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Robot wars & Insight

Written by Jake Pryszlak

On December 12, 2016


AI (or, artificial intelligence) is a topic which is becoming increasingly prevalent within the world of market research. Whilst it is becoming common within the industry, I don’t believe it can replace human interaction and collaboration. And better yet, if it was becoming ever so common, then we would need to find new jobs! But I don’t see that happening, the humanist method of market research cannot be lost and I don’t think it will be. Companies small and large generating more and more data than ever before so, so don’t get me wrong, anything that makes our lives easier would be beneficial, and artificial intelligence could speed up research to be advantageous to us all including clients who are becoming ever so reliant on fast turnaround of data. However, there are some reasons why I strongly believe that artificial intelligence isn’t the magic ‘produce insight’ button we’ve all secretly been wishing for. I still believe a researcher can deliver excellent insights that clients want and expect.

Questioning the Data  

If you just give a client numbers, they’ll drown in them. Whilst they’ll have the data, they won’t have the insight, to use those numbers and make business decisions from. And to get the latter you need human brains to question the data. A human (maybe not a researcher) can ask those questions that artificial intelligence tools can’t; they can look further into the survey results, ask those relatable questions to unearth the ‘why’ from the ‘what’ and the ‘so what’ factor. They can give you true insight. The researcher can also decide which cross-tabs to run, which filters they need to apply to be able to really understand the story. For example, a researcher will see the NPS score and rather than taking it at face value; they’ll look to explore the factors that have contributed to it, build the background story and identify how the business can go forwards making improvements.


Asking those ‘why’ from the ‘what’ and the ‘so what’ factor questions

With artificial intelligence you could calculate your NPS score quickly and accurately, but there would be little depth of understanding behind it and the business won’t know how they can go about improving the score – they’d have the result but not the insight without going into the results themselves. An NPS score can give businesses 24/7 opportunities to showcase outstanding work with internal stakeholders and colleagues or rectify an issue. A researcher can understand the data quickly and potentially talk to members of the correct department to discuss issues. Artificial intelligence or robots wouldn’t be able to do that, and it would take a human to make those decisions whether it is something that needs improvements.

What About Qualitative research?  

At the moment, robots or artificial intelligence isn’t brainy enough to be able to handle qualitative information. For sure, It can help out with projects including data and run your basic frequencies. But in the case of qualitative research, where you might have tens of thousands of words to read through as part of your analysis – it might be good to have a helping hand. In these cases, you’re going to need a researcher. Once the robots have been developed further to be able to handle theming, sentiment analysis and other key qualitative analysis techniques, it can help with the bulk of analysis from online live chats, online research communities where the volume of content is staggering plus online surveys. But then the same issue will emerge with qualitative information that did with quantitative. You will still need someone to go through and make sense of the themes and sentiments emerging from the research. And you would still need someone to make sense of the data and information so you can translate this to your internal/external stakeholders and/or clients. If you have applied a principle called triangulation to your work, then you’re going to have to look to a researcher to blend the findings from all the different elements of the research to give you the insight and articulate in ‘business jargon’.

Bringing the Story to Life

There might be some great data visualisation tools available that give you a quick glance at the data in charts and tables (there are some freebies that offer you a starter for 10), however, without a humanist approach, the data will not be able articulated effectively to create visualisations.

How do you get this?

The story of the research needs to be brought to life; this could be a narrative or a simple infographic. Therefore, you need someone who has been delving into the data and information, becoming part of research and the data behind it. Unfortunately, even though many online survey platforms could argue that they show survey results in graph or easy to read forms, this is not bringing research to life, it’s much more than this, which robots can’t do just yet.

You Can’t Replace Experience

  Someone like an account executive or a research manager would have an understanding of the business/client and the challenges they face that is something invaluable for adding insight to research findings.

Being able to see the problems, apply the insight and tell the business what it really means for them is something that only an experienced researcher can achieve.

Whilst robots might be intelligent and able to save time for the researcher, I can’t see it being able to replace their knowledge and experience a research has gained over their career. I’ve always come back to needing a researcher who is then able to bring out the insight from research. Robots can help with elements of the analysis process but for the insight to be delivered, you need a humanistic approach to data detraction and analysis. If robots can be incorporated to make our lives as researchers easier then I am up for it; but there is a time and a place for a researcher to take over, ask those questions which automation can’t deliver the insight.

How do you think artificial intelligence or better known as robots will impact the market industry?   What percentage of a research project do you think could be automated by robots?

Tweet your thoughts and opinions to me @Jakepryszlak

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