When it comes to researching consumer attitudes toward brands, we sometimes take a less traditional route. For example, we know how valuable social listening is, but we tend to deep dive (which may be one of our core values) into social media to uncover the insights embedded in the chatter. We want to know which specific pieces of content they’re sharing and saving, and we want to know what they’re actually saying in the comments. Are they commenting on their experiences with the brand, the humor of the content, or does the content resonate with them in another way? We also keep an eye on what our competitors (and our client’s competitors) are doing to help us understand the bigger picture. Take the recent buzz around edgy content for CeraVe - even before the collab with Michael Cera, CeraVe was really leaning into interest graph content. This is the most entertaining content and that kind of content gets more visibility in feeds and it demonstrates that being real and relatable can really strike a chord with consumers. Last thing is you want to know is who you’re talking to (or who in the audience is listening) so that we can tailor our approach to the vibe in the audience because knowing that Gen Z prioritizes authenticity while Gen X craves trust and education can make or break your campaign.
In branding there is power in understanding the emotional landscape of the consumer, that's why we use tools like empathy mapping to gain clarity on this landscape. Beyond mapping out their emotions before they purchase, we like to map out their emotions after the transaction or conversion to understand what is the transformation or promise of the brand. Although powerful, these tools are built on a lot of assumptions and educated guesses. I found myself wanting to move away from assumptions and closer to the heart of the end user. This led me to implement a process based on language. One of the first documents I built is called Audience Language. Mind you, it's not the most creative name out there or the most complex document but it accomplishes an important role. This document is a repository for words and expressions the consumer utilizes to describe —with their own words— what we could only assume before. In essence it is quite simple. It would contain expressions you hear in sales calls, reviews clients leave online, comments you hear in person at events and conventions, feedback, testimonials and more. So far, so good. Using AI to organize all of these comments allows me to find patterns and intentions towards the brand very easily. But consider a step deeper. Building community around your industry and your brand allows you to ask questions that will then trigger the language you are looking for. Not only you can create your own community but you can also join other communities where you can ask questions. What I have found in the last decade is that there is power in asking questions. So find more places where you can ask them. And if you can't find them, create them.
As a strategist with an anthropology background, I've always been most interested in informal conversations. In what you can learn about a person and how they see themselves and their culture in a casual chat. Yes, there are tons of research tools, vendors, and methodologies out there that are scientific and generalizable and statistically significant. But what I find most fun is just an informal conversation with a stranger. A real person, not a faceless survey response. At a bar, or a grocery store, or in the concessions line at halftime during a soccer match, wherever. Bonus points if it's a place relatively close to the point of purchase or decision-making process. I think the world is running toward AI and the next tech thing, but really we should be running to people.
Customer reveiws are a great way to truly understand what the general consumer attitude is towards a brand or category. Simply using google review, Redit or other review sights are an easy way to see an authentic view of consumer pain points. And while not so unconventional any more, ChatGPT can be used in ways to further understand attitudes towards brands and understand their POV.
The Mystery Shopper Approach to Brand Perception Research One unconventional method I've used to research consumer attitudes towards a brand is by conducting "mystery shopper" experiences. Instead of traditional surveys or focus groups, I hired individuals to act as regular customers and interact with the brand across various touchpoints. This allowed us to gather genuine feedback and insights without participants being influenced by the research context. The data collected from these experiences provided valuable perspectives on customer perceptions, pain points, and areas for improvement. It was a creative way to get authentic insights into how consumers truly perceive and interact with the brand.
Beyond traditional surveys, we've found success with unconventional methods to understand consumer attitudes. "Social listening on steroids" involves deep dives into online communities where our target audience gathers organically, revealing unfiltered reactions and emotional connections to our brand. Ethnographic research embeds researchers within our demographic to observe natural brand interactions and uncover subconscious triggers. Finally, gamified research through interactive games or apps encourages wider participation and potentially more honest responses. These creative approaches provide richer data and a deeper understanding of how consumers perceive our brand.