Three Steps to Monetizing Your Data through Customer Intelligence

The following is an op-ed by Andrew Wells and Kathy Chiang

Kathy Williams Chiang is VP, Business Insights, at Wunderman Data Management.

Andrew Roman Wells is the CEO of aspirent, a management-consulting firm focused on analytics.

How intelligent is your company about your customer? Do you know enough about them in order to create a personalized customer experience? Understanding your customer through deep intelligence enables you to drive the right actions and experiences that can make the difference in your ability to compete in the marketplace and win with the customer. In today’s world, competing on price alone cannot win at checkout. You need to create a unique customer experience that separates you from your competition. This could be your customer service, return policy, quality of your product or services, or designing a bespoke experience.

Imagine the frustration of working to create an amazing experience for a targeted customer segment but lacking even the most basic information about specific customer interaction with your products or services. In these not uncommon instances, a company will typically guess at the right customers to target or use attributes that they feel are the next best indicator usually sweeping in a number of people that are are not truly targets. This approach leads to marketing campaigns with low response rates and wasted marketing dollars.

To achieve a better yield on your marketing spend, we recommend creating Customer Intelligence analytical solutions that provides your company with a variety of ways to monetize your customer.

Here is a 3-step approach to building a customer intelligence analytical solution:

1. Actions – The first step in our approach is to define the actions you would like to take with your customer targeting strategy. This can include a wide variety of marketing and sales activities. For a retail company, this might be a segmentation strategy based on customer transactions such as value, frequency, and recency of purchase. By segmenting your customers into specific purchase behavioral groups for marketing and sales purposes, you can optimize marketing spend to align to what will attract that customer segment.
An example of event based marketing to a specific customer segment is performed on a regular basis by a company out of New York City, Michael Andrews Bespoke, a premier customer men’s clothier. After analyzing their customers spend, profitability, and referral rate, they invite premier clients to a high end scotch tasting event. To include all of their customers would be cost prohibitive, but for their best customers, the cost of the event  yields high returns.
Other actions you may want to think about include email or mail campaigns, targeted discounts, print media advertising, social media, SEO, paid online advertising, and special events. Each of these activities are designed to deepen your relationship with your customer, but the type of action may yield a different type of Customer Intelligence analytical solution.  Knowing upfront your purpose will help yield the right analytics to help you monetize your customers’ experience with your company.

2. Data – As you work to improve your ability to connect with your customers and build a Customer Intelligence solution, the next step you will need to take is to gather the right data. Based on the actions you want to drive; you will need specific datasets or attributes to drive decisions. This in turn helps you understand the attributes needed and the data you need to collect. We find that starting with the actions and letting them drive your data needs is a clearer path to monetizing your data.

Stitching together the various datasets needed is often a large undertaking where most of the time is usually spent. In some cases, you may have more than enough data to support your customer intelligence needs, but in most cases, you will be missing key pieces of information. In either case, having the right data set is the key ingredient to drive revenue through a better understanding of your customer purchase activity.

Places to look internally for the right data include internal systems such as Point of Sale, Customer Relationship Management, Loyalty, and Order Management systems. If the data does not sit within the walls of your company, think about asking your customer to fill out a short survey. Surveys can be a great tool to help you gather information about what your customers are looking for and what they think about your products and services. We recommend when asking your customer to give you something, you should return the favor by giving them something back. This could entail a 10% off coupon or a free gift.

Another approach to finding the elusive data needed to build your customer intelligence is to purchase the data from a data vendor. There are several data vendors, big and small, that collect a wide variety of information on U.S. consumers. These can include purchasing habits, affinities, social media presence, clickstream data and mobile use among many others. These datasets can often enrich your data to better understand your customers allow you to target them with the right offer.

3. Test & Learn – The final step in our approach is to get out there and execute. Begin with leveraging your Customer Intelligence analytical solution to understand who would be the right candidate customers for the actions and results you want to achieve. Start small with several test and see how they perform. Make sure that you set up a way to measure the test, either through inferred or a direct response.  Based on the results of the test, you can scale the marketing activity as appropriate to achieve the results you want.

Your customer intelligence analytical solution will provide you with the insights you need to enable you to monetizing your customer through actions that best support your business. You will find that the solution is a journey and will grow and mature over time as you achieve success with your customers and win in the marketplace.

Andrew Roman Wells is the CEO of aspirent, a management-consulting firm focused on analytics. Kathy Williams Chiang is VP, Business Insights, at Wunderman Data Management. They are the co-authors of Monetizing Your Data: A Guide to Turning Data into Profit-Driving Strategies and Solutions. For more information, please visit and