Today’s marketers have access to vastly more information and capabilities than ever before. Yet the availability of data and real-time customer feedback—and the ability for AI-informed communication—does not guarantee success.

In fact, if these tools are misused, they are far more likely to repeat (and accelerate) past mistakes. With that danger in mind, l’d like to discuss three familiar patterns or mindsets (“traps”) that I’ve repeatedly seen lead marketers, UX, and insights professionals to misguided decisions.

Getting “too close” to their brands 

By definition, marketers live and breathe their brands and at first glance, that may sound like a positive sign of dedication. But I’ve often seen that this knowledge leads them to lose the perspective of the end-user. When you’ve memorized every promotional claim, it becomes difficult to share the perspective of a shopper or user who spends only seconds making a decision. When you know every feature of your app inside-and-out, it becomes difficult for you to understand the person who struggles with technology. Interestingly, this pattern can lead marketers in two opposite directions: 

  1. Some waste energy experimenting with very small changes (in features, claims, offers, etc.), which are rarely visible nor meaningful to most end-users. They change the 3rd bullet-point on the package, but most users never make it there.  
  2. Others become “bored” with their brands and overeager to make dramatic changes, which often confuse and frustrate users. They change the brand’s core promise or identity, without bringing current users along for the ride (as was the case in massive disasters at Tropicana, JC Penney, and others). 

While these poor decisions (and their implications) vary quite dramatically, they are both rooted in the same problem: the gap between the marketer, who is immersed in their brand 24/7 and eager to make an impact quickly, and the customer, who devotes far less thought to the same product, service, or experience.  

Misusing consumer research 

Broadly speaking, research is intended to help bridge this marketer-consumer gap, and thus help marketers better understand and serve their customers. However, I’ve often seen that marketers inadvertently turn consumers into designers or assistant brand managers by:   

  • Taking people who make largely habitual decisions and asking them to spend 20 minutes or more, thinking deeply about these decisions.     
  • Placing people in situations they would not encounter in the real world—such as viewing 5 alternative package designs for the same brand—and asking them to choose ("Which do you prefer?"). 
  • Asking people about their future preferences and behaviors (“Would you buy this new product or use this new app?”), despite knowing that human decision making is highly contextual, and we are all quite poor predictors of our own future behavior. 

While most research participants are sincerely trying to be helpful, it’s easy to see how these questions often lead to predictable (yet misleading) responses. For example, people will: 

  • Nearly always say that they want more choices or options, despite the fact that more choices often leads to confusion (and a default to the familiar).
  • Nearly always emphasize pricing, despite the fact it is typically not the primary or initial criteria in their purchase decisions.
  • Often respond enthusiastically to new product or service concepts, yet fail to adopt them when they are later introduced. 

Of course, this is not an argument against speaking with customers, as asking the right questions—particularly those that help us understand the reasons behind their decisions—can generate valuable insights. But clearly, it’s also important to understand which questions not to ask—and how to guard against the trap of generating misleading feedback.

Because asking the wrong questions (and/or interpreting responses too literally) can quickly lead to wasted efforts and/or misguided decisions.  

Over-relying on data

This point might seem counter-intuitive, as browsing, shopping, and usage data can certainly provide insights that help marketers to:  

  • Better segment customers (based on their behavior patterns, rather than simple demographics or psychographics) 
  • Better identify “breakdowns” in purchase processes or customer journeys (and the right moments for targeted interventions) 
  • Better develop communications or offers tailored to different segments or audiences 

Yet there’s also a trap involved, as many marketers fail to recognize the inherent limitations of data. By definition, data is a function of what people have done in the past, given a certain set of stimuli, conditions and choices available to them. Thus, it doesn’t tell us what people would do, if they encountered a different context, message and/or set of options.  

By failing to recognize this reality, marketers can make “data-driven” decisions that are actually quite circular or self-reinforcing: For example, when data shows that people aren’t buying a new product, the natural reaction is to assume that the product simply isn’t compelling and therefore to give it less emphasis or distribution. This course of action then results in even fewer sales and thus accelerates the downward cycle. However, in some cases, the product may have simply gotten “lost” in a cluttered shelf or website (and would have been purchased, had people seen and actively considered it).

