Explainer: Predictive Analytics


What It Is: Predictive analytics is the antithesis of the proverbial “dumb pipe” of data that simply presents a series of performance indicators or variables over time. It goes beyond behavioral analysis to the logic of the big picture. Knowing that 70 percent of a targeted audience likes a product is great, but it doesn’t place those statistics in context, making it relevant for strategy development. That’s where predictive analytics comes in. It makes raw data actionable, linking it to past consumer behaviors as well as current variables that allow the statistician to predict the probability of new or continued behaviors.

Why It Matters: Predictive analytics is not an exact science, but it allows marketers to gauge the likelihood that a strategy will be effective based on statistical patterns. This makes business processes more efficient as resources can be diverted proportionately towards marketing initiatives that have a greater probability of reaching performance goals. Enterprise-grade predictive analytics software usually analyzes real-time data, making it easier to adjust project objectives and expectations on-the-fly.
Who Uses It: Most industries, ranging from insurance to finance, uses some form of predictive analytics to guide product line decisions as well as marketing strategy. Some notable predictive analytics software brands are IBM’S SPSS, Accenture and Oracle.
Assessment: Social media “listening” should not replace hard data in the strategy development and implementation process. Creating a viable marketing strategy certainly needs to look at what consumers are saying online, but it is far more important to know what they are doing.

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