Building a Smarter Planet. A Smarter Planet Blog.

by Deepak Advani, IBM Vice President, Business Analytics

Do you remember when you bought your first e-reader?  Was the decision influenced by a digital or TV ad? Or did someone you trust, perhaps a family member or colleague at work, offer you advice and perhaps a quick demo of their device? How fast was the progression from awareness to consideration to purchase to loyalty?

Once upon a time, marketers sold to broad demographics such as “women, 18-34.” But now through insights gleaned from Big Data and predictive analytics, companies can get closer to the customer down to the point of the individual – whether a company has 500 customers, or five million.

From digital marketing and mobile commerce, to websites and social media, marketers are inundated — some say paralyzed — by data amassed from consumers via searches, purchase histories, price-scanning apps on mobile phones, Facebook “likes” and comments on Twitter. Combine that with data about in-store traffic, conversations with call centers and updates from suppliers, and today’s marketers confront a daily cacophony of data waiting to be sifted for nuggets of intelligence they can act upon to boost their business.

Big Data is creating a world of changing conventions in the C-suite. The CIO used to make all the IT decisions.  Now we are seeing that more CMOs are in the driver’s seat.  In fact Gartner Inc. says that by 2017 the CMO will have greater influence over the IT budget than the CIO.

As part of IBM’s effort to reach CMOs and spur a broader conversation about how technology is transforming marketing, we’re trying something a little bit different.  IBM is using the US Open to premier two TV spots about marketing.  They both highlight the need to treat customers as individuals. Here’s one called “Chief Executive Customer”:

Given the age of the digitally empowered consumer, companies need to start paying attention to a whole new set of metrics in this new world. They need to understand who their brand advocates and detractors are, and what shapes their attitudes and drives their behavior. They need to keep track of near-advocates, and what type of interactions will turn them into advocates. Similarly they need to keep a close eye on near-detractors, and what type of actions can reduce the probability of them turning into active and vocal detractors.

The good news is that algorithms can help companies understand and predict customer behavior. This type of customer analytics builds propensity models for each customer to determine the next best action they can take — at every touch point — such as call centers, web sites, branch offices and retail stores.

A telco company used this approach to turn 23% of its detractors into promoters. A financial services company used this approach to turn its call center into a revenue producing channel, which generated €30 million in 12 months. These examples demonstrate that the outcomes driven through the adoption of customer analytics are significant and are starting to go mainstream.

More organizations will learn how to shape their products and strategies based on such individual propensities without eroding customer trust, which in this brave new world will be a more important currency than ever before.

We hope you’ll check out Smarter Planet Facebook Friday with Deepak on September 7.  He’ll discuss how Big Data and predictive analytics are not only transforming the world of sporting events like the US Open, but how sports are evolving as a metaphor for business. 

Here’s a video of Deepak talking about how marketers can better understand their customers as individuals:

Technorati Tags: Analytics, business analytics, CMO, IBM, predictive analytics