So it’s important to avoid the trap of simply following the data and discarding efforts that are floundering, but might flourish in other circumstances.

Of course, it’s far easier to identify mistakes than to propose solutions. Yet, over my career, I’ve searched for approaches to better understand human decision making, through both research methods (such as eye-tracking and shopper labs) and frameworks to influence behavior (such as COM-B and EAST). This journey has consistently led me to behavioral science, as a new lens through which to view marketing and consumer insights. Thus, I’d like to share three principles (rooted in behavioral science) that can help to navigate the traps described above: 

Leveraging Observation (“Seeing is Believing”) 

Behavioral science highlights the inherent limitations of simply asking people questions, given our difficulty in recalling habitual or quasi-automatic “System 1” decisions (and our natural tendency to rationalize our behavior). Instead, it encourages us to start by simply observing people in their natural environment—whether it's navigating the morning commute or doing the laundry—to uncover the influences that they may not be able to recall or express. 

Closely studying people’s routines inevitably reminds us that their lives are inevitably busy and there are relatively few “moments of opportunity” when they are open to a quick message or reminder. Thus, observational or ethnographic research serves as a reality check of sorts that can help marketers maintain an outside perspective, and avoid falling into the trap of becoming too close to their brands. 

Exploring Barriers to Change (“Change is Hard”) 

Behavioral science reminds us that change is very difficult. Even when people actively intend to adopt new habits – such as healthier eating or saving money—they’re often held back by a variety of factors, including:

  • “Hard” barriers, such as affordability or access (which they often express) 
  • “Softer” barriers, such as lack of confidence or social pressures (which they’re less likely to share) 

Therefore, driving trial and adoption of new products or services is always more difficult than anticipated, and marketers are well-advised to develop explicit strategies for moving people “from intent to action.” The use of behavioral frameworks such as COM-B, B=MAP and EAST can be a valuable complement to primary research, as they force marketers to think more broadly and strategically and to avoid falling into the trap of misusing research. 

Emphasizing Experimentation (“Test & Learn”) 

Behavioral science teaches us that decisions are often contextual and that slight changes in how options are presented (“choice architecture”) can have an unexpectedly large impact on decision making. This reality underscores the importance of continually testing new marketing approaches or interventions, and measuring their impact on people’s behavior through A/B tests, pilots or other controlled experiments. Building a robust (and cost-effective) process for experimentation can help marketers avoid falling into the trap of overrelying on existing data. 

Of course, these three principles only scratch the surface of the behavioral science field, as they barely begin to hint at its richness and depth. Yet, my hope is that they provide an initial sense of how a "behaviorally informed lens” can begin to shape our thinking and protect us against misguided decisions.  

Moving Beyond the Nudge

It’s been over 15 years since the initial propagation of behavioral science, through books such as Nudge, Predictably Irrational and Thinking Fast & Slow. In that time, many marketers have become familiar with individual concepts or heuristics. Sadly, however, they have tended to view the field as little more than a new "bag of tricks," selectively—and often somewhat haphazardly—applying specific concepts to address narrow, tactical problems. For example, they may employ loss aversion in a marketing promotion, or modify choice architecture to encourage trade-up to premium offers. 

While these efforts may be well-intentioned, their effect has been to undermine the impact of the field, as many marketers now mistakenly equate behavioral science with “nudging” (or perhaps the clever framing of a message). Yet, when we look a bit deeper, it’s clear that behavioral science can actually serve as a foundation for re-thinking our approach to insights and marketing by: 

  • Grounding us more deeply in people’s everyday habits and decision making (through observation), 
  • Focusing us squarely on influencing decision making and behavior (rather than simply creating awareness and intent), and
  • Reinforcing the importance of testing, learning and adapting.   

With the advent of AI, marketers increasingly have the capability to inform, automate, and execute their efforts at lightning speed. Yet, if they aren't thoughtful, these new tools will simply accelerate many of the wrong marketing behaviors—and lead marketers to the same traps even further and faster.

Therefore, the real opportunity lies not in faster marketing, but in better marketing.

So, in parallel with adopting new AI tools, marketers should also take this transformative moment to step back, re-think their assumptions, and embrace new paradigms for better understanding and influencing human behavior.