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Why Moving From Data-Driven Marketing to Insight-Driven Marketing Makes Sense

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Insight-driven marketing is more valuable than data-driven marketing.

Having large data sets, or Big Data, is like having tons of ore. It's heavy, hard to move around, expensive to manage, and not very valuable. It takes teams of people to find, mine, and manage it. However, buried deep inside the data is precious gold; we as marketers need to determine how to show off the bling.

The Value of Data

Data is most valuable once it is released, shared, consumed, and ultimately applied. It then becomes insight. At this moment, that data is like gold to CEOs. It has far greater meaning and can hold its value even in its rawest state.

What is most interesting is that all research today states that being data-driven provides more productivity and effectiveness than not doing it at all. I'll grant that considering inertia as the alternative choice is probably not the ideal stage for agile marketers. However, there are two points that are fairly spooky when pouring over the research:

  • The number of marketers who are still very far away from adopting even the most basic steps of being data-driven
  • Being an advanced data-marketer is only the first phase of maturity

I believe that there are three phases of maturity:

  • Phase 1: Data-driven marketing
  • Phase 2: Insight-driven marketing
  • Phase 3: Innovation-driven marketing

Let's take each point one by one.

Phase 1

Being a data-driven marketer is not a new concept. It has been around for a few decades. Industries such as finance and insurance are just some of the early adopters that have been dealing with large sets of data, consumer behavior, and product consumption for more than a few decades. Companies like Harte Hanks cut its teeth on building data cards, database marketing services, and predictive analytics for a while. Catalog to e-commerce is another industry example.

The concept behind database marketing—using consumer data to provide the most ideal 1:1 end-user experience—still remains the cornerstone of even the most basic marketing automation tools today. This is not rocket science. We have been hearing about serving up "the right message, the right offer, to the right person at the right time" for years. And the legacy of many of the automation tools has to do with the legacy of email marketing tools, which is only a derivative of old snail mail direct marketing. Now, they are just catching up trying desperately to do a better job of capturing inbound consumer behavior but still have a long way to go.

So, if data-driven marketing has been around for years, and other industries have relished in its value, why can't the rest of the marketing community catch up?

The reasons have to do largely with internal issues: data management (22%), advanced analytics (39%), process (42%), skill (31%), culture (27%), and funding (35%). This gap is still hampering three out of four marketers to prove its marketing ROI.

Having a sound data-driven model should demonstrate the entire lifecycle of investment to conversion, but many tactical marketers think just because they track digital behavior that the job is done.

Tracking behavior is only the beginning of the process, however. This chart reveals that many of the behavioral or channel tactics are important, yet only two represent the business benefit of customer revenue.

The good news is that the development of data-driven marketing programs is on the rise. When this gap is filling, the companies currently executing will have distinct competitive advantage as they will be naturally moved into the next maturity phase, "insight-driven marketing."

Phase 2

Insight marketing is less about an output from the information derived by a data-driven business and more about the use of advanced models of thinking to put it back into a data-driven business.

Insight marketing takes the right combination of both the human intellect (having a hypothesis and imagination) backed by a sufficient amount of information and analytics to conduct the test models.

Marketing is a social science, so rarely is anything is 100% predictable, let alone 100% probable.  Stuff happens all the time, and much of it is invisible even with the best of intentions of adding the data sources into the model.

Moreover, two schools of thought exist regarding reviewing data sets.

One approach involves probabilistic statements about data, given the hypothesis, or making probabilistic statements about the hypothesis, given the data.

The key here is having a hypothesis. Too much data emphasis for data's sake and not enough thinking will end up giving us more data that doesn't help us make a next best judgment. (This is often the case with getting choked with multiple charts and graphs with no story to tell. There is limited or no meaning. Sorry, data miners.)

Having more of the same data often doesn't mean the outcome will be any different. And marketers who are quick to make biased judgment with a hypothesis-strong perspective can quickly drift away from the objective or empirical learnings (data). It is like looking at art and expecting someone else to see and feel exactly what you do.

In a business environment, usually the boss wins in this debate.

"In-depth customer data analysis can raise marketing's profile inside a company, better use of data and reporting helps marketers make the transition from the role of brand center to the source of insight," states Laura Ramos from Forrester.

A good example of insight is the prediction of the Obama win by Nate Silver who accurately predicted 49/50 states. He was insightful enough to pay attention to the overwhelming majority of nonpartisan polls; it was not all that hard to figure out that President Obama was the favorite to win the Electoral College. This is a prime example of developing hypothesis insight then using data to arrive at a conclusion.

I'm afraid that some data-driven marketers—who are so happy to just get at the data, run some models and display on fancy data visualizations tool—may lose the more intellectual demanding craft of thinking with a sound base of knowledge. This requires insight and taking data-driven marketing to the next level: innovation-driven marketing.

Though many marketers won't reach innovation-driven marketing tomorrow, it is what marketers and executives alike should strive to be. The first step towards innovation is to dig deep into the data to begin uncovering marketing and business gold.

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Jeff Winsper is founder and principal at Winsper, a marketing firm.

LinkedIn: Jeff Winsper

Twitter: @jeffwinsper

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