The power of data to generate growth and efficiency for businesses internally is indisputable. But innovators are looking further, finding new ways to monetize data by launching new data-based products, and selling them to third-parties.

So, just how exactly are they doing it?

Below are four compelling use cases of companies that have capitalized on the rich data sets they possess. They’re innovating with new products, entering new markets and creating new revenue streams.

Take a look:

  1. Payment Providers — Credit card companies may have the most valuable data to sell. With access to both cardholder data – and data from the merchant side – payment providers get a unique 360-degree view of transactions. For example, a global payment provider sells data analytics services to retailers who want a full picture of consumer buying behavior. This robust data and analysis also allows credit card companies to forge brand partnerships and offer incentives to influence consumers’ choice of merchants. Case in point: Amex Offers shows real-time coupons relevant to lifestyle and buying habits based on the customer’s physical location – in the moment. These highly personalized, timely offers also create incentive for more businesses to accept American Express cards.
  2. Logistics — Flexport, a global freight services company, saw an opportunity to bring freight shipping logistics out of the dark ages by using automation and software that lets customers digitally track and control their cargo. Along the way, they started a spin-off company, called ImportGenius, which took import data, organized it, and sold subscriptions to their database for $100-400 a month. ImportGenius taps into a much broader customer base (investors, researchers, legal professionals) interested in data vs. pure logistics, and has opened up a completely new business, but still related to the company’s core business.
  3. Retail — Supermarkets are able to build a robust demographic profile on customers using data generated from customer reward programs and member cards. In turn, CPG brands are willing to pay a lot of money for this customer data. Why? They can target customers who purchase rival brands, and offer highly-targeted coupons or other offers. Supermarkets are also using this data to better understand customer loyalty. Sainsbury (a UK retailer) analyzed customer data internally to discover that Grape-Nuts cereal was worth stocking – despite weak sales – because the shoppers who bought it were often big spenders on other items, and more loyal to the Saintsbury brand.
  4. Cars of the Future — The race to create a self-driving car that behaves better than a human driver may just come down to the company with the best data.  Currently, Tesla and Waymo (Google’s self-driving car project) are leading the charge, and they’re each tackling data collection differently. Tesla is collecting real-world data about it’s ~300K cars on the road, while Waymo uses a sophisticated computer simulation system, and then feeds that data into a smaller real-world fleet. Even traditional automakers have been installing wireless connections in vehicles and collecting data for decades. Eventually, the goal is to build a database of consumer preferences that could be aggregated and sold for marketing purposes (ie: targeted ads on your cars display screen). Either way, connected cars – whether gas-powered or electric – are here to stay.

As these examples show, getting data monetization right leads to innovation, growth, and a competitive edge. But first, companies should prioritize building a strong data foundation— including strategy, design, and an open architecture— in order to build the business case and technical platform needed to effectively monetize data.

If you want to take a deeper dive, check out this McKinsey report, Fueling Growth Through Data Monetization.