How Organizations Can Improve Data Monetization With Big Data, IoT, and Blockchain


How Organizations Can Improve Data Monetization With Big Data, IoT, and Blockchain

Businesses can leverage the power of big data, the Internet of Things, and blockchain to improve the monetization of their data.

Several organizations can monetize their data to increase their revenue. In data monetization, blockchain can be a major contributor due to its advanced applications and decentralized nature.

The Fourth Industrial Revolution led to the emergence of data-driven business models. Organizations collect large volumes of data from every department using modern technologies such as Big Data and IoT. Every organization has realized that data is an asset and uses critical data in multiple applications. However, many start-ups and small businesses lack access to the infrastructure and resources to collect and analyze crucial data. To solve this problem, well-established organizations can implement data monetization to sell relevant data to future businesses. With this approach, data vendors can generate new sources of revenue for their business. Several sources suggest that data monetization is a necessity for businesses. Through data monetization, multiple organizations can help create a market for sharing critical data. These markets can democratize data collection and analysis. Therefore, small and medium-sized businesses and startups can easily tackle the cold start problem. In addition, large players can also benefit from data monetization, as their data collection and analysis tasks will be simplified while expanding their business in different industries.


To accelerate data collection and analysis, organizations can deploy modern technologies such as Big Data and IoT. These technologies can help collect and analyze data in the following ways:

How can organizations collect and analyze data?

Big data

Every online activity and every business process generates a large volume of data. Organizations can collect various types of historical and real-time data such as customer data, social media data, employee data, and operational data. Businesses can analyze this data to gain insight into their customer demographics, employee performance, and business operations. Big Data can process large volumes of data at high speed to generate precise results. Hence, big data can be used in various industrial sectors such as healthcare, retail, finance, manufacturing and many more. For example, in retail, organizations can collect customer details and social media comments to generate personalized marketing campaigns for specific customer demographics. Using big data, organizations can analyze large sets of data from different sources to generate complex data models. Using these data models, business leaders can predict upcoming market trends and develop strategies to adapt to those trends. These strategies include concrete steps to meet inventory, production, marketing and sales needs. Additionally, organizations use big data analytics to make product launch and pricing decisions.


Several organizations and smart cities have deployed IoT devices for multiple applications. For example, manufacturing organizations can install IoT sensors to monitor the production flow, from the refining process to final procedures such as packaging, in real time. These advanced applications have led to the increasing adoption of IoT devices. In addition to big data, organizations can use IoT data to achieve more precise results. Analyzing this data helps organizations measure and understand various business procedures. For example, in retail stores, IoT sensors can be installed in shelves to notify the store owner when products are sold out. The sensors can collect data that can help the store owner understand which product is in high demand, what time the shelves are emptying, and on which days customers are buying the most products. Using this information, the store owner can make key decisions regarding inventory management, product orders, and discounts.


To implement data monetization and increase revenue, business leaders need to create an effective strategy. Business leaders can consider the following steps in their strategy:

Recognize different types of data and their use cases

Organizations can collect different types of data from different sources such as social media, IoT devices, the cloud, and the web. Each organization specializes in collecting specific types of data. For example, healthcare organizations collect data on patients, doctors, conditions, treatments, medications, and hospitals. To sum up, business leaders need to ask important questions such as

  • What kind of data does the organization collect?
  • What kind of ideas can be drawn from the data collected?

Using these questions, business leaders can identify innovative use cases for the data collected. Using the example above, the data collected by healthcare organizations can be used by pharmaceutical companies to understand which drugs are in demand and plan production and inventory requirements. Business leaders need to identify all possible use cases for their data to maximize their data monetization revenue. Additionally, organizations should ensure that they share anonymized data to avoid privacy breaches.

Identify potential buyers

After recognizing all possible use cases for the accumulated data, organizations should segment their collected data according to various use cases. Based on the use cases, organizations can identify potential buyers for their data. These buyers can be start-ups or other well-established organizations. For example, retailers gather a lot of customer data that can be beneficial to other organizations in the manufacturing industry for use cases such as improving product quality by analyzing customer demographics and their business models. purchase.

Interested buyers can also be large players who plan to expand their business into different industries. These organizations may wish to simplify data collection and analysis tasks and focus more on mergers and acquisitions in their target market. For example, if an electronics manufacturer is considering entering the telecommunications market, the organization may purchase critical data from a telecommunications company to accelerate its expansion. Therefore, organizations should be aware of the use cases for their data and how the data can benefit multiple organizations. Once business leaders have identified their potential buyers, they have a key decision to make. Business leaders must decide whether they would sell data through a blockchain-based data monetization company or independently.

Select an appropriate blockchain-based data monetization company

Blockchain has the potential to democratize monetization and data sharing. Looking at this potential, several entrepreneurs have created blockchain companies specializing in data monetization. These companies allow organizations to buy and sell data collected using IoT sensors, Big Data, and VR / AR. Therefore, business leaders need to identify the type of data they can provide. To select the most suitable blockchain-based data monetization company, business leaders should research various companies, the type of data they monetize, the services they offer, and their costs. After finding the most suitable blockchain-based data monetization companies, business leaders can decide which company they want to do business with, based on their budget.

Implement data monetization independently

Organizations can also monetize their data independently. To this end, business leaders need to hire professionals with niche skills. Next, organizations need to embrace blockchain networks for data exchange and storage. Decentralized blockchain networks will record every instance of data exchange and encrypt all data.

For blockchain-based storage, organizations can deploy various secure blockchain wallets. Organizations can store different types of data from multiple sources in different portfolios to separate large volumes of data. These blockchain wallets are encrypted and use a secure authentication mechanism to restrict access to data. Using these portfolios, organizations can share data with potential buyers. Additionally, organizations can use smart contracts to verify their buyers’ credentials and documents, receive payments, and automatically share relevant data. With this approach, organizations can implement a self-sustaining data monetization process.

With the help of blockchain, data monetization will soon be available to consumers. Through blockchain-based data monetization, consumers can monetize and trade the value of their data. Additionally, consumers can control what data can be collected by organizations to ensure data security and privacy.

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