sargun-nagpal/Causal-Counterfactual-Forecasting-ACIC2023
Code for Causal Inference (Spring 2023) Final Project @NYU. Causal Counterfactual Forecasting
This project helps e-commerce managers, marketers, or product strategists understand how different pricing strategies might affect future product sales. It takes historical sales data, pricing changes, and other product features as input, and outputs predictions for future sales under various pricing scenarios. This allows business stakeholders to forecast the impact of their decisions before implementing them.
No commits in the last 6 months.
Use this if you need to predict the sales outcome of different pricing decisions over the next few weeks for your e-commerce products.
Not ideal if you are looking for a simple time series forecast that doesn't account for the 'what if' scenarios of different interventions.
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MIT
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Last pushed
May 11, 2023
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