The start of a year brings about exciting opportunities and challenges around the office! So, before we all dive head-first into the holiday season (that seemingly slides all-too-quickly into New Year’s resolutions and task lists!), we hope you will consider looking at a few of the ideas we’ve pulled from our 2022 archive. A few tips or thought-provoking ideas, if you will, that you can take with you as you plan for the new year.
This compilation includes the following topics: marketing research and connecting on a human level; big data, causal analysis and randomized experiments; Gen Z; research storytelling; and customer feedback.
Can you hear me now?
“As a researcher, we are trained to never offer an opinion on a person’s response. That’s a given. Yet I believe there is tremendous value in making sure each person who participates knows they have been heard and that what they had to say, whatever it is, matters. In face-to-face conversations, it’s easy. A smile, a nod, an 'I hear you.' I remind others in a group conversation to remember to focus our attention on the person addressing the group. I don’t let people get away with saying, ‘Yeah, I agree with what he said.’ I ask that person to respond to me in his or her own words. It gives them power and reassurance. It encourages them to share their unique voice.
“Technology gives us fantastic tools and yet it can sometimes create a wall between us. We must remember that there is a person on the other side. And on a human level, we desire – we need – engagement.”
Takeaway: Technology has given the marketing research and insights industry so much, but it’s important to remember to connect with customers – in B2B and B2C – on a human level. Researchers must be sure to let respondents know they are listening to – and hearing – them. Read the full article.
Are randomized experiments the gold standard in causal analytics?
“The notion that big data has removed the need for theory and experimentation made a splash in the business media a decade or so ago and resurfaces now and again. This is a serious misunderstanding. It implicitly assumes more data necessarily means more useful information.
“Many large data files, in fact, are heavily imputed and error-ridden and, in general, the risk of errors in our data tends to increase with the size of our data. Moreover, even with high-quality data it’s quite easy to find something that isn’t really there, as explained in 'Stuff Happens.'
“I’ve also occasionally heard it claimed or suggested that AI and machine learning are now able to automatically identify the causal mechanism underlying any data. This is dubious for many reasons. One is that many of these claims confuse predictive analytics with causal analysis.”
Takeaway: So much of marketing research is part science, part art. This article will allow you to truly contemplate what experiments are and why marketing research and insights professionals use them – and answer for yourself if experiments are truly the gold standard in causal analysis. Read the full article.
For Gen Z after the pandemic, what’s next?
“Gen Z are often described as digital natives. True enough. But the assumption that they spend all their time on smartphones is not accurate, as we’ve documented in previous studies. The real world is so important to them for many areas of their lives, especially for more important moments and interactions.
“In this study, they revealed an even more strongly ambivalent love-hate attitude towards online. Sure, it has been a lifeline in all sorts of ways during the pandemic – for entertainment, information, keeping in touch with their friends and more. But the downsides became clearer. Many reported on digital overkill: of aimless smartphone scrolling, reaching online ground zero. This sits badly with an activist, let’s-do-it mind-set.”
Takeaway: There is still a lot to learn about Gen Z! But the rules of great storytelling – and great marketing research – haven’t changed. Read the full article.
How the elements of story can enliven your research reports
"Archetypes are a very powerful characterization tool. So powerful that they create understanding without plot. The misunderstood hero. The fish out of water. The wise child. Archetypes are more resonant, timeless and universal than personas or segments. Segments or personas exist only in their context as they are constructed from specific, situational behavioral and attitudinal data (plus possible biases). Archetypes also differ from stereotypes or cliches because they are rounded with both light and shadow. Stereotypes or cliches are flattened by biases into one-dimensionality.
“You may already be using archetypes indirectly. When respondents answer questions such as, 'If Brand X were a famous person, who would that be?' they may reveal archetypes. There’s an archetype in a respondent’s answer of, 'I see this brand like Johnny Cash, as a rebel.' Go deeper into the rebel archetype. What’s the secondary pop-culture analysis of Johnny Cash as the rebel? (Perhaps this is a generational view.) You can still use the quote about Johnny Cash but highlight the rebel archetype to take your audience beyond the celebrity aspect. Also, Johnny Cash had a long career, which may represent various archetypes to your audience depending on their generation, their feelings about country music or the band Nine Inch Nails. By going deeper to the archetype, you hit upon the universal (rebel) underlying the specific and take your report discussion to a deeper level beyond musical preferences.”
Takeaway: In this article, the author explores the challenge of moving from accepting storytelling as a part of the research industry to actually applying it. During this exploration, two storytelling myths are busted, specific dialog skills are shared and storytelling elements – including archetype and setting – are discussed. Read the full article.
Why feedback from customers still matters in CX research
"As customer data grows more prevalent, solutions more predictive and business functions more automated, we believe that the need for management to maintain a direct source of feedback will become even more important. Our reasoning is both practical and philosophical.
“A key feature of survey research that cannot be easily replicated via database or transactional data is what people say about who they are and why they do the things that they do. Consumer psychology tells us that direct responses collected through survey research are subject to various biases inherent in human cognition. They sometimes do not reflect what consumers truly think about a topic and, consequently, don’t accurately predict future behavior. Yet, despite all that, surveys provide vital approximation of how consumers reason and rationalize in the course of their decision-making process. Their responses are analogues to System 2 – slow and deliberate thinking that constitutes the stories customers tell themselves to understand their own thinking, mind-set and behaviors. Yes, relying solely on what people say inevitably leads to bias because people often say one thing and do another. But if we only observe what people do without hearing their rationale, we miss invaluable context on their underlying motivations, predispositions and personal aspirations.”
Takeaway: Marketing and customer experience solutions need to be more than just predictive. Researchers need to have a deep appreciation for what consumers say and what they do. Read the full article.