Podcast. Season 2. Ep 8. Market Research & Technological tools: Are we in tune with the times?

Home 5 Podcast 5 Podcast. Season 2. Ep 8. Market Research & Technological tools: Are we in tune with the times?

Market Research & Technological tools: Are we in tune with the times?

James and Paul with the thoughts of special guests Faisal Khan (VP of products, D/A) discuss how technology have both advanced and democratised data and insights for organisations globally. Regardless of this accessibility, why do brands still rely on traditional forms of research? This episode takes us on a no-nonsense discussion on how you can start using technology solutions to advance your consumer insights efforts today. 

Listen to the full recording below or on your favorite podcast platform. 


Transcript:

Dr James Piecowye:  Hi, my name is James Piecowye. 

Paul Kelly: I’m Paul Kelly.  

Faisal: I’m Faisal.

James: And this is, “Know your Audience, the micro mini podcast”.  All right. I know our last podcast, we were talking about market research, we were talking about how there is a long history and tradition in market research. And ultimately how some of those tools, both quantitative and qualitative, when they are used, can ultimately not necessarily deliver the insights that are truly accurate to help you make better decisions. And part of that, as both Faisal and Paul elaborated upon was the challenges of us as rational thinkers, us as human beings. And while Paul would say we don’t intentionally lie about our feelings, we do put our feelings together often, as Faisal suggested, to really satisfy the people who are gathering the intelligence on us. Did I get that kind of close to what we were talking about, Paul?

Paul: Yeah, I think so. I think that’s pretty spot on. And of course, the next step, I guess, in all of this is the opportunities afforded by technology and just how exciting it is that certain industries have changed. I think if we look at everything, whether it’s cars and things like EVs and Tesla, and also but also the integration of technology into cars, I mean, even if we don’t have a one of those kinds of cars, you can just see yourself in new cars, you know, there’s no CD player, there’s no tape deck, there’s no eight track, right anymore. It’s just a Bluetooth thing, right? Because it’s just the technology, technology has changed a lot of things in a lot of industries. And that’s just I guess, one example. But one one industry, I guess that’s maybe a little bit lagging, as we discussed in the last episode was market research. But what’s really interesting to me, and what we’ve made part of this series, in terms of know your audience is really understanding who an audience is, for whatever it is, we’re not just fixed on brands, but it could be also media or entertainment, whatever it is, knowing who you’re talking to, is part of the challenge and market research has some flaws, and being able to answer that it does has, as we discussed, as well, it has a really good place in some areas, like asking people, you know, like, what, what something tastes like or something like that. But having said all of that, technology is very exciting, and what AI can do to understand people how everyday people can leverage it. I think that’s really exciting point, as well as that. It’s not just for big business. 

Technology democratizes a lot of things, look at advertising, for example, you know, 20 years ago, maybe more now, I don’t know. Advertising your services would either require like a leaflet drop, or maybe an ad in the local newspaper or something like that, but a fairly costly affair. So very small, micro businesses didn’t do it. And that’s why there wasn’t very many small micro businesses and look at it now, you know, you can really set up some sort of E-commerce activity on using utilizing the power of say, Instagram and Shopify and different platforms, you can become a global shop very quickly, but you still need to know who your customer is. Otherwise, it’s just pointless. And that’s what’s really interesting about technology is it democratizes the access to information. But also for various industries, like market research and big brands, they can start to leverage big data to really understand their customers and everything like that. And I just find that really exciting movement in an industry that I guess may have been very skeptical about it in the in the very recent past. So it’d be great to explore, I guess, in this one, and get Faisal’s thoughts on what he thinks the role technology can play in all of this and how techniques and some examples maybe of how technology plays a role plays a role in market research.

James: Well, that’s exactly where we want it to go and Faisal introduced this in our last episode. So if you haven’t heard that episode, go back and give it a listen because Faisal introduced this whole concept, this whole idea of technology playing a very positive role in this market research journey when he was talking about some of the old, older and larger organizations that have been doing market research that are fairly wed to the technology and the tools that they’ve been using for some time. And so much smaller organizations maybe would call them more boutique boutique organizations have come into play, who are starting to leverage technology, much, much more and this the technological change has happened so fast in the last couple of years, that it really requires an organization to be nimble, but it really goes a long way using technology to help address some of the flaws that are inherent to the way we have traditionally been doing market research. That’s where you left us Faisal? Can you jump in and and start talking to us about that? 

