---
title: "How To Use Conversion Funnel Data To Diagnose Drop-Off Points"
slug: "how-to-use-conversion-funnel-data-to-diagnose-drop-off-points"
updated: 2025-12-26T11:42:30Z
published: 2025-12-26T11:42:30Z
canonical: "supporthub.usheru.com/how-to-use-conversion-funnel-data-to-diagnose-drop-off-points"
---

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

# How To Use Conversion Funnel Data To Diagnose Drop-Off Points

## Introduction

Understanding *where* and *why* users drop out of your funnel is critical to maximising the performance of a film or content release. Conversion funnel data gives marketers a clear, visual way to diagnose friction points, wasted spend, and underperforming traffic sources, *before* a campaign ends.

At a high level, every release operates across **two distinct phases**:

1. **Awareness Phase** *(****usheru Connect*** *only)* This phase focuses on discovery and intent-building, with conversions such as trailer views or page visits.
2. **Conversion Phase** *(****usheru Select*** *&* ***Connect****)* This phase measures meaningful outcomes, specifically, how effectively users progress from viewing showtimes to clicking through to cinemas or streaming services.

This article focuses exclusively on the **Conversion Phase**, where funnel analysis has the biggest impact on revenue and ROI.

Insights within usheru can be analysed:

- At a **high level** across all campaigns and traffic sources
- By **traffic source** (e.g. Paid, Organic Search, Email)
- At the **individual campaign or ad level**

This layered approach allows teams to move from broad trends to precise optimisation.

## Recommended Steps

**1. Start with *Showtimes Viewed***

**Showtimes Viewed** is the first critical conversion metric in the funnel. It represents the percentage of users who actually see showtimes on their screen after landing.

- **Target benchmark:** **85% or higher**
- **Why it matters:** If users don’t see showtimes, they can’t convert, regardless of campaign quality.

**What impacts this metric:**

- Showtimes not placed *above the fold*
- Poor landing-page layout
- Paid traffic landing on irrelevant pages
- Mistaken or low-intent clicks (common in some social campaigns)

**How to interpret drops:**

- A low percentage at campaign level often signals **high bounce rates**
- For paid social, it may indicate **creative-message mismatch**

### 2. Analyse *Redirects to Cinema or Streaming*

The most commercially important metric in the conversion phase is **Redirects to Cinema or Streaming Services**.

**Performance benchmarks:**

- **< 5%** → Underperforming (requires action)
- **5–15%** → Adequate performance
- **20%+** → Strong performance

**Expected patterns:**

- Higher redirect rates from:
  - Direct traffic
  - Organic Search
  - Email campaigns These users typically have higher intent and are actively seeking showtimes.

**Funnel shape matters:**

A *healthy funnel* shows smooth progression with no sharp contractions.

![](https://cdn.document360.io/54acc8b8-c8a5-4b1d-86af-cac0cfc1bfef/Images/Documentation/Screenshot 2025-12-23 at 08.14.29.png?sv=2026-02-06&spr=https&st=2026-10-14T01%3A16%3A14Z&se=2026-10-14T02%3A16%3A14Z&sr=c&sp=r&sig=K46%2BbXX7v7oxiv53ThWcZPqZch7RX9vuaJPPp0l1KdU%3D)

A *constricted funnel* highlights a clear drop-off and conversion issue.

![](https://cdn.document360.io/54acc8b8-c8a5-4b1d-86af-cac0cfc1bfef/Images/Documentation/Screenshot%202025-12-23%20at%2008.11.55.png?sv=2026-02-06&spr=https&st=2026-10-14T01%3A16%3A14Z&se=2026-10-14T02%3A16%3A14Z&sr=c&sp=r&sig=K46%2BbXX7v7oxiv53ThWcZPqZch7RX9vuaJPPp0l1KdU%3D)

- 
- 

Sharp drops at this stage usually point to:

- Poor showtime availability
- Friction in cinema selection
- Weak call-to-action clarity
- Misaligned traffic sources

**3. Compare by Traffic Source and Campaign**

Once overall performance is understood, segment the data:

- Compare **Paid vs Organic vs Email**
- Drill into **individual campaigns**
- Identify *which* sources drive quality engagement versus volume-only traffic

This is where funnel data becomes actionable rather than descriptive.

**4. Monitor Daily in the Run-Up to Release**

In the days leading up to a release, conversion behaviour can change rapidly.

**Best practice:**

- Review funnel performance **daily**
- Identify:
  - Campaigns delivering strong redirects
  - Campaigns consuming spend without conversion

Pair funnel data with:

- **Ad spend**
- **Cost per conversion**
- **Session duration**

**5. Use Session Length as an Early Warning Signal**

Session duration is a powerful *early-stage* indicator, especially for paid campaigns.

- **< 5 seconds average session time** → Low-quality traffic → Likely mis-targeting or accidental clicks → Should be paused or removed quickly

This allows teams to cut waste early, before it distorts overall funnel performance.

## Summary

Conversion funnel data is one of the most effective tools for diagnosing marketing performance during a release. By focusing on the **Conversion Phase**, teams can:

- Ensure showtimes are being seen
- Identify meaningful drop-off points
- Compare performance by traffic source and campaign
- Optimise spend based on *true* conversion outcomes
- Act quickly using session length and daily monitoring

A strong funnel shows steady progression with no major contractions. When sharp drops appear, they are signals, not failures, highlighting exactly where optimisation will have the greatest impact.