OSS

Data Monetization Market

The growth of the global market is driven by continuous rise in enterprises data, technological advancements in big data & analytics solutions, and increase in focus of organizations to generate new revenue streams1. The increase in the volume of data generation and lower cost of data storage has emerged as one of the strongest factors for data monetization tools and services adoption across regions.

“MarketsandMarkets” estimates the global data monetization market size to grow from USD 2.3 billion in 2020 to USD 6.1 billion by 2025, at a Compound Annual Growth Rate (CAGR) of 21.7% during the forecast period. The global data monetization market size was valued at $44,869 million in 2016, and is projected to reach at $370,969 million by 2023, growing at a CAGR of 35.4% from 2017 to 2023.

Data Monetization Industry Players

Companies have realized that data can be used in day-to-day operations to reduce costs and grow revenue. Therefore, we need to analyze some key players in monetization market such as competitive key players in 1010DATA (Advance Communication Corp.), Accenture Plc, Adastra Corporation, Comviva (Tech Mahindra), Infosys Limited, International Business Machines Corporation, Monetize Solutions Inc., Optiva Inc., Paxata Inc. (Datarobot Inc.), Reltio, SAP SE, Thales Group and TIBCO Software Inc.

Data Monetization Overview

Data monetization is the process of using data for generating and increasing revenue. Now-a-days, information is one of the most valuable resources at the disposal of companies. IoT and other digital technologies allow businesses to gather a massive amount of data that offers insights to customer demographics, preferred products and sales performance. There are two primary types of Data Monetization; internal and external data monetization. Internal Data Monetization - An organization's data is used internally, resulting in economic benefit. This is usually the case in organizations using analytics to uncover insights, resulting in improved profit, cost savings or the avoidance of risk. External Data Monetization - Involves using data to extend an organization's product offering with data-driven services or business models to create new revenue streams.

Government & Economic Data

This type of data monetization can empower a range of use cases from data driven governance that drive better budgeting & spending decisions to improving citizen services, for example in banking, retail, etc.

Consumer Transaction Data & Supply Chain

In this type of data monetization, data regarding consumers and their preferences is being collected by various providers such as supply chain-level data being made available by manufacturers to their business consumers as part of the servitization movement.

Geo-Location Data

Geo-Location data monetization utilize satellite imagery data and location specific datasets can provide hitherto hidden visual insights. For example, retail shopping volumes, bank branch usage, and can be used in fraud detection etc.

Machine Generated Time Series Data

This type of data monetization help monitors assets across manufacturing, telcos, energy & utilities, and smart cities.

Social Media Feeds

In this type of data monetization different social media sources like Facebook, Twitter, Telco operators Tube, Pinterest & LinkedIn produce enormous amounts of sentiment data that can be mined to understand and prioritize news events, user opinions & preferences, in most cases these properties monetize on their data assets by selling specialized views of data via APIs.

Corporate Documents

Financial analysis in domains such as investment banking, private equity, auto finance etc. In data monetization, these datasets support a range of use cases that pertain to due diligence on both the buyer side and the seller side.

Curated Datasets

Curated and specialized data monetization datasets are increasingly prevalent in verticals and micro verticals. For instance, algorithmic traders in high finance analyze supply chain data for large manufacturing to understand demand patterns.

Download