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Intelligent Churn Detection Lab

This is an Instructor-Led Lab

This lab is designed for in-person workshop events led by a Boomi instructor. Participants must be provisioned with access to a dedicated Boomi platform account during the workshop. This lab is not intended for self-led learning.

Looking for Self-led learning?

For self-paced learning, check out the Customer Support Triage (Extended) Lab.

Business Situation​

Retentix is a rapidly growing subscription-based software company facing a critical challenge in customer retention. As their customer base expands, they struggle to proactively identify and engage with customers who are at risk of churning. The customer success team reactively responds to customers only after they show significant signs of disengagement—such as high numbers of failed login attempts or sharp drops in platform usage—resulting in revenue churn and lost opportunities.

The root of the problem lies in how customer health data is siloed across product usage, support, and CRM systems. Customer success teams lack timely insights to intervene proactively, leaving account managers overwhelmed and churn risks undetected until it's too late. This reactive approach is costly, inefficient, and impacts recurring revenue and customer lifetime value (CLV).

Challenges​

  • Customer health data is siloed across product usage, support, and CRM systems
  • Customer success teams lack timely insights to intervene proactively
  • Manual account reviews are overwhelming and churn risks are often missed
  • Reactive outreach happens only after customers show significant disengagement
  • Costly and inefficient processes impact recurring revenue and CLV

Solution​

An intelligent churn agent consolidates customer data, detects risk signals, and triggers workflows to alert customer success teams. This enables proactive outreach and reduces churn by automating the entire process of identifying and acting on churn risks before customers disengage.

Use Case​

In this lab, you'll build an Intelligent Churn Detection Agent for Retentix that transforms customer retention from reactive to proactive. When a customer event—such as reaching a threshold of failed login attempts—breaches a predefined Service Level Agreement (SLA), your agent will:

  1. Automatically gather a complete view of the customer using available APIs, including:
    • Customer profile data from the Golden Record (Customer 360)
    • Usage and engagement metrics
    • Sentiment and feedback history
  2. Analyze this consolidated data to assess the customer's churn probability and classify them into risk segments (High, Medium, Low).
  3. Generate a comprehensive churn prediction report detailing the risk factors.
  4. If the risk is high enough, automatically trigger the Notification and Escalation service to alert internal teams for immediate intervention.
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This lab simulates all ticketing and application system interactions. The focus is on building the intelligent agent workflow that detects churn signals and automates the response process.

Business Outcomes​

  • Reduced Customer Churn & Increased Net Revenue Retention (NRR): Proactively identify and retain at-risk customers before they churn
  • Improved Customer Satisfaction & Loyalty Scores (CSAT/NPS): Timely interventions demonstrate care and responsiveness
  • Creation of Brand Advocates to Lower Acquisition Costs: Satisfied customers become promoters, reducing marketing spend

Key Performance Indicators (KPIs)​

  • Revenue Churn: Percentage of annual churn results in a quantifiable outcome of retained revenue
  • Cost to Serve: Reduce support tickets and require less manual intervention from customer success teams
  • Manual Account Monitoring Effort: Time spent manually sifting through data to identify at-risk customers

Workshop Structure​

This workshop is divided into three hands-on activities that build progressively on each other.

Activity 1: API Tools for an AI Agent​

Create the secure, governed API tools that your agent will use to access customer data and trigger actions. You'll build three critical tools:

  • Customer 360 API Tool: Aggregates unified customer profile data from the Golden Record
  • Customer Retention Metadata API Tool: Surfaces behavioral and sentiment indicators to identify at-risk customers
  • Notification and Escalations Integration Tool: Enables automated alerts and escalation workflows

Activity 2: Building an AI Agent​

Assemble your AI agent by defining its profile, tasks, and guardrails. You'll configure:

  • Agent Profile: Set the agent's goal, voice, and instructions to act as a churn detection specialist
  • Agent Tasks: Equip the agent with the three tools you created to retrieve data, classify risk, and escalate
  • Agent Guardrails: Apply responsible AI controls to protect sensitive data and ensure ethical use
  • Testing: Validate the agent's logic with interactive prompts

Activity 3: Embed the Agent into Business Process​

Connect your agent to real business workflows to achieve true automation. You'll:

  • Invoke the Agent Programmatically: Trigger the agent from an integration process using an Agent Step
  • Close the Loop: Let the agent automatically notify Customer Success teams when high-risk customers are identified
  • Automate at Scale: Run headless workflows that proactively identify churn risk, improving retention and minimizing revenue loss
Ready to Get Started?

Let's build your Intelligent Churn Detection Agent! Click Next below to begin with the prerequisites.