Sales Forecasting Model (using SARIMAX algorithm)

This Bot forecasts growth, trends, and seasonality, for user-specified time periods by analyzing the various combinations of input variables.

Top Benefits

  • Strategic Decision Making: Helps develop an appropriate strategy to reduce gap between targeted and estimated growth.
  • Achieve Sales Goals: Helps in operations resource planning and marketing campaign planning to achieve sales goals.
  • Increase Productivity: Save approximately 40% time in planning process.
  • Zero Maintenance: Model is provided as SaaS using serverless function architecture of Azure.
  • Runs in Cloud: Model runs in cloud and provides output to your workflow and automate your business processes.

Tasks

  • This bot can handle data with a trend and explicitly supports univariate time series analysis with a seasonal component.
  • The Bot takes in the CSV file as input and performs the Seasonal ARIMAX and provides output in the MS Excel.
  • Help in performing seasonal time series analysis for a marketeer to make data driven business decisions.

Inputs:
1. Path: Path of the CSV file. Ex.: C:~sales data-set.csv
2. ColumnCount: Count of columns available in CSV file being provided with input data.
3. InputColumnNames: Name of columns being provided in CSV file. For example 'Month', 'Sales'.
4. InputColumnDataType: Data Type of columns being provided in CSV file in the same order as column names. For example 'string', 'Date', 'Numeric'.
5. MissingNumberValueReplacement: A value that can be used by Model in case CSV file has blank field/s or missing numerical value/s.
6. MissingDateValueReplacement: A value that can be used by Model in case CSV file has a blank field or missing a Date value. This parameter should have value in the YYYY-MM-DD format. Ex: 2020-01-01
7. IgnoreColumns: Names of the column that model shall ignore while estimating forecasting. For example 'Sno',
Input Sample: Retail Sales data of 105 months (1964-01-01 to 1972-09-01)

Actions:
The Bot takes CSV file as an input, performs the time-series analysis using SARIMAX algorithm and provides output in the MS Excel to forecast sales.

Outputs:
1. Output: the result in the form of Excel.
2. Seasonal time series most suitable predictions with upper and lower limits.

Use Cases:
1. An organization looking to forecast Daily, Weekly, Monthly product sales while being cautious of seasonality.
2. A Retail store planning inventory levels based on sales forecast based on seasonal variations.

Get Bot

Free

Bot Security Program
Level 2
Applications
Business Process
Category
Vendor
Automation Type
Bot
Last Updated
April 15, 2020
First Published
April 9, 2020
Enterprise Version
11.3
Community Version
11.3.1
ReadMe
ReadMe
Support

See the Bot in Action

Code
Input Sample
Output Sample
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Code
Input Sample
Output Sample

Setup Process

Install

Download the Bot and follow the instructions to install it in your AAE Control Room.

Configure

Open the Bot to configure your username and other settings the Bot will need (see the Installation Guide or ReadMe for details.)

Run

That's it - now the Bot is ready to get going!

Requirements and Inputs

  • 1. Path: Path of the CSV file.
  • 2. ColumnCount: Count of columns available in CSV file being provided with input data.
  • 3. InputColumnNames: Name of columns being provided in CSV file.
  • 4. InputColumnDataType: Data Type of columns being provided in CSV file in the same order as column names.
  • 5. MissingNumberValueReplacement: A value that can be used by Model in case CSV file has blank field/s.
  • 6. MissingDateValueReplacement: A value that can be used by Model incase CSV file has blank or missing a Date value.
  • 7. IgnoreColumns: Names of the column that model shall ignore while estimating forecasting.