How is Vantage different from ChatGPT or Claude?

ChatGPT and Claude are great for one-off generation. Vantage is a full workspace. It connects your tools, tracks dependencies across projects, catches conflicts between products, and surfaces what needs your attention every morning. It also remembers every past decision, so a new PM can query across all projects and get cited answers in seconds.

Do I have to switch away from Notion or Linear?

No. You keep all your tools. Vantage connects to them and builds intelligence on top. When you're ready, you can push tickets to Linear or Jira. But the value starts before you create anything — just by connecting your tools and seeing what the intelligence layer surfaces.

What happens on day one?

You connect your tools — GitHub, Linear, Slack — 2 minutes each. Vantage indexes your existing data overnight. By the next morning, you see your first decision queue: what's stale, what conflicts, what changed. No manual setup. No templates to fill out.

What if I only manage one project?

Vantage works for single projects, but it shines when you manage 3–5 or more. Conflict detection, cross-project memory, and the decision queue are most valuable when you have multiple projects that need to stay in sync. If you manage one project, start with the free tier and see if the cited query engine alone saves you time.

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How does Vantage keep documents and tickets up to date?

When context shifts, you add the new information and Vantage rebuilds every connected deliverable. Documents, prototypes, and tickets all update. You review the changes, accept or reject each one, and approve. Nothing updates silently, and every change is traceable.

How do I get started?

Sign up free at app.vantageos.tech. Connect your tools, and generate your first grounded document within minutes. No credit card required. Upgrade when you need more projects or features.

How do I calculate churn rate in Amplitude?

Create an event segmentation chart showing unique users who performed any core event in the previous period but not in the current period, divided by total active users in the previous period. Alternatively, use Amplitude's Lifecycle chart which automatically categorizes users into new, current, resurrected, and dormant buckets.

What is a good churn rate for a SaaS product?

Monthly user churn rates below 5% are considered healthy for most SaaS products. Best-in-class products achieve 2-3% monthly churn. Revenue churn (MRR lost) is often more important than user churn — you want net negative revenue churn where expansion revenue from existing customers exceeds lost revenue from churned ones.

Can Amplitude predict which users will churn?

Amplitude's Predictions feature uses machine learning to score users by their likelihood to perform (or not perform) a specific event. You can train a prediction model on your churn event and Amplitude will generate a churn probability score for each user, which you can use to build at-risk cohorts for targeted intervention.

How-To2026-09-0311 min read

How to Track Customer Churn in Amplitude

Churn is the metric that determines whether your product has a future. A 5% monthly churn rate means you lose nearly half your user base every year, and no amount of acquisition spending can compensate for a leaky bucket. Understanding why users leave — and catching them before they do — requires deliberate analytics infrastructure.

Amplitude provides the behavioral analytics depth needed to go beyond surface-level churn numbers and understand the actions (or inaction) that predict churn. This guide walks you through defining churn for your product, instrumenting the right events, building predictive cohorts, and creating dashboards that make churn visible to your entire team.

Step-by-step guide

Define what churn means for your product

Before touching Amplitude, write down your churn definition. For a SaaS product, churn might mean a user who has not logged in for 14 consecutive days. For a marketplace, it might mean a user who has not completed a transaction in 30 days. The definition must be specific, measurable, and aligned with how your business actually loses value when a user disengages.

Analyze your current user activity distribution to find the natural drop-off threshold
Differentiate between user-level churn (individuals) and account-level churn (paying customers)
Document the churn definition and share it with the team so everyone measures the same thing

Instrument engagement and churn indicator events

Track the core engagement events that define an active user — login, key feature usage, content creation, or whatever represents real value delivery. Also track disengagement signals: failed actions, support ticket submissions, settings downgrades, and integration disconnections. These negative signals often predict churn days before the user actually leaves.

Define 3-5 core value events that indicate the user is getting value from your product
Track disengagement events like feature abandonment, error encounters, and billing page views
Ensure all events carry user properties for segmentation (plan, tenure, company size)

Build a retention analysis chart

In Amplitude, navigate to the Retention Analysis chart type. Select your activation event as the starting event and any engagement event as the return event. Set the retention window to weekly or daily depending on your product's natural usage frequency. This chart shows you exactly when users drop off and how retention curves differ between user segments.

Create an unbounded retention chart to see the overall retention curve shape
Break down retention by acquisition source, plan type, and onboarding completion
Compare retention curves for users who adopt key features versus those who do not

Create at-risk user cohorts

Build a behavioral cohort in Amplitude that identifies users showing churn signals. Define the cohort as users who performed a core value event in the last 30 days but have not performed any value event in the last 7 days. This catches users in the disengagement window before they fully churn, giving your team time to intervene.

Create a 'Previously Active, Now Quiet' cohort using the behavioral cohort builder
Create a 'Power User Declining' cohort for users whose weekly event count dropped by 50% or more
Sync these cohorts to your email tool or CRM for automated re-engagement campaigns

Analyze churn drivers with event segmentation

Use Amplitude's event segmentation to compare the behavior of churned users against retained users in their first 7 days. Look for actions that churned users skipped — these are likely part of your activation path. Also look for negative events that churned users experienced more frequently, like errors, long load times, or confusion-indicating behaviors like excessive navigation.

Create a comparison chart showing event frequency for churned versus retained users
Use Amplitude's Compass feature to find events most correlated with retention
Identify the activation milestone — the specific action after which retention jumps significantly

Build a churn monitoring dashboard

Create a dedicated Amplitude dashboard with these tiles: weekly churn rate trend, at-risk cohort size over time, retention curve by signup week, and a breakdown of churn by user segment. Set up Amplitude alerts to notify your team when the at-risk cohort grows beyond a threshold or when the weekly churn rate spikes above its rolling average.

Add a churn rate trend line showing the percentage of active users who churned each week
Include a stacked bar chart showing churn segmented by plan type and user tenure
Set up email alerts for when weekly churn exceeds the 90-day average by more than 20%

Common mistakes

Using a single churn definition for all user segments

A daily-use product and a monthly reporting tool have completely different activity patterns. A user who has not logged in for 7 days might be churned from a messaging app but perfectly normal for a monthly analytics tool. Define churn thresholds per product or feature area.

Measuring churn only at the account level

Account-level churn hides the reality that individual users within an account disengage one by one until the account owner finally cancels. Track user-level engagement within accounts to catch declining adoption before it reaches the cancellation stage.

Reacting to churn spikes without checking for data issues

A sudden jump in churn rate is more likely caused by a tracking bug, SDK update, or ad blocker increase than an actual product problem. Always verify the data pipeline before sounding the alarm on a churn spike.

Ignoring seasonal patterns in churn data

Many products see natural churn spikes during holidays, fiscal year ends, or industry-specific seasonal patterns. Compare churn to the same period last year, not just last month, to separate trend from noise.

Tips

Use Amplitude's Lifecycle chart to visualize the balance between new users, retained users, resurrected users, and churned users each week

Create a 'churn risk score' user property by combining multiple disengagement signals into a weighted formula that you sync back to your product for in-app interventions

Export your at-risk cohort to Braze, Iterable, or your email platform to trigger automated win-back campaigns based on behavioral data rather than time-based rules

Run an Amplitude Notebook analysis quarterly to deep-dive into churn patterns and share findings with the broader product team

How Vantage helps

Vantage helps PMs translate churn analysis insights into concrete product action. When your Amplitude data reveals that users who skip a specific onboarding step churn at 3x the rate, Vantage turns that insight into a prioritized requirement and implementation plan so the fix moves from dashboard to shipped feature.