Is there such a thing as too much data? Modern businesses are finding themselves sitting atop a treasure trove of intelligence, from web statistics to internal figures and customer logs. There are several different ways to exploit this data for different outcomes.
As we wrote last week, the three main types of analytics tools available to businesses today are enterprise business intelligence and digital analytics, which comprise web/app analytics and what we call Predictive Behavioral Analytics™.
With web analytics, businesses can evaluate the success of their websites, computed in page views, clicks, unique visitor numbers and purchase amounts. They can also gauge their best sources of traffic based on referral sources; and verify which pages are the most effective at keeping customers engaged, with bounce page data.
All this information provides great insight into how a business is faring online and allows businesses to tweak their websites/apps in order to draw and retain more customers by improving customer experience.
Enterprise business intelligence operates similarly to web analytics – it helps businesses make smart decisions based on the data available to them – but the focus, this time, is internal.
There is an abundant amount of metrics that describe how a company operates — from sales forecasts and revenue/ costs data, to inventory levels, project progress logs and HR data.
All this data, processed through the right analytics system, can help business leaders quickly identify where the inefficiencies lie. A judicious use of enterprise business intelligence will allow business leaders to ensure they run a tight ship.
But both web analytics and enterprise business intelligence are static. That is, they allow the business to exploit the data only after-the-fact — once the customer has made their purchase online and internal business decisions have been made.
In an era where data is an instantaneous, fluid source of essential business information, such a lag is not only inefficient and costly, but also fully preventable.
That’s where Predictive Behavioral Analytics™ comes in. This analyses a customer’s behavior and responds by creating a bespoke user experience as-it-happens — thus ensuring an optimal sales outcome each and every time.
Plus, the data trail left behind by each single customer interaction is also fed into the program, making the dynamic modeling even sharper next time around.