Latest / The Collaborative Canvas Podcast / From Maya to Rhea — The Evolution No One Talks About | What 30 Years of Research Really Taught Us

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From Maya to Rhea — The Evolution No One Talks About | What 30 Years of Research Really Taught Us · The Collaborative Canvas Podcast

• Speaker 3: Why did you identify Maya as Maya? Speaker 1: belongs to an era where market research was really in nascent stage. Speaker 3: Starting with Maya and reaching out to Rhea, now what those changes that you see Speaker 1: The entire backdrop of the whole book is about Speaker 3: Why you these 5 females? Why did not you choose something else? Speaker 1: The key decision maker in the house is me. Speaker 2: So Maya and Rhea are coexisting in many organizers. Speaker 3: but has been lost. Speaker 1: Most of the clients are living in a very hookah world. Speaker 2: focus of us as a researcher and focus of clients is on the verbal responses. Speaker 3: Writing this book, how has your own definition of understanding people changed? One research disaster you'll never forget. Before we jump in, quick shout out to our partner for today's episode. This episode is brought to you by Hubside Survey. Because let's be honest, data is everywhere, but real understanding? That's rare. Hubside helps brands go beyond numbers, combining qualitative depth with quantitative scale to answer not just what's happening, but why it matters. From interviews and focus groups to global surveys, they run the entire research process end to end. and they don't cut corners. With strict data protection, GDPR compliance and global research standards, every insight is built on trust that fits perfectly with our today's conversation. Because as research gets faster and more automated, the real challenge is staying connected to real people. Hubside Survey. Real voices, real insights, real growth. Check them out at hubsidesurvey.com. Now, let's get into it. What happens when three decades of qualitative research sit down on a goan beach and starts arguing? When cassette tapes meet AI dashboards? When slow listening meets real-time analytics? When instinct refuses to bow to algorithm? Today's episode is not just about a book. It's about the soul of an industry. Between the lines and laugh is a warm, witty, sharply observant journey through 30 years of qualitative research, told through five researchers shaped by their times. Beneath the humour lies a deeper question. In a word, racing towards speed, what does it truly mean to understand people? And to unpack that question, I am joined by two incredible, extraordinary storytellers of our craft. Ashwini, a research specialist with 30 years in the industry known for her deep work in culture, behaviour, change and generational understanding. A Best Storyteller Award winner at GKA MRSI and someone who has shaped insights across Ipsos. Sinowate, Market Probe, ORG Mark and now RSB Insights. And then I have Gita Kya Singh, 25 years of decoding human stories, behavioral changes, practitioner, leadership coach, auto expert, certified independent director and bestseller author. From JFK to TNS to Ipsos India and now co-creating narratives that bridge instinct and intelligence. Today we go beyond the book. So we go between the lines. Welcome Gita Kya and Ashwini. Gita Kya, I read the book Speaker 2: Thank you so much. Speaker 3: and it was like amazing. I mean, since we are into digital personas, I felt very close to the book because you actually decoded different eras altogether. So I'll start with you, Gautik. What was the whole story behind starting this book? Speaker 1: ⁓ So it's been almost 8-10 years that I always felt that this craft deserved to be heard by beyond market researchers. And whenever I have sat down, spoken to some of my colleagues, friends in the profession or even certain juniors who enter certain freshers, there's so much to share. And every time we sit down and share out of memory what happened in different episodes. we always end up with this should be documented, you know. So that this should be documented was always there at the back of the mind. yeah, so somehow the idea always kind of there was an incubation which was happening and it finally happened. Speaker 3: And Ashwini, was actually reading the book again. This concept Goan Beach that you brought into the book. Of course, the first page itself looks like it's book not for almost every MR word but children can also read it. It's so simple to understand and it comes with a story and that wittiness into it. So, Goan Beach, where did it come from? And then all of a sudden, Ashwini, this is again for you, this was the evolution of qualitative. And with respect to you both actually thought about that we every era. How this whole idea actually came up on the first stage. Speaker 2: So Goa because of course it's a favourite destination for everybody and we end up having a lot of MR conferences in Goa. So somehow there was no debate when it came to the destination and we zeroed in on that right in the beginning. And five eras again we debated quite a bit between the two of us, should it be four, should it be three, should it be six? And then we thought of distinct eras which are there from the time we started working in market research which was in the 1990s to today. And we looked at how India had also changed during these last whatever 40 odd years, which 35-40 odd years. And we looked at distinct changes which have happened ⁓ in India as a reason to define that particular era per se. And that's how we arrived at five. Starting from pen and paper, which Maya is all about, to Rhea, which is moving to the complete digital world and the AI world. Speaker 3: You have actually ensured that those names actually come from those era. Rhea is a very modern kind of a name which represents 2025. Maya is a very old school name which represents the pen and paper era. Why do you think that you should relate those? Speaker 1: So you must give us that much of credit. We did some bit of homework on that. And because we have seen those generations, you know, evolve and we see the kind of names which come up in the teams, you know, around in the peer circle. So, yes, the names are very thoughtfully chosen, which represent the various. Speaker 3: Let's decode this because one thing that I remember, the stories have