Monetizing Your Data
Data can be prepared, packaged, and sold as data products within an organization to businesses that want to establish data-sharing partnerships or other external customers.
What Is Data Monetization?
While monetizing data isn’t a new concept, it’s only in recent years that it’s gained notoriety. In its most basic definition, data monetization is the process of producing and selling data for economic benefit. Data can be sold directly to those looking to acquire it—both internally within an organization and externally to customers—or indirectly to other businesses that seek to share this information in partnership with one another.
Data monetization strategy
An infinite amount of data is being produced daily, yet data-producing organizations remain uncertain whether they can—or should—commercialize their data sets to take advantage of untapped opportunities in a market that’s expected to reach $13.46 Billion USD by 2030. Although many business leaders recognize that data monetization leads to generating more revenue and safeguarding against times of economic uncertainty, a few barriers to entry prevent organizations from monetizing their data and unlocking potentially significant financial value.
Emerging technologies such as artificial intelligence and predictive analytics platforms have pushed data science to the forefront of business decision-making, with the COVID-19 pandemic accelerating this trajectory. The adoption of data monetization solutions has grown recently, partly due to the increasing need for enterprises to diversify their portfolio, streamline the customer experience, and source new growth opportunities to ensure a steady influx of revenue during periods of market volatility.
Well-constructed data monetization strategies can assure companies maximize the value of the data they produce.
Benefits of data monetization as a business strategy
AI and Machine Learning
Businesses that use AI, predictive analytics, machine learning, and other smart technologies need data to accelerate the usefulness of these technologies.
Diversify company portfolio
Economic downturns pushed companies to explore options to diversify their portfolios to generate more revenue and safeguard against economic uncertainty. With few barriers to entry, data monetization is an attractive option.
Source new growth opportunities
Data monetization can unlock insights that help companies tap into growth opportunities like new products, partnerships, and new data-related service approaches.
Gain an advantage over competitors
Data monetization strategies that are well-thought-out and executed can help you get a leg up on your competitors through increased process efficiencies, a streamlined customer experience, and more.
Getting the right technology behind data monetization
For most organizations, data monetization isn’t their core business, so they opt to use data marketplaces to sell their data. But using marketplaces as a single marketing source comes with a problem. Data marketplaces are controlled by a single operator, who is usually a cloud provider. This limits a company’s ability to display custom products and test different listings. Getting the right technology in place to distribute monetized data makes data discovery, marketing, and dissemination significantly smoother.
Creating data products with a streamlined process
As a business leader in your data-producing organization, it’s important to understand how a data product is created and delivered to the end user for consumption to ensure its commercial viability.
The process of transforming raw data into data products is part of a process called “the data supply chain”, which includes four distinct steps: manufacture, package, market and sell, and distribute (MPSD).
The first stage of the data supply chain turns prepared data into data products. More often than not, raw data needs to be transformed into another format before it can be considered usable. Data preparation can involve cleaning, restructuring, aggregating, or splitting data up into more granular forms before it is packaged.
Data discoverability, pricing, and access rights are determined during this stage. The most successful data producers always keep the end-user in mind when making important decisions on how to package their data. By lowering any barriers to entry for the end-user, the producer can control how the buyer will find the data, evaluate its worth and access it after making a purchase.
What criteria do data buyers use to determine whether they should purchase a data set?
While there’s no concrete set of criteria that is applicable to all data buyers and their individual use cases, there are four benchmarks that data buyers commonly use to evaluate whether they should move forward with purchasing a particular data set from one provider against another.
- Availability - What restrictions are there in finding and accessing the data set?
- Volume - How much data is made available within a particular data product—is it too vast or too niche?
- Veracity - Is the data clean, accurate, and of high quality?
- Variety - What are the available formats of the data?
The importance of data productization
Productizing data is arguably one of the most important yet difficult areas of the supply chain to get right. A provider must readily make the purpose of the data product, its guidelines, value, and usage available to the consumer in order to streamline the decision-making process.
Market and Sell
Data products and services are now ready to be marketed, but for most organizations, data monetization isn’t their core business. Many companies opt to use data marketplaces as a means to sell their data, but using marketplaces as a standalone marketing engine poses its own set of problems. For one, every marketplace is controlled by a single operator, usually a cloud provider. This limits the provider’s ability to display custom products and test different listings. Getting the right technology in place can make monetized data a significantly smoother process for discovery, marketing, and data dissemination purposes.
