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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.

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Churn Mitigation

By:
ElectrifAi LLC
Latest Version:
1.0.1
Identify customers likely to churn and mitigate customer churn by contacting customers for each marketing campaign.
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    Product Overview

    Know in advance those customers likely to churn with this suite of predictive analytics models. Identify customers more likely to churn, either directly or predicting the churn event or indirectly by analyzing the network experience. The algorithm also targets strategies to mitigate customer churn by contacting customers for each marketing campaign. Our machine learning models are available through a Private Offer. Please contact info@electrifai.net for subscription service pricing. SKU: CHMIT-PS-TLC-AWS-001

    Key Data

    Version
    1.0.1
    Usage Instructions
    Release Notes
    By
    ElectrifAi LLC
    Categories
    ML Solutions
    CRM
    Media & Entertainment
    Type
    Model Package
    Fulfillment Methods
    Amazon SageMaker

    Highlights

    • Know in advance those customers likely to churn with this suite of predictive analytics models and target those customers with appropriate marketing campaigns.

    Not quite sure what you’re looking for? AWS Marketplace can help you find the right solution for your use case. Contact us

    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$700.00/hr

    running on ml.p2.8xlarge

    Model Batch Transform$700.00/hr

    running on ml.m5.2xlarge

    Infrastructure 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$8.64/host/hr

    running on ml.p2.8xlarge

    SageMaker Batch Transform$0.461/host/hr

    running on ml.m5.2xlarge

    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.p2.xlarge
    $500.00
    ml.p2.8xlarge
    Vendor Recommended
    $700.00
    ml.p2.16xlarge
    $900.00

    Usage Information

    Model input and output details

    Input

    Summary

    Input: More than 5 comma separated files (depending on how many service usage the user will provide) in a tar or tar.gz compression format.

    Sample input data
    Expand all input descriptions
    Field name
    More than 5 csv files archived in tar or tar.gz format
    Description
    scoring_date.csv (required), profile.csv (required), bill_records.csv (required), payment_records.csv (required), service1_usage_records.csv (required)**, serviceN_usage_records.csv (optional, N=2,3,4,5...**), subscription_records.csv (optional); ** service1 means the primary service provided to customer; **N=2,3,4,5,6,7...., can add any number of service usage table, follow the same schema of service1_usage_records.csv
    Constraints

    Type: FreeText

    Required
    Yes
    Usage information

    Output

    Summary

    Output is a list of JSON objects containing 'accountID' with original order, and one more column added named 'Score' which contains model's prediction of the churn score for the record

    Sample output: '[{"accountID":"ElectrifAIid594631","Score":0.0631441325},{"accountID":"ElectrifAIid723876","Score":0.0538257323},{"accountID":"ElectrifAIid630371","Score":0.1266254187}]'

    Sample output data
    Expand all output descriptions
    Field name
    accountID
    Description
    'score' contains the model's prediction of the churn score for the account_id Type: FreeText
    Always returned
    Yes
    Data type
    Field name
    score
    Description
    'score' contains the model's prediction of the churn score for the account_id Type: FreeText
    Always returned
    Yes
    Data type

    Sample notebook

    Additional Resources

    End User License Agreement

    By subscribing to this product you agree to terms and conditions outlined in the product End user License Agreement (EULA)

    Support Information

    AWS Infrastructure

    AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.

    Learn More

    Refund Policy

    According to contract

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