> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/mixpanel/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Funnels

> Measure conversions through a series of events

# Funnels: Measure Conversions

Funnels allow you to examine how users perform events in a series, calculating conversions from one event to another within a particular time window. This helps identify where users drop off and which segments convert best.

<img src="https://mintlify.s3.us-west-1.amazonaws.com/mixpanel-docs/funnels_result_header.png" alt="Funnels Overview" />

## Use Cases

Funnels help you answer critical conversion questions:

### Signup and Onboarding

* What percent of users complete the signup funnel within 7 days?
* At what step do most users drop off?
* How long does it take users to complete onboarding?

### Purchase and Checkout

* What's the conversion rate from viewing to purchasing?
* Which payment methods have the highest completion rates?
* How has checkout conversion changed over time?

### Feature Adoption

* What percent of users complete the tutorial?
* How many users go from feature discovery to active usage?
* Which user segments adopt features fastest?

### A/B Testing

* How did the A/B test impact signup conversion?
* Which variant drives better checkout completion?
* Do regional differences affect conversion rates?

## Quick Start

Let's build a funnel to answer:

> What percent of iOS users convert from viewing a product to completing purchase within 7 days?

### Step 1: Define Funnel Steps

A funnel consists of a sequence of events. Add events in the order users should perform them:

<img src="https://mintlify.s3.us-west-1.amazonaws.com/mixpanel-docs/funnels_beta_1.png" alt="Funnels Steps" />

**Example Funnel:**

1. Product Viewed
2. Add to Cart
3. Checkout Started
4. Purchase Completed

<Note>
  You can save funnel behaviors and reuse them across reports. Learn more about [Saved Metrics and Behaviors](/docs/features/saved-metrics-and-behaviors).
</Note>

### Step 2: Choose Measurement

By default, funnels measure the conversion rate (percentage of users who complete all steps).

<img src="https://mintlify.s3.us-west-1.amazonaws.com/mixpanel-docs/funnels_beta_2.png" alt="Funnels Measurement" />

**Available Measurements:**

* **Conversion Rate** - Percentage completing all steps
* **Step Rate** - Conversion at each individual step
* **Unique Users** - Count of converting users
* **Total Conversions** - Count of conversion instances
* **Average Time to Convert** - Time between first and last step

### Step 3: Add Filters

Filter to specific user segments or event properties:

<img src="https://mintlify.s3.us-west-1.amazonaws.com/mixpanel-docs/funnels_beta_3.png" alt="Funnels Filters" />

**Example Filters:**

* Platform = "iOS Native"
* Country = "United States"
* User Type = "Premium"
* Price > 50

### Step 4: Apply Breakdowns

Segment your funnel to compare conversion across groups:

<img src="https://mintlify.s3.us-west-1.amazonaws.com/mixpanel-docs/funnels_beta_4.png" alt="Funnels Breakdowns" />

**Example Breakdowns:**

* UTM Source (marketing channel)
* Device Type (mobile, tablet, desktop)
* User Plan (free, premium, enterprise)
* Geographic region

### Step 5: Select Visualization

<img src="https://mintlify.s3.us-west-1.amazonaws.com/mixpanel-docs/funnels_beta_5.png" alt="Funnels Visualization" />

**Chart Options:**

* **Funnel Steps** - Classic funnel view showing drop-offs
* **Line Chart** - Conversion trends over time
* **Bar Chart** - Compare segments side-by-side
* **Metric** - Single conversion rate number

## Key Concepts

### Conversion Window

The maximum time users have to complete the funnel from the first step.

**Common Windows:**

* 1 hour - For rapid workflows (checkout)
* 1 day - For same-session flows (onboarding)
* 7 days - For multi-session flows (feature adoption)
* 30 days - For long consideration cycles (B2B purchases)

<Note>
  Users must complete all steps in order within the conversion window to be counted as converted.
</Note>

### Counting Methods

How users are counted when they go through the funnel multiple times:

**Uniques**

* Each user counted once, on their first entry
* Best for understanding unique user conversion
* Example: "What percent of users complete signup?"

**Totals**

* All funnel entries counted, users can convert multiple times
* Best for measuring repeat behaviors
* Example: "How many purchases are completed?"

**Sessions**

* All steps must occur in the same session
* Best for same-session workflows
* Example: "How many in-session checkouts are completed?"

