12 Best Churn Prediction Software for SaaS

High customer churn is never a good sign for a SaaS. But it hits even harder when it’s a customer you marked as “safe” because they renew on time and never complain.

I’ve been there: One of my “safe” accounts had quietly dropped 40% in usage over two months. I didn’t see it until it was too late, and they left shortly after.

Churn prediction software would’ve flagged the warning signs early or at least told me where to look. That experience led me to write this guide for product managers and SaaS teams.

In this article, I break down the 12 best tools for predicting churn. I also added what comes next: a simple 4-step framework to retain customers by automating interventions.

What is customer churn prediction software?

Customer churn prediction software analyzes your customer data to identify which users are most likely to cancel their subscription. It does this by turning behavioral signals into a health score for each account.

Here’s how it works:

The software tracks signals like login frequency, feature usage, support activity, and NPS feedback. Those signals roll up into a health score. When the score falls below a set threshold, the system alerts your team. And then, they can intervene before the user hits “cancel.”

Most churn prediction software studies three types of signals:

• Activity signals: Drops in DAU/MAU ratio or fewer logins.
• Engagement signals: Shorter sessions, reduced feature usage, abandoned workflows.
• Sentiment signals: Low NPS scores, negative survey responses, or frustrated customer interactions.

Together, these signals reveal at-risk customers, giving you the chance to act early.

TL;DR: Best churn prediction platforms at a glance

In this list, you’ll find platforms that integrate smoothly into your workflows, deliver accurate predictions, and offer actionable recommendations beyond scores. They have a fast setup and other features that help teams intervene before churn happens.

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The top 12 tools for churn prediction and management

Let’s take a closer look at each churn prediction tool.

1. Userpilot

Best for: Product teams needing actionable insights and fast, no-code user interventions

G2 rating: 4.6/5 ⭐

Userpilot is an all-in-one product platform that helps SaaS teams understand why users disengage. It also helps them take action before they churn. Additionally, you can track retention trends through churn reports, behavioral analytics, and custom dashboards. This way, you see early which segments are at risk.

Beyond monitoring, Userpilot helps you run effective win-back and activation strategies directly inside the product. You can launch interactive walkthroughs, in-app nudges, targeted emails, and churn surveys without engineering support.

Userpilot AI, currently in beta, provides data-backed recommendations for the best actions to prevent churn. It also autonomously launches the right playbooks to engage, convert, or retain users. Join the open beta!

Key features

• Granular event tracking: Userpilot lets you track key user actions through Tracked Events. If someone stops performing value-generating actions, the system flags them so you can step in early. You can also use Autocapture and the Visual Event Labeler to tag events directly in the UI without writing code.

• Retention reports with cohorts: These monitor churn patterns over time. You can therefore compare cohorts, spot drop-off moments, and set reliable benchmarks for activation and long-term retention.

• Path analysis: It reveals where users go after they sign up. For example, users may hit dead ends or get stuck in confusing screens. Userpilot identifies exactly where the UX is causing frustration or early drop-off.

• Automated interventions: Userpilot does more than report churn signals. It lets you build flows (consisting of multiple elements such as tooltips, modals, and checklists) that trigger automatically when a user enters an “At-Risk” segment. Use those to re-engage users in real time.

• Sentiment analysis: Userpilot helps you run NPS surveys directly inside your product. Low scores act as clear churn warnings. Tag detractors and trigger follow-up flows instantly. You can also run churn surveys to learn why users leave and respond quickly.

• Session replays: They show the user stories behind the numbers. When you know where users struggle, hesitate, or abandon key workflows, fixing the problems causing churn becomes easy.

Pricing

• Starter: From $299/month (billed annually)
• Growth: Custom quote
• Enterprise: Custom quote

Customer voices

• Sonika S., a Program Manager at an enterprise company (> 1000 emp.) says:

The built-in analytics and usage tracking help me understand how users engage, which features are adopted, and where they drop off — a big plus for improving product UX.

