IBM's Not-So-Secret Weapon: Big Data Marketing

By Darryl K. Taft  |  Posted 2013-02-26 Print this article Print

"With the rise of digital technologies in all aspects of the customer lifecycle, a greater collaboration has been required between the marketing and IT teams," said Stephanie Pike, vice president of global e-commerce for Office Depot, which also uses IBM's big data analytics technology. "As such, our CIO spends much of his time understanding the business impact of a given project while the CMO must understand the complexity and scalability of technical solutions."

"In the last year, I probably spent more time with the VPs of marketing than I had ever spent before, and probably more time with the VPs of marketing than I spent with any other function," Horan said. "That is definitely a change."

Meanwhile, other projects that are behind data-driven marketing at IBM include IBM Market Basket, which analyzes the purchase patterns of customers to identify those that are likely candidates for cross-sell opportunities, especially in services. It is highly driven by statistics, facts and data.

Instead of relying on chance or hit-or-miss success, Market Basket gives IBM a systemic process to proactively leverage open sales leads as a source of potential new business. This is especially important for IBM, which has acquired more than 100 companies in the past decade and can easily cross-sell products and services to clients of the acquired companies.

IBM COBRA (COrporate Brand and Reputation Analysis) is a Web-based tool that measures and analyzes social media content (blogs, message boards, Twitter, etc.) related to a company's brand, its competitors and influencers. COBRA enables IBM to extract insights, root causes and greater understanding from postings/conversations in online communities. The insights are then analyzed to identify opportunities and sales targets, converting aggregated information into individual and personal outreach.

IBM Client ID connects disparate types of data about IBM clients to produce broader insights and support targeted outreach based on customer needs, purchase history, changing market dynamics and other factors. Before Client ID, customer data had existed in multiple silos, without a common linkage tying them together.

IBM set out to better understand the various "touches" a client received from the company while implementing a predictive model to assess the market opportunity by client. Besides enabling targeted outreach, the common profile within Client ID increases collaboration among marketing, sales and finance by providing a common basis for coordinated customer interactions.

IBM's big data strategy has included the expansion of R&D, acquisitions and business initiatives across its software, hardware and services portfolio.  In the last five years, IBM has invested more than $16 billion in 30 acquisitions to boost its big data analytics portfolio.

"I still have more project requests stacked up for business automation. But there are increasingly many more projects that are requests for 'help me understand how I can make smarter decisions,'" Horan said. "That's all about big data and analytics."


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