### Step Order

By default, users must complete steps in the exact order specified. You can relax this:

**Exact Order**

* Steps must occur in sequence
* Other events can happen between steps
* Most common setting

**This Order or Any Order**

* Steps can occur in any sequence
* Useful for flexible workflows

## Funnel Visualizations

### Funnel Steps View

The classic funnel visualization shows:

* Total users entering each step
* Conversion rate to next step
* Overall conversion rate
* Drop-off percentage at each step

**Identify Issues:**

* Large drop-offs indicate friction points
* Compare segment performance
* Track conversion rate changes

### Trends View

Line chart showing how conversion changes over time:

* Spot seasonal patterns
* Measure impact of changes
* Compare time periods
* Track growth or decline

### Time to Convert

Understand how long conversions take:

* Median time to convert
* Distribution of conversion times
* Identify slow converters
* Optimize for speed

## Advanced Features

### Exclusion Steps

Exclude users who perform certain events:

**Example:**

* Step 1: Sign Up Started
* Exclude: Error Shown
* Step 2: Sign Up Completed

**Result:** Only users who didn't see errors are counted.

### Hold Property Constant

Require the same property value across all steps:

**Example:**

* Hold "Product ID" constant
* Measures users who view and purchase the same product
* Filters out users who switch products mid-funnel

<Note>
  This is powerful for multi-product funnels where you want to track single-product conversion journeys.
</Note>

### Breakdowns and Segments

Compare conversion across up to 25 different segments:

* Identify high-performing segments
* Find underperforming groups
* Guide optimization efforts
* Personalize experiences

### View Users

Click any funnel step to see:

* Users who completed that step
* Users who dropped off
* Save as cohort for further analysis
* Export user lists

## Real-World Examples

### Example 1: Signup Funnel

**Query:**

* Steps: Landing Page → Sign Up Started → Email Verified → Profile Completed
* Conversion Window: 7 days
* Counting: Uniques
* Breakdown: UTM Source

**Insights:**

* Overall conversion: 18.5%
* Biggest drop-off: Email verification (40% drop)
* Top channel: Organic search (22% conversion)
* Action: Simplify email verification process

### Example 2: Purchase Funnel

**Query:**

* Steps: Product Viewed → Add to Cart → Checkout Started → Purchase
* Conversion Window: 1 day
* Counting: Totals
* Breakdown: Device Type
* Filter: Country = "United States"

**Insights:**

* Mobile conversion: 3.2%
* Desktop conversion: 8.7%
* Mobile drop-off at checkout: 65%
* Action: Optimize mobile checkout experience

### Example 3: Feature Adoption

**Query:**

* Steps: App Opened → Feature Discovered → Feature Used → Feature Activated
* Conversion Window: 30 days
* Counting: Uniques
* Breakdown: User Cohort (by signup date)

**Insights:**

* Recent cohorts convert faster (14 days vs 21 days)
* Overall adoption: 45%
* Discovery to usage: 72% conversion
* Action: Improved onboarding helps new users

### Example 4: Multi-Step Onboarding

**Query:**

* Steps: Sign Up → Tutorial Step 1 → Tutorial Step 2 → Tutorial Step 3 → First Action
* Conversion Window: 1 hour
* Counting: Sessions
* Visualization: Funnel Steps

**Insights:**

* Tutorial Step 2 has 55% drop-off
* Total completion: 22%
* Average time: 8 minutes
* Action: Simplify or skip Tutorial Step 2

## Optimization Strategies

### Identify Friction Points

1. Look for largest drop-offs between steps
2. Compare drop-off rates to benchmarks
3. Analyze users who drop off vs those who convert
4. Test solutions to reduce friction

### Segment Analysis

1. Break down by user properties (plan, region, device)
2. Find high-performing segments
3. Understand what makes them successful
4. Apply learnings to other segments

### Time Analysis

1. Measure time to convert at each step
2. Identify steps that take too long
3. Look for users who drop off after delays
4. Optimize slow steps

### A/B Testing

1. Create separate funnels for test variants
2. Compare conversion rates
3. Analyze conversion at each step
4. Measure statistical significance

## Tips for Effective Funnel Analysis

<Note>
  **Define Clear Steps**: Choose events that represent meaningful milestones in the user journey, not every intermediate action.
</Note>

<Note>
  **Set Appropriate Windows**: Match your conversion window to user behavior. Too short misses conversions; too long inflates rates.
</Note>

<Note>
  **Use Exclusions Carefully**: Exclusion steps remove users entirely from the analysis, even if they later convert.
</Note>

<Note>
  **Compare Time Periods**: Always compare funnels over different time periods to spot trends and validate hypotheses.
</Note>

<Note>
  **Drill Into Drop-Offs**: Click steps to view users who dropped off, then analyze their characteristics to understand why.
</Note>

## Common Questions

**Q: Can users skip steps in a funnel?**

A: No, users must complete all steps in order (unless you select "any order" mode).

**Q: What if a user does Step 1 twice before Step 2?**

A: With "Uniques" counting, only the first Step 1 is used. With "Totals", each Step 1 starts a new potential conversion.

**Q: How do I analyze users who drop off?**

A: Click any funnel step and select "View Users" → "Did not convert". You can save these users as a cohort.

**Q: Can I compare funnels across date ranges?**

A: Yes! Use the date comparison feature to overlay multiple time periods on the same chart.

## Next Steps

* Learn about [Saved Metrics and Behaviors](/docs/features/saved-metrics-and-behaviors)
* Explore [Flows](/reports/flows) to discover user paths
* Create [Cohorts](/reports/cohorts) from funnel segments
* Monitor funnels on [Boards](/reports/boards)