Tip: We suggest leveraging data marketplaces and web stores to maximize your potential market reach. Our Chief Product Officer covers how using the combination of marketplaces and data web stores facilitates an environment to mobilize data.
At this point, and with the right technological means, the data should be delivered from the provider’s ecosystem—AWS S3, Snowflake, Databricks, etc.—to the customer’s ecosystem via servers and downloads, cloud access, dashboards, scripts, and more. This can be achieved in various ways, including SFTP, API, cloud delivery, and Queryable API solutions through a platform like the Revelate Data Web Store, which connects multiple data sources to a centralized place in a secure manner. The technology should enable the end-user to access the data they need the way they want.
Licensing in data monetization business models
Did you know… In a 2017 survey by McKinsey that garnered responses from over 500 executives and senior managers, 70% of respondents reported that data and analytics had caused moderate-to-significant changes in their industries’ competitive landscape. The most common change was the launch of new data-focused businesses that undermined traditional business models.
As enterprises form their data monetization strategy, many are using licensing as a means to distribute proprietary data while maintaining full ownership over its usage. Companies that produce data are generating data irrespective of whether they’re selling it or not. Adopting a licensing model allows the data producers to create the data once and sell it indefinitely (or for however long they see fit). If users see value in the data, they’ll likely purchase it.
Licensing also provides a way to get recurring revenue for monetized assets: users can ‘repurchase’ the data via ongoing subscriptions. Business leaders of
data-producing organizations use licensing to create a ‘stickiness’, resulting in longer-lasting relationships with their customers.
Resource: If you’re figuring out how to build a data monetization strategy, we’ve created a concise step-by-step guide on going to market with your data products.
IT resource allocation for data monetization
IT teams usually play a pivotal role in big data monetization. After all, IT is likely the department that will be establishing controls, upholding governance standards, and fulfilling data requests. In addition, IT teams provide administrative support for onboarding and maintenance of new systems, which, unfortunately, can quickly become a time-consuming task that isn’t easily scaled as the business grows, especially if it uses legacy tools and is generating a significant amount of data daily.
Many organizations allocate IT resources with the knowledge and necessary skill set to execute specific tasks such as correctly productizing data or integration, which might require an advanced level of coding. The best way to alleviate the burden IT teams can face is to ensure that there’s a centralized monetization system that is capable of aggregating different data sources. With one system to learn and maintain, it’ll likely lower the total cost of ownership.
How data monetization future-proofs your business
COVID-19 became an accelerator for enterprise executives searching for new ways to future-proof their organizations. One of the ways a company can be future-proof is by commercializing its data.
Although there are numerous benefits, here are a few key areas that contribute to the long-term sustainability of a business that monetizes data:
Generating new revenue streams
New income sources can come in several ways. For example, depending on how granular or substantial the data product can be and how they’re delivered, producers can sell the same product in various ways to appeal to different parts of the market. Income can also come from listing on data marketplaces or partner exchanges. Moreover, in addition to selling data, companies are now expanding their data offering to include data analysis services as well.
Staying ahead of the competition
Every company wants to know how to stand out from the competition, and monetized data can be a differentiating factor. For instance, if an organization directly addresses and appeals to the end user's preferences, needs, and requirements, they’re likely to gain a competitive advantage in the market because they have simplified data discovery, procurement, and access for the buyer, speeding up their time to insight.
Enriching the customer experience
By harnessing the power of data monetization and leveraging other technologies such as predictive analytics tools, organizations can be empowered to streamline the customer experience, even in changing markets. Creating more comprehensive customer profiles and understanding customer needs at all times allows the business to shape or enhance a customer’s journey with the ultimate goal of increasing profits and reducing churn.
Data monetization can provide significant benefits to organizations that want to fully utilize the value of the data they generate. Commercialized data is an indispensable asset, provided it is manufactured, packaged, marketed, and distributed correctly to create one or more steady income streams. However, like most technologies, businesses must have the right tools, processes, and resources to take advantage of the vast amount of untapped opportunities in the data monetization space.