made this book. So let's start with Maya first. Why did you identify Maya as Maya and probably Ashwini or Gitaika, I mean I'll leave it to you because you both have invested in Maya first. Then you move casually to the evolving environment. But before that, let's talk about the evolution of qualitative research because that would define Maya much clearer to the audience. Speaker 2: Right. So the evolution is, that's the purpose of this book also, to show how QOL has evolved in the last 35 odd years and what are the things which have remained the same because when we were discussing and thinking about the book and discussing the various nuances and the chapters, one thing we realized is that the basic premise of QOL remains the same, right? True. Which is about understanding human beings, about requiring good listening skills, about showing empathy. about decoding why people behave in a certain manner that remains the same. It's possibly the way we do research, the tools and techniques and the methodologies which have evolved over a period of time, but the basic principles of qualitative remain the same. So our idea was to show that, you know, through the different chapters to show what has remained unchanged and what is it that has changed over a period of time. So that's how. Speaker 3: So let's say there certain things which have changed. ⁓ And Maya was talking about the era which was more of pen and paper. Right. What was changing then, Kittika? Speaker 1: So ⁓ one of the things which was changing is people actually started doing market research. So Maya belongs to an era where market research was really in nascent stage. ⁓ You probably had only 20-30 qualitative researchers in the country. So Maya is very special from that perspective, almost one of the first one could say. So the change was that, you know, there was a lot more. selling which had to happen of what MR is and what qual is. So she actually we owe a lot to Maya because she is the one who laid the foundation for the entire profession. Speaker 3: Yeah, I could easily relate to Maya because I come from a pen and paper industry as well as an era as well and ⁓ though it was more of a qualitative, I'm more of a conned guy but when I stepped out and start talking to people, street intercepts, I was putting down everything on the pen and paper, it was nostalgic. Was that again a character you defined through nostalgia or it was something else? Speaker 2: So you are very right, it was nostalgia and this was the era that I started working in and obviously I have extremely fond memories of that era per se because that's when I was a child and I was learning the ropes of qualitative research in the 1990s. So there was a lot of nostalgia and we have tried to bring that out. also through the various experiences, kind of incidents, know, the way right from the first day of work, you know, that's something which we consciously thought of was to ⁓ build the tempo and the pace for that particular chapter through the first day of work. So if you see Maya, it was a slow, leisurely meeting with the boss, know, boss taking her out for lunch saying, just immerse yourself in the organization's culture and quality research and we'll think about or we'll talk about work on the next day versus Rhea who doesn't really have like a proper introduction and everything is happening on Zoom and Teams call and she's given a list of tasks that she has to finish. it is a journey of and we've lived through all these eras, mean, so there is a part of us in each of these. So while we are not Rhea in terms of age, but we do have Rhea's in our team and possibly the boss is somebody that we have been. Speaker 3: I tell you a quick story about this. I was reading the, know, specifically that first chapter resonated well with me because I also come from the 90s and ⁓ it was sheer nostalgia on my part because ⁓ meeting people on the street when you don't know them and then you know making that connect, you really need a support from your boss during those times that you know the first chapter begins with here and you know you have to ask these questions, how would you portray? There's an entire training slot that happens. Today, everything is like on the go. ⁓ But I still follow this. ⁓ we got a couple of candidates joined my organization and my company and taking them out for a dinner, taking them out for a lunch and then talking about business was still there. I'm not sure if you know those Gen Z people who have become managers would do the similar kind of it because I was reading some article and they said, you know, Gen Z's are quitting alcohol. They don't prefer alcohol and alcohol percentage has gone down from what millennials used to drink to like 2 % this year. So, the nostalgia was there because every single step we moved into the era, you know, it was correlating. I wanted you to decode that first nostalgia, probably Geetika you can start with and then Ashwini you can follow up on. Starting with Maya and reaching out to Rhea. You know, what those changes that you see, because book is actually denoting that, but I wanted the first hand story from you guys. When you were preparing that, you know, the change that was being seen in the qualitative world. Speaker 1: So you very nicely pointed out this entire shift which was happening and yes the entire backdrop of the whole book is about this shift, right? And how it has impacted the life of a researcher, a qualitative researcher. So if we look back India was changing a lot in 1990s. That's when liberalization happened and that's when a lot of companies came in and that's when MR picked up. That's when advertising picked up like how? So that was the era which defined. However, we did not have so much internet, we did not have Google, we did not have mobile. And yeah, it was easier. But today, while coming to the studio, I was thinking, imagine no Google Maps, no phones. And you're trying to figure out, we did figure out. Speaker 3: life was easier. Speaker 1: You just sat back, yourself into, immerse yourself into music and enjoy because you know somebody will take you. So that was one era. However, there was a lot of learning which was happening. People were very open. There was a lot of scope to make mistakes, which is much lesser now. I think that's one of the very big shift. Today you have to do things first time right. It