Amazon Sagemaker
Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. With Amazon SageMaker, all the barriers and complexity that typically slow down developers who want to use machine learning are removed. The service includes models that can be used together or independently to build, train, and deploy your machine learning models.
KYC based Customer Segmentation
By:
Latest Version:
3.2
Machine Learning solution to segment customers using KYC information
Product 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.
Key Data
Version
By
Type
Model Package
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.
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Pricing Information
Use this tool to estimate the software and infrastructure costs based your configuration choices. Your usage and costs might be different from this estimate. They will be reflected on your monthly AWS billing reports.
Contact us to request contract pricing for this product.
Estimating your costs
Choose your region and launch option to see the pricing details. Then, modify the estimated price by choosing different instance types.
Version
Region
Software Pricing
Model Realtime Inference$4.00/hr
running on ml.m5.large
Model Batch Transform$8.00/hr
running on ml.m5.large
Infrastructure PricingWith Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
Learn more about SageMaker pricing
With Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
Learn more about SageMaker pricing
SageMaker Realtime Inference$0.115/host/hr
running on ml.m5.large
SageMaker Batch Transform$0.115/host/hr
running on ml.m5.large
Model Realtime Inference
For model deployment as Real-time endpoint in Amazon SageMaker, the software is priced based on hourly pricing that can vary by instance type. Additional infrastructure cost, taxes or fees may apply.InstanceType | Realtime Inference/hr | |
|---|---|---|
ml.m4.4xlarge | $4.00 | |
ml.m5.4xlarge | $4.00 | |
ml.m4.16xlarge | $4.00 | |
ml.m5.2xlarge | $4.00 | |
ml.p3.16xlarge | $4.00 | |
ml.m4.2xlarge | $4.00 | |
ml.c5.2xlarge | $4.00 | |
ml.p3.2xlarge | $4.00 | |
ml.c4.2xlarge | $4.00 | |
ml.m4.10xlarge | $4.00 | |
ml.c4.xlarge | $4.00 | |
ml.m5.24xlarge | $4.00 | |
ml.c5.xlarge | $4.00 | |
ml.p2.xlarge | $4.00 | |
ml.m5.12xlarge | $4.00 | |
ml.p2.16xlarge | $4.00 | |
ml.c4.4xlarge | $4.00 | |
ml.m5.xlarge | $4.00 | |
ml.c5.9xlarge | $4.00 | |
ml.m4.xlarge | $4.00 | |
ml.c5.4xlarge | $4.00 | |
ml.p3.8xlarge | $4.00 | |
ml.m5.large Vendor Recommended | $4.00 | |
ml.c4.8xlarge | $4.00 | |
ml.p2.8xlarge | $4.00 | |
ml.c5.18xlarge | $4.00 |
Usage Information
Model input and output details
Input
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/plain, application/zipSample input data
Output
Summary
sample output
| customer_code- | -age- | -customer_seniority- | -income- | -gender- | -Customer_lable- |
|---|---|---|---|---|---|
| 816978 | 55 | 80 | 67804.5 | M | 2 |
Output MIME type
text/csvSample output data
Sample notebook
Additional Resources
End User License Agreement
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Support Information
KYC based Customer Segmentation
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