How Can CMOs Make Sense of Big Data?

Author

John Rampton, Contributor

June 22, 2015

As with so many other areas of the modern economy, marketing has been revolutionized in the past few years by the growth of data analytics. Marketing teams and chief marketing officers (CMOs) are using big data for search engine optimization (SEO), e-mail marketing, customer segmentation, loyalty and rewards programs, and overall marketing strategy. While the vast majority of marketers understand the need for gathering and analyzing data, many still struggle with determining the best way to use that data. A recent survey showed that 45 percent of marketing executives rated their team’s use of data and analytics tools below proficient. It’s clear many CMOs are still in the process of truly figuring out big data. One thing is certain, we know it can make us smarter. Big data is being tasked to provide a “direct measurable impact on knowing the value of budget dollars in marketing,” according to Carl Tsukahara, CMO of cloud business intelligence provider, Birst. Aligning Data with Objectives A Gartner study found that the top three priorities for CMOs are:

  • Driving their company’s growth
  • Responding to any competitive threats
  • Delivering an outstanding customer experience

The question, then, is how data analytics can help marketers measure the success of their campaigns in meeting these goals. Too often, marketers view this data gathering and analysis as a passive process. They run the same campaigns and just use data to track things like hits and conversions, maybe tinkering with their strategy if certain elements are working better. A more useful way to utilize big data is to be proactive about experimentation, trying out unique campaigns and targeting, then figuring out what works through data analytics. You want to marry human creativity that can’t be contained in raw numbers with the analytical rigor to establish which efforts need to be pursued further. On the customer experience side of the equation, big data can be used to anticipate customer needs. You want to develop a platform that is immediately responsive to customer requests, and that means tracking user activity and feedback on your site in order to determine their primary needs. Getting to the Core Metrics CMOs need to determine how to make the transition from big data to useful data. Often, marketing teams get so overwhelmed with the sheer volume of data they receive from CRMs, databases, market research and other sources that they end up losing the forest for the trees. The key step for marketers is to figure out which metrics are essential to their brand, and which are merely interesting factoids. That means determining which metrics are most closely correlated with key brand objectives such as sales growth, market share and customer retention. According to Azita Martin, CMO of big data analytics and visualization company, Datameer, essential data metrics are those that clearly identify what gets prospects to convert to customers, and identifies which campaigns have had the most impact on customer acquisition. On the brand awareness side, brand mentions and search, media impressions, social media mentions, and number of social media followers are essential metrics to understanding customer interaction. “Nice-to-have” metrics, on the other hand, while important for understanding the overall health of marketing, are less immediate. “Those metrics which are more the ‘canary in the coal’ mine ones,” explains Wynn White, CMO of converged data specialists, Druva.  “You want to track them because they show trends in the business that when take a dip (or spike) means something is probably not working the way it is supposed to and gives you an area of focus in which to drill into,” White concludes. The most obvious example of the kind of data points that might not have much of an impact on sales are things like Twitter followers, Facebook likes, etc. If you’re increasing your followers but not growing sales, then those followers aren’t doing you any good. Find the metrics that are essential to your business, have tangible links to your key objectives, and experiment with ways to improve those metrics. The Human Element People sometimes bemoan how the increased volume of data in all walks of life seems to hide people behind statistics, but the truth is exactly the opposite. Data is a way to understand people and it requires an investment in your own human capital to understand. A recent Adobe survey of marketing professionals found that many companies lack the analytical skills to properly make use of their data. Machines can gather data, but it takes people with analytical and creative minds to turn all those numbers into actionable insights. “The job market has not caught up to the reality of this role, nor has the marketing community in general,” explains Jason Rose, SVP Marketing at human data platform, DataSift. That’s why employment growth for statisticians is expected to significantly outpace the overall labor market over the next decade. In addition to investing in their own people, marketers need to think of data as a way to understand their customers as people. The end goal of data analytics is to be able to respond to individual needs. Reflecting on his own recent hiring experience trying to find a qualified marketing analyst, Rose advises, “I would consider not including marketing in the job spec and finding a general “kick-butt” analyst who can crunch numbers.” And those numbers may be getting more and more finite, as executives have gone so far as to say that big data means customer segmentation will become irrelevant. Businesses will eventually need to understand each customer as an individual, some predict. “Marketers will say my job has always been to understand customers segments,” says IBM CEO Ginni Rommetty. “The shift is to go from the segment to the individual. It spells the death of the average customer.” This article was written by John Rampton from Forbes and was legally licensed through the NewsCred publisher network.

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  • How Can CMOs Make Sense of Big Data? - Content ... - 06/25/2015 11:20
    […] Big Data, business strategy, cmo  […]

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