You’re shopping online on Amazon, and you notice “Featured Recommendations” as you scroll down the page. Chances are you will buy something from those “featured” suggestions more, as compared to the rest of the site. And that’s Predictive Analytics for you, actionable business intelligence in it’s ecommerce persona!
Predictive analytics is an explicit selling point to the end consumer – in the above case, Amazon’s featured recommendations are actually Amazon predicts these will be of interest to you.
Now if you look at the fine print on that same page on Amazon, it says “Inspired by your purchases”. In this case, maybe, but predictive analytics also integrates and leverages powerful sources of data such as social data and unstructured text. We have a real-world example where one major telecom doubled churn model performance by integrating social data, since, if friends of a subscriber change mobile operator, the subscriber is more likely to as well.
Whether manufacturing products or providing service offerings, the enterprise’s central function is to produce and deliver with increasing effectiveness. To this end, prediction plays a key role in advancing core business capacity with actionable business intelligence.
Predictive analytics also advances central enterprise functions for supply chain optimization, HR decisions, political constituent scoring for political campaign optimization, and more.
Predictive analytics is specifically designed to generate conclusive action imperatives. Each customer’s predictive score drives action to be taken with that customer. In this way, predictive analytics is by design the most actionable form of business intelligence.
Scoring and ranking transactions with a predictive model dramatically boosts fraud detection. In a similar manner, predictive analytics extends also to information security with the detection of online intrusions by hackers and viruses, as well as to the identification of criminals by law enforcement.
Predictive analytics delivers a powerful aggregate win by driving millions of operational decisions, such as whether to mail, call, offer a discount, recommend a product, show an ad or expend sales resources on a lead. For fraud management, the predictive model drives decisions to audit, investigate or block for fraud. And, in core business applications, analytically-driven decisions include whether to inspect an item or system for failure, load a component on a repair truck, dispatch assistance, provide a loan, fast-track an application or buy a stock.
So how does Predictive Analytics – the most actionable business intelligence – fit into your organization? Join our webinar on November 17, 2016, or you can email Team Cresco at email@example.com now.