What is Predictive Analytics?
Predictive Analytics is the use of data mining, artificial intelligence and machine learning to predict future events. That doesn’t really explain much though and is littered with a few increasingly popular buzz words. So, let’s look at an example…
A goalkeeper is faced with a penalty. Their objective is to save the penalty.
The goalkeeper knows where their opponent has aimed their previous penalties. Left, Right, Right, Left, Right, Right.
The goalkeeper has identified a pattern from the previous penalties and decides to dive left.
Success! The opposition goes left and the goalkeeper makes the save.
Admittedly this is a very simple example, but by having historical data the goalkeeper was able to identify a pattern and apply the learnings to a future event to achieve the desired outcome.
How does Predictive Analytics work?
Without data, there is no Predictive Analytics. The first step for anyone wanting to employ Predictive Analytics is to capture the right data. This data can come from a variety of sources such as website browsing, transaction details and person data. The majority of time spent building a predictive model is on data preparation. Data comes in all shapes and sizes, so data dictionaries are invaluable when it comes to preparing and mining the data that feeds into a predictive model.
Data mining will identify patterns, correlations and anomalies within the data. These insights are used to determine the most suitable algorithm(s) to use and the relevant data to be fed into the chosen algorithm(s). There are a whole host of algorithms at an analyst’s disposal so it’s not as simple as clicking a few buttons and letting machine learning do its thing. Each model is evaluated in order to establish which is the best one to implement. With this in mind, black-box solutions are great if you want to get a predictive model live quickly, but they have their obvious limitations.
Why is Predictive Analytics important?
Simple. It works. Someone who makes an informed decision is more likely to make the correct decision and this is exactly what predictive analytics offers. It removes any guesswork and allows marketers to make more strategic decisions.
How does Predictive Analytics help businesses?
Once you’ve got a working model and you’re satisfied with its performance it can be applied to real world situations. It could provide product recommendations to customers to increase sales and conversion rates. It could also help identify customers close to churning so you can reach out to them before you lose them. Another use would be measuring the predicted lifetime value of your customer base so you can see the effects of your marketing strategy and avoid any nasty surprises further down the line. Chances are Predictive Analytics can help with any one of your business goals.
Want to find out a bit more about implementing Predictive Analytics in your business? Head to our Predictive Analytics page or get in contact with us here.