Funnel Analysis

Funnels let you measure how users progress through a sequence of steps - like a signup flow, checkout process, or onboarding sequence. See where users drop off and identify opportunities to improve conversion.

How funnels work

A funnel is an ordered sequence of events (pageviews or custom events). Moneat calculates how many visitors completed each step and what percentage dropped off between steps.

Step 1: Visit /pricing         →  1,200 visitors  (100%)
Step 2: Click "Start Trial"    →    840 visitors   (70%)
Step 3: Complete Signup        →    504 visitors   (42%)
Step 4: First Service Created  →    302 visitors   (25.2%)

Key concepts

Strict ordering - Steps must occur in the defined order within a single session
Session-scoped - All steps must happen within the same visitor session
No time limit between steps - Steps can occur at any point during the session
Pageviews and custom events - Mix both types freely in a funnel

Creating a funnel

Via the dashboard

Navigate to Analytics → Funnels tab
Click New Funnel
Add steps by selecting event names or page paths
Click Analyze to see results

Via the API

HTTP

GET /v1/analytics/{projectId}/funnel?steps[]=pageview:/pricing&steps[]=Signup Start&steps[]=Signup Complete&period=30d

Each steps[] parameter defines one funnel step:

Format	Type	Example
`pageview:/path`	Pageview on a specific path	`pageview:/pricing`
`EventName`	Custom event	`Signup Complete`

Reading funnel results

The funnel response contains:

JSON

{
  "steps": [
    {
      "name": "pageview:/pricing",
      "visitors": 1200,
      "conversionRate": 100.0,
      "dropoffRate": 0.0
    },
    {
      "name": "Start Trial",
      "visitors": 840,
      "conversionRate": 70.0,
      "dropoffRate": 30.0
    },
    {
      "name": "Signup Complete",
      "visitors": 504,
      "conversionRate": 42.0,
      "dropoffRate": 28.0
    }
  ],
  "overallConversionRate": 42.0
}

Field	Description
`visitors`	Number of unique visitors who reached this step
`conversionRate`	Percentage of step-1 visitors who reached this step
`dropoffRate`	Percentage of previous-step visitors who did not reach this step
`overallConversionRate`	Percentage of step-1 visitors who completed the final step

Funnel examples

Signup flow

Step 1: pageview:/pricing
Step 2: Start Signup
Step 3: Complete Signup

Measures: How many pricing page visitors convert to signups.

E-commerce checkout

Step 1: Add to Cart
Step 2: pageview:/checkout
Step 3: Enter Payment
Step 4: Purchase Complete

Measures: Cart-to-purchase conversion rate and where buyers abandon.

Onboarding completion

Step 1: Complete Signup
Step 2: Create Service
Step 3: Install SDK
Step 4: First Event Received

Measures: How effectively new users complete onboarding.

Content-to-conversion

Step 1: pageview:/blog/getting-started
Step 2: pageview:/pricing
Step 3: Start Trial

Measures: How blog content drives trial signups.

Combining with filters

Apply any filter alongside a funnel to segment results:

HTTP

GET /v1/analytics/{projectId}/funnel
  ?steps[]=pageview:/pricing
  &steps[]=Signup Complete
  &period=30d
  &filters[]=country_code:is:US
  &filters[]=device_type:is:Desktop

This shows the funnel conversion rate for US desktop visitors only.

Best practices

Start broad, then narrow - Begin with 2–3 steps and add detail once you understand the high-level flow
Use meaningful step names - Name custom events clearly so funnels are self-documenting
Compare segments - Run the same funnel with different filters to find which audience segments convert best
Track both intent and completion - Pair "started" events with "completed" events (e.g., Start Checkout → Complete Purchase)
Monitor over time - Check funnel conversion rates weekly to catch regressions after product changes