Five Steps to Improve Marketing Effectiveness with Big Data

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Figure out the business case. What is it marketers want to know that they don’t know today? What are the goals they want to achieve? Improve customer experience? Increase customer retention? Gain more visibility into customer behavior? Understand the analysis of their marketing campaigns? All of these are solid Big Data use cases.

CMOs across the country are turning to Big Data and business analytics in an unprecedented drive to improve the outcomes of their marketing efforts and lower costs. ICC, a nationally recognized enterprise technology leader that provides business-critical application development, digital and Big Data analytic solutions to its Fortune 1000 national and global clients, has identified five steps for marketers to get started using Big Data.

Big Data analytics holds out the promise to change everything about marketing. From next-best-offer to cross-sell and upsell, the insights gleaned from Big Data and Big Data analytics will allow chief marketing officers (CMOs) to back up long years of experience and gut instinct with data-driven decision making that will lower costs and improve outcomes on every dollar spent.

“We are just starting to see the results among early adopters, and they are very positive” says Jim Gallo, a Big Data expert at ICC. “Big Data is giving these marketers an edge over their competition because they are able to reach their customers in ways that are more meaningful and timely with the right offers at the right time.”

For most CMOs, however, Big Data is two words on a page, and what matters is what it can do for their organizations. Do they want to improve their customer experience and engagement? Improve loyalty? How about leveraging existing customers to turn prospects into clients? What about growing the top line, increasing share of wallet or entering new markets? Big Data can help to do that and much more.

Big Data analytics allows marketers to segment their prospects and customers into micro-targeted groups based on behavior, not just demographics or transaction histories. Sentiment analysis from social media can combine with CRM data, for example, to create a more holistic view of customer lifetime value and improve cross-sell and upsell opportunities.

“While off-the-shelf solutions from vendors like IBM, Oracle or SAP look very complete, they still require integration before they can work in a specific environment,” says Gallo. “The good news is, no one has to reinvent how to do Big Data from a technology point of view. It just requires a commitment to get the work done.”

 

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