Faisal: Yeah, sure. So technology, these times with technology, I think is an extremely exciting times for market research. When the milestones of market research will be written, I think this will surely be there. And it’s finally becoming exciting, because like I said, you know, it’s an industry that’s taken some time to catch up. But it’s there, it’s there. Today, we have access to a lot of big data, like Paul was just saying, and through technology. So basically, this has really changed since the world has come online and especially in a post pandemic world where the significance of the online world online consumers has grown multiple times. 

There’s just so much information there. So today, we live in a time where we don’t necessarily need to ask people what they think, or how they feel, because there are enough expressions of them at much larger scale available online. So for real time examples, like you and I, we have to order food, I’ll go to a talabat, a Zomato, chapter reviews, check people what they’ve said about it, and then take a decision or go on food booking sites. I’m going on Amazon buying, I don’t know, if I need to take a decision on the next phone, I’m gonna buy the next button I’m gonna buy, I’m gonna go online check consumer experiences, what they’re really saying about it, get firsthand. And this cuts across any decision that you’re going to take, whether that’s buying, staying at a hotel, ordering food, going to a restaurant, planning your next vacation, your next phone, your next pair of shoes, headphones whatsoever. And when you and I are doing that on an everyday basis, brands can leverage that also. Because they just don’t need to ask people now anymore, right? They can just with the help of technology, with the help of artificial intelligence, source all this information that people are constantly talking about online, have that collected, analyzed and interpreted using technology, we’re talking about millions of data points, thousands of users, so it beats the size and scale and even the timing of let’s say traditional market research, because you’re getting real time data market research traditionally, is retrospective service. This is real time data at much larger scale in size.

James: So this, this enables us to do much more significant consumer intelligence. But ultimately, it creates a system where we can predict and understand what people are saying through what they’re posting up in their socials. Is that what you’re telling me?

Faisal: Yes, yes, that’s correct. And I think I’d pick up the word predict, because prediction in today’s day and age is becoming much more important to brands. It’s the Holy Grail of our brands, right is using technology for prediction? So of course, no, no technology can claim to predict the future but the probability of what’s going to happen next, increasingly increases significantly, because you have historic data. So I know what consumers were talking about a certain topic, two years back, three years back to how that’s evolved today, right, and how that’s how that’s changing, and how that’s likely to be in the future.

Paul: And also, on that, I just want to interrupt that James, I think, sometimes we place a lot of impact, or let’s say, emphasis on very time sensitive points in time. So let’s go back to 2020, the pandemic and everything like that, and the predictions around how behavior would change and all that sort of thing. At that time. If you’re at that time, and didn’t see beyond that time, you would probably believe some of them right like, like, just to complete societal shifts, because in living memory, or very few people, at least in living memory had lived through a pandemic. 

However, when you look at a lot of data over time, and in our last episode, we touched on the Netflix example, and the most probable explanation of their decline in subscribers is the fact that people are returning to not being at home all the time, or not, at least not being at home for a significant proportion, you know, with changes to quarantine, close contacts, all that sort of thing, people’s behaviors have gone back to normal very quickly. And if you travel to, between countries, for instance, that have restrictions and countries that don’t have restrictions. It’s just amazing how quickly it takes somebody who’s used to restrictions like myself to be somewhere that doesn’t have them, and then understand that, you know, our behavior won’t take very long to come come back. Yeah. Some things have changed and changed for the better if we, we talk about work and work from home and people like more trusting on that, but people have been doing that too, for 20 or 30 years. It’s why the cloud was invented. It was the portability of software. It’s that future the telecommuting as it was called only 20 years ago, it wasn’t work from home, then it was that the whole idea of telecommuting, it’s not new. But this was an this was an accelerant. But if you look at trended data over time, there are certainly behaviors that changed. I’m not saying nothing changed. I’m just saying that when you have the beauty of time based behavior over a long period of time, and you’re not just stuck in one period, or asking somebody a question, when they’re in the middle of a like say, if you had to talk to say a working parents in in, say, let’s say late May of 2020, they would have had a very different outlook on the world than they did six months before and probably six months after, when their kids were at home. They were trying to manage their work, trying to manage the kids schooling, all that sort of thing, it put a lot of pressure on people, and that changes your perspective. But then as time progresses, and certain parts of normality comes back, those opinions will change again, right? 

So if you have a long trended piece of history over time that you can see how behavior you can sort of say, okay, it was, you know, after the fact, is this something that we can expect, or will certain behaviors change, and it really helps us scenario planning, when you have a significant amount of historical data about behavior about personality. The whole theory that people’s personalities never change, which was very early psychological thinking has been blown out of the water now for about 30 years, as we age as our life circumstances change, our personalities change. All that kind of stuff can’t be factored. If I’m asking you today, James, how are you today, Faisal? Like, you know, how do you feel about something, because it’s what you’re feeling right now, not necessarily your life, full life experience, and how things have changed over time. And that’s the power of this stuff, I think, is that you just get this kind of information. And then AI enables the mass organization, there’s no way someone could sit through there and look through, say 2.8 million posts or pieces of information, or run a query on Excel, even, you can’t do it. Ai enables us to do and understand data at such a massive scale, that leveraging it is almost a no brainer.

