Most companies today have access to an array of data on their supply chains, operations, strategic partners, customers, and competitors. Yet despite this, MIT determined that only 8% of companies monetize their data fully—meaning most companies are leaving money on the table.
With the business world irrevocably changed due to the pandemic, many companies need new avenues for boosting revenue, which is why companies need to assess leveraging their greatest corporate asset—internal data.
5 MOST COMMON FORMS OF DATA MONETIZATION
There are ample opportunities for data monetization, but these five are the most frequently used and applicable across a wide array of organizations and verticals.
INTERNET OF THINGS (IOT)
Millions of smart devices are connected worldwide and are continuously gathering data. This data is an untapped market opportunity for the companies that collect it.
For the information to be valuable, however, it must be organized. Refining the data collected to identify trends or patterns is what makes it a valuable resource. Companies that sell smart device products that monitor useful information—such as energy efficiency or malfunction causes—can also package the data and create a valuable product to be sold to supporting manufacturers or service firms.
SUPPLY CHAIN OPTIMIZATION
Disruptions in the supply chain are costly. Companies such as parts suppliers or logistics firms can monetize actionable supply chain data and analytics gathered at each stage of the supply chain.
This data provides other companies with the ability to evaluate supply chain changes and potential downstream impact. Because minimizing or preventing a supply chain disruption is highly sought after, this data is a valuable commodity.
Pooling is when your company combines its data with a partner to provide a broader, more useful data set.
Leveraging this data happens in one of two ways. First, your organization can use it internally to gain better GTM strategy insights. Second, you can sell the data as an industry insight platform. The benefit of data pools is that they provide a much larger data set for more accurate predictive analytics—most often seen in the healthcare and life sciences (HCLS) and financial services markets.
MONETIZING CUSTOMER DATA
Advertisers routinely seek more effective methods for reaching their target audience. That need means companies can monetize customer data in one of three different ways, each of which can be a valuable revenue source.
- Raw Data: least work, but lower revenue
- Processed Data: cleaned up, revenue increases
- Insights: the most valuable
Different data customers will have different needs and budgets. Understanding that one size does not fit all not only allows your company to monetize your customer data in multiple ways, but expands your prospect pool as well.
The caveat to customer data, of course, is compliance with increasingly stringent privacy laws and regulations. Be aware of the lines that have been drawn for your industry and geographic service areas and do not cross them.
This is likely the most commonly used method of data monetization, where a company leverages internal customer data to optimize products and services. While most organizations use BI tools such as Tableau or Microsoft Power BI, utilizing the data effectively—to strategize, advance the organization, or create a competitive advantage—is rare.
To best use internal data monetization successfully, KPMG cites two categories driving the process.
The first is performance contributors. This data answers the question, “How well are we doing?” Analytics-driven and frequently within an industry-centric context (e.g., Benchmarks), performance contributors are critical to informing strategic decisions.
The second is predictive contributors. Instead of looking at an overall picture of how well you’re doing, this category uses data as a predictive signal within a larger model, creating a more qualitative decision-making process. Examples of this include using weather data to inform retail sales predictions or using IoT-captured driving data to determine car insurance rates.
You must evaluate the data in both of these categories to effectively monetize internal data.
WHAT CAN GOOGLE DO TO HELP?
Google Cloud has successfully helped its customers monetize company data for years. Combining Apigee, Looker, and Google Cloud BigQuery, Google doesn’t merely provide an analytics tool for large data sets—It actively builds an end-to-end solution.
Apigee Analytics alone collects and analyzes a broad spectrum of the data across your APIs, providing visualization tools such as interactive dashboards, custom reports, and more to help identify API proxy performance trends. Customers can then unlock all of this rich content by exporting data from Apigee to Google Cloud Storage or Google Big Query.
By doing so, companies can take advantage of the repository’s built-in and powerful query and machine learning (ML) capabilities. To make implementing and integrating these platforms with your data set even more manageable, Google recently launched a Google Cloud Big Query extension for Apigee.
Apigee works so well that SoftServe recently optimized data monetization for Keller Williams using it. To understand the greatest opportunities and best ways to monetize your data, you must partner with the right team. Click Here to watch our webinar with Keller Williams to learn more about this project.
Let’s talk about which data monetization method meets your needs today.