wasn't that way. People were more forgiving, if one could say. And as you move to Sonal, she started experiencing mobile phones and I belong to Sonal's era. I started work in 2000. So there was mobile phones, right? You also, while you paid a bomb to even pay for an incoming call initially. But yeah, that's something which was happening. There was a lot in terms of technology, in terms of internet. We could Google things and find out. Although Google was not very prevalent then, it was more Ask Jeeves or things like that. But yeah, so that was something which Sonal benefited from. She could plan things in advance. Although communication, though mobile was entering, was not very prevalent. I remember those days when I would actually call up my boss. You know, that today's feel was that this done and this is left. And client was very happy and this thing was So that was a big high. You know, the end of the day calling and almost kind of updating. Speaker 3: I know. Speaker 1: which nobody does now because it's not needed because there's so much predictability. That era did not have predictability. There was so much uncertainty those days that you don't know what time you would reach, you don't know how many respondents would be there. The entire back checking, the entire preparation work was very different as compared to what it is now. So I think you must appreciate audience the kind of things which you have a privilege to everything is set everything is taken care of there's so much predictability it saves your time effort and the last minute all the glitches you know so yes Speaker 3: As you were speaking about it, I was actually having goosebumps because the moment I completed my first day of getting all the interviews done, I used to go back to my boss and he used to praise me a lot because you spend whole day to make sure that no interviews get packed. Today, it's a different story. So, when you move from Sonal to the other era, Speaker 1: Yeah, so other era was again defined by, you know, ⁓ lot of more, again, changes happening in the country. You know, there was so much better ⁓ mobility, there was so much better in terms of transport. And that defined and redefined the way research was being done. Because clients expected, you know, lesser spends and more ⁓ easy insights in terms of ⁓ reaching out to smaller places, I give a very typical example Kolhapur is something which Air Deccan made possible as a research centre because no other airlines was flying to Kolhapur. So I think suddenly newer destinations came up. So that's something which happened only because there was a wider reach to different kind of places and of course clients realized also if you realize you know India was getting a lot more into rural. You know this entire shikshampu success made companies realize that this is a huge audience sitting there, we cannot ignore them. They wanted to understand them more and more. So the art of listening to them and understanding and decoding them required a very different skill, right? So you could not talk to a rural consumer the way you talk to an urban consumer. So it was a lot of learning which was happening on go and like I said, you know, there were mistakes. Of course, there was a lot of time. Time was luxury, know. ⁓ Time was available then and time is luxury today. But people did give you that kind of time, effort, they appreciated you. So that's something which was fairly very different. Speaker 3: When I was actually reading the third era, I had that one question and glad that you actually brought up the rule conversations. Unilever was selling Dove then back as well. That one rupee sachet all of a sudden came around 90s as well. But it wasn't Dove, was, know, Dove was considered to be very premium, then it was chick shampoo and what not. It was predominantly being done for this rule segment and we still say that, you know, Indian population is 70 % all rural. Why did not Khol then approach the rule the way they approached the urban population back those days? Speaker 1: because Kual was being born in urban. You know that see your research gets dedicated to a place where the clients want attention to. So if the clients are focusing on urban market, remember the liberalization which is what focused on urban first. So while Coke got launched in Hathras, but Hathras was not its main ⁓ potential market, I would say. It wasn't the key target market. the target market was still to begin with urban. It's only when the distribution went much interiors is when the focus started. Speaker 2: But we were doing a fair bit of rural work, know, mean Unilever being a case in point, even in the 1990s. In fact, I would say that it tapered off a little bit, you know, towards maybe after post-2005 or so. But initially, there was a lot of focus on rural and all the big ⁓ FMCG players were doing fair bit of work in these rural areas. But then again, one is of course the access, the other is the time taken, right? Because time, cost, there are several considerations when you're doing rural and like she said, it's probably easier to manage. Speaker 3: I think the consumption power was high in ⁓ urban. Which is more of a reason because I remember the questions that I used to fill was for Maruti cars back those days. So it was more of an urban thing not a rural thing. In probably it was jeep or tractors. Those were the runnings. But when it comes to consumer products, whether it be shampoo or anything which they actually buy. I think rule segment ⁓ which is again my understanding because I was just remembering the conversations you know that chapter the third one that we didn't go to rule because of number of reasons I think time is definitely one cost is definitely one it's just where the profit margins actually set so people were more focused on that what Yuki Tika mentioned ⁓ but one thing which your book And coincidentally I relate to that when I started my podcast, the first Gen Z I interacted with was a female. So why you these 5 females? Why did not you choose something else? Speaker 2: Because gine chune men hai in the fall world and so that was, mean there was just instinctively we thought it's like a know women and we told the story also from a woman's perspective in a lot of ways. Speaker 3: I thought it's more of you know that emotional thing because men are harsh, women are soft. Speaker 2: And