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