Data has become the main raw material of the 4th Industrial Revolution, and making money from data has become a huge business opportunity. Here we look at how any business can monetize data.
Once businesses start storing, analyzing, and acting on insights from data in a strategic way, they can easily find they have more information than they know what to do with. The solution many companies have found has simply been to sell it. By doing this, they’ve gone on to build some of the biggest corporate empires and most famous brands in the world.
But making money from data is by no means only possible if you’re a Silicon Valley giant. Today, I believe any business can monetize data. There are two tried and tested routes to doing this: selling it to create new revenue streams, or using it to increase the value of their company.
In this article, I will overview some of the methods that have been used to do this successfully in the past and provide some ideas for anyone looking to put their own data to work for them.
For many businesses, data is a hugely important asset; in fact, it's often one of the most valuable assets they hold. A large number of high-profile, strategic acquisitions have taken place in recent years where the value to the buyer came primarily from the data that a company holds. For example, Amazon bought the retailer Whole Foods Market in 2017 for $13.7 billion, one of the most expensive acquisitions it has ever made. What made the business attractive was not only its chain of retail stores but the data it has built up over 40 years of running them. This data on food and grocery shopping habits helped them plan their own move into the fresh produce sector. Amazon now offers deliveries of fresh produce in under an hour to some areas – something it would not have been able to do with the limited data it had on this market, before it acquired Whole Foods Market.
A company’s data is increasingly being seen as high value, when it comes to company valuation and analysis of its share price. During the Caesars casino chain bankruptcy proceedings, the data contained in its Total Rewards customer loyalty program was valued at $1 billion – its most significant asset. And during the pandemic, United Airlines put up the data from its MileagePlus frequent flyer program as collateral against a $5 billion loan it needed to keep itself going.
In particular, having access to data on less well-explored markets or customer behaviors can make it attractive to big players looking to leverage new and up-and-coming trends. Smart home devices have been a huge growth market, growing from $24 billion to a predicted $53 billion by 2022. Google clearly anticipated this with its purchase of smart home automation specialists Nest. Understanding the impact that smart home devices and "ubiquitous computing" were likely to have over the next decade, Google made the play not just to have a ready-built line of devices but also for the data on how early adopters were learning to coexist and interact with the new breeds of smart thermostats, security cameras, and alarms.
It’s telling that among the 2020 Fortune 500 companies ranked by value, every one of the top five positions is held by companies that have invested heavily in data, and their own ability to collect and analyze it – Microsoft, Amazon, Apple, Alphabet, and Meta. All of these companies have a stratospheric valuation because the business world is fully aware of the importance of the old adage that “knowledge is power”!
Data can be sold as a product or service. Additionally, it can be either sold in its raw form, or in the form of insights that have been derived from it. This is how internet companies like Google and Meta have grown from university startups to world-conquering behemoths. At the root of the business model of both of these companies is a service that's provided for no monetary cost to the end-user, and a data-for-sale service aimed at businesses.
In financial services, the major credit card companies all engage in a profitable side-hustle involving selling information derived from their transactional data as insights to retailers, insurers, and utility providers. This is also true of credit reference agencies such as Experian and Equifax. Both companies collate data on shopping, spending, and payment habits that are sold on to other businesses. In fact, they even sell it back to the data subjects (aka us) themselves, providing subscription services that let us check our credit ratings and assess our own likelihood of getting credit.
Logistics companies have been quick to capitalize on the possibilities of selling data. Finnish pharmaceutical distributor Tamro found that it had broader insight into buying trends than either the pharmaceutical companies it buys from or the local pharmacies it sells to. This enabled it to start selling data both upwards and downwards in its industry vertical.
Data marketplaces have also emerged online, where any business that thinks it might have a dataset of value can put it up for sale. One such marketplace is run by Snowflake, which offers health, demographic, meteorological, financial, and many other types of data from third-party sellers.
The most advanced use cases today, though, look towards offering real-time insights based on real-time data. Cosmose AI collects anonymized data from smartphones – over one billion of them – as well as in-store sensors, which is used to model the movement of people around retail environments. Its customers, who include Walmart, Gucci, and Samsung, use the information to understand shopping behaviors in order to make better use of the selling space they have available. During the pandemic, it has proven particularly useful for understanding how behaviors were changing, often on a day-to-day basis.
Most companies begin their journey towards data-driven transformation by using the information to improve their own product and service offerings or to create internal efficiencies. However, as they mature in their ability to collect, analyze and execute based on insight, it often becomes apparent that there are ways to monetize it directly, too. Understanding the data that your company has and how it could be valuable to a range of buyers, either inside or outside of your usual customer base, is key to getting on board with this powerful trend.