James: So I’m gonna, I’m firing this to Faisal. And to you, Paul, we got three, three things, really, we’ve got our historical data that is going back, you know, many, many years, let’s say 40 years, let’s just pick up 40 years as a random number. We’ve got our new AI generated data that is actually rather new, we’ve got the old data can the two be brought together, because in my mind and Faisal, I’d love to hear your thoughts on this, in my mind, based on the discussions we’ve been having throughout this podcast, season one and season two, the AI data is based a lot a lot more on real time it’s happening and it isn’t collecting that those insights from materials where people might be expressing them in a way to satisfy someone who they’re talking to, or is interacting with them. They’re just getting their thoughts out there. That’s that’s the the the online stuff that our AI tools are helping us to organize, versus the more traditional quantitative and qualitative data that’s collected through surveys or interviews, or etc, etc, can the two be put together?

Faisal: They can surely coexist. But having said that, I think they have their own roles to play. If I want any kind of if there is need is to understand any behavioral data, or any consumer understanding or any explanatory understanding. There is enough and more available online sources through out I mean, even forget about people typing and sharing their experiences. Even let’s say Google searches, right? If you just rent, what are people searching, that can give you a lot of trends and explanations, a lot of behaviors. So for any behavioral data, I think there is enough and more available online, whether that’s Google searches, or people sharing their experiences are talking about what are their feelings and emotions. And that’s historically available to us. 

The role of traditional research is best in today’s age and time is not for these studies, but for anywhere where I need a response to a stimulus, where I need to have developed a communication and I’m going to take it to them and show that I need to show them something that can you see this communication and tell me what you think about it. Because in this case, you have to ask people, or you’ve developed, let’s say, a cheese recipe and there are three of them and one needs to be launched in the market. You’re going to get literally what they call it a central location, get 100 People get them to taste it, tell them what they feel about it which one kind of witch. So wherever there’s a reaction to a stimulus, I think traditional market research is the best. And wherever there is a behavioral understanding, I think there’s enough and more online. 

And this is more true in this region, it may not necessarily be true everywhere. But in this region, the internet penetration, social media penetration is almost for all practical purposes. 100%. So there is no distinction you can make between an offline consumer. So they were, if you asked me 20 years back that, should I do an online study? Should I use data from social? I may say no, because there’s a niche profile of people that’s there. Today, it’s 100% overlap, there’s no distinction. Maybe in some of the lesser evolved markets, I would still say that, you know, you need to rely on traditional market research much more, because you’re still getting a slightly niche profile online, right. But for this region, and I say this region, I’m talking about GCC and larger parts of Middle East, most of the Arabic speaking nations were the internet penetrations, almost 100% social media, and they’re one of the most engaged audiences. So for these days, there’s always there were topics which I never thought will be available online. You know, but you’ll just be surprised. Yeah, we were we were doing some study on the personal beauty. Right? And there is just I wasn’t sure how much people will talk about skin types, what products would suit for the skin? Or for that matter, oral care? What toothbrush, fresh breath? Is it something I’m going to go and talk about? Not necessarily. So these are topics, I was not sure whether I’m going to find online. But what’s interesting that if you don’t find them as content that people are creating, you will for sure find enough content, how people are reacting to content creators. So there could be a post on oral health let’s say. And it’s not a topic you go and talk about. Or the water I drink, for instance, the water I drink, it’s not something I’m gonna go talk about that the Hey, this is alkaline water, and I like alkaline water. But there will be enough comments and people reacting to people sharing their experiences, and that forms collectively huge set of data, data points that’s there. 

James: So when we when we think about that way of using and collecting sentiment, this is this is opening up in a sense, a new door, because you’re looking almost at you’re looking at reactions to other other posts that, as we’ve talked about in the past, would take hundreds if not thousands of person hours for someone to go through all of these posts, and all of the comments on the posts to collect that insight.

