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 you calculate a customer health score in Amplitude?

Create behavioral cohorts based on engagement frequency, feature breadth, and core workflow completion. Assign each account to a health tier (Healthy, At Risk, Dormant) using rules like 'performed core action 3+ times in 7 days.' For a numeric score, use a weighted formula combining these signals in Amplitude's formula feature or export to a downstream tool.

What events should you track for customer health?

Track the three to five events most correlated with retention: login frequency, core value-delivery action completion, feature breadth (distinct features used per period), collaboration actions (invites, shares), and expansion signals (new seat additions, plan upgrades). Validate these against your actual churn data to confirm they are predictive.

How often should you review a customer health dashboard?

Review the dashboard weekly in a dedicated CS sync, with automated Slack alerts for threshold breaches between meetings. Monthly, run a deeper analysis to validate that your health definitions still correlate with actual churn and expansion outcomes. Recalibrate thresholds quarterly as your product and customer base evolve.

How-To2026-09-0311 min read

How to Build a Customer Health Dashboard in Amplitude

Customer health is the leading indicator that most product teams measure too late. By the time a customer reaches out to cancel, the behavioral signals have been flashing red for weeks. Amplitude's behavioral analytics platform lets you build a customer health dashboard that synthesizes usage patterns into actionable scores — without needing a dedicated data engineering team.

This guide covers building a multi-signal health dashboard that tracks engagement frequency, feature adoption breadth, and critical workflow completion rates at the account level. You will set up cohorts for at-risk and healthy customers, create composite health scores, and configure alerts that notify your CS team before a customer goes silent.

Step-by-step guide

Define your health signal events

Before building anything in Amplitude, identify the three to five events that most strongly correlate with retention. Typically these are: login frequency, core workflow completion (the action that delivers your product's primary value), feature breadth (number of distinct features used per week), and collaboration actions (invites, shares, comments). Document these in a shared spreadsheet with exact event names.

Export your event taxonomy from Amplitude's Data section
Cross-reference with your renewal and churn data to identify predictive events
Validate with your CS team — they often know which behaviors signal trouble before the data confirms it

Create account-level behavioral cohorts

Navigate to Amplitude's Cohorts section and create cohorts that represent health tiers. Start with 'Healthy' (performed core action 3+ times in the last 7 days), 'At Risk' (performed core action 0-1 times in the last 14 days), and 'Dormant' (no events in the last 30 days). Use the group-by feature to analyze at the account level, not individual user level.

Go to Cohorts > New Cohort > Behavioral
Set the group analytics property to your account identifier (e.g., company_id)
Define each tier with clear, non-overlapping criteria

Build the engagement frequency chart

Create a Segmentation chart showing daily or weekly active accounts over the last 90 days, segmented by your health cohorts. This gives you the trend line — is the 'At Risk' cohort growing or shrinking? Layer on a stickiness chart (DAU/MAU ratio) to see how habitual usage is across your customer base.

New Chart > Segmentation > Any Active Event, group by account ID
Apply cohort filters to segment the chart by health tier
Add a second chart showing DAU/MAU ratio for a stickiness view

Add feature adoption breadth tracking

Create a chart that counts the number of distinct event types each account triggers per week. Amplitude's 'Uniques' metric on a property group lets you measure this. Accounts that use only one feature are fragile — one bad experience and they leave. Accounts using four or more features have built the product into their workflow.

Create a Segmentation chart with event type as a group-by property
Use 'Uniques' aggregation on the account-level group
Set up a distribution chart to visualize the spread of feature adoption across accounts

Track critical workflow completion rates

Build a Funnel chart for your product's core workflow — the sequence of steps that delivers the primary value. For example, if you are a project management tool: create project > add tasks > invite teammate > complete first task. Measure completion rate at the account level and watch for accounts whose completion rate drops over time.

Create a Funnel chart with each step in your critical workflow
Group by account ID to see per-account completion rates
Set the conversion window to match your expected workflow duration

Assemble the dashboard and add alert thresholds

Create a new dashboard and arrange your charts in priority order: overall health distribution at the top, engagement trends in the middle, and feature adoption and funnel completion at the bottom. Add text blocks explaining each section for stakeholders who are not Amplitude-native. Configure webhook alerts for when the 'At Risk' cohort exceeds a threshold percentage.

Go to Dashboards > New Dashboard and name it 'Customer Health'
Drag charts into a logical layout with summary metrics at the top
Set up a Slack webhook alert that fires when At Risk accounts exceed 20% of total

Common mistakes

Measuring individual user health instead of account health

A single power user at an account can mask that the rest of the team has stopped using the product. Always analyze at the account or company level using Amplitude's group analytics, not at the individual user level. The account is what renews, not the person.

Using login counts as the only health signal

Logins tell you someone opened the app, not that they got value from it. A user who logs in daily but never completes the core workflow is not healthy — they are frustrated. Always include at least one value-delivery event in your health definition.

Setting static thresholds without seasonal adjustment

Usage naturally drops during holidays and summer months. A static 'At Risk' threshold will generate false alarms during predictable dips. Use relative thresholds (e.g., 50% below that account's own trailing average) rather than absolute numbers.

Tips

Export your At Risk cohort weekly to your CRM so customer success reps can run targeted outreach campaigns without logging into Amplitude.

Add a 'Last Active' property chart so you can instantly see which accounts have gone dark in the last 7, 14, and 30 days.

Create a 'Health Trend' notebook in Amplitude that tracks cohort sizes over time — a growing At Risk cohort is the single most important metric for your CS team.

Use Amplitude's Predict feature if available on your plan to get ML-based churn probability scores alongside your rule-based cohorts.

How Vantage helps

Vantage's analytics integration lets you pull Amplitude cohort data directly into your product context, so when you are writing a PRD for a retention initiative, the actual health metrics and at-risk account counts are embedded in the generation context. This means your requirements are grounded in real data, not guesswork about which customers are struggling.