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Information service providers (ISPs) monetize information by utilizing their knowledge and expertise to create valuable publications.
These publications cater to the demands of a wide range of consumers, including institutions, organizations, professionals, students, and the public. Generally, consumers can access these publications through paid subscriptions on digital content delivery platforms.
Most ISPs don’t take advantage of the data available to them because data privacy concerns have hindered the exploration of such information. Using this data to create new business opportunities is impacted by regulations surrounding personally identifiable information (PII). While data privacy laws like the EU’s General Data Protection Regulation (GDPR) are essential for protecting consumer information, they make it difficult for businesses to use the data they have collected.
Companies need to explore innovative and intelligent data monetization solutions to share this data with ecosystem partners and across geographies. We explore how to use fragmented data and monetize it.
We propose an AI-powered tool that analyzes anonymized data of content users and generates personas based on four criteria: subscriptions, consumption, behavior, and search. This tool creates a replicable way to recommend options for cross-selling and up-selling data. It also analyzes new publications using natural language processing (NLP) to estimate their potential user demand and popularity. With this estimated data, editorial and marketing teams can make intelligent, strategic decisions about the pricing for new publications.
Defining data monetization
Organizations are looking to leverage data to obtain quantifiable economic benefits.
We define data monetization as generating revenue from available data sources or real-time streamed data through the discovery, capture, storage, analysis, dissemination, and use of information. Companies can leverage information collected through business operations, individual social media or customer interactions, electronic devices, and sensors to gather valuable insights for future strategies.
Direct data monetization includes directly generating revenue from the sale of raw data produced from company analysis, data trade, and the creation of APIs. Indirect data monetization consists of the usage of collected data to reduce costs, improve productivity, develop new products or services, or discover potential markets.
The data monetization market
In 2020, the global data monetization market was valued at $2.1 billion and is projected to reach $15.4 billion by 2030.
This exponential growth trajectory represents an estimated 22.1% CAGR over a period of ten years. The growth in this sector is due to the consistent rise in enterprise data, technological advancements in big data and analytics solutions, and an increased focus on generating new revenue streams. Notably, the telecom industry has been reaping the fruits of the data monetization expansion. In 2021, North America was the largest region in terms of data monetization in the telecom market. Data monetization in the telecom market is segmented by components like tools and services; by data types like customer data, product data, financial data, and supplier data; by the size of the organization such as small and medium-sized enterprises (SMEs) or large enterprises; and by deployment types like on-premises, cloud. Corporations experiencing optimum growth and performance have adopted data monetization as an essential part of their strategy.