# Funnel Analysis

Funnel Analysis shows how users move through a defined sequence of events. It helps you see where users continue, where they drop, and which audience converts better. This makes it easier to understand whether a journey works as expected or loses users before the final outcome.

In practice, this means you can look beyond total conversion and inspect the exact step where momentum weakens. That is often the fastest way to separate a targeting problem from a journey problem.

Use this page when you want to answer questions such as:

* Where do users drop?
* Which audience converts better?
* Did a release or campaign change the flow?

<figure><img src="/files/NG3Loa753vYdHzhBUGkM" alt=""><figcaption></figcaption></figure>

### When to use Funnel Analysis

Use funnels when you need to analyze a fixed path such as:

* onboarding,
* product discovery to purchase,
* checkout completion,
* feature adoption,
* or campaign-driven flows.

A funnel works best when the steps represent real progress. For example, **Product Viewed → Added to Cart → Checkout Started → Purchase Completed** describes a clear purchase path, while loosely related events usually make the result harder to interpret.

### What Funnel Analysis helps you answer

* Which step loses the most users?
* How does conversion change by segment or platform?
* Did a new release improve or hurt progression?
* Which campaigns bring higher-quality traffic?
* How many users finish the full journey?

These questions matter because the same top-line conversion rate can hide very different behaviors. Two funnels may end with a similar final rate, while one loses users early and the other loses them near the end.

<figure><img src="/files/nxrAx7DT8iIVYbwWAPYW" alt="" width="563"><figcaption></figcaption></figure>

### Core concepts

* **Funnel steps** represent events in the journey. Choose events that clearly show forward movement, not general activity.
* **Conversion** shows the share of users who move from the first step to the final step.
* **Drop-off** shows where users stop progressing. Large drop-offs usually point to friction, weak intent, or a technical issue.
* **Audience scope** lets you compare all users, a segment, or users affected by a specific push campaign.
* **Time scope** lets you analyze the funnel within the selected period or within a single session.
* **Excluded events** let you remove users who performed actions that break the intended flow.

Example funnel:

* **Product Viewed**
* **Added to Cart**
* **Checkout Started**
* **Purchase Completed**

Read these concepts together. A high-level conversion rate is useful, but the real value usually comes from seeing exactly where the journey weakens and which audience is affected.

<figure><img src="/files/aQyaLUFEo7Uq0vO6iD5p" alt="" width="375"><figcaption></figcaption></figure>

### Best practices

Keep steps meaningful and make sure each one reflects a real stage in the journey. Use events that clearly represent progress, avoid adding too many steps to one funnel, and compare similar audiences whenever possible.

When you see a large drop, do not stop at the funnel alone. Compare the result with [Event Insight](/netmera-user-guide/reports-and-analytics/analytics/event-insight.md) and [Profile](/netmera-user-guide/reports-and-analytics/analytics/profile.md) to understand whether the issue is related to behavior, platform, or audience composition.

### Related pages

* [Create New Funnel](/netmera-user-guide/reports-and-analytics/analytics/funnel-analysis/create-new-funnel.md)
* [Event Insight](/netmera-user-guide/reports-and-analytics/analytics/event-insight.md)
* [People Insight](/netmera-user-guide/reports-and-analytics/analytics/people-insight.md)


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