Marketing Analytics is very much different from predictive analytics in that, the area of concentration is more customer focused, based on future consumer behavior which has many latent components involved.
Predictive Analytics is used in a wider range of applications besides marketing. The key to PA is the cross over from different business processes f.e. using credit & fraud models in marketing applicatons as well. If you look at the original definition of predictive analytics it captures any analytics that support decision making based on expectations of future values
"Predictive analytics connects data to effective action by drawing reliable conclusions about current conditions and future events."
If I take a wider view I'ld describe PA as:
Predictive analytics, like enterprise resource planning (ERP) and customer relationship management (CRM), is both a business process and a set of related technologies. Predictive analytics leverages an organization’s business knowledge by applying sophisticated analytic techniques to enterprise data. The resulting insights can lead to actions that demonstrably change how people behave as customers, employees, patients, students, and citizens.
The predictive analytics process begins by exploring how specific business issues relate to data describing people’s characteristics, attitudes, and behavior. These numeric and free-form data sets, which originate from both internal systems and third party providers, are cleansed, transformed, and evaluated using statistical, mathematical, and other algorithmic techniques. These techniques generate models for classification, segmentation, forecasting, pattern recognition, sequence and association detection, anomaly identification, profiling, propensity scoring, rule induction, text mining, and advanced visualization.
Combining predictive analytic models with organizational business knowledge provides insight into such critical issues as customer acquisition and retention, up-selling and cross-selling, fraud detection, and outcome improvement. Through measuring uncertainty surrounding these issues, predictive analytics enables proactive risk management, refining key decision making processes through controlled, iterative testing of potential actions and their likely intended—and unintended—consequences. These findings and their corresponding business rules can then be deployed within front-line operational systems to identify new revenue opportunities, measurable cost savings, repeatable process improvements, and sustainable competitive advantages.
Predictive analytics carries strategic and tactical ramifications for organizations that recognize the inherent value locked within their existing enterprise data. Strategically, predictive analytics provides a quantitative foundation for rapidly identifying, objectively evaluating, and confidently pursuing new market opportunities. Tactically, predictive analytics identifies precisely whom to target, how to reach them, when to make contact, and what messages
Although I agree that PA is conceptually a wider body of work than MA, rarely have I seen organizations treat it as a separate function or an enterprise level function. We typically see PA fall into a functional area within the organization and not the other way around.
I don't think that means that your statement is not true. It is possible that a company or organization would realize the greatest gain by placing emphasis on PA at an enterprise level. It may simply be the difference in conceptual vs organizational thinking.
Predictive analytics consists of the more substantive theoretical and methodological applications of statistical analyses of quantitative and qualitative data guided by a general conceptual framework and operational objectives. Often, predictive analytics tends to be largely abstract in its interpretation of findings as it builds conclusions primarily on the parameters of the very techniques used in the analyses. Marketing analytics, on the other hand, encompasses predictive analytics and integrates into these analyses the more pragmatic perspectives and interests of sellers and buyers such as the "Returns of Investments" (ROI) and other similar business measures formulated upon the statistical foundations of predictive analytics.