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The Utilization Gap: Big Data’s Biggest Challenge

Big data’s the buzz. It’s in the press, all over the web… heck, it even has its own hashtag– #bigdata. CMOs recently reported that the percent of their companies’ marketing budgets devoted to big data will increase from 6% to 10% over the next three years. Multiply this 66% increase across all of the other areas Big Data is showing up in companies (e.g., supply chain management) and you have a sizable strategic expenditure. The bigger the company, the larger this increase. In data collected from The CMO Survey, companies with sales revenue of $10B or more will spend 13.7% of marketing budgets on marketing analytics in three years while companies with sales revenue of $25M or less will spend 9.2%.

Despite this big spend, there are reasons to worry that Big Data is not delivering its full strategic wallop. When asked to report the percentage of projects in which their companies use marketing analytics that are available and/or requested, CMOs report a dismal 30% usage rate. This number has decreased from 37% a year ago. So while companies are spending more on Big Data, less of it is being used.

Where does this “utilization gap” come from? I see ten sources:

  1. Producers of marketing analytics produce data but not insights. Users need insights.
  2. Marketing analytics arrive outside the decision making window.
  3. Potential users of marketing analytics may not have a strategic planning process or marketing decision making process that builds in a step to use available analytics.
  4. Marketing analytics systems are not sufficiently customized to the company’s marketing decisions.
  5. Producers and users of marketing analytics do not have a strong relationship that allows the analyst to understand or anticipate users’ needs.
  6. Users do not have sufficient training to understand marketing analytics. A crash course in regression and other simple analytic tools may be necessary.
  7. Marketing analytics is often viewed as a silver bullet and companies fail to collect deep, non-quantitative, insights about customers that provide the bigger picture into which analytics needs to be placed.
  8. Companies need to figure out how to use marketing analytics to create new growth for their companies, not just penetrate existing markets. Many companies have not figured out how to use analytics to enter new markets or to compete in wholly new ways.
  9. Accuracy is essential and yet there are areas in which marketing analytics fails to inspire confidence. Mining text is a good example of this gap. Investing in tools to understand what customers are saying about your company on the web and the valence of these statements is important. My friends in analytics tell me that these tools are not fully developed.
  10. Top managers need to model the use of marketing analytics. Asking for the data, asking questions about the data, pushing for insights, and taking actions in response to those insights shows the rest of the company what role marketing analytics plays in decision making.

Going after these sources of big data’s utilization gap is a good first step for companies. Maybe then we’ll see a new hashtag– #bigdatause– that heralds the impact of big data, not just its size.