Customer Segmentation Model
This bot segments customers based on a variety of characteristics to help you identify key groups of customers.
Top Benefits
- Increase Productivity: Save ~30% of an analyst's time to prepare Customer Segmentation for business processes.
- Target Right Segment: Get relative viable clusters for targeting right customers i.e. behavioral segmentation.
- Zero Maintenance: Model is provided as SaaS using the serverless function architecture of Azure.
- Ease of use: Model is easy to setup, highly scalable, and fault tolerant (Each request is independent of another request).
- Runs in Cloud: Model runs in cloud and provides output to your workflow and automates your business processes.
Tasks
- Prepare rapid unsupervised customer clusters or segments and personas.
This bot segments customers based on a variety of characteristics to help you identify key groups of customers. This bot enables segmentation of targets with similar traits and assigns them into clusters. Output can be used in a workflow to automate your business processes.
Use Cases:
- Identify the most profitable customers and target them in your marketing campaigns to increase sales per customer.
- Segment your customers by purchase history and their interest to target the right product or service.
- Segment patients based on their medical history and demographic to recruit the right patients for a clinical trial.
Inputs:
- Path: Path of the CSV file. Ex.: C:~Car.csv
- Column Count: Count of columns available in CSV file being provided as input data.
- Input Column Names: Name of columns being provided in CSV file. For example: 'Choice','Hsg2','Coml5'......
- Input Column Data Type: Data Type of columns being provided in CSV file in the same order as column names. For example: 'String','Numeric','Numeric'....
- Missing Number Value Replacement: A value that can be used by Model in case CSV file has blank fields or missing numerical values.
- Missing String Value Replacement: A value that can be used by Model in case CSV file has blank fields or missing string/character values.
- Cluster Count: Count of clusters to be made by the user. For example: 3/4/5 to any user-defined number
- Ignore Columns: Column name that model shall ignore while calculating customer segmentation. For example 'SNo','Range6' to any user-defined input
Actions: The bot takes in the CSV file and performs the customer segmentation and stores the output in an Excel file.
Outputs: Customer Segments
- Output: The result in an Excel file.
- Viable customer segments/personas (5 clusters in the given example) that are cluster output and segmental counts (for unique cluster identification).
Free
- Bot Security Program
-
Level 2
- Applications
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- Business Process
- Customer Service & SupportMarketingSales
- Category
- Cognitive AutomationInsightsProductivity
- Downloads
- 22
- Vendor
- Automation Type
- Bot
- Last Updated
- December 11, 2020
- First Published
- April 9, 2020
- Platform
- 11.3
- Community Version
- 11.3.1
- ReadMe
- ReadMe
- Support
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- Nextgen Invent Corporation
- Mon, Tue, Wed, Thu, Fri 9:00-17:00 UTC+0
- 508-753-1512
- bot.support@nextgeninvent.com
- Bot Store FAQs
See the Bot in Action
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.