Big Data Analytics a Big Benefit for Marketing Departments

Today's companies collect a lot of customer data. Much of it sits on servers. Here's how firms in a variety of sectors can mine that data and turn it into increased revenue (and how IT departments can help).

By Reda Chouffani
Mon, September 24, 2012

CIO — Marketing has evolved tremendously over the years, largely because technology has enabled it to reach, when the situation calls for it, either a bigger audience or a more specific, targeted audience. The Internet has helped businesses reach audiences at much faster speeds and lower costs than more traditional advertising methods.

Simply having a Web presence and using the right keywords will drive search engine users to a website. Unfortunately, this has a side effect: More brands than ever are competing for consumers' attention. That makes it even harder for businesses to ensure a memorable and impactful encounter with potential customers.

Ebook: Strategic Guide to Big Data Analytics

To that end, today's marketing departments face many challenges. Organizations are still identifying methods to make their products more customer- and market-driven, while businesses are pressured to drive more qualified leads to their sales teams and to work with product development to ensure they're delivering the products and services clients are asking for.

Addressing these issues requires a creative strategy and a platform that makes it easier to close the gap with the competition, increase brand awareness and reach customers at the right time.

Incorporate Big Data Into Marketing Strategies

Some have identified marketing analytics as a way to resolve these challenges. A recent survey directed by Professor Christine Moorman and Sr. Professor of Business Administration T. Austin Finch with Duke University's Fuqua School of Business, found that marketing executives in the Fortune 1000 and Forbes 200 plan to increase their spending on marketing analytics in the next three years, some by as much as 60 percent. Many will be starting from scratch, as only 35 percent of respondents currently use marketing analytics.

Marketing analytics used in conjunction with big data will help many organizations properly evaluate their marketing performance, gain insight into their clients' purchasing habits, market trends and needs and make evidence-based marketing decisions. As one example, look at how politicians are using big data to identify their target audience and reach out to the so-called "silent majority."

With big data, there are several ways marketing executives can leverage existing data that's available internally, as well as external information received from a third-party vendor, in order to track the effectiveness of various marketing efforts. These big data strategies include the following:

  • Sentiment analysis
  • Soft surveillance and consumer behavior tracking within retail stores
  • Open communication channels with clients
  • Predictive analytics (which can monitor inventory levels and ensure product availability)
  • Analysis of customers' purchasing behaviors
  • Response to value-added services based on clients' profiles and purchasing habits
  • Effectiveness of real-time micro-segmentation of clientele targeted with custom tailored ads
  • Marketing departments should engage IT departments, and IT leadership, to help them accomplish these new goals. CIOs can then assist in creating a strategy that builds upon the data that's available internally. Such collaboration between forward-thinking CIOs and CMOs will become the basis of both competition and growth in organizations, as employees will look to use big data to find unique ways to outperform their competitors and peers.

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    It's safe to say that businesses of all sizes have access to platforms that in turn provide access to data and analysis. While in some cases internal systems may not have all the transactional and historical data regarding operations, customer purchasing habits and marketing performance, many of today's systems do provide an easy, cost-effective way to get a head start on big data, as there are numerous open source big data technologies available for firms to use. For large data sets, there are several scalable pay-as-you-go services that can process and host data.

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