When it comes to talking about Big Data and analytics, the most popular conversations always seem to come down to dollars and sense. This is logical since Big Data often requires big investments. As such, quantifying the financial gains associated with these investments is paramount for any sort of decision-making.
In fact, my earlier blog looked at the idea of directly attaching a dollar value to the time that data analysts spend doing data preparation activities. Our rough estimate shows that investing in superior data preparation solutions likely saves an organization somewhere around ~$22,000 a year for each data analyst they invest in.
Anyone compelled by those numbers would do well to note that there are many arguments that follow a similar logic showing how better analytics can be applied to areas such as reducing customer churn, creating better advertising, and optimizing prices. However, while this is all well and good, using data analysis for lowering costs and squeezing higher margins is only a piece of the puzzle.
Borrowing from the logic of Justin Timberlake’s role as Sean Parker in The Social Network – I pose this question to our audience:
Using data to save money isn’t cool. Do you know what’s cool?
Using your data to make money.
The term “Data Monetization” has been bubbling its way into the conversation and is just starting to achieve the critical mass necessary to break into the mainstream. Part of what has dogged the term in the past is the assumption that data monetization implies directly selling your data. Whether for privacy, compliance, or competitive reasons, this proposition was quick to raise eyebrows – but it shouldn’t.
This is because, at its core, data monetization is really about taking an underutilized asset and making it work for you. It is about taking all of your investments in collecting, curating, and analyzing data and turning them into a profit center. Data monetization can be as simple as repackaging existing data or it can be a more complex process of enriching existing data with outside data sources and providing a value-added synthesis.
Data monetization in itself is not new. Companies such as Dun & Bradstreet, Experian, and (the previously alluded-to) Facebook have been doing this for as long as they have been around. But, what has changed is the opportunity for just about any company to get in on the action. The digital exhaust of doing business is extensive. Whether it is logs of customer behavior, easy access to third party data sources, or signals from machine sensors – these data sources are an insight goldmine for those who know where to dig.
Last year, we at Blue Hill Research published a jumpstart guide to how businesses should begin thinking about data monetization. In the paper, we lay out how organizations should begin by auditing their existing data assets and defining the persona they are hoping to sell to.
Once you identify your goal, the next step is to assess how your organization should executive on the vision and what tools you will need to do so. Certainly, existing internal tools may do the trick, but there is an array of specialized vendors designed to specifically address data monetization objectives. Blue Hill Research notes three companies of particular interest because of their novel approach and the emphasis of data monetization within their go-to-market strategy: GoodData, Juice Analytics, and 1010Data.
For its part, GoodData has been leading the charge in pushing data monetization in everything from their Make Money Summits to aggressive investments in building revenue generation strategies for their customers. GoodData has long pushed its embeddable and white-labeling capabilities as a means for organizations to distribute their data to a range of external third parties and as a means of providing data-enabled service offerings on top of existing products.
In a similar vein, Juice Analytics has made the pivot from a pure-play data visualization provider to focusing on building data products. Juice Analytics specializes in offering solutions with customer-ready interfaces already built in and on helping organizations curate existing data assets to drive net-new revenue generation. As with GoodData, these offerings are made with the assumption that insights will be disseminated as products to a large number (sometimes in the thousands) of external users and will need to fit into the end consumer’s existing workflow or user experience.
1010data takes a novel approach to helping their customers monetize their data through enabling direct data sharing. This means organizations can make available gigantic portions of their data to share with other organizations through customizing access, permissions, and usage rights within the 1010data platform. This has particular appeal for organizations looking to make customers out of organizations within their industry vertical’s value chain. For instance, a retailer can create a lucrative business by selling point of sale data about particular products back to the product producer, or a supplier may find an eager customer in a manufacturer hoping for access to inventory or production data so that they can make real-time production adjustments.
Whatever the case may be, data’s role in the enterprise is again morphing to provide additional layers of value. Data is shifting from being a tool for business optimization into an avenue for net-new revenue generation as well. As more businesses begin to take this approach, expect the conversation around data monetization to heat up.