3 Ways AI is Changing Market Research in 2018

3 Ways AI is Changing Market Research in 2018

No doubt you have been hearing all about Artificial Intelligence -

“It’s going to take over the world”

“We need to start using it on our business!”

“I think Alexa knows too much…”

It’s clear that many forms and applications of AI are impacting all industries - from media to finance to consumer goods. We’ve seen Artificial Intelligence in our everyday for quite some time now - facial recognition in our pictures on Facebook, personalized shopping recommendations on Amazon, and smart personal assistants such as Siri, Alexa, and Echo - are just the tip of the massive AI iceberg (A.I.ceberg, if you will.)

Many of these examples of artificial intelligence in daily life are consumer-facing but serve to show just how pervasive AI already is in our lives.  According to a study by software company,Pega, while only 33% of consumers think they use AI-enabled technology, 77% actually use an AI-powered service or device. On the business side, astudy by PwCstated that 72% of executives termed AI as a “business advantage.”

As for market research in 2018, AI is disrupting the way we think about insights - how to collect data, how to engage with our audience, and how to draw out hidden truths.

Traditionally, there are two forms of research - qualitative and quantitative. For decades now, researchers have developed advanced methods which allow us to analyze quantitative data in sophisticated ways - think cluster analysis and factor models (we told you they’re sophisticated). Now, AI is finally letting us apply these typically quantitative-only methods on extremely valuable qualitative data such as video, audio, and text. If you’ve been on the internet lately (which you are right now ), it should be clear that these qualitative data formats represent the way we communicate as humans -tweets, live video, Youtube, etc. After all, qualitative is the data that tells you thewhy.

AI market research toolshelp us to encode large quantities of complex qualitative data, and look at them en masse- in order to determine statistical significance.

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