Insight as a Service (Part 2)

In a previous post introduced the concept of Insight as a Service and described some of the issues that will need to be addressed for such services to be possible.  Insight as a Service refers to action-oriented, analytic-driven solutions that operate on data generated by SaaS applications, proprietary corporate data, as well as syndicated and open source data and are delivered over the cloud.  This definition is meant to differentiate Insight as a Service, which I associate with action, from Analytics as a Service, which I associate with data science, and Data as a Service which I associate with the cloud-based delivery of syndicated and open source data.  For example, a cloud-based solution that analyzes data to create a model that predicts customer attrition and then uses it to score a company’s customer base in order to establish their propensity to churn is an Analytics as a Service solution.  On the other hand, a cloud-based solution which, in addition to establishing each customer’s attrition score, automatically identifies the customers to focus on, recommends the attrition-prevention actions to apply on each target customer and determines the portion of the marketing budget that must be allocated to each set of related actions, is an Insight as a Service solution.

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