Fueled by the exponential growth of online communications and commerce, marketers now have access to an immense amount of data regarding customers and potential buyers. Marketers have recognized that this vast sea of data can be a rich source of insights they can use to improve marketing performance and drive business growth.
The use of data in marketing has a long history, but it’s been one of the hottest topics in marketing circles for the past several years. The benefits of “data-driven marketing” have been touted so frequently by so many industry analysts, consultants and technology providers that leveraging data is now viewed as essential for effective marketing. As a result, many marketers have made substantial investments in data collection and analytics capabilities.
The Real-World Use of Marketing Analytics
Despite the abundance of data and the increasing power and sophistication of data-related technologies, the actual use of data analytics in marketing isn’t as pervasive as all the hype would suggest. In the September 2022 edition of The CMO Survey, respondents reported that marketing analytics is used in 48.9% of projects
A survey of marketing analytics users conducted by Gartner earlier this year produced similar findings. In that research, respondents said marketing analytics influences just over half (53%) of marketing decisions.
When Gartner asked survey participants why analytics isn’t used to support more marketing decisions, the two most frequently cited reasons related to data quality and management – “data are inconsistent across sources” and “data are difficult to access.”
However, Gartner’s survey also found that the practices of business decision makers are impacting the use of marketing analytics. For example, a third of the respondents said decision makers tend to use the output of analytics when it supports the action they’ve already decided to take and to ignore such output when it points to a contrary action. Hello, confirmation bias!
In addition, about a fourth of the survey respondents said decision makers don’t review the information provided by marketing analytics, reject the recommendations provided by marketing analytics, or decide to rely on gut instincts to make their decisions.
Satisfaction With Marketing Analytics is Mixed
Research has also found that satisfaction with the impact of marketing analytics is mixed. For example, the September edition of The CMO Survey asked participants to rate the contribution of marketing analytics to company performance using a 7-point scale, where 1 = “Not at all” and 7 = “Very highly.”
Fifty-eight percent of the survey respondents rated the contribution of marketing analytics at 5 or above, indicating a relatively high level of satisfaction with the impact of analytics.
But in earlier research by Gartner, 54% of the surveyed senior marketing leaders – CMOs and VPs of marketing – said marketing analytics had not produced the impact on their organization they had expected.
Some industry analysts have suggested that underutilization and the perceived lack of business impact may cause some company leaders to reduce their investment in analytics capabilities.
Commenting on the findings of Gartner’s 2022 survey, Joseph Enever, a Senior Research Director in the Gartner marketing practice, said, “By 2023, Gartner expects 60% of CMOs will slash the size of their marketing analytics department in half because of failed promised improvements.”
A Cautious Approach to Analytics May Be Wise
But is it altogether bad for marketing leaders to approach the use of marketing analytics with a healthy amount of caution? I don’t think so, and here’s why.
Marketing analytics can fail to deliver the expected benefits for several reasons. First, the hype surrounding the use of data and analytics in marketing has raised the expectations marketers and other business leaders to inflated levels. And second, marketers are still learning how to generate insights from data and analytics that will make meaningful contributions to business performance.
It’s also becoming clear that the data most marketers are relying on, and how they are using that data, can produce “blind spots” that lead to less-than-expected results. An October 2020 article in the Journal of Marketing identified four of these potential blind spots.
- “First, marketing data may result in prioritizing short-term growth ahead of long-term growth.“
- “Second, marketers may overly rely on historical, internal data at the expense of forward-looking, external growth opportunities.“
- “Third, marketing data may create a preference for more easily measured digital touchpoints at the expense of offline channels.“
- “Finally, marketers may rely on available data in lieu of representative or predictive data.“
(Emphasis in original)
The fourth blind spot cited in the Journal of Marketing article alludes to a broader issue relating to the use of marketing analytics and also points to an important limitation of data-driven marketing.
As I noted earlier, marketers now have access to a huge amount of data regarding their customers and potential buyers. But the data most marketers are using to fuel analytics, while vast, is not comprehensive. It doesn’t provide a complete picture of the wants, needs or mindset of a potential buyer. Therefore, the recommendations produced by analytics are not always as accurate as we often assume, and this partially explains why analytics doesn’t always deliver the expected results.
Given this limitation, business leaders (including marketing leaders) should view the outputs of marketing analytics with a critical eye and not become overconfident in the accuracy of those outputs or the business impact they will produce.
Like all humans, we marketers have a strong tendency to base our decisions on the evidence that’s readily available, and we tend to ignore the issue of what evidence may be missing. Daniel Kahneman, winner of the 2002 Nobel Prize in Economic Sciences, 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.
The vast amount of data at our fingertips and the seductive capabilities of marketing analytics technologies can easily lead us to believe that the data we collect and analyze is the only thing that matters, and that simply isn’t true.
I’m not arguing that marketers should not use data, analytics and data-driven marketing. These tools and techniques can be immensely powerful. The key is to use them wisely and to remember they’re neither complete nor perfect.
Image courtesy of Rick B via Flickr (Public Domain).
