What is Predictive Analytics?

Predictive analytics is a field of business intelligence, statistics and machine learning that has emerged from academia over the last decade or two.  It’s become the state-of-the-art method for analysing business data in real-time or otherwise for predictability of commercial endgames.

Predictive analytics is what drives Amazon.com’s ‘You might also like this’ suggestions. A telecom might use it to determine which customers need a special deal to stop them from switching to another company. An email marketer might filter their list to avoid annoying off-target customers.

Predictive analytics is any method that allows you to predict what your customers are going to do. Just by tracking your customers’ purchases and noting what other items customers who bought item X bought is a simple form of predictive analytics. But in it’s truest sense predictive analytics is used to discover patterns beyond the non-obvious.

Using simple statistics methods like MLR (multiple linear regression) predictive analytics can uncover how non-obvious correlations might exist between your customers’ purchase history or their demographics and their future purchases as determined by historical data. Not only can MLR discover the obvious two or three correlations (like lots of purchases mean lots more) but that your other ten variables also carry additional predictability (like from the customer’s particular combination of demographics).

The only limitation for simple methods like MLR are that they can only handle linear correlations. For example, what if some variables combine in strange ways such as: a shopper is likely to buy more food if they’re from a poor demographic but purchase luxury items if they are in a wealthy demographic. These sort of complex intertwined correlations can only be discovered by machine learning algorithms like artificial neural networks (ANN), decision trees or support vector machines (SVM). These methods, that require genuine expertise, can add 10-30% more predicability over and above what MLR can provide. And as I always say, that means 10-30% more sales.

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About Paul Pallaghy

I'm a PhD physicist & technologist with track records in computational physicist, AI, bioinformatics, structural biology, marine biology, outbreak epidemiology and multiple tech, biotech & agtech startups.
This entry was posted in Machine learning, Multiple linear regression, Predictive analytics. Bookmark the permalink.

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