How do I Sell my Data

In my work assisting customers for IBM, I’m once again hearing new types of questions that are indicating a fundamental change in how business earns money. For several years we’ve been working on applying analytics to improve business results. The internal data monetization has already done an amazing job at transforming business in all verticals by improving customer experience, enabling more personalized marketing and sales, deterring fraud and so on.

What many companies have started to realize is that the raw data they possess could be cleansed, sliced and diced to meet the needs of data buyers. Customers ranging from banks, telecommunication providers, energy and utilities companies and retailers have potential to earn new revenues from the vast amount of data they hold. Each of these businesses are experimenting with different ways to monetize the value of the data they gather during their normal operations. Each are expecting to make considerable revenues based upon the difference between the cost of collecting and storing the data, and what the insights and outcomes can be sold for. These customers are asking the next logical question: “How do I sell my data?”

Recognize it as a business question not a technology question

Even though the source of the question to me has been from the Business Intelligence team or the Information Technology team, the first item to recognize is this; the question is a business question and not a technology question. We need to approach it from a Marketing Process Perspective.

Approaching it from a marketing process perspective means developing a profile of your target customers, verticals, and their parameters for success. Identify who would be interested in buying my data and how much would they be willing to pay. The following questions need to be answered.

Situation Analysis & Discovery

What does the customer need? For example: Do they want to tap into the growing demand for data to fuel smarter strategies or a more connected experience. Are they trying to cut through the noise and stand out by making every interaction relevant? Or are they simply trying to make every dollar go further by finding and engaging the best audiences? Does the data I possess answer the customers need? Do I need to augment it or fill in gaps to provide a viable product?

What is the value to the customer? Before asking a customer to purchase my data I need to understand what value the data has to that customer. Business customers invest to increase profit so it is incumbent on me to help the customer identify the return he or she can expect for the investment.

How much is the customer willing to pay? Once I’ve quantified the value of my data to my customer I can now estimate what my customer is willing to pay. Which leads to the most important question of all. At this price, can I make an acceptable profit? Assuming the answer to this final question is yes, we’re ready to take the next step.

Define the Strategy & Objectives

Data monetization is much more than just storing and selling the data. Data monetization is about making revenue out of data enablers like insights, outcomes and partnerships. Operationalizing your data monetization strategy calls for having the right business model, the right strategic alliances and the right partners.

The companies that are working on driving sophisticated data as a service business models based on both volumes and values. The win-win business model will be highly influenced by the number of insights business can provide to customers and value those insights can generate for their customers.

The definition of the Strategy & Objectives for selling data is no different than it is for selling any other type of product. The distribution channel needs to be defined, the product needs to be packaged, and the price per package set. For example: Do I initiate the delivery of the data to the customer? Does the customer log into a portal and initiate a download? 

I also need to define the packaging. Does the buyer of my data sign up to receive a data feed or preassembled reports. Is the data delivered on a scheduled basis or when requested?

Finally the pricing needs to be set.

Conclusion

Direct Data Monetization is increasingly becoming a significant business activity for most companies including my IBM Clients.

Selling your data does not have to a painful and drawn out undertaking if you view data itself as the product. By taking your data product to market as a ‘business undertaking’ using a well defined ‘marketing process perspective’, data itself can become one of your company’s most lucrative and profitable revenue streams. By developing a data monetization plan now, you can reap the rewards of the new Data Economy.