Data monetization: Use of data to increase profitability within businesses, either by selling it directly or by utilizing it to optimize processes.

It really is predicted that as 2023 unfolds, more than a third of organizations will be either sellers or buyers of data within online markets like data commerce platforms.
When deciding whether to monetize your company’s data, it’s important to start by exploring the current landscape of data products you are looking to commercialize and how they are being used with existing technologies.
It’s also pertinent to comprehend which industries and use cases your computer data assets can be handy for, and the potential profits on return those customers will obtain with your data.
Direct data monetization involves selling direct access to your computer data to third parties.

First, Customer Interaction increases brand loyalty and improve comments from customers.

Thus, LDVC allows to identify and categorize potential pitfalls and also helps to increase the value of production by forming a global value.
Big Data-driven organizations, that relies on BDVC approaches, generate higher benefits than traditional organizations since, once data is generated, it is usually mined multiple times and for different needs .
This data could be exploited by others in its different forms or built on and exploited often over.
Thus, an increasing amount of organizations are claiming to monetize their data as exchangeable or salable services.
In 2022, there’s been an uptick in the literature on blockchain technology for data monetization as researchers continue to find solutions to resolve the dominance of storage and delivery networks by cloud providers.

• [newline]The most forward-thinking organizations are not only selling non-information products, but additionally selling quality information solutions.
• Data monetization concept consists of using data from a business to create profit.

Internal monetization is normally the initial stage for organizations because they cope with limited organizational and technological resources (Lange et al. 2021).
Common methods involve retailers feature of Sale transaction data to consumer research firms like IQVIA, Kantar, Nielsen, etc.
Given that selling raw data poses privacy concerns and questions contractual obligations, companies are developing alternate revenue streams by selling information from reports and analytics .

Selling analysis This involves selling analysis and restricting usage of the original data.
Considering that data doesn’t change hands, privacy and security concerns are mitigated.
The less versatile usage of the analysis given that buyers cannot combine it with other data sources brings to light questions around value.
Criteria such as data quality and business context relevance also play a crucial role in determining the worthiness of insights (Rix et al. 2021a, b).
Being an all-in-one solution, Analytics-as-a-Service offers the most potential to generate revenue for data providers, but additionally carries the best IT management burden.
Overprovisioning data services access could also result in data breaches and leaked confidential information.