• Arlo Gilbert, Founder and CEO of Osano, used Userpilot to reduce delinquent churn by 40%.

 

[CASE STUDY] ‘Significant delinquent churn reduction’ and 25% fewer support chat requests – how Osano uses Userpilot to push for more upgrades and Product-Led Growth

Learn how Osano achieved ‘Significant delinquent churn reduction’ and 25% fewer support chat requests with Userpilot!

userpilot.com

 

Considerations

Userpilot may not be a fit for early-stage startups because of its pricing and platform complexity (since Userpilot provides a comprehensive toolset, it takes some time to master all its features).

2. ChurnZero

Best for: Customer success teams managing accounts at scale

G2 rating: 4.7/5 ⭐

ChurnZero is a Customer Success platform built to help CSMs predict, manage, and reduce churn. It connects deeply with your CRM, support tools, and product usage data to create a unified customer view. What’s more, its “ChurnScore” blends signals from email, chat, feature adoption, and billing history to show which accounts need attention now.

Key features

• Command Center: Creates a daily, prioritized to-do list for CSMs based on customer health scores.
• Journey mapping: Visualizes customer lifecycle stages and highlights where accounts often stall or disengage.
• ChurnScore: Combines behavior, engagement, and sentiment data into a real-time churn prediction model.
• Playbook automation: Triggers email sequences or outreach tasks when specific risk conditions appear.

Pricing

• Undisclosed, custom quote only.

3. Gainsight

Best for: Large enterprises with complex customer portfolios

G2 rating: 4.5/5 ⭐

Gainsight is a success and product tool for companies with thousands of accounts and mature Customer Success operations. It excels at modeling highly complex customer health scores using dozens of weighted variables. This depth helps enterprises monitor high-value customer segments that drive most of their revenue and spot churn risk early.

Key features

• Horizon AI: Analyzes sentiment in emails, calls, and support tickets to predict churn signals that usage data alone won’t surface.
• Scorecards: Creates multi-layered, weighted health scores tailored to enterprise needs.
• Journey Orchestrator: Automates playbooks across email, CS outreach, and in-app actions when risk indicators appear.
• Risk alerts: Flags stakeholder turnover, contract changes, or sudden engagement drops.

Pricing

• Undisclosed, requires contacting the sales team.

4. Mixpanel

Best for: Data teams analyzing behavioral patterns to uncover churn drivers

G2 rating: 4.6/5 ⭐

Mixpanel is a pure product analytics platform, meaning that it doesn’t provide a health score by default, but it gives you the behavioral data you need to build one. However, you can use correlation analysis to learn which actions lead to customer retention and therefore predict churn.

Key features

• Signal reports: Identify which user actions correlate most strongly with long-term retention.
• Cohort analysis: Track how different user groups behave over time to pinpoint drop-off moments.
• Funnels: See exactly where users abandon key workflows that impact churn.
• Custom events: Build tailored metrics to monitor activation, engagement, and pre-churn behavior.

Pricing

• Free plan: Available forever, capped at 1M monthly events
• Growth: 1M monthly events free and $0.28 per 1K events after (volume discounts available)
• Enterprise: Custom quote

5. Baremetrics

Best for: SaaS businesses focused on financial and revenue churn

G2 rating: 4.6/5 ⭐

Baremetrics is a subscription analytics tool for businesses that want deep visibility into revenue churn, especially those using Stripe. It focuses on the financial side of attrition and offers powerful tools to reduce involuntary churn. Its “Recover” system automates dunning so failed payments don’t quietly erode your MRR.

Key features

• Recover: Automates dunning and payment recovery to reduce involuntary churn.
• Cancellation Insights: Collects real-time cancellation reasons with in-app exit forms.
• MRR and churn analytics: Tracks revenue churn trends, expansion, contraction, and retention.
• Forecasting tools: Helps model future MRR and churn scenarios.

