Customer Survey Analysis (Linear Discriminant Analysis)

The Bot takes in the input data in a CSV file and performs the LDA algorithm-driven classification and provides output in the MS excel.

Top Benefits

  • Improves customer survey analysis process up to 25%.
  • Reduced time with rule based grouping and augments quick decisions based on predictions from survey data.
  • Provides high level of accuracy based on quality of input data parameters.

Tasks

  • Bot model could be used for dimensionality reduction in the pre-processing step.
  • Bot model could be used for modeling differences in groups i.e. separating two or more customer classes.
  • Bot takes in the input data in CSV file and performs LDA and provides output in the MS excel.

Inputs:
• Path: Path of the CSV file Ex.: C:~Airline_Passenger_Survey.csv
• NoOfColumn: Number of Columns in the CSV file
• InputColumn: Header of the input columns of the CSV file Ex: 'Gender','Customer Type','Age','Type of Travel','Class','Inflight wifi','Timeless','Online booking','Seat comfort','Inflight service','Cleanliness','Survey Result'
• InputColumnDataType: Data Types of the input column (Available datatype: Numeric, String, Date) Ex: 'String','String','Numeric','String','String','Numeric','Numeric','Numeric','Numeric','Numeric','Numeric','String'
• MissingNumberValueReplacement: By which value you have to replace the missing number values
• MissingStringValueReplacement: By what string you have to replace the missing string values
• IgnoreColumns: header of the Columns which you have to ignore in the model.  Ex: 'Inflight wifi'
• PredictionColumnName: Header of the column on which you want to predict Ex: 'Survey Result'
Ex: This below mentioned input example shows the survey result of the airline passenger based on different features like customer type, class, inflight wifi, Timeless, seat comfort

Actions:
The Bot takes the CSV file and prepare the linear discriminant Analysis and output the Excel
Outputs:
• Output: the result in the form of the Excel
• The output provides various customer groups
Ex: The below examples show the Predicted class which shows the passenger is satisfied or not

Get Bot

Free

Bot Security Program
Level 1
Applications
Business Process
Category
Vendor
Automation Type
Bot
Last Updated
June 17, 2020
First Published
June 17, 2020
Enterprise Version
11.x
Community Version
11.3.1
ReadMe
ReadMe
Support

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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

  • Path: Path of the CSV file.
  • NoOfColumn: Number of Columns in the CSV file.
  • InputColumn: Header of the input columns of the CSV file.
  • InputColumnDataType: Data Types of the input column (Available datatype: Numeric, String, Date).
  • MissingNumberValueReplacement: By which value you have to replace the missing number values.
  • MissingStringValueReplacement: By what string you have to replace the missing string values.
  • IgnoreColumns: header of the Columns which you have to ignore in the model.
  • Header of the Column on which you want to predict.