Sold by: ElectrifAi LLC
Deployed on AWS
Identify past guests/prospects more likely to book a cruise after receiving an email campaign.
Overview
Very specific marketing is needed to attract potential clients to book a cruise. This propensity model identifies past guests/prospects who are more likely to book a cruise after receiving an email campaign. This model leverages advanced, high-precision targeting for customer acquisition and can be applied towards both domestic and international markets. Previous ElectrifAi clients have seen an increase in booking rates by 97% after implementing the solutions from this model. Our machine learning models are available through a Private Offer. Please contact info@electrifai.net for subscription service pricing.
SKU: DMCOP-PS-TAT-AWS-001
Highlights
- Direct mail campaign optimization to target those past guests/prospects more likely to book a cruise after receiving an email campaign.
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.m5.4xlarge Inference (Batch) Recommended | Model inference on the ml.m5.4xlarge instance type, batch mode | $700.00 |
ml.m5.4xlarge Inference (Real-Time) Recommended | Model inference on the ml.m5.4xlarge instance type, real-time mode | $700.00 |
ml.m5.12xlarge Inference (Batch) | Model inference on the ml.m5.12xlarge instance type, batch mode | $900.00 |
ml.m5.2xlarge Inference (Batch) | Model inference on the ml.m5.2xlarge instance type, batch mode | $500.00 |
ml.m5.12xlarge Inference (Real-Time) | Model inference on the ml.m5.12xlarge instance type, real-time mode | $900.00 |
ml.m5.2xlarge Inference (Real-Time) | Model inference on the ml.m5.2xlarge instance type, real-time mode | $500.00 |
Vendor refund policy
According to contract
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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
7 csv files archived and zipped in a single tar.gz file
- Input MIME type
- application/json
https://github.com/ElectrifAi/direct-mail-campaign-optimization/blob/master/input_data.tar.gz
https://github.com/ElectrifAi/direct-mail-campaign-optimization/blob/master/input_data.tar.gz
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
input_data.tar.gz contains 7 required input files in csv format | scoring_date.csv (required), profile.csv (required), email_sent.csv (required), email_click.csv (required), email_open.csv (required), transactions.csv (required), dm_sent.csv (required)
| Type: FreeText | Yes |
Resources
Vendor resources
Support
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