Project Overview

The client was looking for a solution to optimize their marketing expenses for product promotions and assist the sales team with planning future activities and estimating demand.
Our goal for this project was to develop a tool that would enable the customer to efficiently access statistical models based on his datasets to address specific issues. For instance, this tool could be used to predict sales, demand, and simulate marketing strategies to increase the net volume of sales.

We employed a time series regression analysis approach and conventional ARIMA models as well as a modified LSTM deep learning network to gain valuable insights on sales drivers and provide the client with accurate predictions. Additionally, we created a dashboard that automatically updated models and forecasts in response to new data being uploaded. 
Received sales prediction enabled FMCG company to identify potential problems or risks and implement necessary corrective measures to mitigate them.

In essence, sales forecasts are a profitable investment, because they assist companies with sales planning, demand planning, inventory management, financial planning, internal control, gaining insights, and marketing advantages.
Django, Keras, Tensorflow, Plotly, Dask.


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