Analyze campaign performance for better marketing decisions, ideal for startup founders, with 28 GitHub stars
intermediate⏱ 30 minutes💵 Free (no API costs needed)
28 stars12 forksJupyter NotebookQuality 8/10Updated 9/13/2022100% free · open source
What it is
Use this to analyze your marketing campaigns and see how different channels are performing.
What you can make with it
Automations like analyzing customer purchases on Amazon to see which ads really drive sales.
How it helps
This tool helps you understand which marketing channels are working best for your business, so you can adjust your strategy to save time and resources.
Real use case example
"A founder wants to boost sales of their new outdoor gear. In 30 minutes, they use this tool to analyze their recent Amazon ads and see that Google Ads are performing best. They then adjust their ad spend and messaging to maximize returns, increasing sales by 15% in a month."
If you're new
New to AI marketing, this is a great starting point for beginners.
If you're senior
Senior marketers and founders use this for detailed campaign analysis and optimization.
Common confusion cleared up
Don't worry if you're new to marketing analytics or AI - this tool is designed to be user-friendly and requires no prior experience.
Best inside these AI tools
Claude DesktopCodex CLI
Pairs with
Amazon product dataGoogle Ads APICustomer purchase records
Why we list it on WorkflowStacks: This skill is included in the marketplace because it provides easy and free access to marketing campaign analysis.
What it does
Analyze campaign performance across different marketing channels to inform better marketing decisions by comparing control and experiment groups
Install / run
Clone the repository from https://github.com/vikrantarora25/Marketing-Campaign-Analysis and open the Jupyter Notebook file
When to use it
•When you need to compare the effectiveness of different marketing channels
•When you want to measure the impact of changes to your marketing campaigns
•When you need to identify which customer segments respond best to specific marketing channels
Quick start
1Open the Jupyter Notebook file and run the cells to import necessary libraries
2Prepare your campaign data by formatting it according to the example data provided in the repository
3Assign your campaign data to the `control_group` and `experiment_group` variables
4Run the cells that calculate campaign performance metrics, such as conversion rates and click-through rates
5Visualize the results using the provided plots to compare campaign performance across channels
Ready-to-paste prompt
Run the cell that calculates the conversion rate for the experiment group using the `calculate_conversion_rate(experiment_group)` function
Heads up: Ensure you have the necessary Jupyter Notebook and Python environment setup, including libraries like pandas and matplotlib, which are required to run the notebook
Saves to your device
What's inside — free to inspect
No purchase needed
Read the entire source before you build — unlike paid marketplaces that hide it behind a buy button.
2
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folders
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license
Key files
README.md
File tree
Marketing Campaign Analysis.ipynb
README.md
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Details
Creator
vikrantarora25
Language
Jupyter Notebook
Category
marketing
Published
4/26/2020
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