---
title: "Building A Data Platform That Predicts and Prevents Attrition"
id: "92692"
type: "resource"
slug: "building-a-data-platform-that-predicts-and-prevents-attrition"
published_at: "2026-05-12T14:40:22+00:00"
modified_at: "2026-05-12T14:40:22+00:00"
url: "https://tealium.com/resource/video/building-a-data-platform-that-predicts-and-prevents-attrition/"
markdown_url: "https://tealium.com/resource/video/building-a-data-platform-that-predicts-and-prevents-attrition.md"
taxonomy_resource_type:
  - "Video"
taxonomy_product:
  - "Tealium for AI"
taxonomy_vertical:
  - "Education"
---

Video

# Building A Data Platform That Predicts and Prevents Attrition

## In this higher education data strategy session, Luis Sanchez (Product Manager of Analytics at Western Governors University - WGU) explains how to shift from reactive data reporting to proactive attrition prevention. For universities and enterprise organizations alike, user churn (attrition) is a massive challenge. Rather than analyzing why students or customers have already left, WGU architected a modern data platform designed to intervene before it happens. This session breaks down how WGU uses predictive analytics and unified customer data to identify at-risk behaviors and automatically trigger retention efforts in real time.

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