Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    data analytics
    How Data Analytics Can Help You Construct A Financial Weather Map
    4 Min Read
    financial analytics
    Financial Analytics Shows The Hidden Cost Of Not Switching Systems
    4 Min Read
    warehouse accidents
    Data Analytics and the Future of Warehouse Safety
    10 Min Read
    stock investing and data analytics
    How Data Analytics Supports Smarter Stock Trading Strategies
    4 Min Read
    predictive analytics risk management
    How Predictive Analytics Is Redefining Risk Management Across Industries
    7 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Death of Consumer Segmentation – Ridiculous!
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Business Intelligence > CRM > Death of Consumer Segmentation – Ridiculous!
Business IntelligenceCRMData MiningPredictive Analytics

Death of Consumer Segmentation – Ridiculous!

TomAnderson
TomAnderson
5 Min Read
SHARE

If thinking about segmentation, make sure you talk to someone who has actually done a few different types!

There’s another article on consumer segmentation this week that seems to be getting a lot of buzz on twitter etc. You can read the article here in AdAge CMO Strategy section. Steve Rubel argues about the weakness of segmentation.

I disagreed with this article and will respond briefly here because I think segmentation studies are the most important type of research a company can engage in. If your company does only one piece of research this year, it should be customer segmentation to find out where to spend precious marketing dollars, and where not to.

First, segments don’t have to be static, in fact I believe they should be dynamic. Part of the deliverable/output should be scoring algorithm which can be applied at any time, and this one customer can fall into a different segment if their variables on file change.

More Read

Handling the Information Overload in Marketing With Big Data
Some of us like to name things
The Dirichlet Process Part 3: Dirichlet Process
IBM and ILOG – Thoughts on Jerry Cuomo’s WebSphere Top 10
Who’s the main competitor to the new method? What’s the catch?

Naturally, no segmentation has an indefinite shelf life. And thought should be given to updating segmentation every 3-5 years or when new better data sources become available, or when marketing tools change.

The second argument of belonging to more than on…

If thinking about segmentation, make sure you talk to someone who has actually done a few different types!

There’s another article on consumer segmentation this week that seems to be getting a lot of buzz on twitter etc. You can read the article here in AdAge CMO Strategy section. Steve Rubel argues about the weakness of segmentation.

I disagreed with this article and will respond briefly here because I think segmentation studies are the most important type of research a company can engage in. If your company does only one piece of research this year, it should be customer segmentation to find out where to spend precious marketing dollars, and where not to.

First, segments don’t have to be static, in fact I believe they should be dynamic. Part of the deliverable/output should be scoring algorithm which can be applied at any time, and this one customer can fall into a different segment if their variables on file change.

Naturally, no segmentation has an indefinite shelf life. And thought should be given to updating segmentation every 3-5 years or when new better data sources become available, or when marketing tools change.

The second argument of belonging to more than one segment, is also rather weak. It’s almost irrelevant in most cases. If your segmentation schema is good, whether you fall into segment 1 or segment 2, the treatment will and should likely be the same, if those two segments are similar. Again it depends on product category etc. but this really should not be an issue either. Also, segment algorithm I mentioned above should give you a score of likeliness to belong in each segment. Marketers can then decide if extending a message intended for segment 1 customers, to customers who are second most likely to be in segment 1 should also get that message/offer.

Finally, the comment about 1-1 segmentation is a nice idea, but in practicality, we are a long way from implementing that in a meaningful way that would save marketers from wasting dollars.

It takes a bit of background in statistics and the segmentation methods available, as well as experience conducting a few different types of segmentations in different industries before you can discuss this topic intelligently. I’m sure that is not the case in the article. Actually, there are few true segmentation experts in our industry. If you need to do a segmentation, ask your consultant how many they have done, and what types of different methods they are familiar with.

Tom

Link to original postTom H. C. Anderson – Anderson Analytics

TAGGED:market research
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

ai kids and their parents
How Cities Use AI to Improve Playground Design
Exclusive News
human resource data
The Integration of Employee Experience with Enterprise Data Tools
Big Data Exclusive
protecting patient data
How to Protect Psychotherapy Data in a Digital Practice
Big Data Exclusive Security
data analytics
How Data Analytics Can Help You Construct A Financial Weather Map
Analytics Exclusive Infographic

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

What is Your Market Research Identity?

5 Min Read

MR Heretic Explained

20 Min Read

The Anderson Analytics Facebook Application in Advertising Age

3 Min Read

Two in Five Market Researchers Optimistic

4 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data
ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?