CEO Perspective: Moving Data Analytics from Cost Center to Revenue Generator
How can you move data analytics from being a cost center to become a revenue generator? Roman Stanek, CEO of GoodData, explains how this transformation drives business growth.
- By James E. Powell
- October 5, 2020
Upside: Organizations increasingly recognize that data is one of their most valuable assets. Now they’re beginning to realize that they can monetize their data assets to get even more value from them. What do you mean by monetization?
Roman Stanek: Monetization means creating new revenue streams from the data that companies collect. For years, data analytics has been a cost center, an investment companies make to wring insights from data. Now, we’re moving to the next phase: where data becomes a revenue generator.
A great example of a company that does this very well is a GoodData customer called Zalando. A leading online platform for fashion and lifestyle in Europe, Zalando captures data from over 300 million monthly visits to their website and uses that to help its brand partners better understand their consumers and their changing preferences. By doing so, the brand partners are able to drive stronger revenue (data monetization) and Zalando proves itself as a crucial partner to the brand.
What do you mean when you say data monetization is a continuum?
Every company wants to become a data company. Actually becoming one requires a company to take on the mindset that data monetization is a continuum. The very first step is to prioritize data input. This means the data must be high quality, timely, in compliance with privacy and security needs, and thus able to inform insights-driven decision making. Monetizing data needs to build on the previous step before moving along the continuum in which businesses extend data monetization opportunities to their networks, helping create new revenue opportunities or strengthening previous ones.
How do you determine where your organization is along this continuum?
Benchmarking your organization is a terrific first step. At GoodData we start by understanding what data an organization collects. Next, we try to understand what they do with it. Only then can we go into the third step, which is to lay out the vision of how to monetize it in a way that protects consumer privacy, before finally executing on this plan.
What tools and processes do you need to move your organization along that continuum?
As I said earlier, before you invest in tools and processes, you need to understand where your company is benchmarking. We like to start by ensuring that companies have a good understanding of where they fall in our data maturity assessment model. This means knowing their data capabilities, educating their employees, identifying gaps, and comparing their progress to industry peers. Only then does moving into a discussion on tools and processes work.
What data should you consider monetizing? That is, what data assets provide the greatest reward?
When deciding what data to monetize, think about what your customers need and want, and what will produce the greatest impact to their business. If your customers tell you what they want, that makes your decision on what to monetize that much easier.
One of GoodData’s customers, TownNews, provides a good example. TownNews is a leading provider of content management systems and platforms for local media organizations in the U.S. It uses GoodData technology for its Data Insights product to give TownNews’ media customers new tools for gathering, understanding, and acting upon the multitude of data that impacts their businesses. For instance, Data Insights makes it easier for those media outlets to draw connections between their core business products -- videos, articles, and other content -- and the revenue that's generated from those products.
Several Data Insight customers quickly discovered, via the data, that they weren’t getting the optimal advertising revenue. Data to optimize advertising revenue is a great example of what a media outlet would want from TownNews’ product.
With all the new privacy and security regulations enterprises must heed, what data security considerations must your enterprise take into account before you decide to monetize your data assets?
Protecting consumer privacy does not come at the cost of revenue. Consumer privacy must be your number one priority. Aggregated data, with a focus on higher-level trends and insights, is not a second-class citizen. In fact, it is incredibly powerful and can move the needle in the revenue goals of any company. The key things to pay attention to are removing all personal and identifiable information and securing all data.
What are the biggest mistakes enterprises make when beginning to monetize their data? What best practices can you recommend to avoid these problems?
The biggest mistake is that they don’t first understand their customer needs. They need to start with that and ask how data can tie back to their customer’s revenue, growth, and customer experience goals. Then the question becomes whether what they want to do is feasible and how to do it.
About the Author
James E. Powell is the editorial director of TDWI, including research reports, the Business Intelligence Journal, and Upside newsletter. You can contact him
via email here.