Sold by: Mphasis
Overview
Customer segmentation aggregates the data captured in the KYC details and creates customer groups. The KYC data comes in various categories such as Geographic, Demographic, Behavior and Financial variables. This solution leverages machine learning to identify patterns in the data and segment the customers. These segments can be utilized for marketing analytics and campaigns.
Highlights
- Segmentation helps enhance business outcomes by letting the decision makers understand customers better and tailor customer experiences. Applications of this solution include personalization, effective acquisition & retention, better ROI of marketing and unearthing new opportunities among markets with different customers.
- This solution supports a variety of clustering techniques of the user’s choice to identify customer segments using multiple parameters provided.
- Mphasis HyperGraf is an omni-channel customer 360 analytics solution. Need customized Deep Learning/NLP solutions? Get in touch!
Details
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Delivery method
Latest version
Deployed on AWS
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Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m5.large Inference (Batch) Recommended | Model inference on the ml.m5.large instance type, batch mode | $8.00 |
ml.m5.large Inference (Real-Time) Recommended | Model inference on the ml.m5.large instance type, real-time mode | $4.00 |
ml.m4.4xlarge Inference (Batch) | Model inference on the ml.m4.4xlarge instance type, batch mode | $8.00 |
ml.m5.4xlarge Inference (Batch) | Model inference on the ml.m5.4xlarge instance type, batch mode | $8.00 |
ml.m4.16xlarge Inference (Batch) | Model inference on the ml.m4.16xlarge instance type, batch mode | $8.00 |
ml.m5.2xlarge Inference (Batch) | Model inference on the ml.m5.2xlarge instance type, batch mode | $8.00 |
ml.p3.16xlarge Inference (Batch) | Model inference on the ml.p3.16xlarge instance type, batch mode | $8.00 |
ml.m4.2xlarge Inference (Batch) | Model inference on the ml.m4.2xlarge instance type, batch mode | $8.00 |
ml.c5.2xlarge Inference (Batch) | Model inference on the ml.c5.2xlarge instance type, batch mode | $8.00 |
ml.p3.2xlarge Inference (Batch) | Model inference on the ml.p3.2xlarge instance type, batch mode | $8.00 |
Vendor refund policy
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Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
Bug Fixes and Performance Improvement
Additional details
Inputs
- Summary
content types: application/zip
contains both .csv file and .json file.
Input.csv
customer_code age customer_seniority income gender 816978 55 80 67804.5 M parameters.json
{ "Clustering algorithm": "hdbscan", "Segmentation type": "combined", "Cluster parameters": [1000,80] }
- Input MIME type
- text/csv, application/json, text/plain, application/zip
https://tinyurl.com/emubdxxc
https://tinyurl.com/emubdxxc
Resources
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Support
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