In today’s market research landscape, attending a conference without encountering a presentation on AI is akin to embarking on a quest for the mythical unicorn – as close to impossible as you can get. It’s the topic of the day at any conference, and I increasingly hear visitors complain that there is little else these days.
Right or wrong, there is no denying that AI is on everybody’s mind, dominating the conversation. But amidst all the hype surrounding AI, are we overlooking something important?
Let’s take a step back and look at how market research has evolved over the years. Working in the industry for over 15 years now, I’ve seen it evolve and grow. Long gone are the days of asking people a battery of questions, a long list of pre-defined statements and 5-point scales to answer. As marketing science evolved, so did market research. Consequently, we have developed techniques to measure implicit associations, to register behaviour and to gain rich insights through qualitative techniques at scale. These techniques have helped us to better understand and predict human behaviour and to help marketers be more successful.
So what then about AI? Going back to those presentations at conferences, oftentimes AI is heralded as the complete makeover of the industry. The holy grail, which makes all other techniques obsolete. And this is where I fundamentally disagree. We have built great research instruments and tools, there is no need to throw all of that away. Market research is not broken, it doesn’t need to be fixed, but it can always be improved. So instead of treating AI like a disruptor that’s here to overhaul everything, what if we saw it as a tool to enhance what we’re already doing?
Let’s look at a case in point: copy testing. In decades past, the strength of a copy was measured by forcing people to watch an ad in full and then sharing their thoughts through pre-defined statements. Today, we measure ads by showing them in context, registering people’s behaviour and adding innovative qualitative techniques for a much richer understanding of ad evaluation.
Already, this is leaps and bounds beyond what traditional market research approaches looked like. So let’s not use AI to do all those great things differently, but instead find ways in which AI can complement that. Indeed, we have recently integrated predictive AI into our approach, to understand consumer viewing patterns as they consume video content. The key point is that AI is not the solution itself, but rather just another piece to the puzzle which can help us see the bigger picture of ad performance.
At the end of the day, it’s all about delivering value. AI isn’t a magic bullet that’s going to solve all our problems overnight. But when we combine it with our established methods, we can use it to fuel our current approaches and to unlock new insights. It’s about taking the next step, rather than starting anew.
So, where do we go from here? AI may be stealing the spotlight, but it’s not here to steal the show. It’s here to join the ensemble cast and help us deliver standout performances. Let’s embrace AI as an evolution rather than a complete overhaul, challenge ourselves, and keep pushing the boundaries of what’s possible in market research.
