Survey based segmentations are a staple of consumer insight, but they often struggle to make the leap from research into everyday decision making. At Sky UK, we faced this challenge with a robust research led segmentation built from twelve “golden questions”: rich in attitudinal insight, but disconnected from our customer level data estate.

In this talk, I’ll share how we translated that research segmentation into an operational model across the Sky UK customer base using only attributes available in our BigQuery customer database. I’ll walk through the end to end journey, from understanding which survey questions genuinely differentiated segments, to identifying scalable behavioural and product level proxies, and finally building and validating a customer level classification that balanced statistical rigour with real world usability.A key focus will be the trade offs encountered along the way. Not all attitudinal nuance survives operationalisation, and not every elegant model survives contact with messy enterprise data. I’ll discuss how we decided what to simplify, what to preserve, and how we tested whether the resulting segments were still “true enough” to the original research intent to be useful.

Finally, I’ll cover the often overlooked part of segmentation work: socialisation. I’ll share how we explained the differences between segments to non technical stakeholders, shifted conversations away from model mechanics, and helped teams across marketing, product and strategy actually use the segmentation in decision making.Attendees will leave with practical lessons on operationalising research led segmentations, common pitfalls to avoid, and concrete approaches for bridging the gap between insight, analytics and business adoption.