An inquiry call from a digital strategy agency advising a client of theirs on data commercialization generated a lively discussion on strategies for taking data to market. With few best practices out there, the emerging opportunity just might feel like space exploration – going boldly where no man has gone before. The question is increasingly common. "We know we have data that would be of use to others but how do we know? And, which use cases should we pursue?" In It's Time To Take Your Data To Market published earlier this fall, my colleagues and I provided some guideance on identifying and commercializing that "Picasso in the attic." But the ideas around how to go-to-market continue to evolve.
In answer to the inquiry questions asked the other day, my advice was pretty simple: Don’t try to anticipate all possible uses of the data. Get started by making selected data sets available for people to play with, see what it can do, and talk about it to spread the word. However, there are some specific use cases that can kick-start the process.
Look to your existing customers.
The grass is not always greener, and your existing clients might just provide some fertile ground. A couple thoughts on ways your existing customers could use new data sources:
The data economy — or the system that provides for the exchange of digitized information for the purpose of creating insights and value — grew in 2014, but in 2015 we’ll see it leap forward significantly. It will grow from a phenomenon that mainstream enterprises view at arm’s length as interesting to one that they embrace as a part of business as usual. The number of business and technology leaders telling us that external data is important to their business strategy has been growing rapidly -- from one-third in 2012 to almost half in 2014.
Why? It’s a supply-driven phenomenon made possible by widespread digitization, mobile technology, the Internet of Things (IoT), and Hadooponomics. With countless new data sources and powerful new tools to wrest insights from their depths, organizations will scramble to use them to know their customers better and to optimize their operations beyond anything they could have done before. And while the exploding data supply will spur demand, it will also spur additional supply. Firms will be taking a hard look at their “data exhaust” and wondering if there is a market for new products and services based on their unique set of data. But in many cases, the value in the data is not that people will be willing to pay money for bulk downloads or access to raw data, but in data products that complement a firm’s existing offerings.
I had a fascinating inquiry this morning with a government securities commission (not the SEC and not in the US). The client had a classic question about how to navigate the new data economy. The commission produces and consumes large volumes of data but continue to struggle to answer persistent business questions like how well they are doing or even who they are doing it for. Yes, securities commissions regulate securities markets; they monitor publically traded companies, investment houses, and brokerage firms. Howevver they continue to ask, “for whom?” Who are the investors that they are protecting with their regulation? As they expressed the question, “How do we know what Mrs. Smith is investing in?” They currently work with several large data providers who provide financial information on companies but that information wasn’t exactly what they were looking for. Essentially, in this Age of the Customer, they want to know who their “customers” are. This was a question about how to best serve their customers, in this case the investors.
They wanted to know how to source additional third-party data that would give them a clearer picture of the investors that they are serving. Census data provides a wealth of information about households and individual finances. But the data teams at the commission are not experts in navigating census data. Data providers like Thompson-Reuters provide data on the financial services industry. Others such as Experian or Acxiom provide information on consumers. What kinds of other data providers can help them with their data strategy to answer that basic question of how to better serve their customers, and who they are?
An explosion of data is revolutionizing business practices. The availability of new data sources and delivery models provides unprecedented insights into customer and partner behavior and enables much improved capacity to understand and optimize business processes and operations. Real time data allows companies to fine tune inventories and in-store product placement; it allows restaurants to know what a customer will order, even before they read the menu or reach the counter. And, data is also the foundation for new services offerings for companies like John Deere or BMW or Starwood.
Last month, GovLabs, a research organization at New York University released a beta version of its Open Data 500 project. The study set out to profile US companies that use open data to generate new business and develop new products and services. Not all of the companies identified have been profiled but the list of 500 provides a wide range of both existing companies and start-ups that benefit from the use of open data.
While the start-ups are interesting illustrations of innovation and economic value-creation, the presence of big, existing companies illustrates how data transforms business.
Insurance companies such as AllState and Allianz no longer only insure people and property.
As an analyst on Forrester's Customer Insight's team, I spend a lot of time counseling clients on best-practice customer data usage strategies. And if there's one thing I've learned, it's that there is no such thing as a 360-degree view of the customer.
Here's the cold, hard truth: you can't possibly expect to know your customer, no matter how much data you have, if all of that data 1) is about her transactions with YOU and you 2) is hoarded away from your partners. And this isn't just about customer data either -- it's about product data, operational data, and even cultural-environmental data. As our customers become more sophisticated and collaborative with each other ("perpetually connected"), so organizations must do the same. That means sharing data, creating collaborative insight, and becoming willing participants in open data marketplaces.
Now, why should you care? Isn't it kind of risky to share your hard-won data? And isn't the data you have enough to delight your customers today? Sure, it might be. But I'd put money on the fact that it won't be for long, because digital disruptors are out there shaking up the foundations of insight and analytics, customer experience, and process improvement in big ways. Let me give you a couple of examples:
Banks have a reputation for being stodgy and conservative. But Credit Agricole (CA) has broken the stereotype. I had a great discussion a few weeks ago with Bernard Larrivière, Director of Innovation, and Emmanuel Methivier, the CA Store Manager, about the CA Store launched last fall. The store houses new services developed by third-party developers using the bank’s secure customer data — one small step for CA, one giant step for the banking industry and the data economy.
The CA Store was not only inspired by the Apple Store model but also by government open data initiatives. The public sector provided the model of exposing APIs to internal data and working with independent developers to encourage application creation. However, in a move that will likely be carefully watched by their public sector brethren, CA recognized the need for a better business model to incent developers to use the data, and to sustain the development and maintenance of the applications.
. . . Nor has it ever really been. Government data has long been a part of strategic business analysis. Census data provides insights into local standards of living and household budgets, health needs, education levels, and other factors that influence buying patterns for all kinds of goods and services. The US Bureau of Labor Statistics and the International Labour Organization provide data on employment and the availability of skilled labor that helps inform decisions on where to locate manufacturing or other facilities. The World Bank and UN data provides insights into global trends.
Moreover, the release of government data has itself spurred billion-dollar industries. Think weather data released in the 1970s by the National Oceanic and Atmospheric Administration – which gave birth to the weather industry and services like Accuweather, weather.com, wunderground, and newer services like ikitesurf.com’s “wind and where.” Data from the US Global Positioning System (GPS) was opened to civilian and commercial use in the 1980s and has given rise to thousands of location-based services. Think FourSquare, Yelp, and Where’s The Bus?
Eighteen months ago, when I started down the path of what would become our body of Personal Identity Management (PIDM) research, there were only a few customer intelligence professionals who gave much credence to the picture we were painting. What a difference a year makes. Today, privacy, data governance, consumer empowerment, and understanding "the creepy factor" are core to the conversations I have with CI pros in both marketer and vendor organizations.
At the center of those conversations is often the question, "Who are the players in tomorrow's consumer data ecosystem?" We've just published a report, Making Sense of a Fractured Consumer Data Ecosystem, that reviews the strengths and weaknesses of four existing vendor categories plus three emergent business models. These include:
Consumer data giants: Companies, like Acxiom, Epsilon, Experian, and Infogroup, that have an opportunity to become consumer-friendly data managers but are at greatest regulatory risk
Reputation management providers: Companies, like Intelius and Reputation.com, that could help consumers manage data access but need to focus on their B2C business models to do so
Online services giants: Companies, like Google, MSN, and Yahoo, that already have access to highly personal data but serve too many masters