marketing data analytics benefits, social media analyticsBusinesses and not-for-profit organizations clearly want data to guide their marketing decisions. But at the same time, many marketing executives realize that data-driven marketing falls short of its promise.  

Most successful marketers (81%) want to increase spending for data-driven marketing, and 83% believe it’s important to make data-guided decisions, according to recent research from ZoomInfo completed with Ascend2. However, only about a third of professionals now practicing data-driven marketing call the strategy “very successful.”

Recent Forrester Research found similar results. Most executives (81%) are unsatisfied with the speed of analytics and 69% were unsatisfied with the quality of data. More and more experts say an overemphasis on data and lack of qualitative analysis produces the dissatisfaction with data analytics.

The Question of “Why?”

In addition to wanting to know what happened, business executives want to know why things happened, writes Christopher Penn, vice president of marketing technology at Shift Communications. They seek patterns. They want to know what they should do. They want solutions.

While analytics tells you what happened, it doesn’t explain why it happened. That’s the domain of qualitative research, anthropology and ethnography, Penn says. Analytics performs a poor job at prescription. That’s a role for human researchers.

“Analytics is the rear view mirror in the car. It’s generally a very poor idea to drive the car forward while using only the rear view mirror as a navigational aid,” he says.

To better use analytics, Penn recommends:

  • Think not only in terms of what, but also why. Think about what to do next.
  • Anticipate the questions executives ask and answers they want.  Develop those answers proactively.
  • Build tools, dashboards and workflows to generate the deep insights and action-orientated recommendations, not just the answer to the immediate question.

Think like an Anthropologist

Three experts writing in the Harvard Business Review agree that focusing more on “why,” or the meaning and context, will provide better insights. Concentrating less on data and more on context will help obtain the full benefit from social media listening. In other words, business managers must “think more like an anthropologist,” they argue. The article was written by Susan Fournier, Boston University professor of management; John Quelch, a Harvard Business School professor; and Bob Rietveld, co-founder of a Netherlands-based marketing analytics firm.

“Social listening promises the Holy Grail in business: superior understanding of customers. Why, then, do managers fail to fully exploit it?” the article authors ask.

Information science professionals who typically analyze social media data are trained to organize and interpret hard data. They typically seek data that confirm predetermined views rather than seeking unexpected insights that change perspectives, as an anthropologist would. As quantitative analysts, they often lack an appreciation for meaningful context and are wanting in the knowledge, skills and methodologies used by anthropologists and other social scientists to develop truly important insights.

Trained human analysts can understand the context and interpret the meaning of social media comments that automated algorithms cannot. Their social media monitoring reports deliver candid recommendations about needed changes to products and business services based on consumer input. In other words, they can answer the question of “why.”

Others believe an addiction to numbers squashes creativity. Over-relying on analytics, marketers think little about why consumers engage, comments Evan Dunn in Econsultancy. That’s why data-centric marketers may not understand what truly motivates customers.

“Marketing – getting people to invest time/attention/money in brands, products & services – will always live partially in the poetic,” Dunn says. “Connecting with customers inherently has one foot in the abstract, ethereal, creative – and one foot in the scientific, mathematic, quantifiable.”

Looking more deeply into the content, context and motivations – not just the data — can yield better insights from media monitoring and measurement efforts.

Bottom Line: Data-driven marketing analytics falls short of expectations due to lack of human-based qualitative analysis. Numbers report what happened but not why. Relying more on human analysts to review social media comments can deliver deeper understanding and reap the full benefits of social media analytics by answering why.