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
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
    big data and remote work
    Data Helps Speech-Language Pathologists Deliver Better Results
    6 Min Read
    data driven insights
    How Data-Driven Insights Are Addressing Gaps in Patient Communication and Equity
    8 Min Read
    pexels pavel danilyuk 8112119
    Data Analytics Is Revolutionizing Medical Credentialing
    8 Min Read
    data and seo
    Maximize SEO Success with Powerful Data Analytics Insights
    8 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Understanding Value
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Uncategorized > Understanding Value
Uncategorized

Understanding Value

TeradataAusNZ
TeradataAusNZ
4 Min Read
SHARE

It is interesting when we talk about the value of a customer (sometimes referred to as profitability). There are a number of different rules of thumb presented as the best way to derive value; the approach tends to be determined by the use of the outcome. Marketing wants to understand value to be able to differentiate services and offers, while finance wants to reconcile to the GL, and so on. Some approaches have flexibility to be a little wrong and others strive for perfection. So there is no wonder that the conversation of customer value causes so much excitement in organisations.

The challenge that becomes evident very quickly is that there is no such thing as the perfect model or a right way to build a model, there is only a wrong way in the eyes of the end users. Users will never use a model once it has been deemed incorrect for purpose, hence the proliferation of profitability models in organisations. In my experience organisations have at a minimum three different profitability based models, there is no wonder that a profitability conversation is so passionate! How do you move towards accepting a single model?

The adoption of any model takes time, people need to …

More Read

Nail-biting finish for Netflix Prize
The War of Word Craft
The Hadoop Honeymoon Is Over
5 Key Takeaways for Businesses from Google I/O 2015
Time To Manage Your Social Media



It is interesting when we talk about the value of a customer (sometimes referred to as profitability). There are a number of different rules of thumb presented as the best way to derive value; the approach tends to be determined by the use of the outcome. Marketing wants to understand value to be able to differentiate services and offers, while finance wants to reconcile to the GL, and so on. Some approaches have flexibility to be a little wrong and others strive for perfection. So there is no wonder that the conversation of customer value causes so much excitement in organisations.

The challenge that becomes evident very quickly is that there is no such thing as the perfect model or a right way to build a model, there is only a wrong way in the eyes of the end users. Users will never use a model once it has been deemed incorrect for purpose, hence the proliferation of profitability models in organisations. In my experience organisations have at a minimum three different profitability based models, there is no wonder that a profitability conversation is so passionate! How do you move towards accepting a single model?

The adoption of any model takes time, people need to understand the rules and assumptions that have been used when building the model, for all users to agree to its make up. Education needs to evolve with the capabilities of the organisation and model to ensure that people stay onboard. The complexity of the model needs to provide the end users of the model with the information required to perform their jobs.

The only gotcha is that the model needs to have the ability to become more complex over time, using more detailed information and more detailed rules as the organisation matures. On day one, no user is going to be interested in drilling down five levels to understand the why’s. But in time they will, consequently the model needs to be able to support detailed investigation not just a score without any context.

 

Daniel Tehan

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

image fx (2)
Monitoring Data Without Turning into Big Brother
Big Data Exclusive
image fx (71)
The Power of AI for Personalization in Email
Artificial Intelligence Exclusive Marketing
image fx (67)
Improving LinkedIn Ad Strategies with Data Analytics
Analytics Big Data Exclusive Software
big data and remote work
Data Helps Speech-Language Pathologists Deliver Better Results
Analytics Big Data Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Saving Face

3 Min Read
Image
Uncategorized

The World According to IT: The Star Wars Spectrum of User Intelligence [INFOGRAPHIC]

1 Min Read

The lesson of the Palace of Culture and Science

11 Min Read

Why Publishers Don’t See Google As A Friend

5 Min Read

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

AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots
data-driven web design
5 Great Tips for Using Data Analytics for Website UX
Big Data

Quick Link

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

Sign in to your account

Username or Email Address
Password

Lost your password?