Monthly Archives: October, 2016

Why Dynamic Analytics Are The Way of the Future

October 12th, 2016 Posted by Analytics 0 thoughts on “Why Dynamic Analytics Are The Way of the Future”

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.

Three Types of Analytics to Leverage Big Data

October 6th, 2016 Posted by Analytics 0 thoughts on “Three Types of Analytics to Leverage Big Data”

In an era of Big Data, businesses are finding more and more ways to fine-tune products for their customers. There are several layers of information to glean insights from: web analytics, enterprise BI, and behavioral analytics.

With web or app analytics, a company will gather up data on clicks and page views, as well as a number of other metrics that indicate what kind of traffic the website is attracting. Those include the number of unique visitors; downloads; referral sources; and page bounces.

Using this data, the companycan for instance aggregate data on hot topics and on the most valuable pages on its website. This basic data serves as the blueprint for a website that is pleasant to navigate and attractive to customers.

Like a judicious accountant, web analytics allows firms to get a clearer view of what is driving sales performance.

But companies nowadays have an opportunity to go even deeper. With enterprise business intelligence, they can turn the lens back on themselves to reveal the inefficiencies within.

Companies nowadays have a dizzying array of internal data at their fingertips, from sales forecasts to inventory levels and revenue or cost data. Slicing and dicing this data with flexible reporting and ETL processes allows businesses to learn valuable things about themselves.

Enterprise business intelligence is like the eagle-eyed consultant who swoops in to identify how the firm could improve.

But Big Data has also given rise to an entirely new dimension of data analytics based on the real-time processing of customer patterns. Now, companies can observe customer behavior as it happens and respond instantly through dynamic webpages.

The company’s own past data on customer journeys – where users go on the website or mobile devices and what they end up doing – can help create different types of behavioral profiles, called customer segments. Once the website learns to recognize a hesitant buyer, it will respond accordingly – directing the customer to a discount offer, for instance.

This form of analytics, we call it Predictive Behavioral Analytics™, will allow companies to offer a user experience that is as personal as interacting with an affable customer service representative. In other words, Predictive Behavioral Analytics™ is like having Donald Draper assist every single customer that passes through your website!

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