Researchers have looked to technology to overcome the obstacles brought on by the pandemic. The newest tech being used is A.I in market research. This sudden increase in technology usage has many researchers questioning where else technology can better their services, with many turning to Automated Intelligence to add a competitive edge.
Automated Intelligence (or AI for short) gives computers the ability to ”perform tasks that normally require human intelligence, such as speech and image recognition, iterative learning and creative thinking”. AI has had an immediate impact on quantitative research, making formerly labor intensive processes that used to take multiple hours from several employees now only taking a few minutes of analyzation done by a single application.
AI will certainly be used by qualitative researchers to expedite technological processes, but many are questioning how. Below are a few ways researchers have seen how AI has already shown its place in market research’s future:
Word Clouds/Visualizing Data
- AI’s ability to quickly analyze and display information is among the most practical applications for AI’s use in qualitative research. Word clouds have proven to be helpful in deriving the words used to describe what it being researched, giving researchers a bird’s eye view of how consumers describe your product or service. This can be a double edged sword however, as this process has yet to be perfected and can require human intervention if the AI model begins categorizing nonsensical or irrelevant words or phrases.
Data Cleaning
- Online Bulletin Boards’ cost effectiveness and ability to capture the emotions of respondents while allowing respondents the ability to participate at their own pace has led it to it being an increasingly used method among researchers. AI hopes to play a vital role in this method, removing unrelated or unusable answers so that researchers are only shown relevant and useful responses. But, much like the Word Clouds above, there may need to be human intervention when the AI model struggles to classify what is and is not useful.
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