men in Koal can be soft. So I think it was because predominantly it's a women dominated industry. Speaker 3: That's all. Speaker 1: See, it also started, yeah, I quite agree to what Ashwini is saying. In fact, you know, the key decision maker in the house is a woman. So when the research as a profession started, especially qual, you know, you always spoke to the lady and the best conversation happened when a lady spoke to a lady. Right. So that's how it attracted more women in the industry. Speaker 3: Women wrote about five women. That's Speaker 1: And later on, know, it so happened that women can even talk to men very comfortably and stuff like that. Speaker 2: I think it's also there is a bias amongst men because I know that when we interview a lot of people, somehow we're towards quantitative because qualitative they think is this emotion, touchy feely, like just basically pull things out of your hat kind of thing and they believe that they're not best suited for qualitative. it's both. Please do we need more men. Speaker 3: I'm taking that as a feedback. ⁓ I mean the fact is that you know I can actually relate to that because quantitative was always easier game. You just go ask, pull down the questions, done. Qualitative needs depth and that's the beauty of my conversations with the people that I'm approaching and answering questions about Maruti sir, cars, those days because the depth actually came out not from those questions but the conversation that I'm having, why they're facing a problem. Those questions are just the reference point for me to understand the consumer empathy. and that's what I, you know at this age when I started the podcast that's what I'm trying to do because I generally don't want to keep the questions as scripted you know and when you asked me I answer then I said no I don't need those answers I really wanted to decode you know where we are actually heading into this whole story line so Ashwini when you these 5 females what was the real person in at time? Speaker 2: There were bits and pieces of, so I would not say there was one person, ⁓ there would have been bits and pieces of people that we have interacted with. There are bits and pieces of us also in each of these characters. So it is not based on one particular person, but like I said, a mix of several people. Speaker 3: And when you both were writing the book and when you were recalling those era, when you were defining this Maya to Sonal to Rhea, anybody that clicked your mind, that inspired you to write this book, think about her and you being part of their journey to you guys or you being part of their journey, was anything inspirational? Speaker 2: It's been inspired by everybody we've interacted with, our bosses, our colleagues, our team members, right from, in fact, our dedication mentions everybody, including the field team, all the support staff who's been there with us through thick and thin. So it's been inspired and it's all true incidents that we've spoken about. None of it is fictitious. These are all experiences that we've lived or we've heard other people talk about. It's inspired by all Speaker 3: I was actually thinking, probably you know... Okay, so I thought there are certain people that gives you a kick when you actually learn from them. ⁓ So probably your bosses, somebody. So I was able to gauge and imagine that who could these people be. But it was more like a ⁓ complete feminine package. Everybody, female. So the first question which I already asked. The second was to understand why. Speaker 2: including competitions. Speaker 3: Was this only the real people that inspired you? ⁓ Speaker 1: So I'll tell you, in my case, when I entered there was certain imagery of a Quall researcher, you know, and which is exactly what Maya is all about, which is, know, a saree clad lady, you know, very authoritative, yet very patient in listening, lot of empathy. Yet when she spoke in the presentation during the meetings, there was a lot of silence from the other end, people would listen to what she says. So it is not like one person as Ashwini said, it is the era. You know, it was a bunch of people then and bunch of people in 2000s and the bunch of people today. You look at the Gen Z and we have tried to create a persona of a Gen Z there who are a part of our teams, you whom we interact with day in day out, including our clients. So not one person, honestly. Speaker 2: We've received interesting feedback from the readers because some of them have called and said you are X, right? I mean, I'm going to name the person, you know that X person is based on Y, you know, somebody who's working in this office. So everybody's, you know, Speaker 3: Relating to the book person is of course. Speaker 2: So, than relating it to people who are there in the... Speaker 3: So, I don't know any of them. I was just reading the persona that you created for the tape recorder era to the Gen Z era and I was able to relate that even your preface says that these are real stories. So, it became easier for me to actually think of or imagine how Maya would look those days. Considering that we moved from instinct to algorithm, Maya from being a tape recorder to I think Rhea the AI era. and people are still debating and these guys still exist. How do you see the ⁓ combination if they both go together to an interview or the qualitative interview that they going to take? How would that ⁓ picture would look like? Speaker 1: So I'll put it this way, like I say, with time you have to evolve, know. So Maya has also evolved. She tries to connect better with Rhea, the best she can. So and she appreciates, you know, there has been a gap and a lot of water has flown since the time she entered to the time Rhea has entered, you know. So yes, she may not be completely out there and there could be certain philosophical differences. But like Ashwini said in the beginning, qualitative principles remain the same. There is an art of listening, there is an art of questioning and there is an art of empathy which needs to be put into practice. Having said that, ⁓ the way things are seen, heard and then ⁓ synthesized could vary when it comes to Maya. The reliance on say AI tools may not be completely out there. for Maya as compared to Rhea, maybe that becomes a starting point. AI tools could be a starting point for Rhea, whereas Maya would still prefer ke mai ek