By Jayajit Dash
Data monetization is a powerful tool for businesses, but it can be tricky to get started. With a few simple steps, you can harness the power of data monetization and make sure your business is getting the most out of its resources. Mind you, it’s no small business. The data monetization market valued at $2.1 billion in 2020, is estimated to reach $15.4 billion by 2030. (Business Wire report)
Data monetization starts with understanding what kinds of data are available and how they can be used. It includes everything from customer demographics to market trends and even competitor finances. After you’ve figured out what kind of data your company would benefit from, start collecting it! You can create more targeted marketing campaigns and better products and services by utilizing surveys or other forms that capture user feedback.
Then comes the fun part — turning those numbers into cash! In addition to identifying potential growth opportunities within an industry, companies can also uncover new revenue streams like advertising partnerships or subscription-based services, based on user preferences gleaned from their datasets, with predictive analytics software like IBM Watson Analytics. Combining these insights with traditional marketing tactics like email campaigns and social media outreach can maximize profits without spending too much on research & development.
By leveraging the power of big-data insights, companies can not only increase revenues but also gain an edge over competitors who don’t yet understand how valuable it is! Don’t wait — get started today so that you’re ahead of the game when it comes to leveraging digital assets tomorrow.
Know how to turn your data into money
Data monetization is turning data into cash. Businesses are realizing the value of their data and looking for ways to capitalize on it. So, how do you harness this power? Here’s what you need to know:
Understand your data: Before you can start monetizing your data, you need to know what it contains and how valuable it is. Identify patterns in your current data to generate new revenue streams or improve existing ones.
Identify Potential Customers: If you know what type of information your dataset contains, research potential customers who might want to buy it or use the insights it contains — whether it’s direct sales or licensing agreements with third parties like software companies or marketing agencies looking for specific types of customer intelligence from large data sets like yours!
Develop a Monetization Strategy: Now comes the fun part — turning all those hard-earned insights into cash! Think about different pricing models based on usage, access levels (like full vs. limited), subscription fees, pay-per-view options, etc., so customers have options when choosing the plan that’s right for them. You could also offer consulting services related to interpreting, understanding, and utilizing data sets!
Monitor & Execute: The last step involves executing these strategies and watching them closely — keep track of metrics like customer acquisition rate/conversion rate/ROI etc., so you can compare changes over time! You’ll be able to maximize success with regards to monetizing your company’s valuable assets — its DATA — by doing this!
How have companies monetized data?
1. Targeted Advertising: Companies like Facebook and Google use data to show ads to people based on their interests. By targeting the right people, they can charge higher rates.
2. Personalized services: Companies like Amazon and Netflix use data to personalize their services. It lets them charge more for better service.
3. Predictive analytics: Walmart and UPS use data to predict customer behaviour. They can charge more for better service this way.
4. Brokerage: Organizations such as Acxiom and Experian sell data to other companies. They can monetize data this way.
In the future, data monetization will combine traditional and innovative approaches. To monetize their data, companies will still use subscription fees, advertising, and direct sales. However, we also expect to see more data-driven products and services, like data-as-a-service and data marketplaces. To get more value from their data, companies will also leverage Machine Learning (ML) and Artificial Intelligence (AI). The more valuable data becomes, the more companies will invest in data security and privacy.
(Photo by Firmbee.com on Unsplash)