Churn risk & prevention

Sid Chaudhary

Written by

Sid Chaudhary

Founder & CEO

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Utilize predictive analytics to identify users at risk of disengaging or churning. Implement tailored retention strategies to maintain their interest and loyalty.

About the Growth Play

Churn risk and prevention is crucial for SaaS companies aiming to retain their user base and maintain steady revenue growth. Churn, or customer attrition, represents the percentage of users who stop using a service over a given period. High churn rates can significantly impact the sustainability and profitability of a subscription-based model, making it essential to implement effective strategies to mitigate this risk.

This use case effectively leverages Intempt's lifecycle agent and automated engagement tools to address the challenges of churn management.

Benefits

  • Early identification of at-risk users: Predict which users will likely churn before they disengage completely.
  • Targeted retention strategies: Implement personalized campaigns to re-engage at-risk users.
  • Increased customer lifetime value: Retaining users longer by addressing their needs and concerns promptly.
  • Improved user experience: Enhance satisfaction by providing timely and relevant interactions.
  • Data-driven decision making: Utilize insights from predictive models to make informed marketing and product decisions.

How it works

Step 1: Set up data collection

Ensure you have at least 21 days of data collection with a minimum of 10,000 daily events.

Verify that the goal event (e.g., churn) has at least 200 true and 200 false occurrences over 30 days.

Examples of events that can represent churn:

User cancels subscription.

User has not logged in for 30 days.

User reduces usage significantly (e.g., logging in less frequently, using fewer features).

User submits a negative feedback or support ticket indicating dissatisfaction.

Step 2: Create a lifecycle agent

Navigate to the Agents section in Intempt

Select "Create agent" and choose the target goal event representing user churn.

Configure the Agent.

If necessary, filter out unnecessary users based on login date, feature usage frequency, subscription status, or support ticket submissions.

Train the model using historical data to predict the likelihood of churn.

Intempt will create an output attribute that stores prediction values for each user.

Step 2 output attribute

Step 3: Segment users based on lifecycle scores

Once trained, the model categorizes users into Champion, Regulars, promising, Needs attention, At risk

Step 4: Design and implement retention strategies

For high-risk users:

Create a journey:

Go to the Journeys section and create a new journey.

Name the journey (e.g., "High-Risk User Retention Journey").

Create journey

Set a trigger:

Choose a trigger based on the likelihood score (e.g., users with a high likelihood of churning).

Set trigger

Add actions:

Send personalized re-engagement emails:

Use the "Send Email" action to create an email campaign offering exclusive discounts or features. Customize the email content using user attributes like first name and recent activity. Example:

Subject: "We miss you! Here's 20% off your next month"

Body: "Hi [First Name], we noticed you haven't logged in recently. As a valued customer, we're offering you a 20% discount on your next month. Use code STAY20 at checkout. We'd love to hear any feedback you have to help us improve your experience."

Email body example

Schedule follow-up calls:

Use the "Send SMS" or "Webhook" action to notify customer success teams to call high-risk users.

Provide them a script to discuss the user's experience and offer assistance.

Follow-up calls

Add conditions:

Check email engagement:

Use the "Condition" block to check if users have opened the email or clicked on links.

If not, send a follow-up email after a few days.

Check email engagement
Email engagement condition

Check follow-up call status:

Ensure that follow-up calls were made and track the outcome.

If a user remains unresponsive, escalate to a higher support tier.

Implement personalizations:

Create a personalized dashboard message:

Go to the Personalizations section and create a new personalization.

Set the target audience to high-risk users.

Design a message or offer that appears on the user dashboard when they log in. Example:

Message: "Welcome back, [First Name]! We've missed you. Enjoy a 20% discount on your next month with code STAY20."

Dashboard message

For medium-risk users:

Create a journey:

Go to the Journeys section and create a new journey for medium-risk users

Name the journey (e.g., "Medium-Risk User Engagement Journey").

Medium-risk journey

Set a trigger:

Choose a trigger based on the medium likelihood score.

