AI and Automation - More Time for the Good Stuff.
AI and Automation. These are terms that were first associated with big data, then with structured data, and now with small unstructured data (read “qualitative”). The capabilities of AI and automation are filtering into most aspects of the qualitative process. And the result is qualitative research that is often cheaper, faster, and - recognizing that this word is subjective – better. But more importantly, it opens the analyst’s time for the good stuff – solving the client problem.
Here are a few ways our qualitative life is being changed by automation and AI.
- Sampling – sample providers are using API’s to integrate with qualitative platforms to enable fast, efficient, and cheap access to consumers for a variety of qualitative approaches: communities, IDI’s, online groups and emerging hybrid approaches.
- Data collection – Online platforms for qualitative and hybrid approaches allow for quick turn qualitative research unimaginable a few years ago. Need to conduct 12 groups globally in a day? Done. Need to test concepts with 1000 people and get qualitative feedback in 24 hours? Done. Need to conduct “micro-communities” for a week on new positioning? Done.
- Moderation – the emergence of talent marketplaces now gives buyers the ability to become research DJ’s; to mix the right individuals with the right skillsets globally with the right technology to meet the business need in real time and all online. Qualitative research is entering the “Democratization Age”, where technology drives the human elements as much as it does the data collection process.
- Analysis – advances in AI, text analytics and data visualization tools now allow for the fast (within seconds, literally) categorization, clustering, thematic discovery, emotional analysis and even voice or facial analysis of responses as part of the tool kit. This makes the analysis of transcription, video, image and voice data as easy as running basic descriptive statistics in quantitative data.
It’s important to note that the effectiveness of all these tools are dependent on the right people, talking about the right things, in the right way. Recruiting, study structure, and moderation are still critical elements. AI and automation are still only as good as the thoughtful humans directing it. The advancement in these tools are drastically reducing the human time and effort it takes to gather and analyze qualitative information while improving the types of information and volume of information that can be analyzed.
This leaves the analyst with more information to work with and more time to focus on the implications of the insights to address the business issue. Isn’t that what we really need – more time for the good stuff?