Customer segmentation provides foundation to increase customer life time value
Case Study

Customer segmentation provides foundation to increase customer life time value

Customer segmentation provides foundation to increase customer life time value
Case Study

Customer segmentation provides foundation to increase customer life time value


A Fortune 500 insurance company and one of the largest providers of insurance related products for individual homeowners.

The Business Challenge

The organization was experiencing its position in the market as a leading provider of insurance related products slip in comparison to its competitors. The marketing department was challenged with coming up with new ways to engage with customers and win their leading position back. They realized that one potential contributor to the problem was that they had not updated their customer segmentation model in over 5 years. They were currently only segmenting based on demographic data and not using the customer behavior and persona data they had available. Because of this they felt that they were not able to provide differentiated experiences to the customer micro-segments or consistent customer experiences across channels and geographies.    

The Baker Tilly Approach

In an effort to regain their leading market position, the company engaged with Baker Tilly to develop an updated customer segmentation model that took all of their available customer data into consideration. The new analytics-based segmentation model would then be used as a foundation to market, engage and sell to each micro-segment of their customer base in different ways.

The Baker Tilly Analytics team used an advanced analytic approach to:  

  • Develop an analytics driven customer segmentation model that leveraged customer demographic, product, and behavioral data to identify ten customer segments and unique customer personas.   
  • Conduct a data assessment of existing internal data sources to determine what data was useable, what was not reliable, what could be leveraged to improve the existing segmentation model and what was missing.
  • Identify a data collection plan to fill in gaps related to their understanding of the customer, helping them gain a more complete understanding of their customers.
  • Utilize statistical techniques to:  analyze hundreds of customer attributes; narrow down those that are most important for grouping customers into segments; and understand the key drivers of each group’s behavior.   

Value to the Customer

  • Gave the organization a solid basis on which to raise questions that challenged previous beliefs based on the old customer segmentation model.     
  • Creation of ten unique customer segments allows them to then make different tactical decisions on how to deliver a unique customer experience for each individual group.
  • This segmentation process helped the company identify not only gaps in their customer data collection processes, but additional, valuable, customer information data collection points as well.  They have a plan in place to capture customer data at these critical interaction points.

Business Impact

Providing unique visibility of customer needs, trends, and similarities, the new segmentation model is expected to serve as the foundation for follow on initiatives targeted to increase conversions, increase spend, maintain loyalty and reduce churn. Highlights of the before and after impact of the segmentation model:



Losing market share

Positioned to gain market share and an expected $3M annual sales revenue increase

Gut feeling customer treatment strategies

Consistent, repeatable customer treatment strategies based on data and insights on that data

Demographic data driven segmentation models

Behavioral and demographic data driven segmentation models

Inability to monitor customer behaviors over time

Ability to monitor customer behaviors over time and get ahead of emerging customer trends more quickly.

Inconsistent customer experiences across geographies, products, and sales territories

10 micro treatment strategies enable consistent forms of engagement with customers from each identified segment

Customer segmentation is not a onetime event. Customer segmentation models that include customer buying behavior data over time provide the foundation for increasing the overall customer life time value.

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