Drawing conclusions from data is really the core in market research, so the step to using AI to automate is fairly small. If you have datasets of images or text, you can easily use them to classify different factors such as geography, demography, ethnicity, and connect them with habits, opinions, and much more.

The majority of data that market research companies possess is text. 
Text data that can be classified into different categories, text data where correlations are found with other text data, and text data with a past which makes it possible to predict the future. All of which AI can help, to make things go faster and be more accurate.

Asking questions could be a really simple task, but knowing how to professionally build up a survey with the “right” questions is a whole scientific field of its own. For instance - you can ask “How old are you?” and you get the answer “42”.  But if you read the answer two years later it’s no longer correct. Instead, asking “What year were you born?” with the answer ”1978”, could be a much more valuable answer to keep for the records.  

Same question in two different ways, where the latter will remain useful also in a few years...

For the Question Library Similarity Search, we used the questions from 90’000 projects, resulting in som 600’000 raw questions as input and used state of the art NLP (Natural Language Processing) techniques to provide users with similar questions, to present good alternatives to choose from.

By systemizing the process of finding new alternatives for questions with help of AI, Ipsos can raise the quality of how their research is done, and maintain a high and consistent standard across the globe. And - in many cases save a massive amount of time. All of which will give Ipsos a better competitor advantage.

If you’re curious to hear more about the project, here’s a good video of Ipsos and Peltarion talking about "Similarity Assessment Using Bert in Market Research - Ipsos Digital", at Re Work’s Deep Learning Summit in London.