3 Key Ways to Monetize Your Data
11 August 2021
I’ve written a book on data strategy, and one of my primary jobs is guiding businesses through the process of using their data effectively.
One of the most common questions my clients ask me is “We have all this data. How do we monetize it?”
In this post, I’m going to break down the three primary ways you can monetize data to drive business performance.
Better Insights with Data
The first way I recommend companies monetize data is by using it to understand market trends and shifting customer demands. Data is a highly useful tool for discovering what customers want now, and what they will want in the future.
Looking at customer data on an ongoing basis enables you to create better, more relevant, more personalized products and services, which in turn drives revenue for your company.
Using this strategy for monetizing data is a great long-term move for your company, because your responsiveness establishes customer loyalty, which in turn increases the lifetime value of each customer.
Using Data to Cut Costs
You can also use data to streamline your operations and reduce business expenses.
Use data to optimize processes, automate jobs with AI, reduce transportation and logistics expenses, eliminate marketing costs, and more. Examine your data to identify where you might be able to use it to make your company more effective and efficient, and increase your profits.
Selling or Renting Your Data
When clients ask me about how to monetize their data, selling or renting the data to outside parties is typically what they’re thinking of.
A company's data is becoming increasingly important as an asset in its own right. When a company is valued in preparation for a potential sale, for example, the value of that company's data is included in the overall valuation.
Selling or renting your data is definitely a path to monetization, particularly if your data is unique or difficult to find from other sources.
When I worked with the telecom company EE, they created a department to evaluate how they can use their data, including location data, on their customers. We asked questions like, "Who might be interested in this type of data? Who might pay for it?" Then we formulated our strategy from those insights.
Even organizations that are not strictly data companies can make money from their data. For example, farm equipment and tractor manufacturer John Deere created an intelligent farming system that pulls in soil and weather information, then provides recommendations to farmers about what to plant, when to plant it, how much fertilizer to use, and so on. John Deere makes over a billion dollars a year selling their data to farmers.
Visa makes over a billion dollars a year selling data back to retailers who need information about customer purchase patterns. These retailers may not have their own loyalty card programs, so they can only see what customers buy in their individual shops and can't get an overall view of purchasing behavior. Visa can sell these retailers valuable, aggregated data on their customers and make a lot of money doing it.
These are the key ways organizations can monetize their data: By creating better products that meet the needs of future consumers, by cutting costs, and by selling or renting their data directly.
If you’d like to learn more, I encourage you to check out my book, Data Strategy: How to Profit from a World of Big Data, Analytics and the Internet of Things, or visit my website or YouTube channel to get more data monetization ideas for your company.
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Bernard Marr is a world-renowned futurist, influencer and thought leader in the fields of business and technology, with a passion for using technology for the good of humanity.
He is a best-selling author of over 20 books, writes a regular column for Forbes and advises and coaches many of the world’s best-known organisations.
He has a combined following of 4 million people across his social media channels and newsletters and was ranked by LinkedIn as one of the top 5 business influencers in the world.
Bernard’s latest book is ‘Generative AI in Practice’.
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