Global data monetization market was valued at USD 2.78 billion in 2021, and it is expected to reach a value of USD 10.9 billion by 2028, at a CAGR of 21.54% over the forecast period (2022–2028).

As businesses continue to turn to data to fuel successful operations, monetization of data has emerged as a key focus. Solutions that allow businesses to make the most of their data assets include data insights and consulting, big data analytics, cloud-based solutions, and corporate intelligence. As per SkyQuest’s findings, there are a number of ways businesses can monetize data. Some methods in the global data monetization market include charging for access to data records, selling analytic products or services that use anonymized data, charging for insights into customer behavior derived from big data, and charging for using specialized machine learning algorithms. Here are three ways in which businesses are using data monetization to drive profitability:

1. Data insights and consulting – Through analysis of large sets of information, businesses can identify patterns and trends that may not be apparent when looking at individual pieces of data. This helps industries such as healthcare, retail, and finance identify opportunities and improve operations.

2. Big data analytics – By analyzing massive amounts of data with AI in real time, businesses in the global data monetization market can spot trends and make better decisions faster than ever before. Using techniques such as machine learning and statistical modeling, businesses can identify correlations that might otherwise go unnoticed.

3. Cloud-based solutions – Offering quick delivery times and scalable architecture, cloud-based solutions offer a cost-effective way for businesses to access data whenever and wherever they need it. This is particularly helpful for organizations with a dispersed workforce or limited IT resources.

The report would help Data Monetization market participants in gaining insights about market dynamics, key trends, opportunities, major players, pricing analysis, consumer base, segmental analysis, market data analysis, competitive landscape, and market share analysis, among others.

Marketing Technology News: Voxfeed “Lite” Makes It Easy to Get Social Media Content From Happy Customers

Advertising is the top revenue Garneting Domain Global Data Monetization Market

SkyQuest has published new report. The study found that despite some challenges (such as regulatory uncertainty), especially in terms of removing duplicative information from data sets, there are numerous areas where companies can generate revenue by selling or renting their data. In total, the nine domains investigated accounted for more than $1 trillion in revenues in 2021. In each domain, SkyQuest analysts identified five strategies by which businesses can generate monetizable data.

The top three sources of revenue for data-driven companies in the global data monetization market are advertising (28%), selling customer insights (25%), and selling applications or services powered by the data (21%). However, not all companies are seeing the same levels of profitability from these methods. Advertising is the most profitable path for most companies, generating an average net margin of 33%.

But while selling customer insights is a more lucrative source of revenue for some businesses, it’s less lucrative for others. For example, the net margin for selling customer insights is 20% for those with $5 million in revenue and 5% for those with $1 billion in revenue.

Data monetization market analysis by SkyQuest looks at how data can be used to drive profitable business processes. They offer the following insights:

• There is a huge untapped opportunity for firms to generate revenue from the data they have.
• Businesses must take a data-centric approach in order to capitalize on this opportunity.
• There are different ways organizations can generate revenue from data and there is no one right answer.

Data monetization, a critical component of enterprises’ data management strategies, is growing in importance as businesses grapple with how to create value from their data and figure out how to effectively leverage big data and analytics.

One measure of data monetization efforts is the volume of monetizable data, or the amount of data that could be sold or rented to third parties for use in marketing and other business operations. This topic is addressed by the SkyQuest in a recent study on data monetization market. The study looked at 9 commercial domains in which monetizable data could be generated and examined whether these domains are exhibiting growth rates that support profitable exploitation of large volumes of such data.

SkyQuest has done a detailed study of global data monetization market and has identified current growth opportunities, challenges, top area and their profit margin, revenue generation opportunities, new revenue pockets, top players in the market, market share analysis, competitive landscape, among others.

AI Offers End-less Opportunity for Data Monetization Market

When it comes to data monetization, the sky is really the limit. There are endless opportunities to use artificial intelligence (AI) in order to optimize and improve how data is used for various applications in the global data monetization market. SkyQuest has done a detailed study on how AI is being across different domains for data monetization. Here are three examples of how AI can be used to help optimize data monetization across different industries.

First, consider how AI can be used to improve the efficiency of marketing campaigns. With the help of AI, marketers can quickly identify which marketing messages are resonating with the target audience and adjust their campaigns accordingly. This can save a lot of time and money while still providing the same level of customer engagement.

Second, AI can be used to improve customer experience in the global data monetization market by automating processes that currently rely on human expertise. For example, instead of having customer service personnel manually handle orders, AI could be programmed to process these transactions accordingly. This would save both time and money for companies, while also improving customer satisfaction rates.

Third, AI can be used to optimize business operations in general. For example, AI could be utilized in order to better monitor financial data in order to make strategic decisions concerning future investments. By using this information in conjunction with other data sources, businesses can develop better growth strategies.

One example of how AI is being used to grow revenue is through product recommendation. Large online retailers, such as Amazon, use machine learning algorithms in order to recommend products to customers based on their past purchases. This allows retailers to generate more sales by targeting specific products and customers. Similarly, banks in the data monetization market use AI to detect frauds and other illegal activities. AI can also help analysts identify patterns in customer data that may indicate potential risk.

Another growing sector where AI is transforming data monetization is marketing automation. With marketing automation, companies can automatically send targeted emails and SMS messages to users based on their interactions with the company’s website or app. This saves time and money for marketers, who can instead focus on strategy and execution rather than manual tasks.

Marketing Technology News: MarTech Interview with Max Koziolek — CEO of Spectrm.io