Pricing

• Starting price: Pricing varies based on MRR but typically starts at $49/mo
• Enterprise: Custom quote

6. Vitally

Best for: Modern CS teams that need fast, flexible customer health tracking

G2 rating: 4.5/5 ⭐

Vitally bridges the gap between product analytics and Customer Success. It gives SaaS teams a unified place to monitor account health, track usage, and run playbooks. Built for B2B SaaS companies that want enterprise-grade CS capabilities, it avoids the slow, heavyweight feel of older platforms. Its speed and flexibility also make it a strong fit for scale-ups and mid-market teams.

Key features

• Success traits: Define the behaviors of a healthy customer (e.g., “daily activity,” “NPS > 8”) and get alerted when an account drifts off track.
• Playbooks: Automate outreach sequences and CS actions when users hit risk thresholds.
• Project management: Assign, track, and complete CS remediation tasks directly inside Vitally.
• Health scoring: Combine product usage, sentiment, and account attributes into customizable health models.

Pricing

• Undisclosed, custom pricing only

7. Zendesk

Best for: Support-led churn prediction and reducing churn caused by poor service

G2 rating: 4.3/5 ⭐

Zendesk is best known as a customer support platform. But thanks to its newer AI and sentiment analysis capabilities, it now has a churn prediction layer. Zendesk can analyze ticket patterns, frustration signals, and response quality. This reduces poor support, a top driver of churn, and provides teams with an early warning system.

Key features

• AI sentiment analysis: Flags “rage tickets” automatically by analyzing tone and urgency.
• Churn prediction from support patterns: Identifies at-risk customers based on ticket frequency, escalation, or repeated complaints.
• Agent performance insights: Surfaces slow responses or poor resolutions that correlate with churn.
• Ticket anomaly detection: Alerts your team when support behavior deviates from normal patterns.

Pricing

• Support Team: From $25/agent/month
• Suite Team: From $69/agent/month
• Suite Professional: From $149/agent/month
• Suite Enterprise: From $219/agent/month

8. Hotjar

Best for: Understanding why users churn through qualitative insights

G2 rating: 4.3/5 ⭐

Hotjar complements your analytics stack by showing the human side of churn. While product analytics tells you what users did, Hotjar reveals why they struggled through heatmap analysis, recordings, and in-page feedback. That is why it’s especially useful for uncovering UX issues, confusing flows, or moments of frustration that push users to churn.

Key features

• Session recordings: Spot rage-clicks, hesitation, and abandonment points that signal churn risk.
• Heatmaps: Reveal where users focus, ignore, or get stuck in key workflows.
• Feedback widgets: Capture real-time sentiment tied to specific pages or actions.
• Funnels (Observe): Identify where users consistently drop off before completing critical steps.

Pricing

• Growth: From $49/month
• Pro: Custom pricing
• Enterprise: Custom pricing

9. ProfitWell

Best for: Subscription churn prediction and automated recovery

G2 rating: 4.8/5 ⭐

ProfitWell, also ProfitWell Metrics (now part of Paddle), specializes in subscription intelligence. This makes it ideal for SaaS teams focused on revenue churn. Like Baremetrics, its prediction models rely on billing behavior, benchmarking, and payment patterns. That is how it surfaces revenue risk long before a customer fully churns.

Key features

• Retain: Automates failed-payment recovery with intelligent retry logic to reduce involuntary churn.
• Engagement metrics by plan: Highlights usage and retention gaps across billing tiers (e.g., Enterprise vs Pro).
• Revenue recognition & forecasting: Predicts revenue shifts tied to churn patterns.
• Benchmarking: Compares your churn health to similar SaaS companies in your segment.

Pricing

• Free (analytics)

10. Retently

Best for: Predicting churn through customer sentiment and survey analytics

G2 rating: 4.7/5 ⭐

Retently is a customer feedback and sentiment-analysis platform built around NPS, CSAT, and CES surveys. It identifies churn risk by analyzing trends in customer sentiment. It also captures the language users use in open-text responses. For SaaS teams that rely heavily on feedback loops, Retently provides an early-warning system rooted in “what customers feel.”