baar dekh leti hoon kya hua. I want to go through the videos, may not be transcripts, but videos before I actually rely on AI. So that difference will exist. Speaker 2: Just to add, I think they coexist, right? Even in any organization that you look at, there are people with 30 years of experience and there are people with 2 or 3 years of experience. So Maya and Rhea are coexisting in many organizations. And it's a give and take. They each, I think, sort of understand what Maya is bringing to the table and what Rhea is bringing to the table. So Maya appreciates Rhea. for some of the skills which is her AI, maybe the way she is crafting a presentation in terms of the look and feel because Maya's style could be a little bit different or the fact that she is able to understand AI much better. And Rhea appreciates Maya for the fact that she has got so many years of experience, she is able to call out insights, she is able to maybe have a certain process and system to the way in which insights need to be arrived at. So there is mutual ⁓ appreciation to a certain extent and they are coexisting. There will always be some conflict which will be there but you know that's Speaker 3: I was not thinking about any conflict as such. was actually thinking about that Maya comes with an experience where listening was very important. I think Genzies do listen but they validate every listening. Whereas, know, era of Maya and us, we never used to validate it. We used to consume everything and then started to look into what is relevant and what is not. Every single sentence which goes out now, I think there are people who would probably judge on every single sentence. that if you said then you will this. Whereas our time we used to After we used This conflict remains. I think this is not going. I think this is more of a personal attribute or character that comes along with it. But when it comes to understanding from instinct to algorithm, we are combining the two different ⁓ units together. What has been there, we already got to know from you. What has been lost? Speaker 1: Interesting. So some bit of the fact that everything is not said, you know, that's very important to understand, which is reading between the lines and that's the title of our book, you Between the Lines. So that's something which I won't say has been lost, but to seek evidence for everything and not believe unless someone has said it, you need to take that leap of faith and you need to have experience to understand where to take that leap of faith. So that's something which is becoming ⁓ lesser and lesser and I would say it happens from all the ends including the clients ask us, ye kitne logon ne bola hai. So that's a very big dilemma which we always face. Qualitative is not about kitne log, it's about kya shayad nahi bhi kaha but socha or that's the intent. Yeah, so that's something which needs to be respected and valued a lot. Speaker 3: Yeah, mean whenever I speak with a lot of my fellow colleagues in the MR ward, I mean for past two years I have been advocating qualitative research somehow because of the podcast or what. But I tell them and you actually cited this very well, I tell them that you know there are different seas. You either can count those seas or you can see the deepness of that sea which you will choose per say. So it could be an Indian Ocean, it could be any other ocean but the more you go deep into it which is why we always validate quantitative with the qualitative. It has never been about the number. I completely agree with that. But ⁓ as this industry is moving from being slow to almost like AI driven or probably we are preference plus we dashboards. There are few things which are not going as it should go. I I am trying to make a controversial thing without saying that it's a controversy. When brands actually look into the qualitative part, because they generally validate it, what do they actually look versus what they don't see what qualitative can bring onto the table. Speaker 1: So one of the things which qualitative research can actually do is bring to life what exists in market out there, it in households, be it in shops, be it in modern trade, be it in consumers mind. So now that's something which comes of course with experience and with the craft. Right? So the clients sometimes don't appreciate enough of giving time. to recreate that, you know, the entire experience, right? Many times discussions are limited to time or in the boundaries of focus group discussions. Whereas there's a lot more which is happening outside, you know, in the real world. So it's called ethnography, for example, you know, going and studying and understanding and observing. So that needs to be, but that needs time and that needs a lot of... ⁓ chewing on to what you are observing, analyzing on the ⁓ Speaker 2: Yeah, ethnography, exploration, the initial stages of initiation of any brand which is the overall understanding of people, the category, the context, the culture in which that brand operates. I think that is getting a little limited now. Focus is more on diagnosis. Problem hai toh help me understand why there is a problem. Or like you said, it's becoming like who want. you know and help me understand why something is happening in quant. No, I don't think so. I think that is not there. It's sometimes a lot of it is because of the time pressure because the call does take significant amount of time. then it becomes that, you know, there is already a significant understanding of the consumer. So let's go ahead with that, quantify that and then see if there's a call, you know, which is needed. Speaker 1: Actually we also need to appreciate that most of the clients are living in a very vuka world and there's so much of competition. They need to make quick decisions. So that's also a reason but having said that whenever there are enough clients who also appreciate and give this kind of time, efforts, money to do some kind of foundational work, the number may be decreasing for sure. because the pace of movement doesn't allow that kind of time. Speaker 3: Then is this something they actually miss behind the viewing mirror as the misunderstanding kuch hai wahaan pe because you guys are you know talking to them directly clients are not do they miss something there or should Speaker 2: It makes a lot of difference when clients are actually attending groups