Companies have been collecting data for years. Useful data can offer competitive advantages and be the basis for many services and better customer experience. There have also been many companies that have wanted to become data aggregators, collecting and selling data. But the big data success stories are not in selling data. Sometimes data is almost a toxic asset. What can we learn from the ways that data has been best utilized and monetized? We now have the same question with personal data, and many parties want to repeat the same old mistakes.
Fifteen years ago, in one of my earlier startups, we developed a marketing slogan: Data – the black gold of the 21st century. It was and is still a relevant comparison, but to make money from data is very different from the oil business. There you have separate business lines to drill and refine oil and then sell refined products. We can see something similar in the data business, but making big money in the value chain is very different in the oil and data business.
Google, Facebook and Amazon are the superpowers of the data market. They primarily collect and then build services that utilize data. They might buy some third-party data, but it is not their primary way to get data, and they don’t actually sell data. The reputation of companies that focus on trading data is nowadays quite shaky. As a person who runs data operations for a Silicon Valley giant once said to me, they are more and more skeptical about buying data when they don’t know its sources, how accurate it is, how those companies that are selling it got hold of it and how they conduct their businesses.
Don’t get me wrong, some companies make significant revenue by selling data, and some companies spend hundreds of millions buying data. But it hasn’t been an area to build unicorns and companies that shape the world as was expected maybe 10 or 15 years ago. Then there were a lot of expectations for data exchanges and other creative data trading business models.
Today data is traded more like a commodity than a unique source of value add. Companies buy outside data to enrich their data and help their solutions to utilize data better. The real value is achieved when companies build solutions to use data in marketing, sales and operations. One could even claim, the winner doesn’t have the most data, but the best tools to utilize the data. Of course, the Internet giants have heaps of data. Still, banks, telecom carriers and retailers have lots too (and the opportunity to collect more), but they have generally been slow to utilize it. Those successful companies also offer the data’s value to their users, like Google search, maps and other services, and Amazon’s better customer experience.
We are now seeing early days of personal data, i.e. how people can utilize their own data. Some initiatives and companies want to build solutions based on ideological views; people have moral rights to own and control their data. Those haven’t done too well; only a small set of people are interested in these ideological projects.
Then there are those companies that want to help people collect their data and sell it. This has many practical challenges, including how to get a data market to work with enough demand and supply. Pricing is also a complex challenge, as are the associated terms and conditions, whether you sell your data for one purpose and how to track its use. It is not easy to get this personal data market working correctly. The user value promise is often disappointing, like being paid a few dollars monthly to watch ads.
The most obvious option that has worked with the big data businesses for over ten years is forgotten. Why not offer people better tools to collect and utilize their data. When some companies want to help people to control and use their data by selling it, it is similar to recommending Google, Amazon and Facebook to sell all data they collect. Those companies have achieved their current position and power by having top tools to utilize the data they get. It is the same with individuals. If you want to empower them with their data, you need to offer the best tools to utilize that data personally.
Utilizing personal data will include many concepts, and we don’t know them all yet. We need an open market to innovate and develop those tools. But it can have, for example, tools to plan better personal finance, find the best prices, manage better health and wellbeing, and get help in all kinds of daily needs and activities. The longer-term vision is to build personal AI that offers a dashboard to guide all daily activities.
As with data businesses, personal data could also be enriched with external data sources. For example, public data like price comparison, traffic, public health and map data combined with personal data making it more powerful. Data model training for Machine Learning and AI improves when it can use data from many users.
In many ways, the best way to utilize personal data is similar to what the leading data companies have done for years. But it seems that with a new business opportunity, many parties first go to very complex models, like justifying data with ideological thoughts or wanting to build a blockchain-based data exchange with digital rights management systems. Often the simplest and best solution is to copy one that has worked earlier elsewhere.