Key features

• Advanced survey engine: Automate NPS, CSAT, and CES surveys with targeted delivery to at-risk segments.
• AI-powered text analysis: Detects churn signals by analyzing sentiment, themes, and emotion in open-ended responses.
• Trend insights: Reveal long-term sentiment shifts that precede churn.
• Automated workflows: Trigger follow-up emails or alerts when detractors appear.

Pricing

• Basic: From $100/month
• Pro: From $299/month

11. Pecan

Best for: Data teams building advanced, AI-driven churn prediction models

G2 rating: 4.7/5 ⭐

Pecan is a predictive analytics platform that helps data teams build churn-prediction models without heavy manual coding. It pulls in your product, billing, and historical customer data, then uses machine learning to identify the behavioral patterns most strongly linked to churn. For SaaS companies with rich datasets, it turns raw activity logs into clear, reliable churn forecasts your team can act on.

Key features

• Automated ML modeling: Builds churn prediction models based on your historical data with minimal setup.
• Behavioral insights: Identify the exact events and patterns that increase churn likelihood.
• What-if simulations: Test the impact of changes (e.g., faster onboarding, better support) on predicted churn.
• Data integrations: Connects directly to warehouses like Snowflake, BigQuery, and Redshift.

Pricing

• Starter: From $950/month
• Team: From $1750/month
• Business: From $2500/month

12. ProsperStack

Best for: Reducing churn during the cancellation process

G2 rating: 5/5 ⭐ (only 12 reviews)

ProsperStack’s specialty is saving customers at the moment they decide to leave. It replaces your default cancellation page with a dynamic, personalized flow that offers incentives, gathers feedback, and presents tailored alternatives.

Key features

• Dynamic cancellation flows: Personalized offers, pause options, or plan downgrades based on user profile and behavior.
• Real-time churn insights: Tracks why users cancel and surfaces emerging trends.
• Incentive testing: Experiment with discounts, extensions, or alternative plans to see what best retains each segment.
• No-code editor: Build and deploy cancellation experiences without engineering involvement.

Pricing

• Grow: From $200/month
• Prosper: From $750/month
• Enterprise: Custom pricing

What are the benefits of churn prediction software?

Reports tell you what has already happened. A churn prediction software one-ups them: It tells you what’s about to happen. And the early warning helps you prevent customer churn.

By implementing predictive analytics into your workflow, you unlock three major competitive advantages:

1. Proactive revenue protection: Instead of conducting exit interviews to find out why you lost revenue, you receive alerts while the user is still active. This allows you to secure Annual Recurring Revenue (ARR) that would otherwise be lost.
2. Resource optimization: Your CSM team cannot call every customer. Predictive software acts as a triage system because it surfaces accounts with low health scores. This helps CSMs focus their time on high-value customers with the highest churn risk.
3. Product loop closure: It helps you identify the specific features (or lack thereof) that correlate with cancellations. That insight feeds directly into your product roadmap, showing you where onboarding fails, which features aren’t delivering value, and where friction is costing you users.

How to choose churn prediction software?

Use this practical checklist to evaluate which of the 12 churn prediction software is right for you to reduce attrition:

1. Evaluate scalability and cost models

Make sure the pricing is transparent and grows fairly with your business. One way to do that is to look for generous limits on MAUs, events, or usage so you don’t hit a wall months in. Also, check how many “must-have” features sit behind add-ons, as they inflate bills. And lastly, always ask upfront about renewal increases to avoid surprises later.

2. Audit the integration ecosystem

A churn prediction software is useless in a silo. It must sync cleanly with your CRM (HubSpot, Salesforce) and your product data. So, look for true bi-directional sync so health scores and risk alerts flow back into your CRM for Sales and CS. Not only does it integrate with platforms such as Segment, Hubspot, and Salesforce, but its all-in-one nature also helps avoid a bloated toolstack that poses a risk of data leaks.

