Beware of WYSIATI on the Road to Data-Driven Marketing

Fueled by the explosive growth of online communications and commerce, marketers now have access to an immense amount of data regarding customers and prospects. Many marketers have recognized that this vast sea of data is a potential source of insights that can be used to improve marketing effectiveness and drive business growth.

As a result, big data, marketing analytics, and data-driven marketing have been among the hottest topics in marketing for the past several years, and many marketers have made - and continue to make - substantial investments in data acquisition and analytics.

Yet despite the abundance of data and the increasing power of analytics technologies, many marketers aren't satisfied with the results they've obtained from their investments in data and analytics. In my last post, I discussed some of the findings in Gartner's Marketing Data and Analytics Survey 2020. Gartner's research found that:

• 54% of senior marketers (CMOs and VPs of marketing) say that marketing analytics has not made the impact on their company that they had expected.
• On average, marketing analytics influences only 54% of marketing decisions.

When Gartner asked survey participants why they don't use marketing analytics to support marketing decisions, the four reasons most frequently cited by respondents were:

• Data findings conflict with intended course of action
• Poor data quality
• Analysis does not present a clear recommendation
• Results of analysis are not actionable

The Limitations of Data-Driven Marketing

So why have data and analytics failed to produce the impact that marketers expected? Part of the explanation is that marketers are still learning how to generate insights from data and analytics that can make meaningful contributions to growth. But it's also becoming clear that the data most marketers are relying on, while vast, can produce "blind spots" that result in less-than-optimal growth strategies.

An October 2020 article in the Journal of Marketing identified four of these potential blind spots:

1. "First, marketing data may result in prioritizing short-term growth ahead of long-term growth."
2. "Second, marketers may overly rely on historical, internal data at the expense of forward-looking, external growth opportunities."
3. "Third, marketing data may create a preference for more easily measured digital touchpoints at the expense of offline channels."
4. "Finally, marketers may rely on available data in lieu of representative or predictive data."

The fourth blind spot cited in the Journal of Marketing article alludes to a broader issue regarding the limitations of data-driven marketing. The vast amount of data that we can now access and analyze, and the growing power and sophistication of marketing analytics software can easily lead us to overestimate the potential of data-driven marketing to drive business growth.

This overconfidence can make marketers susceptible to a version of the McNamara Fallacy, which the noted social scientist Daniel Yankelovich described in the following terms:

"The first step is to measure whatever can easily be measured. This is OK as far as it goes. The second step is to disregard that which can't be easily measured or to give it an arbitrary quantitative value. This is artificial and misleading. The third step is to presume that what can't be easily measured really isn't important. This is blindness. The fourth step is to say that what can't be easily measured really doesn't exist. This is suicide."

Like all humans, we marketers have a strong tendency to base our decisions on the evidence that's easily available, and we tend to ignore the issue of what evidence may be missing. Psychologist Daniel Kahneman has a great way to describe this powerful human tendency. He uses the acronym WYSIATI, which stands for what you see is all there is. My point here is that it can become easy for us to believe that the data we can track, collect, and analyze is the only thing that matters, and that simply isn't true.

I'm not arguing that marketers should ignore or avoid using data, marketing analytics, and data-driven marketing. These tools and techniques can be immensely powerful. The key is to use them wisely and to remember that they're neither complete nor perfect.