The market research industry turns over big dollars by providing reassurance to marketers that when they are wrong, they have an acceptable excuse.
The recent election campaign and associated polls demonstrate comprehensively how broken market research can be. It should have been simple. Is Labor going to win, will the conservatives take the lollies, or will it be a split result? It was almost a binary choice, but no poll I saw was even close.
Given that failure, how in heaven’s name can we reasonably expect such a broken system to deliver reliable answers to challenging questions about the future behaviour of customers and potential customers in a competitive and volatile environment? Add into the mix the inability of most marketers to understand the competing forces in their market sufficiently well to ask good questions and therefore write quality research briefs. That delivers a perfect recipe for pissing money against the wall in pursuit of reassurance.
Over the years as a much younger marketer, I spent a lot of money on market research. It took a while, but I did come to realise the data was only a tiny proportion of the game. The real challenge was building the wisdom, insight, and market gutfeel to be able to ask those really good questions. Then, when a surprising response emerged, have the curiosity to further interrogate it from a positive and genuinely inquisitive perspective to get an answer to the eternal question: Why is it so?
In the last year or so, and accelerating at an astonishing rate, is the ability delivered by AI to gather and process market and behavioural information that can be used to ask those challenging; why is it so’ questions.
The process of market research has been totally up-ended. No longer do you need to spend tens or even hundreds of thousands of dollars over months to get shallow and often dated results. Now you can replicate the task quickly and cheaply with superior results using AI, and what is emerging as ‘synthetic research’.
Traditional research is good at telling you what has happened. It is good at counting. However, if you need to know what will happen in the future, and you use yesterdays tools, good luck!
