Use Case

Customer Segmentation


The essence of customer segmentation is being able to identify different types of customers, then figuring out how to find more prospects with the same profile. Using analytics that combines external and internal signals, companies can develop customer segmentation models around the patterns and trends that comprise each segment.

Customer Experience

Uncover deeper understanding of your customers’ needs

Top-Line Growth

Optimize marketing and manufacturing investment through greater understanding of demand trends

Efficiency Gains

Create and operationalize segmentation models within the same workflow


Business Problem

How does your organization approach customer segmentation? Keeping segmentation in view is a part of everything from the messages you convey on your website to the way you allocate production resources. When you have a clear, accurate picture of who buys from you and why, it becomes easier to appeal to like-minded prospects in the same segment.

It’s easy to see which of your products and services your customer segments bought last year, but how do you extrapolate that into the future? Few marketers can successfully navigate customer preferences on intuition and instinct alone, and in an era of abundant customer interaction points, data determines the market winners.

Alteryx Solution

Every customer interaction is the result of data and every interaction generates data. Only through the combination of external and internal signals from multiple sources do patterns and trends emerge and gradually form useful customer segmentation models.

With analytic workflows that run regularly on diverse data streams, companies can take full advantage of information on customer characteristics and historic sales levels. Marketers can then turn patterns in consumption and behavior into data-driven segmentation models, which can then be used to make decisions about products, promotions, messages, and go-to-market strategies.

Alteryx Customer Segmentation Starter Kit provides an easy method for combining customer level transaction data with customer geographic and psychographic data. This data can be blended and segmented based on categories such as average spend and number of store visits. Once the analysis is complete, it can be easily exported into Tableau for visualization and analysis.



1 – Data Access

Read in transaction data and customer demographic data

2 – Automate Prep & Analytics

Automatically segment customers based on spend

3 – Data Connections

Export segment tables for analysis in Tableau


Additional Resources

Customer Journey Analytics
Learn More
Customer Lifetime Value
Learn More
Marketing Analytics
Learn More
Analytics Automation for Customer Intelligence
Learn More
Starter Kit for Marketing Analytics
Learn More
Starter Kit for Customer Analytics

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