Three steps to data monetization
The amount of data available globally grows each day and so does the challenge to monetize data. It is estimated that by 2025, Data would have increased ten fold and real time data would make up 25% of it. Such data will require much more sophisticated processes and systems to adequately capture and utilize them.
Strategies for approaching data monetization
A lot of the questions we get asked at imonetize revolves around how to leverage “dead data” value. Before we get into this, we’d like to say again that data monetization involves the collection and use of data to gain insights on how to deliver services that provide users with more value or to create products that generate revenue. Just as value implies, data monetization is more than transferring and selling data and it’s assets, rather top data monetization strategies focus on indirect and direct strategies. Indirect strategies include things like using data to drive cross selling, improving customer experiences, and or performance while a direct strategy could include collaborating with outside partners to create new sources of revenue.
Data volumes continue to grow and so companies are also finding more creative ways to make use of their data. Retailers use their customers’ purchase history to target them with marketing for similar or complementary products, manufacturers use weather patterns to better their logistics and supply chain activity and so much more. Data provides endless opportunities for its users and what’s great is that you do not need to work magic to tap into the gold that data presents. All you need to do is master these three fast and easy to implement strategies.
Identify your data
To begin monetization, you need to identify relevant data. Doing this is usually a simple process however it can be a hard thing to do for some organizations. As many as 63% of companies do not have a data governance or management strategy or in some cases, they have too many strategies being implemented in multiple parts of the company. Only a shocking 2% of companies have solid and centralized strategies for data management and 35% mix centralization and fragmentation. When there’s no data governance in place, it can be quite hard for organizations to understand just how much value their data has. In larger organizations determining the amount of available data alone could result in cross sections between departments. Each team may have their own tools which could contribute to making collating their companies data much more difficult.
What then are the best ways to identify data? Organizations can start by documenting their current data landscape taking note of what data they have, where it is stored in the organization, it’s quality and what tools and systems it is associated with. In cases of decentralized data with no governance in place, you can design and put one in place as you go about your data monetization efforts. Upon the proper examination of internal data landscapes, the external factors like data use cases and market trends should also be taken note of. You should also pay close attention to those factors that already provide value to the organization like customers and suppliers. This can introduce new ways of using or combining “dead data” with datasets that have value in significant levels.
After data has been correctly identified, monetization initiatives should be developed for every dataset. Monetization initiatives cover anything that has data as its major component. Some examples of this are;
Developing a new product or service
- Selling raw data
- Boosting operational efficiency
- Growing your analytics capabilities for both external and internal use.
In the process of developing your initiatives, there are two questions that must be answered
- Does your data solve a problem?
- Is solving the problem valuable?
These questions should also be about the direct monetary value you’ll get from monetization such as saving costs and generating revenue. There are also indirect benefits like improved operations, better publicity, higher employee satisfaction and more. What every organization finds more valuable may be different so it’s helpful to have a custom framework for evaluation that includes the objectives, priorities and risks your business faces. With a framework that duly captures your criteria, you’ll enable your company to better assess its initiatives and cut down to ideas that would actually work. Estimating the amount of value your data has will be quite challenging even with a great framework in place. As a first time data monetization company, you may be shocked at your lack of expertise in estimating the value of data. However this is a normal thing for first timers. With the help of a third party group such as imonetize, you can easily assess and add value to a company’s data set. In the end you’ll get a solid data list that shows whether or not you should go ahead with data monetization.
The last step of the monetization process is to create a market plan for all of your data opportunities. At this stage you should carefully consider the important details like which segment of customers you should target, the kind of marketing to use and what channels would be best to use them on. All ideas presented in this phase should be closely looked at and vetted before implementing so that any areas of internal capabilities are built on while areas in the external environment use their expertise to implement. This can be found mostly with organizations that do not have a data governance strategy and would benefit the most from it. Using a powerful go to market strategy, any organization can begin to use and monetize its “dead data”