Interview
The Gist
- Data dual narrative. Data powers businesses by aiding decision-making and spearheading digital transformation, bridging a previously existing gap.
- Data monetization approaches. Strategies like improving work, wrapping products with data experiences, and selling information solutions are revolutionizing industries.
- Building data democracies. Fostering collaboration between data and domain experts is key, creating "purple people" that drive effective data initiatives.
Data monetization can be a game-changer for businesses across industries. And that’s all the way down from the chief marketing officer to the chief information officer.
Data’s everyone’s game. This powerful strategy not only unlocks new revenue streams but also reshapes how organizations approach value creation.
We caught up two data monetization fans and authors: CMSWire Contributor Myles Suer and Leslie Owens, one of the authors of the book, “Data Is Everybody’s Business: The Fundamentals of Data Monetization,” and discussed data monetization and its potential on business outcomes. Myles also wrote about the topic in his recent CMSWire column, "Finally, a Data Book for CMOs Detailing Data Monetization Strategy."
Related Article: Good Customer Data Fuels AI Revolution in Customer Experience Management
The Importance and Dual Narrative of Data in Business
Data has historically served two main purposes in businesses: assisting in decision-making and spearheading digital transformation. Suer emphasized that there's been a gap in understanding how data holistically powers and adds value to businesses. He was particularly drawn to the book because it seemed to bridge this gap, providing insights into ensuring that data initiatives truly bear fruit.
“We've all known that data is critical to a business,” Suer said. “But it seems to have had two different stories. It had a story that had to do with how do you make better decisions. And then it has a story over here, which was about digital transformation. And nobody has really looked at it exhaustively in terms of how does data power the business? What are the things that you should do in order to make sure that if you're doing a data initiative, it's actually going to have value on the other side. And so that was what was really exciting to me about this book.
Related Article: Finally, a Data Book for CMOs Detailing Data Monetization Strategy
Data Monetization Approaches
Owens detailed the three primary strategies for monetizing data: improving work, wrapping products with data-fueled experience and directly selling information solutions. She clarified that these strategies aren't necessarily linear and can be adopted based on specific industry needs and challenges.
“And I think something new that our book offers is that we capture all three of those approaches under this umbrella of data monetization,” Owens said. “And I think a lot of people come into the book, or I'm assuming some readers might come into the book, thinking data monetization is selling data. But what we're offering is a framework that's helping them say, ‘Oh, we're doing a little bit of this or a little bit of that.’”
For example:
- Industry commodification: If a company operates in an industry where products or services have become undifferentiated (commodified), making it challenging to stand out, Owens suggests focusing on the "wrapping" strategy. This entails enhancing products with data-driven features or experiences. Since today's world is interconnected with smart devices, businesses should leverage data to offer unique, delightful customer experiences. By doing so, they can potentially justify raising the prices of their products, thereby deriving and actualizing value from the data.
- Special datasets: If a company possesses a unique and valuable dataset that potential partners might be interested in purchasing, they could focus on the "selling" strategy of data monetization. This involves selling access to or insights from that specific data.
- Non-linear approach: Owens emphasizes that the journey of data monetization is not a fixed sequence. A company doesn't necessarily have to start with the "improving" strategy, then move to "wrapping," and finally to "selling." Instead, depending on its industry and specific situation, a company might adopt one, two, or all three strategies simultaneously. The choice of strategy is flexible and varies across different industries.
Related Article: Customer Data Management Is the Key to Consumer Trust, Profitability
Role of CMOs and Marketing Departments in Data Utilization
Suer highlighted the significance of the "wrapping" approach, especially for chief marketing officers. By enhancing products or services with data-driven experiences, businesses can significantly elevate customer engagement.
He pointed out that marketing departments have been traditionally data-savvy. However, the current challenge lies in harnessing data's full potential, especially in personalizing customer experiences. The essence of good marketing today, as illustrated by Suer with examples like Amazon, is the ability to use data to tailor experiences, ensuring customers see products or services most relevant to them.
“I think this is an opportunity for a marketing person to think about, well, what is the CIO doing? What's relevant to me?” Suer said. “And holistically, how do I make sure that there's value on the other end for the business? So I think it's an opportunity for CMOs to get closer to digitally-savvy CIOs and help them drive the agenda.”
Related Article: Should the CMO and CIO Be Best Friends?
Building a Data Democracy and Bridging Data With Domain
Owens introduced the concept of "data democracy," emphasizing the importance of fostering collaboration between data experts and domain experts. By breaking down organizational silos, businesses can drive more effective data initiatives.
“A lot of people struggle with the language problem,” Owens said. “Data experts are in one camp and domain experts, maybe that would be the marketers, but also sales operations, product managers, etc…they don't have that bridge. And so we address that in the book and talk through ways to connect data and domain people."
Innovation could be in one pocket of the company. You want it to grow, and there are different diffusion mechanisms you can use. Or maybe you're trying to stimulate innovation in the first place, she said. "People feel locked up and don't feel free or maybe they don't think their data is ready," Owens added. "So we talk through how to unleash and motivate people to participate in this thing we call a data democracy.”
Suer and Owens discussed the idea of "purple people,” individuals who seamlessly blend expertise from the realms of data and domain. These are the linchpins in creating a successful data-driven organization.
“And the idea is that if the data people are red, and your people are blue, and that if you get them intermixing, you're going to create a purple population,” Suer said. “And really good data democracy (organizations) have high purple populations.”
Related Article: The Role of Data Privacy in Customer Trust and Brand Loyalty
Practical Implementation and Challenges of Data Initiatives
Owens shared insights on common challenges faced by businesses when trying to implement data initiatives, such as trust issues with data, accessibility challenges and governance concerns. The book offers strategies to address these challenges, such as creating cross-functional teams to handle data and building data assets that can be trusted and reused.
Suer shared an anecdote about a friend in the life sciences sector who demonstrated how starting with a single group and allowing practices to organically expand can lead to broader organizational buy-in and success with data initiatives.
“The way he succeeded in introducing things like data catalogs, was he got the group that was the most analytical to start using data,” Suer said. “And then they started talking to other groups, and then it organically spread. But he started with one group, and made them purple as can be used, and the rest of the organization started, then he got a promotion to running everything for the entire organization has to do with data.”
Conclusion: Aligning Data Strategies With Business Goals
Owens emphasized the need to align data monetization strategies with overarching business goals. Citing Microsoft as an example, she illustrated how CEOs setting clear directions can help individual departments align their data initiatives accordingly, ensuring cohesive progress toward shared organizational objectives.
Ultimately, Suer and Owens contend the realm of data monetization offers unprecedented opportunities for businesses willing to embrace its potential. As industries continue to evolve, those that leverage data as a strategic asset are intrinsically tied to effective data monetization.
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“And so you can align the different work you're doing around data with these high-level priorities that maybe even the C-suite keeps bringing down and saying, 'This is what we're about right now. Guys, we are marching in this direction,'” Owens said. “Well, you want your thing to match what the direction is from the CEO. We tell a story about Microsoft in the book, a case study around how effective it was to have the CEO describe a services-oriented transformation. And then people knew that what they needed to do was their data monetization initiatives need to add value to that outcome that Satya Nadella was seeking.”