because like you said there is a lot which is happening inside the group which is not always possible to recreate in a presentation. So the verbal responses is the non-verbal, the silences, the pauses which are there, laughter, the look on their face when they actually reading a certain concept or looking at an ad. Those are very very critical which when clients don't attend. they somehow miss some of those nuances and then possibly the whole gist of the data does not come out as brightly as it would if they had attended the Speaker 3: Actually then I think I just again have this on one question you actually mentioned the body language. There's a lot of companies which have come up as eye tracking. They whether they are moving or not, they check that as well. Considering that we are sitting in an era which is more technologically advanced and you are doing a qualitative. Are there any avenues or you know I am not too sure I am just randomly asking this question that does qualitative research or the moderator wears some kind of a gadget sorry, not respondent, wears some kind of a gadget that can help decode their body language, character, what's going in their mind when you are asking certain questions. Speaker 2: So there are various techniques like you saying eye tracking and all is there, there are sensors and all which are available. Some kind of the application is limited to certain kind of researchers, so it's not as if like for everything you can use that and I think that human lens is still important, so you can't just rely only on what that heat map is showing but you will have to decode why it's happening in a certain manner, see patterns over a period of time for you to be Speaker 3: If we are talking now, sometimes I am looking at Githika and then I not looking at your face. So I not sure exactly if you are communicating eye to eye in that case. That happens more often during these conversations when you sitting in a focus group. So, there certain avenues which gets missed, there are certain characters with that we cannot decode. These AI or probably you those technologies can actually decode that. Does the client generally ask you to decode these through them because I am not attending and then I really want to... So, how deep we go in this case? Speaker 2: that has. So, I would still say that the focus of us as a researcher and focus of clients is on the verbal responses. know, 90 % would be on verbal responses and only partially it is on the non-verbal. And non-verbal also makes a lot of difference when you are testing any kind of stimulus, right. So, if you are getting them to try a product or look at an ad or those two would be the most prominent cases. So, in that case, these kind of techniques, the non-verbal actually starts playing a lot more. bigger role. Speaker 3: So they add a value to the deep dive conversations that we are having. Speaker 2: Yes, absolutely. terms of emotions which were getting associated, attention, whether people were actually focusing on that or not, what was the kind of emotion which was. Speaker 1: So I would also like to add to that. So tech definitely helps to many times capture where even a respondent either is not able to articulate or is not even aware of the behaviour or the movement or the eye movement. They are not able to ⁓ do it very consciously most of the times. So that is where the tech helps and human element helps them to focus and ask why. you did move your eyes from A point to B point. So let's understand what was interesting in B. What made you ⁓ focus there. Speaker 3: I remember I was attending this conference and they were talking about probing the AI. I again went back to the Maya era where we used to probe respondents. Can you guys give me that one example where this probing actually helped you deep dive into that conversation and brought out something which was client amazed? All responses. One thing that you remember. Random question that I am throwing on you because that probing always you know help a call researcher to understand that empathy. Speaker 1: So I'll tell you, I have this ⁓ vivid example in my mind wherein we were doing some work for a pharmaceutical company and for a brand which they felt needed a 2.0 version. I'm talking about early 2000s and it was a very popular brand written by lot of doctors but they said it's losing its sheen, right? And we did this personification exercise, you know, it's a for the audience personification exercises where we ask the brand, the respondents to think of a brand as a person and gives its characteristics of that person or an animal. So in one of these exercises the respondent said, brand toh elephant hoga. So we said, okay elephant hoga kyu? And ⁓ after a lot of probing we understood elephant not because of elegant walk. Elephant not just because of size, elephant because of pace. It's moving very slowly and I think that was a very big eye-opener while it's moving by it's moving so slowly and it needed to be like a horse is what another respondent said. You know it needs to run like a horse and from this brand when we consume this particular tablet, we don't want the effect to be so slow. So somewhere that completely changed the way the client started looking at the brand in terms of next steps. So that was an eye-opener. Speaker 3: So in the era where we have snackable outputs, what are we missing from not doing qualitative research? Speaker 1: Qualitative research is and snackable output is also very important because time is luxury like I said. Nobody has time to sit down and go through 2 hours of 120 slides. So it is very important. Speaker 2: And just to add, I think there's a misconception that something which is snackable is not deep. That something which is snackable is superficial and just surface level kind of stuff. That is not true. Now, if you look at the food industry, there are snacks which are full of all kinds of ingredients and super healthy. So a snackable content can also be very sharp and insightful. So it's just that it's... like she said, instead of 120 slides, it's been put down into 12 slides, but all the key insights and its implications are there. Speaker 1: So for everyone out there, you need to understand the kind of efforts which goes behind to bring out those snackable insights. So it does retain depth. Speaker 2: tougher, you know because when clients