3. Prioritize direct actionability

You might argue that you can build a predictive model using raw data and a BI tool. While true, this approach creates a dangerous latency gap. By the time you analyze the data, export the list, and instruct your CS team to act, the customer is gone. So, instead, prioritize tools that allow for direct intervention (in-app messages, flows) the moment a risk signal is detected. This is the difference between churn prevention and churn autopsy.

4. Verify ease of setup and time-to-value

Implementation shouldn’t take quarters. So, focus on tools that launch with a simple JavaScript snippet. It is also important that such tools are self-serve afterward through drag-and-drop, no-code editors. This way, marketing, success, and product teams can build interventions without waiting for development sprints. By extension, these steps will accelerate your time-to-value and your time-to-retention.

4 Steps to predict churn risk and increase retention

Buying churn prediction software doesn’t fix churn on its own. Retention comes from how you use it. That’s why I added my exact workflow to guide you.

Follow these steps to spot risk early and push retention upward:

Step 1: Reverse-engineer your “red flag” metrics

You can’t predict churn unless you know what a healthy user looks like. So, start by studying your power users. Identify the behaviors they repeat consistently.

For example, power users may be exporting weekly reports, inviting teammates, or completing key workflows. These are your “green flags.” If anyone stops, such a user becomes at “risk.”

In Userpilot, creating such a segment is easy. The criteria might be: Last seen > 14 days ago AND Feature usage count < 5. This dynamic segment will automatically populate with users who fit the criteria.

Step 2: Automate the intervention

Once you’ve identified customers at risk, don’t rely on a human to spot the pattern. Intervene automatically the moment the customer slips into the “At-Risk” segment.

Here are two sample scenarios to see how it’s done:

• Scenario A (User goes dormant): If a user hasn’t logged in for a while, trigger an automated win-back email through your CRM integration. A gentle prompt, paired with a resource or shortcut, often reactivates faster than manual outreach.
• Scenario B (Feature usage drops): If a user stops using a core feature, trigger an in-app nudge to remind them of the product value. E.g., “Quick tip: This report can save you up to 5 hours a week.”

Step 3: Establish a customer feedback loop

Waiting for an exit survey is reacting too late. Instead, trigger short microsurveys at key friction points, e.g., when users are confused, stuck, or hesitating.

These real-time signals surface issues long before they turn into churn. So act.

For instance, say a user reports frustration, offer help instantly. Link them to your Resource Center, surface a relevant guide, or route them directly to support. Catching friction in this moment is one of the fastest ways to save a slipping customer.

Step 4: Verify your impact with cohort analysis

Your churn model isn’t finished until you validate that it actually works. So, use cohort analysis to compare retention across signups from different months.

The goal is simple: confirm that the users you onboarded and intervened with this month are sticking around longer than those from six months ago.

If users who eventually churned were not flagged by your at-risk criteria, that’s a signal your model needs refinement. In other words, adjust your inputs (feature usage, login patterns, and sentiments) until the model consistently identifies the users most likely to leave.

Manage, predict, and reduce churn with Userpilot

Your users are constantly sending signals through their clicks, their silence, and their support tickets. The right churn prediction software translates those signals into clear, actionable next steps.

This is where Userpilot shines. It turns customer behavior patterns like “User hasn’t clicked Publish in 10 days” into “This account is at risk, intervene now.” And when paired with the right strategy, the results are real: Osano used Userpilot to deploy interactive walkthroughs and a resource center, cutting their delinquent churn by 40%.

You can achieve similar results with Userpilot’s analytics, customer segmentation, and in-app engagement tools.

Book a demo today and start reducing customer churn with data-backed precision!

Turn Behavioral Signals into Higher Retention Rates using Userpilot Churn Prediction Software

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