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Predicting Churn with Tableau, Data Science, and GenAI

Learn how Mimecast armed its customer success teams with information and dashboards in order to tackle identifying and prioritizing customer churn using Tableau, data science, and generative AI.

, Senior Manager, Business Intelligence & Analytics, Mimecast

, Director Analytics Engineering, Mimecast

Role: Data Analyst

Industry: Technology

Topic: Tableau Cloud, Tableau AI

Session Type: Breakout

Session Level: Intermediate

Session Track: Product & Industry

Monday, Apr 299:30 AM - 10:10 AM PDT

(4:30 PM - 5:10 PM GMT)
Breakout 05 -- Room 22
Monday, Apr 294:00 PM - 4:40 PM PDT

(11:00 PM - 11:40 PM GMT)
Breakout 02 -- Room 3

Session Summary by Einstein: The session provided an extensive overview of how to predict churn and downsell using advanced analytics and AI tools, with a focus on actionable insights and operationalization. The presenters from Mimecast, a global cybersecurity company, shared their approach to data science and generative AI, emphasizing the importance of embedding insights within tools like Salesforce and Tableau to assist customer success managers (CSMs). They demonstrated how risk scores, impact indexes, and customer engagement signals are used to proactively manage customer retention, with a model accuracy goal of 70% and the capacity to adapt to changing customer behaviors. The integration of these systems has led to the development of a 'customer retention AI copilot' that provides CSMs with early warning signals, enabling timely and effective actions to mitigate churn risks.

Key Takeaways by Einstein:

• Mimecast leverages a combination of discrete and unstructured data types to assess churn risk, applying a data science model that dynamically adapts to customer behavior changes over time.

• The session showcased an analytics dashboard embedded in Salesforce, offering CSMs a prioritized view of customer accounts, risk levels, and actionable insights to address potential churn and downsell scenarios.

• A 'customer retention AI copilot' serves as an aid for CSMs, summarizing vast amounts of unstructured data into actionable signals and generating customer health scores to guide retention strategies.

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