Why are we data rich and insight poor?

  1. Data rich insight poor

How is it that we can be so data rich and insight poor at the same time?

I recently saw a marketing research ad online that said “Machine speed. Results in hours.” Was this an ad for new eyeglasses? Then I saw the punchline: “Agency quality insights in hours.” Wow. I may not know much, but I know you can’t get customer insights in a matter of hours.

What can you get in a few hours? You can collect some observations. Conduct a shop-along or an IDI. Field a “quick n’ dirty” survey on the web or mobile. You might even get in some quick analysis to provide an answer to a business question such as “which banner ad design do potential customers like more? Design A, B, C?”

But that’s not insight. Data does not equal insight and, I hate to tell you this, but insights are not agile. Only humans can have them. They take time and effort to generate. This seems to be a fact that many insights teams know, but struggle to communicate to the larger organization.

Even in the brave new world of digital marketing –  awash in data, analytics and metrics – marketers lack insight. A study by Adobe of 1000s of digital marketers in the US revealed that 77% have difficulty proving campaign effectiveness, 75% have difficulty demonstrating ROI, and almost 8 out of 10 have difficulty simply “understanding campaign effectiveness.”

The old adage “half the money I spend on advertising is wasted; the trouble is, I don’t know which half” still rings true today. The problem is the guy that said it died in 1922.

So what accounts for this dilemma? How can we be so data rich and insight poor at the same time? Some of my thoughts are provided below. I’d love to hear your thoughts.

#1. The vast majority of marketing research conducted is quantitative, confirmatory and often … duplicative.

Confirmatory survey research is designed to provide answers: you have a pretty good idea what’s going on but you require new data to prove a hypotheses. In my experience, organizations tend to conduct tons of confirmatory research to help make a decisions, and then commission more when the answers are not clear.

How many times have you felt like your customer insights team is “reinventing the wheel?”

We have boat loads of information from past ad-hoc surveys, customer segmentation studies, and on-going trackers. Meanwhile, technology-enabled data collection and reporting allows us to collect more data, faster and cheaper, than ever before. The global consolidation of panel, sample and online community management firms has made subscription-based data collection via standardized research products the norm.

As a result, many organizations have abandoned custom face-to-face research with their customers; but this is a major mistake when it comes to insight generation. There are some questions that can only be understood by an in-person approach.

When planning new research, look for sources of information that complement what you already have. Try some qualitative exploratory research to uncover the “why” of your “what.”

#2. We’re looking for a magic bullet.

New sources of data outside of traditional marketing research continue to appear – primarily from CRM and CX, but increasingly from third-party sources such as social media, review networks, the blogosphere, the IoT, government and other publicly available sources.

Each new technology or data source jumps on the hype-cycle rollercoaster, while gleefully touting “traditional [fill-in the blank market research methodology] is dead!”

Our newfound ability to combine sources of so-called “Big Data” – say your customer loyalty card records, plus third-party data on lifestyle segmentation, plus social media scraping – has created a whole new field called “(Predictive) Analytics.” The hope is that through algorithms we will discover a magic marketing bullet that will excuse us from ever having to speak directly to our customers again.

And while its seduction is difficult to deny, a recent IDG Research white paper on the Internet of Things painfully points out the obvious stating that “abundant data by itself solves nothing. Its unstructured nature, sheer volume, and variety exceed human capacity and traditional tools to organize it efficiently and at a cost which supports return on investment requirements.”

While this sector of the industry has attracted billions in venture capital, it remains to be seen if it can overcome its hype-cycle. Former GfK CEO Matthias Hartmann said the “waterfall of data hitting businesses is just the beginning of the new information age, as the internet of things adds to the weight of passive consumer data already being generated … but big data alone is not delivering any answers. I think the winners will be those who are able to convert and combine those data streams into real insight. So it’s not about big; it’s about smart.”

I think it’s about asking the right questions.

#3. We believe our customers are going to provide us with the big aha! insight.

Insight teams are often surprised when I tell them that their customers don’t have the insights. Your customers don’t sit around mulling over their behaviors, motivations or emotions. It’s our job to analyze the data, deeply understand our customers, and create new insights by connecting disparate pieces of knowledge in new or original ways.

#4. We don’t know how to synthesize data into insight.

If your customers don’t have the insights you want, then insights cannot be “automated,” “gathered,” “crowdsourced,” “collected,” or generated “on-the-go.”

No matter the methodologies or technologies you use, marketing research gathers only data (observations, facts, opinions, perceptions, beliefs, attitudes, stories, experiences, feelings, etc.). The collected data must then be analyzed to produce knowledge. Knowledge must be synthesized to create insights. But the world of Analytical Thinking ends at knowledge.

The problem is not many know what an insight is, and isn’t. For most organizations, insight means everything and therefore nothing. Nor do they have a process by which they can shift to Insight Thinking and turn knowledge into insights.

The question you want to ask is, what does customer insight actually mean to us? What makes it valuable and how can it drive your business strategy? Where could it enhance your branding, marketing, channels, innovation, etc. Where has it made a big impact in the past? Once you have these answers, you have a good starting point on which to build an effective insight delivery system and culture and measure its success.

A first step to developing this important capability is to define customer insight for your organization and create a template for writing them up.

Good insight statements should:

  • Explain the dilemma/problem/tension and explain why it is real
  • Test the status quo and provide a fresh perspective
  • Inspire action and show a clear path to the next step
  • Describe how you can help solve this dilemma and add real customer value

Becoming insights rich starts by understanding what an insight is, defining it for your organization, and developing an ongoing capability to generate new insights. Some of the most powerful insights come from combining existing knowledge with new findings; literally seeing new connections that can transform large amounts of data into compelling, actionable truths. True insights always inspire action. Data alone? Not so much.

About the Author

John Holcombe

John is currently the Founder of Wellspring Insights & Innovation and a member of the Board of Directors for the Miami Innovation Fund. John helps many iconic brands and organizations fill up their innovation pipeline with insights, ideas and new concepts. He also offers workshops and training on how individuals and organizations can have more and better insights by developing a culture of insight.

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