Create a Demand Sales Forecast Model and Minimize the Error

Create a Demand Sales Forecast Model and Minimize the Error

Create a Demand Sales Forecast Model and Minimize the Error. In this article, we’ll do a simple sales forecast model with real data and then improve it by finding relevant features using Python.

Sales or Demand Forecasts are a priority *on ahuge amount of companies (from startups to global corporations) Data Science/Analytics departments. To say the least, there is a *low supply of experts in the subject. Reducing the error even by a small amount can make a huge difference in revenue or savings.

In this article, we’ll do a simple sales forecast model with real data and then improve it by finding relevant features using Python.

What we’ll do

  • Step 1: Define and understand Data and Target
  • Step 2: Make a Simple Forecast Model
  • Step 3: Improve it by adding New and Financial Indicators
  • Step 4: Analyze Results

Step 1. Define and understand Data and Target

For this article, we’ll use real weekly sales data provided by Walmart.

Walmart released data containing weekly sales for 99 departments (clothing, electronics, food…) in every *physical store *along with some other added features.

analytics machine-learning time-series-forecasting data-science sales-forecasting

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