tell us that okay we need like a 30 slider, we all initially say, 30 slider then it's going to be easy, it's tougher because you know it's easier for us to put down all the data in 120 slides than to think of okay what is the crux and what are the main things that I want to tell the client in know sharp say 15-20 slider. Speaker 3: for me, snackable output as something that I'm presenting one pager about my company financials, just one pager about my company financials when I'm pitching for investment. That is a snackable content. But when it comes to qualitative, which we actually validate a big con with small portions of deep dive insights, for me snackable content ⁓ is good. now I'm basically now I understood. I would probably ⁓ echo that. But I still believe, you know, deep Diving with a consumer to know much better about what can my product, you know, improve to is always good. Then a snackable. Speaker 2: Absolutely, that is you are completely right. Speaker 1: So we do have different methodologies, for example, there's something called consumer connects, which we do, which gives a window for the client to actually go, the brand manager to go out there, interact, observe and see what is happening in the life of a consumer. So that's a separate thing. Whereas in day to day regular researchers, so they rely a lot on researchers today than in Maya's era. So a lot of responsibility of the researcher, I would say to bring those micro expressions and nonverbal cues to the client, to bring everything in snackable time and also to make sense of everything for the client such that it's actionable. Speaker 2: Yeah, and sometimes you know, I mean, just to add to your point, not every time client is looking at very, very deep inside, sometimes the questions are fairly tactical, right? And you just have say one or two things that you want to get an understanding of. So then the objective is to give the client answers to those two, three questions. Speaker 3: Yeah, and to give you a context of this, there is an article written by Sean Roy from Haleon and ⁓ I think Abhay Mathur or Akshay Mathur from Quantum, they did a case study together on synthesized data. They did about 70 internal journals because now the time was only one and a half weeks, probably like I think 1.5 weeks. Rather than going deep into six months of work, they actually squeeze it. with relevant questions what you mentioned that's you know, the or three things that you us a pointer, we'll get to know exactly what is there because the data was backing them up and they had the data so they synthesized that data. So I think now I understood you know that is basically for me as a snackable output because now I have something which I'm relying on and then I'm just you know, validating it with three or four points which I needed the most. That's amazing. I I think we the qualitative have actually evolved as we spoke. Speaker 1: Right. Speaker 3: The one specific question that I had about this book was that, you know, I call it the bigger question that after writing this book, how has your own definition of understanding people changed? Speaker 2: So one is of course, I mean, we really appreciate the fact that we spent and now we know why we spent so many years in market research and a lot of people, you know, used to ask us that, don't you get bored? mean, 30 years in market research and doing cool research, isn't it boring? And it's not. Every day is interesting. Every day is exciting. Every day you're learning something new. And it's thanks to understanding people because there is a vow in our job. Practically every day, think, know, because you just because we've got so many hours of experience doesn't mean that we know it all. You know, work is throwing challenges at us in terms of new methodologies in terms of you know, like I think Gita also mentioned that initially consumers also had time. Now consumers also have very limited, you know, time that they give us now how do we get the best? of understanding people within that limited time which is available to us. How do we make the best of understanding people in terms of reporting, you know, findings to the client within a few days of finishing fieldwork. So I think the way understanding people, you know, has, it has progressed, it has redefined itself a little bit over the last so many, you know, decades that we've been working, but the basic premise of empathy, listening, ⁓ you know, trying to see what is new is something which stands true even today. Speaker 1: I quite agree. In fact, you know, this entire understanding of people is so gratifying. You not only see the change that the way people have changed, the way India is changing, it's very gratifying. You also get to learn a lot about different categories. In fact, that's one of the best things which as a profession we have, we never get bored. Because you are like, you know, my earlier boss used to say we do work from engine oil to cooking oil, know, everything. So, every day is a new category, right? And the category which you have done in early 2000 or 1990s and now how it has evolved. You know, for a small example of how truckers used to be in early 2000 or 90s and now how they are. mean, Jio has really changed the way they consume data, the way they look at YouTube shots and stuff and the way they are well ⁓ updated with latest things. Speaker 3: Thank you so much. I mean, think we just read between the lines from the two beautiful ladies sitting next to me. There's a lot to talk about in the story as such, but we would not end it here, Ashwini and Gitika. There's something which we really wanted you to answer in just one word. Let's not deep dive. Let's one word for each decade in qualitative research. Speaker 2: So starting with the first one. Speaker 3: Yes, one word. So, mazmaya. Speaker 2: Maya was I would say ⁓ slow, slow in a positive manner. Speaker 3: Yes of course. Geetika, what do you think? Speaker 1: For Maya, she had the time and forgiveness around to make mistakes and learn. Speaker 3: Then so on. Speaker 2: ⁓ Sonal was adaptive, primarily because know lot of things, changes were happening around her, whether it was in terms of little bit of technology, phones coming in, the way people were travelling, liberalisation and all the new brands and so she was very adaptive. Speaker 3: and Githika for Gen Z Ria. Speaker 