliers that can provide likely traits of your visitors, but it may be difficult to derive tastes for the specific products that you sell based on the rather generalized demographic and psychographic information they provide. 

A straightforward way to get relevant data quickly is to simply ask your customers directly.  At, customers are invited to take a short and easy quiz.  The key is knowing what questions to ask and how to present them.  Questions should get at the heart of what you need to know to make a good assessment without burdening your customers.  For example, when it comes to purchasing furniture, a few important factors include each customer’s style preferences, budget, the relative importance of quality and features, and the amount of available space the customer has. 

The customer characteristics derived from the survey method may be sufficient to begin the process of creating relevant personalized customer engagements.  However, if you are able to combine the survey data with third party data sources (e.g., Nielsen Prizm Data), it will enable you to make more granular assumptions and recommendations.  In any event, the next step is to map specific customer profile characteristics to attributes of your products. 

Breaking Down Product Data

To generate relevant personalized customer engagement,  you will need to develop a way to associate the attributes of products with relevant customer characteristics.  This requires a complete understanding of the products that you sell.  The best way to gain this knowledge is to break down each product into fundamental attributes and characteristics, classifying and assigning values to each, and rating the products relative to other products in the same category. 

The information cataloged for products must be relevant to and associated with the information collected for customers.  For example, if you determine that quality/features are characteristic that are relevant for certain customers, you must also build a complementary data set for quality/features on each product.  This can be done by assigning values to the types and grades of materials used, manufacturing process, duration of warranty, and product defect rates.  It is important to use this data to rank products relative to each other within the same category  (i.e., compare specifications of laptops to other laptops and do not compare laptops to desktops because the price to feature ratios are very different). 

At the beginning, you will have to make some assumptions about how individual product attributes should be associated with customer characteristics, but over time, customer behavior will validate whether your assumptions are correct or need adjustments.  To create a scalable system, you will need to develop automated processes that measure customer actions (e.g. viewing a product page, adding items to a shopping cart, ordering the product, returning a product, etc.) to constantly improve results. This automated process is generally referred to as machine learning. 

Remember the Goal of Personalization

There truly is no limit to what you can do with personalization.  The question is what should you do?  The simple answer is to use personalization as a tool to create a more meaningful connection between your customer and products (and vicariously, you and your customers).  As retailers, our role in the value chain is to know our products, to know our customers, and to connect the two.  Your personalization tools should be the place where you showcase your understanding of how your products solve the problems of your customers.   Just as Netflix displays movies most likely to appeal to its subscribers, you can create personalized web experiences that showcase products that are most likely to appeal to individual customers. You can extend personalization to virtually every touchpoint once you have the right processes in place. 

Though web based personalization may seem daunting, it’s really the digital version of what good retailers have been doing for hundreds of years.  Our goal with personalization at is to become the perfect retail salesperson; someone who takes the time to get to truly know customers, has an encyclopedic knowledge of our products, and combines the two in a perfect match that seems intuitive and simple for the customer.  Using common sense, some clever programming and experimentation, you can create a truly personalized and positive customer experience that will keep your customers coming back time and time again.

T. J. Gentle is the President & CEO of, the pioneer of Design on Demand® for ecommerce. Since joining in 2005, Gentle has led the Smart Furniture team in partnering with the some of the world's leading furniture brands, such as Herman Miller and Steelcase. He sits on the board of several community organizations and serves as an advisor and mentor to local entrepreneurs. T. J. was a speaker at Customer Engagement Technology World in November 2013.