dscigametrics

dscigametrics enables users to easily compute four important metrics:

  1. Ratio of new to returning visitors: measures the ratio of new users to returning users of each campaign in certain period.

  2. Conversion rate: measures the percentage of users who complete a specific desired action of each campaign in certain period.

  3. Total transaction revenue: measures total transaction revenue of each campaign in certain period.

  4. Average transaction revenue: measures average transaction revenue of each campaign in certain period.

Fuctions in the package

The package also provides convenience functions to compute summary statistics, produce visualizations of the data and find the best and worst campaign:

  1. compute_metrics summarises general performance of campaign based on four metrics.

  2. stat_summary summarises variance of campaign performance based on four metrics.

  3. daily_plot visualises performance changes of campaign based on four metrics.

  4. find_campaigns identifies the best and worst performing campaigns based on a selected metric.

Where this package fits in

The popularity and influence of Google Analytics means that there is already a decent number of related python packages, such as googleanalytics, which can be found on PyPI: [https://pypi.org/project/googleanalytics/]. However the majority of these packages provide functionality that allows developers to interact with the Google Analytics API, which presupposes a fairly high level of technical skill. Our package is intended to help users with a novice familiarity with python by operating directly on downloaded GA data sets instead.

Installation

Since the package has not uploaded to PyPI, this is not feasible for now. Please see the developer installation instructions to install it.

$ pip install dscigametrics

Developer Installation Instruction

Step 1: Clone the Repository

git clone git@github.com:UBC-MDS/Group_9_GA_Metrics.git
cd Group_9_GA_Metrics  # Navigate to the cloned repository directory

Step 2: Create and Activate the Conda Environment

$ conda env create -f environment.yml  # Create Conda environment
$ conda activate ga_package  # Activate the Conda environment

Step 3: Install the Package Using Poetry

Ensure the Conda environment is activated. You should see Group_9_GA_Metrics in the terminal prompt.

$ poetry install  # Install the package using Poetry

Online Documentation

You can read the documentation on Read the Docs

Documentation Status

Main Contributor

Beth Ou-Yang, Ian MacCarthy, Yili Tang, Weilin Han

Contributing

Contributions are welcome and greatly appreciated! If you’re interested in contributing to this project, take a look at the contributor guide.

License

dscigametrics was created by DSCI524 Cohort8 Group9. It is licensed under the terms of the MIT license.

Credits

dscigametrics was created with cookiecutter and the py-pkgs-cookiecutter template.