/ Why you should monetize your data—and how to get started
Why you should monetize your data—and how to get started
Big data has been a hot topic for a few years now, and it doesn’t look like that’s going to change anytime soon. Everyone from entrepreneurs to enterprise companies are looking to get in on the action.
But one thing that’s been missing from the conversation is how to actually make money off of the massive amount of data that’s being collected out there. Sure, it can be used to improve business practices and get a leg up on the competition, but how do you turn that into practical revenue?
With these problems in mind, we’ve compiled a guide to monetizing your data so that you can start seeing some real financial returns from your big data initiatives.
The first step would be to figure out what big data actually is.
What is big data?
The term “big data” is thrown around a lot, but it’s not always clear what people actually mean by it.
In short, big data refers to the large and ever-growing volume of data that companies are collecting. This can include anything from customer data to website traffic to social media posts.
But simply having a lot of data isn’t the only thing that makes it “big data.” The most important requirement is that these datasets cannot be processed using traditional methods such as spreadsheets and workbooks. Instead, companies need access to big data analytics and processing capabilities to be able to make sense of all their information.
Now let’s take a look at some of the most common uses for this data:
One of the most valuable things that companies can get from their data is customer insights. This includes everything from understanding what products or services people are interested in learning to what drives them to make certain buying decisions.
This information can improve marketing efforts, create more effective product offerings, and even target specific customers with personalized ads. In fact, it’s been estimated that companies who can effectively use customer insights can see a 10-15% increase in profits.
Another key benefit of data collection is using it for product innovation. This includes things like developing new products and services, improving current ones, and even coming up with entirely new business models.
Teams can use data to research customer needs and preferences, track industry trends, and monitor competitor activity. With all of this information at your disposal, you’re in a much better position to innovate and stay ahead of the competition.
Aside from producing insights and innovations, data can also be used for operational efficiency. This includes everything from streamlining business processes and increasing productivity to reducing costs, optimizing resource allocation, and more.
All of this contributes to a better overall customer experience, which is always beneficial for a company’s bottom line.
Finally, one of the most critical benefits of big data analytics is its ability to help with customer retention. This includes identifying at-risk customers, understanding what drives them to leave, and taking corrective action.
In many cases, it’s cheaper and more effective to keep existing customers than to acquire new ones. And with the help of big data, you have the tools you need to do just that.
Moving from reactive to proactive data
Data analytics in companies often moves from reactive to proactive. Reactive behavior is when you only use data to answer specific questions. For example, you might analyze customer data to figure out which products they are buying and how often.
This type of analysis is essential, but it’s limited in what it can tell you. To better understand your customers, you need to be proactive and use data to anticipate their needs.
One way to do this is by using predictive analytics. Predictive analytics is a type of data analysis that uses past data to predict future events. When harnessed for products, companies can use predictive analytics to monetize products before they are even released.
Monetizing your data
Now that you know what big data is and how you can use it, let’s look at how you can begin to monetize it effectively to enhance your business.
First, consider what your business is currently doing with its data. Are you using it to drive decision-making, achieve competitive advantage, or improve efficiencies? Then think about your plans for using that data and how you can turn those insights into value.
1. Save money internally with business intelligence
Business intelligence is an umbrella term for technology that allows organizations to collect, store, process, and analyze data. This includes everything from reporting applications to real-time analytics systems.
Organizations use business intelligence software to understand their customers’ needs better, make more intelligent decisions, increase customer satisfaction, differentiate themselves from competitors, improve operational efficiency, and more.
The beauty of business intelligence is that it can save your organization money on many levels. For example, you can use it to reduce inventory costs, improve marketing campaigns, find new efficiencies in your operations, and more.
2. Provide insights into collected data for customers with embedded dashboards
A dashboard is a graphical interface that presents data in an easy-to-read format. It can be used to show a variety of datasets, including performance data, financial information, customer data and more.
Organizations are using dashboards to provide insights into collected data for their customers and partners. Dashboards can be embedded into external-facing portals, websites, or products to provide a value-add for customers and partners and make sharing and exchanging data simple.
Businesses can also use dashboards to collect feedback from customers and others who use their products. This can include knowing whether there are any problems with the product, new features they’d like to see, which marketing campaigns are most effective, etc.
3. Create new revenue-generating products with predictive analytics
Companies can use predictive analytics to take customer data and find new monetization opportunities for its use. This is done by using predictive algorithms to analyze the data you’ve gathered about your customers’ behavior patterns and preferences.
Then, using this information, businesses can begin to create products that align with what they believe their customers want. These products can then be released before the competition does and increase revenue for the company.
4. Create a tiered access data analytics service
Data permissioning is another way to monetize your data. This type of service would give customers different levels of access to your data, depending on their needs.
For example, a company might offer a basic level of access that would include information such as customer demographics and purchasing behavior.
They might then offer a more detailed level of access that would include data such as what products customers are buying, how much they’re spending and when they’re buying them.
And finally, they might offer an even more detailed level of access that would include customer contact information and social media data. These different access levels give the right information to decision makers at the right time.
Monetization starts with analytics
Before you can begin to monetize your data, you must have a firm grasp on what it is and how you can use it to create value for your organization.
This means having a well-defined data strategy in place and using the right tools (such as business intelligence software) to turn that data into valuable insights.
Once you have these insights, you can begin to think about new ways to use them to create value for your organization.
By utilizing your data with embedded business intelligence software, you can better understand your customers’ needs and create new revenue-generating products. And with predictive analytics, you can use the data you’ve collected to discover new monetization opportunities that will help you in the long run.
Check out some related resources:
Why Every Organization Should Have a Data Relationship with Their Customers
Full Event: Revolutionizing Embedded Analytics
Domo Customer Stories: BI & Analytics
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