1: ⁓ she is completely bold and very open to learning and very quick. Speaker 3: One word for you guys, I mean, separately. Paper transcripts or AI summarizers? OK. Speaker 2: I can't say a mix of both. First paper followed by a little bit of AI summaries. Speaker 1: So I would say AI summaries on their own are useless unless you have actually gone through a little bit of know first hand feel or through videos and stuff. So you can't totally rely on them whereas on transcripts you could rely on because it's as good as you know going through the whole thing again. Speaker 3: ⁓ One research disaster you'll never forget. Speaker 2: Okay, so this was, I don't know whether I should be saying this on camera, but yeah. So once we ended up going to the wrong centre, you know, because there was the same centre was there in two states and without cross checking, we just assumed that this is Bilaspur, which is wherever it was. And when we went there and we realised that the client had actually reached the other centre. or was planning to reach the other centers. So it was a big disaster. So obviously we learned that you need to clarify all these things with the client and not assume just because you know of one place that's the state that they are referring to. Speaker 1: It's always the technical glitch. would say in earlier times the floppies won't work and now somewhere the internet doesn't work. Speaker 3: So one research disaster I will never forget is I was given a task to interview thousand people in France and thousand people in Germany and that was entirely the SaaS model that I have to work upon. What I did was I pasted the French invite to German and German invite to French and there was zero complete snakes there. So I remember that was my failure. Moderator instinct or structured framework? Speaker 2: So when you say structured framework, this is for the discussion, Yes. Speaker 3: discussion guide, the entire discussion guide. Speaker 2: Again, it's not either or really, but there needs to be a structured framework and yeah, so I would say structured framework is quite important. Speaker 1: I agree, unless you have a framework in place. So instinct doesn't always, it becomes very person-led, know, and clients sometimes don't appreciate and even I would in fact say that instinct comes only at the end, you know. Speaker 2: Once the decision between A and B and A and B are both equal and then there is a little bit of instinct which you can't do moderation or know based research on instinct. I feel this is what will work and won't work. Speaker 3: So long brief dinners or 20 minute zoom wrap ups. Speaker 2: I think the long deep, I think these are two extremes, so something in between but definitely not a Speaker 3: You have anyone else. Speaker 2: because you extremes. Speaker 1: If I have to choose one, it would be 20 minutes wrap ups because nobody has time today. Speaker 3: and one myth about qualitative research you want to break. Speaker 2: So, I think ⁓ one myth is that it is all very like you said instinct and you know depending on the person and it doesn't really always is not always based or backed by data. I think there's a lot of first principles which is involved there's a lot of science in qualitative research so that is something which you know people need to be aware of that it's not only emotions and fuzzy and what. Speaker 1: I would like to definitely let the viewers and everyone know that Koal can stand on its own. It's not always dependent on quant and Koal is not just about adding verbatims to the presentation. It's a lot more. Yeah, a lot of fundamental decisions could be made basis Koal and it's basically understanding human beings, right? And human is what the market sales is all about. That's the human being which buys your product and brands. Speaker 3: If call research were a movie genre, what would it be? Speaker 1: Psychological thriller. Speaker 2: Life of life. Speaker 3: slice of life. One habit every young researcher must build early. Speaker 1: listening. Speaker 2: Listening skills are extremely important. Speaker 1: You know earlier ⁓ researchers allowed, we were trained to let there be pauses. Now it's very difficult to let the consumer or even the researcher to pause because pauses bring in a lot of thought and then you start putting it forth, right, as ⁓ a respondent. I agree. So that patience needs to be there to let the pause be. It's okay. Speaker 3: Listen, pause and have patience. Beautiful. Thank you so much for making time out, Ashwini and Gitaika. I this was a beautiful story to be written again. I mean, think between the lines and laugh, should not be the first book to end with the last book. I think there should be more stories that you should decode. Thank you so much again for writing this book. All appreciations because when I read it, I'm sure people would love it and they would actually read through it and may have more questions. I am encouraging them to actually when they see this episode live they should actually point out some questions about qualitative research. Speaker 2: will be great. Thanks so much, Ankesh, for giving us this opportunity. Speaker 1: Thank you so much. This was wonderful and for the audience would like to highlight the intent of writing the book was to let people out know that research as a profession is extremely gratifying. It's a very exciting profession and do come in. We need more and more young minds and we do need men in the profession also. Speaker 3: So what I'm taking away from this conversation is very simple. Tools will keep changing, formats will keep shrinking, AI will keep accelerating, but the heart of the qualitative research has never been about speed. It's been about curiosity, listening, interpretation and empathy. Through Maya, Sonal, Aisha, Priya, Riya, this book reminds us that every era believes it is the most advanced, yet every era still depends on one thing, the ability to be truly their own people. And to everyone listening, the next time you look at the theme, a quote or a dashboard, pause for a moment. There's always a human story between the lines. So next time, stay curiosity, keep your curiosity going and learn from how human tendency changes, how human behave. And of course, read this book definitely. We'll meet you next time. Thank you so much. Thank you. Speaker 1: Thank you. Speaker 3: you