The Customer 360 Profile solution provides you a scalable way to build a customer profile enriched by machine learning. It also allows you to uniformly access and operate on data across disparate data sources (while minimizing raw data movement) and leverage the power of Microsoft R Server for scalable modelling and accurate predictions.
This technical guide walks you through the steps to implement a customer 360 profile solution using Cortana Intelligence Suite on Microsoft Azure. The solution involves:
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Ingestion and Pre-processing: Ingest, prepare, and aggregate live user activity data.
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Integration of Data Sources: Integrate and federate customer profile data that’s embedded across disparate data sources.
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Feature engineering and ETL: Segment customers into [RFM][LINK_RFM] segments based on their browsing and purchase behavior.
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Machine Learning (ML)): Build an ML model to predict how likely a customer will purchase in the next few days and from which product category. The ML model enriches existing customer profiles based on their most recent activities.
This solution contains materials to help both technical and business audiences understand the solution. All components are can be deployed and built on Azure.
In this repository you will find a folder called Solution Overview for Business Audiences. This folder contains a PowerPoint deck that covers the benefits of using this solution and the ways that Customer Profile Enrichment can help businesses better understand and focus on their customers' need.
For more information on how to tailor Cortana Intelligence to your needs connect with one of our partners.
See the Technical Manual Deployment Guide folder for a full set of instructions on how to customize and deploy this solution on Azure. For technical problems or questions about deploying this solution, please create an issue in this repository.
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