Paul: Yeah, I think on that one of the, one of the biggest benefits of AI, as we’ve discussed, and doesn’t matter what the data is, I mean, this could be first party stuff as well, it doesn’t matter. What it enables is an analysis of a far greater scale than anything that would have been possible before. So a market research survey or something might have been limited, like a political polling, for example, is a good example, you know, that might be limited to what, six 600 to 1000 respondents with a fairly high margin of error in built into that. There’s a limitation to asking the questions to analyzing the data, all that sort of stuff, especially in the days when it was hand coded. But now, we have at our disposal tools that can understand political sentiment, they’re not perhaps asking specific questions like in markets, where there’s, for instance, political parties, and voting and things. They’re not asking, you know, who you’re gonna vote for. But what you can do is look at people with different political tendencies or what what issues matter most to people at a huge scale, you know, you’re talking about 10s of millions of points of information on on in any one month, to understand what really matters to people and then to understand what matters to people within a specific spectrum. 

So that’s when you start segmentation and you start to realize, okay, these people with this sort of beliefs that believe strongly in you know, I don’t know something like universal health care where these people with this belief system don’t and so what I want to know is those people in the middle what they are interested in and what is important to them, and, and then expanding those audiences and things like all that sort of stuff would not have been is not possible without artificial intelligence, being able to analyze, report and organize information but but like I’ve said Data, Data is information. What you do with that information is critical and that’s something that humans still need to do. But our ability to interpret that information is made so much easier by the fact that we have a machine that can really develop and understand sorry, process not understand process information at just an unimaginable scale. In such a short timeframe, you know, something that might take an AI four or five have six hours to analyze 10 million bits of information. You know, that’s just not possible if it was somebody sitting there with, with an Excel sheet. So yeah, that’s, that’s just something that’s worth, I think, really reflecting on and how artificial intelligence makes our life a lot easier. And in the context of market research, what it enables us to do is open up a whole new world of insight that potentially was just unavailable to everybody,

James: What excites me when I, when I’ve listened to this entire conversation about market research, and the bringing of AI into the tool chest, is we’ve still got our traditional tools that we need, and there are times when we need them. But what AI is enabling suddenly, is I’ve got now a much larger time span that I can I can do my research on as in the timespan doesn’t have to stop. Whereas if I’m doing traditional research, I’ve got a survey, I’m sending it out. And it’s that very particular time, or if I’m doing interviews, it’s a very particular time, AI is expanding the time. And the time can keep going. And as you said, scale, I’ve got scale of data that I can collect for insights. So time and scale become very nice pieces to add on to what I’m doing in a very closed time and closed space situation Faisal, you want to jump in? 

Faisal: Yeah, there’s one thing I’d like to add, which we often don’t say enough about. But when you’re talking about AI, or traditional research. In traditional research, I sit with a team, I will think of 10 questions or 15 questions or 30 questions to ask the consumer. Right? These questions are things I know I need answers for. And that’s why I’m taking them. But there could be questions I haven’t thought about, right? And because these are, they’re not known to me. Now what happens in an AI world when it’s naturally capturing and collecting organic conversations that are happening there, It removes the human bias element completely, because there’s no questions asked, right? There could be things which I haven’t ever thought of asking. And because they didn’t strike me, right, because it’s our human mind, it’s limited. And that kind of opens up multiple, more insights that we didn’t in any direction which we haven’t thought about. And that really helps you building trends and understanding, better quality, more accurate, and much more, better quality of insights, because these are just things that otherwise, what happens you keep repeating the same Insights is the same people putting their brain together and just keeps repeating. What about the things we haven’t thought about? That’s only possible when you’re capturing organic conversations. 

James: Faisal, you’re you’re you’re in this field, what is preventing folks who are engaged in traditional market research from adopting the tools that we’re talking about? Is there anything preventing them from doing that? 

Faisal: Not really. So the market is really opened up. The users of research have now believe in the data that’s coming in and there are no strong barriers at this point. They’re getting data in real time. They’re getting data at much larger scale, they’re getting data that is much more informative, much more accurate, much more real time. So there are no strong barriers. But having said that, it’s time because like I said, market research dates back to 100 years, there are certain things we’ve been doing all our lives in a certain way. So for any change, there’s always going to be changed resistance. There’s always resistance to change. Right. So it’s a slow and steady process. But I think there is there are no strong barriers. And that’s great news. Everyone sees the benefits of it. It is just about the time, the natural time it takes for a transition to happen. That’s that’s pretty much it.

James: There’s great opportunity. All I keep hearing is opportunity. This is an opportunity moment and an opportunity time that is here and all we have to do is engage with it. And we can get our superior insight to whatever we’re working forward to. Wonderful. Faisal. Thank you very much. This has been an absolute pleasure. And I look forward to us picking up this conversation again in the future. I’m James Piecowye.

Paul: I’m Paul Kelly.  

Faisal: Faisal. 

James: And this is the “Know your Audience Micro Mini podcast”.