Challenge: Implement a Linear Attribution Model
In multi-channel marketing, customers often interact with several touchpoints before converting. Linear attribution addresses the challenge of fairly distributing credit by assigning equal value to each channel involved in a customer's journey. This approach ensures that no single channel is over- or under-valued, making it easier for you to understand the collective impact of your marketing efforts. By using linear attribution, you can more accurately assess the performance of each channel, optimize your budget allocation, and foster collaboration between different marketing teams.
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Write a function that implements a linear attribution model for marketing channels using a DataFrame of customer journeys. Each row contains a list of channels and a conversion indicator. Assign equal credit to each unique channel in journeys where a conversion occurred, and summarize the total conversions attributed to each channel.
- Iterate through each row in the DataFrame.
- For rows where a conversion occurred, distribute equal credit to each unique channel listed in the
channelscolumn. - Accumulate the total credit for each channel across all journeys.
- Return a DataFrame with columns
channelandtotal_conversionssummarizing the results.
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In multi-channel marketing, customers often interact with several touchpoints before converting. Linear attribution addresses the challenge of fairly distributing credit by assigning equal value to each channel involved in a customer's journey. This approach ensures that no single channel is over- or under-valued, making it easier for you to understand the collective impact of your marketing efforts. By using linear attribution, you can more accurately assess the performance of each channel, optimize your budget allocation, and foster collaboration between different marketing teams.
Swipe to start coding
Write a function that implements a linear attribution model for marketing channels using a DataFrame of customer journeys. Each row contains a list of channels and a conversion indicator. Assign equal credit to each unique channel in journeys where a conversion occurred, and summarize the total conversions attributed to each channel.
- Iterate through each row in the DataFrame.
- For rows where a conversion occurred, distribute equal credit to each unique channel listed in the
channelscolumn. - Accumulate the total credit for each channel across all journeys.
- Return a DataFrame with columns
channelandtotal_conversionssummarizing the results.
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