Sold by: ElectrifAi LLCÂ
Overview
Businesses succeed when existing customers enhance their accounts through rate plan and device upgrades, feature addons, and line additions to grow account size. The Upgrade Device model is part of ElectrifAi's propensity model suite which enhances a business's predictive accuracy in targeting optimal customers across Growth and Cross Sell/ Upsell efforts. ElectrifAi's test/ control performance measurement set up shows Upgrade Device can likely maximize uplift and revenue. To preview our machine learning models, please Continue to Subscribe. To preview our sample Output Data, you will be prompted to add suggested Input Data. Sample Data is representative of the Output Data but does not actually consider the Input Data. Our machine learning models return actual Output Data and are available through a private offer. Please contact info@electrifai.net for subscription service pricing. SKU: UGDVC-PS-TLC-AWS-001
Highlights
- This model enhances a business's predictive accuracy in targeting optimal customers across Growth and Cross Sell/ Upsell efforts.
- As this model is part of the propensity model suite, the data ingestion, signal generation, scoring, etc. are all completed on one platform and are consistent with one another. One of the additional benefits we get from our propensity models is reason code analysis. We start from the raw data, then derive propensity scores at first and dive into factors that drive the score.
Details
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Delivery method
Latest version
Deployed on AWS
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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.p2.16xlarge Inference (Real-Time) Recommended | Model inference on the ml.p2.16xlarge instance type, real-time mode | $0.00 |
ml.m5.2xlarge Inference (Batch) Recommended | Model inference on the ml.m5.2xlarge instance type, batch mode | $0.00 |
ml.p2.xlarge Inference (Real-Time) | Model inference on the ml.p2.xlarge instance type, real-time mode | $0.00 |
ml.p3.16xlarge Inference (Real-Time) | Model inference on the ml.p3.16xlarge instance type, real-time mode | $0.00 |
ml.m5.4xlarge Inference (Batch) | Model inference on the ml.m5.4xlarge instance type, batch mode | $0.00 |
ml.m5.large Inference (Batch) | Model inference on the ml.m5.large instance type, batch mode | $0.00 |
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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
Vulnerability CVE-2021-3177 (i.e. https://nvd.nist.gov/vuln/detail/CVE-2021-3177 ) has been resolved in version 1.0.1.
Additional details
Inputs
- Summary
A zip file containing 9 comma separated csv files: billing_history.csv (REQUIRED) voice_call_transaction.csv (REQUIRED) data_service_transaction.csv (REQUIRED) device_history.csv (REQUIRED) memo.csv (REQUIRED) payment_history.csv (REQUIRED) rateplan_history.csv (REQUIRED) sms_service.csv (REQUIRED) subscription_status.csv (REQUIRED)
- Input MIME type
- application/json
https://github.com/ElectrifAi/model-aws-upgrade-device/blob/main/sample.zip
https://github.com/ElectrifAi/model-aws-upgrade-device/blob/main/sample.zip
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
A zip file containing 9 comma separated csv files |
billing_history.csv (REQUIRED)
voice_call_transaction.csv (REQUIRED)
data_service_transaction.csv (REQUIRED)
device_history.csv (REQUIRED)
memo.csv (REQUIRED)
payment_history.csv (REQUIRED)
rateplan_history.csv (REQUIRED)
sms_service.csv (REQUIRED)
subscription_status.csv (REQUIRED) | Type: FreeText | Yes |
Resources
Vendor resources
Support
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