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UK Insights

Watch: How can we make sense of unstructured data?

Matt Dodd

Managing Director, Analytics, Media & Digital, UK & Ireland

Digital 04.03.2019 / 14:00

ocean

AI opens up a huge opportunity to make sense of a new ocean of unstructured data, finds Kantar Analytics.

As our recent Media Predictions report stated, and as numerous publications have also claimed, Artificial Intelligence will continue to grow in importance to marketers over 2019. In business, we are generally comfortable with the idea of ‘robots’ taking on the basic, repetitive tasks that humans would rather avoid. But in a world where robots, artificial intelligence and clever algorithms can crunch and analyse huge data sets – the “Big Data” we also hear plenty of chatter about – what is the role for human beings?

The answer is that robots may change the types of jobs that are on offer, will it will not get rid of work – of our roles, to create new meaningful insights that drive business outcomes. There is still a place for humans in many facets of market research.

In this MSI webinar we share four examples of how STAN (Social Text AI and Natural language), the award-winning AI tool kit from the Kantar Analytics practice, has attempted to go beyond text and images to decode emotion and voice, as well as convince one of the most reserved industry sectors (that is, the government) to help us make better sense of big data.

The webinar demonstrates that while STAN can do plenty to help companies make sense of text, images, sales and other unstructured data, answer key business questions, and deliver business value, it has limitations. AI still can’t crack emotion or voice fully (yet), so we still need to triangulate these with qualitative, survey and consumption/audience panel data.

It is the combination of human understanding, machine learning and business purpose where brands can make most of the new technologies. It is reminiscent of the hype around social listening 10 years ago: brands jumping in without truly understanding the metrics do very little to driving business outcomes. The same is true now with AI – but we would argue that if you want to make the most of the new AI opportunity, you need to:

  1. Get rid of the “black boxes” and fear factor, by ensuring Data Scientists and Analytics experts speak the same language – a lot needs to be demystified. Show the human behind the machine.
  2. Think business. Focus on meaningful insights, and start with a business question in mind.
  3. Remember that data analysis is now the domain of machines. But machines can’t create stories, use frameworks or drive the organisational change that is still the domain of us insight (human) professionals.

Watch here.

Source : Kantar

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