Customer Analytics: the collection, management, analysis and strategic leverage of a firm’s granular data about the behavior(s) of its customers.[1]
The idea of using analytics to gain a competitive advantage is not a new idea. Businesses have used analytics to influence their companies’ strategy long before now. What is new is how the analytics are being used by companies and how the use of analytics is spreading across a wide variety of industries. Companies are using the data about human behavior to re-work their supply chain, sales theory, and marketing campaigns, reduce customer churn, attract new “lifetime” customers, reward customer’s loyalty, and the list of possibilities goes on and on. Even sports teams have been able to use behavior analytics to increase tickets sells, improve stadium parking, stadium food, acquire better players and reduce player injuries.
“Analytical cultures and processes are appearing not only in professional sports teams, but in any business that can harness extensive data, complex statistical processing, and fact-based decision making.”[2]
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| Photo Courtesy of http://chainbigdata.eventbrite.com/[6 |
I have not been able to find a manual on how to use the gathered data, it appears to be an art that each company can perfect, but here is a list of what the raw data should look like:
· Inherently Granular: must be individual-like
· Forward-looking: orientation towards prediction not just description
· Multi-platform: combining behaviors from multiple measurement systems, but with best efforts to do so at the individual level
· Broadly applicable (and industry agnostic): consumers, donors, physicians, clients, brokers, etc.
· Multidisciplinary: marketing, statistics, computer science, information systems, operations research, etc.
· Rapidly emerging: traditionally viewed as just one form of “business analytics,” but starting to take on its own unique identity as a “standalone” area of analysis and decision making
· Behavioral: many firms’ customers analytics problems incorporate descriptors such as demographics and attitudes; but, the customer analytics primary focus is on observed behavioral patters
· Longitudinal: it’s ALL about how these behaviors manifest themselves over time
Courtesy of Wharton Customer Analytics Initiative
The use of customer’s analytics has enormous potential to positively affect companies ROI. An interesting read is how Target is able to predict if its customers are pregnant.[3] The use of these analytical techniques Target credits with its growth in revenue- $67 billion in 2010 compared to $44billion in 2002.[4]
How the data is used also has the potential to level the playing field;
“We have the seventh-largest revenue stream in terms of ticket sales of all 30 teams and we’re the 20th largest market in the NBA. It’s because we can take data and analyze if so effectively.[5]” – Alex Martins, CEO, Orlando Magic
The challenge from companies is to figure out how to use the collected data in the most productive way, without violating the customer’s privacy or by creeping customers out.
[1] Htto://www.whartons.upenn.edu/wcai Accessed on 1/15/2013
[2] Davneport, Thomas H., Cohen, Don, and Jacobson, AL. “Competing on Analytics.” Babson Executive Education. May 2005
[3] Duhigg, Charles. “How Companies Learn Your Secrets.” The New York Times, February 16,2012. Nytimes.com Accessed on 1/15/2013.
[4] Hill, Kashmir. “How Target Figured Out a Teen Girl Was Pregnant before Her Father Did.” Forbes.com 2/16/2012
Very well-written article, Steve. Thanks!
ReplyDeleteThank you Sir, I hope you gained something you can use.
ReplyDeleteGood job Steve.
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