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This study concerns the practical methods used to design segmentation models for digital advertising. I illuminate some of the collaborative activities workers rely on to create these web analytics based groupings. This work remains overlooked as the popularity of automation and statistical methods for segmenting customers continues to grow. I explain some of the ways the advertising customer is present as a background expectancy while workers make segment composition decisions. This approach is meant to complement established evaluative, technical, and statistical methods used to create segments and personas in design and marketing. This may inspire similar approaches to designing for specific groups of people while working with large data sets. Incorporating these customer-orienting practices in design and advertising processes could lead to novel approaches for both segment targeting and customer relationship management (CRM) software.

The Work of Mad Men that Makes the Methods of Math Men Work