Telecom & Technology Consulting
In the constant quest to create more revenue streams, companies don’t have to restrict themselves to developing new products or services. They can also leverage the goldmine in their enterprise data.
Most likely, your organization is sitting on a massive, yet untapped, amount of data from both consumers and business activity. That information can be monetized by leveraging it into a new offering that meets a growing market demand. And with IT leaders now being expected to contribute to the bottom line, this is a sales strategy worth pursuing.
There’s nothing complex about developing a line of business that monetizes data. In fact, it entails traditional product development fundamentals: idea development, market research, pricing analysis, and go-to-market plans. As such, simply start by following a sound product development process. Lay out the basics by defining the offering, spelling out the rationale for market need and demand, listing competitors, and conveying your unique value proposition.
Also choose a viable revenue model. Subscription-based models are popular, and are appealing for direct sales to commercial enterprises, research institutions, and government agencies on a local, state, and national level. Other options include data-as-a-service, where you can compile and bundle datasets; insights-as-a-service, where customers receive prescriptive/predictive modeling capabilities; and platform-as-a-service, where subscribers have the freedom to integrate their data into your insights platform. You can also offer embedded analytics – this model allows customers to use data to improve internal operations, enhance customer experiences, and develop individualized product/service options.
After laying out the groundwork and deciding on the revenue model, you’re ready to define the technology required to manage and maintain the data, as well as which technology will enable customers to use your offering.
Of immense importance, however, is ensuring that your data has true, actionable value. You can only monetize data if it provides insights that can’t be accessed from any other source. These insights foster informed decisions. Potential customers will also seek user behavior data, which they can apply for refining their marketing and sales strategies.
Old or non-contextual data doesn’t provide any significant value, so leave that type of information out of your offering. For example, raw traffic statistics that aren’t segmented don’t deliver the personal data required to improve a marketing plan. Indeed, stick to data where insights can easily be transformed into substantial value. Think user behavior patterns, transaction data, and geolocation insights. This type of granular data provides the clearest path to monetization.
As with any new initiative, be aware of potential risks. Data monetization can present challenges, especially for enterprises that don’t typically perform financial transactions. Data inherently presents an enhanced threat of security breaches. Strict security is fundamental – mistakes can lead to massive fines for inappropriate data handling, or not receiving permission and consent from users. Of course, if a data breach leaks to the media, your reputation can be tarnished for years to come. Additional risks include offering data (unintentionally) that’s owned by others, or if the data can’t be integrated across the customer’s network.
View your data monetization effort as an initiative with a future rather than a short-term experiment. In that light, it’s critical to reinvest a certain percentage of revenue into refining your data collection methods, improving security, and refining analytics. Doing so not only creates a higher performing offering, it can enhance the chances of long-term growth and drive competitive advantage. Just like if you created a new product or service.
