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Multi-Channel Funnels

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Introduction

Multi-Channel Funnels (MCF) in Google Analytics provide insights into how different marketing channels work together to create conversions. This feature helps you understand the customer journey and the role each channel plays in driving conversions.

Key Concepts

  1. Conversion Path: The sequence of interactions (clicks, views, etc.) that lead to a conversion.
  2. Assisted Conversions: Conversions that were influenced by a channel but not directly attributed to it.
  3. Top Conversion Paths: The most common sequences of interactions that lead to conversions.
  4. Time Lag: The amount of time it takes for a user to convert after their first interaction.
  5. Path Length: The number of interactions it takes for a user to convert.

Understanding Multi-Channel Funnels Reports

  1. Overview Report

The Overview report provides a summary of the key metrics related to multi-channel funnels, including assisted conversions, top conversion paths, and the value of each channel in the conversion process.

  1. Assisted Conversions Report

This report shows the number of conversions and the value of those conversions that each channel assisted. It helps you understand the indirect impact of each channel.

  1. Top Conversion Paths Report

This report displays the most common sequences of interactions that lead to conversions. It helps you identify the typical paths users take before converting.

  1. Time Lag Report

The Time Lag report shows the time it takes for users to convert after their first interaction. This helps you understand the length of your sales cycle.

  1. Path Length Report

The Path Length report shows the number of interactions it takes for users to convert. This helps you understand the complexity of the customer journey.

Practical Example

Let's look at a practical example to understand how to use Multi-Channel Funnels in Google Analytics.

Example Scenario

You run an e-commerce website and want to understand how different marketing channels contribute to sales.

Steps to Analyze Multi-Channel Funnels

  1. Navigate to Multi-Channel Funnels: Go to Conversions > Multi-Channel Funnels in Google Analytics.
  2. Select the Date Range: Choose the date range you want to analyze.
  3. View the Overview Report: Start with the Overview report to get a summary of key metrics.
  4. Analyze Assisted Conversions: Go to the Assisted Conversions report to see which channels are assisting in conversions.
  5. Examine Top Conversion Paths: Check the Top Conversion Paths report to identify common paths users take before converting.
  6. Review Time Lag and Path Length: Use the Time Lag and Path Length reports to understand the time and number of interactions it takes for users to convert.

Code Example

While Google Analytics does not require coding for basic usage, you can use the Google Analytics API to extract Multi-Channel Funnels data programmatically. Here’s an example in Python:

from googleapiclient.discovery import build
from oauth2client.service_account import ServiceAccountCredentials

# Define the scope
scope = ['https://www.googleapis.com/auth/analytics.readonly']

# Load the credentials
credentials = ServiceAccountCredentials.from_json_keyfile_name('path_to_your_service_account.json', scope)

# Build the service object
analytics = build('analytics', 'v3', credentials=credentials)

# Query the Multi-Channel Funnels data
response = analytics.data().mcf().get(
    ids='ga:YOUR_VIEW_ID',
    start_date='30daysAgo',
    end_date='today',
    metrics='mcf:totalConversions',
    dimensions='mcf:sourcePath'
).execute()

# Print the response
print(response)

Practical Exercise

Exercise

  1. Navigate to the Multi-Channel Funnels section in Google Analytics.
  2. Select a date range of the last 30 days.
  3. Identify the top three channels that assist in conversions.
  4. Analyze the top conversion paths and note the most common path.
  5. Determine the average time lag for conversions.

Solution

  1. Go to Conversions > Multi-Channel Funnels.
  2. Select the date range of the last 30 days.
  3. In the Assisted Conversions report, identify the top three channels with the highest assisted conversions.
  4. In the Top Conversion Paths report, note the most common path.
  5. In the Time Lag report, find the average time it takes for users to convert.

Common Mistakes and Tips

  • Ignoring Assisted Conversions: Don’t focus solely on last-click conversions. Assisted conversions provide valuable insights into the customer journey.
  • Overlooking Time Lag and Path Length: These metrics help you understand the complexity and duration of the customer journey.
  • Not Segmenting Data: Use segments to analyze different user groups and their conversion paths.

Conclusion

Multi-Channel Funnels in Google Analytics provide a comprehensive view of how different marketing channels contribute to conversions. By understanding the customer journey and the role of each channel, you can optimize your marketing strategies and improve conversion rates. In the next section, we will delve into Attribution Models to further enhance your understanding of channel performance.

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