Customers Behavior: Changing How Company’s Compete

 

“In virtually every industry, many former strategic alternatives are no longer viable or likely to be successful.” [1] 

  

 More and more companies are facing increasing levels of difficulty to perform financially.  In many circumstances the tools that gave companies a competitive advantage no longer work as effectively.  To stay relevant companies can no longer look backwards solely at their financial metrics when making decision. [2] Companies need to learn how to harness the power of data from their customer’s behavior. 

"...a new form of competition based on the extensive use of analytics, data, and fact-based decision making."                                           

                                                                                                         - Competing on Analytics [3]
  

         

Image taken from: http://econsultancy.com/us/blog/10288-companies-struggling-to-perform-attribution-and-online-offline-measurement

The company SAS® describes wonderfully on their website how utility companies can use customer analytics to make more informed decisions.  While the text below is taking from SAS's promotional information, it illustrates the concept of how companies need to be looking at the data from consumer behavior to add more value to the customer and the company:

Every Customer interaction is an opportunity to capture data and convert it into knowledge that can improve decision making.  With SAS, you can:

·    Create an accurate, single view of the customer by consolidating data from every source, using embedded data quality routines to correct, standardize and verify data, then transforming it into a complete picture of the entire customer relationship.

·      Use advanced analytic techniques to comply with regulator guidelines for energy efficiently efforts by discovering how different customer segments consume energy during peak or off-peak hours.  Effectively recover debt by gaining insights into the major factors that cause customers to pay late or not at all and adjusting billing strategies and plans accordingly.

·      Connect the right offers to the right customer segments by using automated campaign planning to pull more relevant, predictive lists, then pair that information with knowledge of the right opportunities so you can respond to customer needs or opportunities in the generation/transmission value chain.

·      Improve organizational decision making by using predictive analytics to model future customer behaviors, forecast growth in demand by various customer segments and optimize utility reactions based on past events. [

"...a new form of competition based on the extensive use of analytics, data, and fact-based decision making."                                           

                                                                                              

Image Courtesy of http://analyticsoc.com/humor/

 

Here are a some examples of how companies have started to use the data and statistic to change they way the compete and do business:

Image courtesy of Fathead.com

• Following the Oakland A’s use of analytics based off of players behaviors, the Red Sox’s started using data to shape their teams strategy, which is credited to have helped them win the 2004 World Series.

•  While the use of data is not new in baseball, the Red Sox’s used non-traditional data they had compiled about players behaviors to
  select their players.

•  Data is collected to measure the “fans experience.” How did they decided to attend a game, which route(s) did they take to get to the ballpark, how effective is the cleaning crew, etc.

• The data is used to help maximize the team’s revenue.  Ticket price elasticity is derived from the data and models were created to help add new seats in unused locations. [5]

Image courtesy of Fathead.com

•  The Patriots won 3 Super Bowl’s in 4 years, part of the success is due to their data analytical models.  The data helps the team on and off the field.

•  The analytics help the team select players, stay below the salary cap, and aids in the calling of plays based upon game variables and statistical outcomes.

•  Data is used to track and measure “the total fan experience.”  During home games, 20-25 employees are assigned to take quantitative measurements of the stadium food, parking, personnel, and bathroom cleanliness, etc.    

       

•  Data is collected and analyzed specific to external vendors.  The measurements are used to evaluate contracts and create incentives around performance.  [6]

Image courtesy of Wikipedia

• The American retailing company views new parents as customers who's  shopping habits are vulnerable to change.  Instead of waiting to send these new parents coupons after the birth announcement is made public (following the crowd of other companies that do this) Targets marketers wanted to figure out how they could send the coupons to pregnant women in their second trimester.

• Target assigns each customer their own “Guest ID number” that keeps track of everything they buy. [7]

• Using this data, Target was able to see patterns in customers purchasing behaviors and identify when someone might be pregnant.  Specifically, when women started to stock up on large amounts of scent-free soap and extra-big bags of cottons balls.

• Using 25 specific products, Target was able to assign the shopper a “pregnancy prediction score and even estimate the due date within a small time frame. [8]

To stay relevant, companies need to learn how to use the warehouse of data on consumer behaviors.  It is worth the cost.  For some companies the real challenge might the task of changing the companies culture to be data driven.
 

If you are interested in learning more about customer analytics check out this post: Customer Analytics: Incorporating Customers “Secret” Behaviors in the Company’s Strategy.   

To learn more about what the data should look like, check out Whartons' Customer Analytics Initiative.

 

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1.     Davenport, Thomas H., Cohen, Don, and Jacobson, AL.  “  Competing on Analytics.”  Babson Executive Education, May 2005

2.     Davenport, Thomas H., Cohen, Don, and Jacobson, AL.  “  Competing on Analytics.”  Babson Executive Education, May 2005

3.     Davenport, Thomas H., Cohen, Don, and Jacobson, AL.  “  Competing on Analytics.”  Babson Executive Education, May 2005

4.     http://www.sas.com/industry/utilities/customer-analytics/index.html

5.     Davenport, Thomas H., Cohen, Don, and Jacobson, AL.  “  Competing on Analytics.”  Babson Executive Education, May 2005

6.     Davenport, Thomas H., Cohen, Don, and Jacobson, AL.  “  Competing on Analytics.”  Babson Executive Education, May 2005

7.     Duhigg, Charles.  “How Companies Learn Your Secrets.”  The New Tork Times.  February 16, 2012.

8.     Hill, Kashmir.  “How Target Figured Out a Teen Girl Was Pregnant before Her Father Did.”  Forbes.com 2/16/2012

Customer Analytics: Incorporating Customers “Secret” Behaviors in the Company’s Strategy

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]  

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 20^th 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.

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[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

[5] www.sas.com.software/customer-intelligence
[6]  http://chainbigdata.eventbrite.com/