Instead of solely relying on data, marketers should use a process-oriented approach that digs deeper ... [+]
As a marketing professor, a common question I receive concerns what has changed in the modern era of marketing. Defining the modern era can be tricky, especially since some accounts date the origins of marketing to be as far back as 1500 BCE. For simplicity, one can take a narrower scope and inquire about the last decade. If one takes such a lens, channels have certainly changed; platforms like Instagram, TikTok, and Twitch were either in their early stages, lacked an advertising capability, or did not even exist.
One of the most significant changes is the rise of informational currency. Marketers now possess the ability to rapidly build, access, and process massive repositories of data. With so much data available, shifts have occurred in the marketing function. It has become more action-oriented; marketers take the data they have access to—market share by geographic region, consumer purchase habits, changes in website traffic, consumer comments in forums— and generate an action or response. For example, if sales are down in a region, marketers might react by pushing advertising toward that region. If a TikTok influencer receives a lot of likes, a brand might seek to sponsor the user. If a consumer lingered on a website with items in their cart, but did not purchase, the brand might send an email promotion. A staple of what we term an action-oriented approach is that marketers collect data in droves and react to it.
This might all seem well and good, but as I have recently written with my co-author[1], Aparna Labroo, we view this action-oriented thinking as leading to potential short-term thinking, data tunnel vision, and precarious decision making. For example, focusing on the data that is coming in offers no guarantee that one is using the most important or the most relevant data. Indeed, we have found ourselves perplexed at brands that favor data because it is cheap or accessible, even though it provides little relevance to a problem at hand. Even when brands have good data—for example, clean data that establishes a decline in online sales— the presence of good data does not necessarily mean the appropriate action is taken. Knowing sales is down might tell you a problem of some form exists, but it does not tell you whether the solution require a change in the product, the advertising channels, the message, the creative work, or some other element.
What is the alternative? As we train the strategists we develop at Kellogg and in practice, rather than adopt a reactionary, action-oriented approach, marketers can instead develop and execute what we term a process-oriented approach. A process-oriented approach eschews a reactionary measure to data. Instead, it uses the data as a starting point to ask why a problem is occurring and what additional data will confirm or reject the hypothesis. A process-oriented leader uses the power of hypotheses to cut to the heart of a problem in a manner than leads to the development of successful long-term solutions as opposed to immediate (and potentially ineffective) short-term ones. A way to contrast the action-oriented and process-oriented approach is as follows: an action-oriented approach sees a problem and begins pulling levers in response to the problem; the hope is that one of the levers will do the trick. In contrast, a process-oriented approach sees a problem and steps back to ask what lever to pull and why.
How does one generate hypotheses, you ask? Although that’s a longer story for another time; it begins with applying what we call our INSIGHT framework. More specifically, marketers must understand the (I)ndidvidual consumer, the (N)etworks they belong to, and the (S)ituation that surrounds the consumer. Each of these involve curating the right data. Next, marketers can explore the (I)mportance of elements within each of these prior factors to understand the weight they carry. Notice, each of these steps involves seeking to understand the data as opposed to immediately reacting to it. Next, the fun part begins. With these elements in place, it becomes possible to (G)enerate (H)ypotheses and engage in (T)esting of these hypotheses. Essentially, via investing in developing and understanding insight, brands can direct their efforts to both gather better data and test ideas to avoid roads to ruin and identify how to pave paths to success.
In the modern era of marketing, it is all too easy to fixate on data in a way that ignores the real problems brand face and, as a result, leads to reactionary efforts that fail to solve the problems. Marketers need to take back the reigns of strategy by adopting a process-oriented approach that places a greater emphasis on understanding the root that underlies a problem as opposed to the rotten fruit on the branches.
[1] Rucker, Derek D., and Aparna A. Labroo (2023). The Consumer INSIGHT Framework: A Hypothesis-Driven Approach to Data Analytics” in Kellogg on Marketing, 3rd Edition.
