Welcome to Part III of this article series on data monetization. (Here are Part I and Part II for easy reference.)

Data monetization opportunities are determined by defining a problem to be solved in terms of focus and state. If the focus of the problem to be solved is external and the state is existing, then the defined monetization opportunity is developing new products, services or channels for customers. This means that you are using your customer intelligence data and applying it to their problems. And while the ultimate business goal is to increase customer loyalty and grow revenue, the data is being used to solve the needs of the customer, not the needs of the business.  When using data to solve customer problems, the customer defines the value of the product or solution by variables within the scope of their intended use. This value assessment can be a moving target for businesses to identify and can make the related monetization efforts difficult.

Using data to solve customer problems creates an interesting conundrum for businesses because the value of the solution is defined by the customer; however, the monetization value is still recognized by the business. This means the business still expects to drive revenue or increase customer loyalty but it cannot be successful in doing so without the customer finding value in the solution. This requires the business to have a keen understanding of the customer needs and the variables that could cause a shift in value at any point.

When considering data collection for these monetization opportunities, data privacy and ethical data use reign supreme. The methods of data collection must be appropriate and generally accepted by the target customer audience. Customers expect to be made aware that their data is being collected and used and they further expect that the collection of their data is at a minimum for a mutual value proposition. Advancements in technology make the collection of customer behavior data easy, inexpensive and often unobtrusive. But, without transparency, customer data collection can quickly be considered “creepy.” Customers are more likely to share their data when they understand the value proposition the business will provide using their data. Businesses that are clear about how and why they collect customer data are more likely to be successful in their data monetization efforts.

Packaging Data Products and Services

Packaging data in products and services for customers is about creating utility value and ease of use. In some cases, the packaging may not be as obvious as in other monetization opportunities. In fact, the customer may never see the actual data but rather see the improvements in a product based on the analysis of data. For example, an online streaming music provider may create new music recommendations for a listener based on behaviors of other listeners with similar listening profiles. The customer utility value is high as they are introduced to new music within their range of preferences (without having to sift through a bunch of duds) and in turn, their listening rates increase which is the measure of success for the streaming provider.  

Other monetization packaging possibilities include adding insights derived from data to increase the value of the product for the customer. LinkedIn has many great examples of this as they package insights about profile visits, network and community activity and related industry data, and share it with their customers (both individuals and businesses). The packaged insights make it much easier for the LinkedIn members to get a quick overview of what is going on in their industry and individual networks and quickly act on items of importance. The information is of great value for the members as it is not information they would be able to access or assimilate quickly on their own. In addition, the packaging of the information drives the likelihood of the members to upgrade to premier products, which is, of course, a positive for LinkedIn.

Where's the Value?

The delivery of data products and services that answer external customers’ existing needs requires businesses to not only deliver an effective solution for solving the customer’s problem but to also communicate the value in a way that drives action. Just sharing insights or creating new products without effectively messaging the value or how to take action on the added value is like the old adage of “You can lead a horse to water, but you can’t make it drink.” The key to monetizing data through new products, services and channels is in “making them drink.” The value in the delivery of these products and services must be so obvious and compelling that customers can’t afford not to take action.

Solving existing problems of customers using data helps to inform new products, services or channels for businesses to offer. To remain successful in this approach to data monetization, businesses must be keenly aware of customers’ needs and evolving preferences. They must also be clear and transparent when collecting and using customer data and should always offer the consumer a value proposition for sharing their data. When packaging and delivering these data-based products and services, businesses should ensure high value, ease of use and that they not only effectively communicate the value but also compel action.

Read Part I
Read Part II
Read Part III (Above)
Part IV: Coming Soon
Part V: Coming Soon

Anne Buff is a thought leader on SAS's best practices team.

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