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Conversational Research: Rise of Qual or More Qualitative Quant?
Imagine you are organising a trip for a group of friends, and your mission is to create an itinerary that delights everyone. What would you do to uncover each person's preferences and desires in this case?
You would probably initiate casual conversations, either talking or chatting with them individually or facilitating a group discussion. In other words, you would embrace a qualitative approach. You are unlikely to deploy a comprehensive U&A study or a concept test when there are 10 people to talk to.
However, if your task involves coordinating a team-building event for a company of 200 employees, your strategy might shift toward a more quantitative approach.
The point is that while our innate preference leans towards dialogues with fellow humans, scaling this engagement obliges us to adopt more structured communication methods, such as polls or surveys.
It inherently implies a compromise between people asking and those responding. The physical impracticality of conversing with hundreds of individuals within a reasonable timeframe and effort (some don't like talking to people at all!) propels us towards utilising formal tools. It allows us to scale up but at the cost of a deeper understanding.
The share of conversational research will grow with the development of AI systems. Currently, systems like Yasna.ai can conduct interviews (not only research ones) at the level of an average moderator (and those are the majority) while spending fewer resources.
But does it mean we are in for a blossoming of qualitative research? I don't think so.
Instead, we will see the rise of more qualitative-quantitative research, which will continue to require researchers to have a quantitative view of the world (and skills!). Still, we will become much better at answering the question "why", giving a more comprehensive picture of reality.
Traditional qualitative research will become an increasingly niche product, retaining the territory of "complex" topics and territories where (at least for now) humans beat the machines.
However, if your task involves coordinating a team-building event for a company of 200 employees, your strategy might shift toward a more quantitative approach.
The point is that while our innate preference leans towards dialogues with fellow humans, scaling this engagement obliges us to adopt more structured communication methods, such as polls or surveys.
It inherently implies a compromise between people asking and those responding. The physical impracticality of conversing with hundreds of individuals within a reasonable timeframe and effort (some don't like talking to people at all!) propels us towards utilising formal tools. It allows us to scale up but at the cost of a deeper understanding.
The share of conversational research will grow with the development of AI systems. Currently, systems like Yasna.ai can conduct interviews (not only research ones) at the level of an average moderator (and those are the majority) while spending fewer resources.
But does it mean we are in for a blossoming of qualitative research? I don't think so.
Instead, we will see the rise of more qualitative-quantitative research, which will continue to require researchers to have a quantitative view of the world (and skills!). Still, we will become much better at answering the question "why", giving a more comprehensive picture of reality.
Traditional qualitative research will become an increasingly niche product, retaining the territory of "complex" topics and territories where (at least for now) humans beat the machines.