Medium-risk trigger

Add actions:

Send feature promotion emails:

Use the "Send Email" action to create emails that promote new or underutilized features. Example:

Email Subject: "Discover new features to enhance your experience"

Email Body: "Hi [First Name], did you know about our new feature [Feature Name]? Click here to learn more!"

Feature promotion email

Offer loyalty rewards:

Send emails with loyalty rewards or incentives. Example:

Subject: "Unlock exclusive rewards!"

Body: "Hi [First Name], as a thank you for being with us, we're offering you exclusive rewards. Log in to your account to see what's available and keep enjoying our services."

Loyalty rewards email

Add conditions:

Monitor email engagement:

Check if users interact with the emails

Follow up with additional tips and offers to deepen their engagement.

Monitor email engagement
Email engagement follow-up

Implement personalizations:

Create feature highlight banners:

Create personalizations to display banners highlighting new features on the user dashboard.

Target medium-risk users to encourage feature adoption.

Feature highlight banners

For low-risk users:

Create a journey:

Go to the Journeys section and create a journey for low-risk users.

Name the journey (e.g., "Low-Risk User Engagement Journey").

Low-risk journey

Set a trigger:

Target users with a low likelihood of churning.

Low-risk trigger

Add actions:

Send regular engagement emails:

Use "Email" actions to maintain regular contact with content updates and check-ins. Example:

Email Subject: "Stay updated with the latest features!"

Email Body: "Hi [First Name], we're excited to share some new features and updates with you. Stay tuned for more great updates to enhance your experience with us."

Regular engagement email

Promote advanced features:

Send emails highlighting advanced features. Example:

Email Subject: "Explore advanced features to get the most out of our service"

Email Body: "Hi [First Name], did you know about our advanced features like [Feature 1] and [Feature 2]? These tools can help you achieve more with our service. Log in now to explore!"

Advanced features email

Add conditions:

Track engagement:

Ensure users remain engaged by monitoring their activity.

Move them to other journeys if they show signs of becoming at risk.

Track engagement

Implement personalizations:

Create an onboarding checklist:

Create personalizations to display an onboarding checklist for new features on the user dashboard.

Target low-risk users to encourage deeper engagement with the platform.

Onboarding checklist

Step 5: Monitor and adjust strategies

Regularly review the effectiveness of your retention campaigns using Intempt's journey analytics.

Track user responses and adjust strategies based on the analytics data.

Continuously retrain your model with new data to maintain accuracy and relevance.

Frequently asked questions. Answered.

You'll need at least 21 days of data collection with a minimum of 10,000 daily events. The goal event (like churn) should have at least 200 true and 200 false occurrences over 30 days. This gives the model enough signal to make accurate predictions.

It depends on your business, but common examples include: user cancels subscription, user hasn't logged in for 30 days, usage drops significantly (fewer logins, fewer features used), or user submits negative feedback or a support ticket showing dissatisfaction. You define what churn means for you.

Once trained, the model segments users into groups like Champion, Regulars, Promising, Needs Attention, and At Risk. These categories are based on predicted churn likelihood, so you can treat each group differently instead of blasting everyone with the same message.

Yes. When configuring the agent, you can filter out users based on things like login date, feature usage frequency, subscription status, or support ticket history. This keeps your predictions focused on the users who actually matter for retention.

You've got options. Send personalized re-engagement emails with discounts or special offers, trigger SMS or webhook notifications to alert your customer success team to make follow-up calls, or display personalized messages on their dashboard when they log in. The idea is to reach them before they're fully gone.

You can add conditions in your journey to check email engagement and whether they open it. Click anything? If not, send a follow-up email after a few days. If they're still unresponsive after a call attempt, you can escalate to a higher support tier. The journey adapts based on what they do (or don't do).

Yes. You can create personalizations that display different messages depending on the user's risk level. High-risk users might see a "We miss you, here's 20% off" message when they log in, while low-risk users see tips about advanced features. Same dashboard, different experience.

Use Intempt's journey analytics to track user responses, opens, clicks, conversions, drop-offs at each step. Review regularly, adjust your strategies based on what the data shows, and keep retraining your model with new data so it stays accurate as user behavior evolves.

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Churn Risk Prevention: Keep Your Customers