Multi-channel attribution in Digital Marketing - Mini Project: Build & Apply

Understanding Multi-channel Attribution

📖 Scenario: You work as a marketing assistant for an online store. Your manager wants to understand how different marketing channels contribute to sales. You will create a simple model to track and analyze the impact of each channel.

🎯 Goal: Build a step-by-step model that shows how to collect data on marketing channels, set up a way to measure their impact, calculate the contribution of each channel, and summarize the results.

📋 What You'll Learn

Create a data structure to hold marketing channels and their touchpoints

Add a configuration variable to set a minimum contribution threshold

Calculate the contribution percentage of each channel

Summarize and finalize the attribution results

💡 Why This Matters

🌍 Real World

Marketers use multi-channel attribution to understand which marketing efforts drive sales and where to invest budget.

💼 Career

Knowledge of attribution models helps marketing analysts and managers optimize campaigns and improve return on investment.

1

Set up marketing channels data

Create a dictionary called channels with these exact entries: 'Email': 120, 'Social Media': 300, 'Paid Search': 180, 'Direct': 100. These numbers represent the number of customer touchpoints from each channel.

Digital Marketing

# Create the channels dictionary with exact entries
# Your code here

Need a hint?

Use a dictionary with channel names as keys and touchpoint counts as values.

2

Add minimum contribution threshold

Create a variable called min_threshold and set it to 0.1. This will represent the minimum percentage contribution (10%) a channel must have to be considered significant.

Digital Marketing

channels = {'Email': 120, 'Social Media': 300, 'Paid Search': 180, 'Direct': 100}
# Create min_threshold variable and set it to 0.1
# Your code here

Need a hint?

Use a simple variable assignment for the threshold value.

3

Calculate contribution percentages

Create a new dictionary called contributions. Use a for loop with variables channel and touchpoints to iterate over channels.items(). Calculate each channel's contribution as touchpoints divided by the total touchpoints. Store these values in contributions with the channel as the key.

Digital Marketing

channels = {'Email': 120, 'Social Media': 300, 'Paid Search': 180, 'Direct': 100}
min_threshold = 0.1
# Calculate total touchpoints
# Create contributions dictionary with percentage values
# Your code here

Need a hint?

First sum all touchpoints, then divide each channel's touchpoints by the total inside the loop.

4

Filter and summarize significant channels

Create a list called significant_channels that includes only the channels from contributions whose contribution is greater than or equal to min_threshold. Use a list comprehension with channel for channel, contribution in contributions.items() and the condition contribution >= min_threshold.

Digital Marketing

channels = {'Email': 120, 'Social Media': 300, 'Paid Search': 180, 'Direct': 100}
min_threshold = 0.1
total_touchpoints = sum(channels.values())
contributions = {}
for channel, touchpoints in channels.items():
    contributions[channel] = touchpoints / total_touchpoints
# Create significant_channels list with channels meeting min_threshold
# Your code here

Need a hint?

Use a list comprehension to filter channels by contribution.