Solution architecture: Predictive marketing campaigns with machine learning and Spark

Marketing campaigns are about more than the message being delivered; when and how that message is delivered is just as important. Without a data-driven, analytical approach, campaigns can easily miss opportunities or struggle to gain traction.

Through machine learning informed by historical campaign data, this solution architecture helps predict customer responses and recommends an optimised plan for connecting with your leads, including the best channel to use (by email, SMS, a cold call etc.), the best day of the week and the best time of the day.

Optimising your campaigns with predictive marketing helps improve both sales leads and revenue generation and can provide strong ROI for your marketing investment.

This architecture enables efficient handling of big data on Spark with Microsoft R Server.

Predictive marketing campaigns with machine learning and SparkLearn how to build a machine-learning model with Microsoft R Server on Azure HDInsight Spark clusters to recommend actions to maximize the purchase rate.DashboardMachine LearningHDInsightBlob Storage

Implementation guidance

Products/Description Documentation


Microsoft R Server on HDInsight Spark clusters provides distributed and scalable machine learning capabilities for big data, combining the power of R Server and Apache Spark.

Power BI

Power BI provides an interactive dashboard with visualisation that uses data stored in SQL Server to drive decisions on the predictions.


Azure Storage stores campaign and lead data.

Machine Learning Studio

Machine Learning helps you easily design, test, operationalise and manage predictive analytics solutions in the cloud.

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