What should a company consider before it starts selling its data?

Make your data work for you without the hassle and the overhead.

More and more companies are recognizing their data as an asset, and want to sell it.

You have a company with data, you have someone to buy data. Get the data to your partner, format the data, and get paid. This is a lot harder than it looks.

This post discusses six things to do before trying to sell data:

• Create a long-term business plan on where you want the data to lead.
• Catalog and review the data you hold.
• Have a point of view on its value before meeting buyers.
• Be wary of data brokers.
• Choose sales channels to reach customers.
• Mind data laws to avoid legal troubles when selling data.

Data is the new oil. This sentence is a cliche, but the sentiment behind it is true. Selling data is no free lunch; it needs real time and resources to extract value.

Selling data usually involves finance, legal, engineering, sales, analytics, product management and top leadership. Each function must remain involved over the long term.

You won’t build a multi-million dollar business overnight. The year after deciding to sell data often leads to many lessons, and only a few deals. Year one is still immensely valuable, because those first few deals could start the snowball of repeatable revenue.

The Kinds of Data You Have

Everyone talks about “data” as if it is a cohesive thing. The word “data” is a vague catch-all word; it often obscures what kind of data is being discussed. Study the kinds of data you have before deciding which sets to sell.

Do an audit to find the data sets you will sell:

• Can you get a complete list of data you hold that you could sell?
• Do you hold data on consumers, or personal information?
• How is the data collected?
• What system(s) house each type of data?
• What is its schema and format?
• Can the data easily be taken out of its current system and moved elsewhere?
• How do you value it? What is the data worth to you?
• Are there legal and/or regulatory risks to sharing data?
• How will buyers use it?
• Is this for analytics or for marketing?

You know your data better than your buyers. Before selling any data, develop a point of view on its utility and explain that to any potential buyer.

You know your data’s value to your firm; can that be extended outside your own use case? Listing all the ways you use the data internally is a starting point on its outward-facing usefulness. Compare the internal value of the data with external value too. Who are all the companies that fit a potential buyer profile?

Use cases you already know are easiest to predict, and those use cases you already solve are the best starting points. Understanding the size of the customer need helps you size the market.

You will never predict every use case for the data. Some of the buyers of your data will put it to uses that you never imagined. That being said, having a well-developed point of view on the use cases makes early sales much faster.

Data Brokers

The data brokering industry arose to make it easier to sell data. Those brokers act as middlemen to bring buyers and sellers together; this made the process of selling data more accessible, but stripped sellers of much of the nuance needed for a lasting data business.

Look at your typical broker’s gross margin, for example LiveRamp’s: it shows the middleman keeps most of the value.

Brokers cause three problems that block sellers from a scalable data business:

• Data brokers are like many other middlemen; they fear disintermediation by the buyer and seller circumventing them. To prevent it, they obscure the buyer’s identity from the seller. Without knowing your buyers, you are flying blind.
• Many brokers set rigid rules for sellers and buyers. The broker won’t bend those policies to let you treat your account with the nuance that you need; whether it is a pricing strategy or a contract, you run by the broker’s playbook.
• Data brokering is also one-sided on the money. Broker gross margins run from 50 to 95 percent, leaving the seller with only a small share.

Data brokers often seem like the easy way to get started. Over time, the opacity and rigidity of their systems will limit your data business to remain only the size the broker wants it to be, which will cap your growth.

How do you spot a data broker? Ask if the company actually buys data. If a company doesn’t gather data itself but works heavily in the data market, then it is a broker.

Data brokers are one way to sell data. Other ways to sell data include data marketplaces and direct sales.

Data marketplaces work a bit like eBay; they make it possible to reach many buyers right away, since anyone who browses the site could buy your data. Data marketplaces are a good place to start.

Before joining a data marketplace, ask a few questions.

• Do you set the price of each sale?
• Do you have any control over who the buyers are?
• How much of each sale does the marketplace keep?
• Does the marketplace get any rights to your data?

If the answers fit your goals, then use that marketplace. If the answers make you uneasy, look for another one.

Data Privacy

Never underestimate data privacy. Many new laws are being passed, like GDPR in the European Union and CCPA in California. Older laws, such as HIPAA, still apply, too.

These laws are there to protect people whose information is being collected.

Don’t be afraid: the laws do not ban data businesses, they ask companies to be more careful in how they collect data. These laws should benefit everyone in the long term; the aim is a healthier, lasting ecosystem that respects consumer rights.

Selling data can and does provide real, meaningful revenue. Data is an asset only when you make it so, by making a plan and sticking to it as it unfolds. Well-run companies that start informed and ready to do the work will do well.