Predictive insights is the ultimate application for AI in market research
Toluna's country head Sej Patel looks to a future where consumer trends are known ahead of time.
Surprises aren’t generally considered a good thing in business. That’s why brands invest in market research – to test the reactions to new products or ideas before they’re released to the public.
Brands need to know what they’re up against at all times and must constantly monitor changing consumer sentiment in order to avoid surprises.
But imagine if a brand had the ability to not only monitor current consumer sentiment, but to predict future sentiment? Imagine if a brand could gather all the current consumer data available and filter it in a way that allowed them to see patterns and predict future trends? The advantages of this when it came to strategy and product development would be unfathomable.
The reality is, this isn’t too far fetched of an idea. The rapid adoption of emerging technologies such as artificial intelligence (AI) and machine learning in market research has completely changed the way we collect and analyse data. So as these technologies develop, it’s entirely possible that they’ll have the capacity to predict consumer trends in the not-so-distant future.
Real-time data
Market research has accelerated at incredible speed over the past several years. It used to be the norm for research to take weeks or even months to complete – the results of which would inform the next 6-12 months’ planning. But in the world of a 24/7 news cycle and round-the-clock social media consumption, businesses no longer have that kind of time at their disposal.
Now, businesses need access to insights that match the speed of the changing landscape. And thanks to the rapid advancement of research technologies, market research can now be turned around in a matter of days. What’s more, rather than waiting to analyse a thick paper-based report, brands can now open an app and watch their survey responses ticking through in real-time, getting a sense of where the findings are headed before the research is complete.
These kinds of rapid insights proved incredibly useful during the pandemic, with sentiment shifting and swaying dramatically in response to major events. In addition to the global health crisis, major social and political issues, as well as environmental concerns, have all permeated the collective consciousness, drastically changing the way consumers feel, behave, and act. Businesses that have kept track of these changes — and were able to adjust their strategy accordingly — are the ones who’ve managed to come out in front.
But as we look to the future, we need to ask ourselves if real-time data is going to be enough to remain competitive in future. How can we shift from having our finger on the pulse, to looking three steps ahead? With AI, predicting future outcomes is a very real possibility.
AI analytics
When it comes to data volume, you might think the more data, the better. But the fact is, too much data is simply impossible to analyse. With millions of consumers and millions of data sources each, the sheer volume of data that can be mined is astounding. But if you can’t make any sense of it, you might as well have no data at all. This is where AI comes into play.
AI completely transforms the speed at which data can be analysed. It breaks data down into easily digestible information, analysing it and presenting it in a way that delivers rich, detailed, and useful insights. AI can pull together millions of data points in mere seconds —a job that would be impossible for a human to do manually. And it’s particularly useful when it comes to sentiment analysis in open-ended questions — something which can be one of the most time-consuming aspects of reviewing data.
Using AI in this way is quickly becoming industry standard. But the real potential lies in how we can harness AI to predict the future. When combined with machine learning technology, AI learns as it goes, getting smarter and smarter, day after day. As it analyses the millions of data points from millions of people across the globe, it starts to notice patterns. And it’s those patterns which may hold the key to predicting future insights.
Looking ahead
Already, we have the ability to measure future brand health. We can, based on the consumer attitudes and beliefs today, measure a brand’s ability to fight competitive threats and have future relevance — and, if not, what needs to be changed.
What we can’t yet do is run a survey that tells us what consumer attitudes will be in one, two, or even five years from now. However, given the rate at which technology has been advancing, and the way AI and machine learning technology have completely revolutionised market research, the potential capability for such predictions is there. And what business wouldn’t love the ability to predict future consumer trends?
Sej Patel is the country head AUNZ of Toluna.
