Carlos Gomez–Corona - Embrace Psychology
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Carlos Gómez–Corona is the Director Human Insights & Sensory at Firmenich. His main responsibilities are to understand the future consumption of proteins, and the perception of natural and sustainable flavors and ingredients. He has conducted research both in academia and the industry, as well as teaching in the area of sensory and consumer science, collaborating with several research groups worldwide. His publications focus mainly on consumption experience, product perception and representation, and social responsibility. He obtained his master’s degree in Sensory & Consumer Research from the University of Burgundy in France, followed by a Ph.D. in Consumer Research at UAM-Mexico, in collaboration with the Centre des Sciences du Gout and ISA Lille. Carlos was awarded the Rose Marie Pangborn Sensory Science Scholarship in 2014 and is part of the editorial board of Food Research International, and editor at Cogent Business & Management.
Transcript (Semi-automated, forgive typos!)
Tian: Welcome to AigoraCast, Carlos.
Carlos: Thank you. Thank you for the invitation.
Tian: We're very happy to have you here. So to begin with our conversation today, we often like to ask our guests to explain how they end up in this field because we all have our very specific path to come to the sensory and consumer research field.
Carlos: I arrived like in the traditional way so my background is in food science, as in many people working in sensory. Then I started working in the food industry, I actually started working in Kraft when it was Kraft before Mondelez. So I was working in Kraft in the R&D department and I always liked sensory, but I was working as a kind of developer, so I was there for four years. There was no change so I decided to quit and went to France to study for a Master's in Sensory and I chose France because at the University of Burgundy, there still is a special Master, which is a master in sensory and consumer research so it is not food science with a specialty in sensory. So it's really sensory and consumer and statistics and something on psychology. So I didn't know French at that moment so I started to learn French, and then I went to the university, and I think it was there where I learned the most sensory. So I think the only limitation is that currently, the courses are in French, but for people that want to know more about sensory, I think France is a good destination.
Tian: Can you imagine that? What did you do after?
Carlos: Well, during the sensory master, you need to do like a kind of an internship so I did the internship in Mexico in PepsiCo, and then after the internship, I started working there in the sensory and consumer research department in Mexico City. It was a big department, so there were several people working in sensory, and we could have the budget to do all the studies and learn new things. I was there for four years and a half and there I started to give some courses at University in Mexico to students also in food science. So giving them courses on sensory, so I did that for four years while I was still working at PepsiCo. And then I decided I needed to maybe specialize a little bit more. So I started a Ph.D. in Consumer Research. That time I didn't want to quit again and come to France so I talked with one of the teachers that I liked the most, Dominic Valentine. She was our Statistics teacher, multivariate statistics teacher, and psychology. So I came back and told her that I wanted to make my Ph.D. With her. So we managed to find a university in Mexico that could enable the collaboration between here in France and a university in Mexico and then we had celviciolet because of the Ph.D. was in beer drinking experience and celviciolet has a lot of experience in the beer and it's a nice product to work with.
Tian: Yeah, it's very nice. People are jealous.
Carlos: It's easy to find consumers if you work with beer.
Vanessa: That's very interesting. Yeah, thanks for sharing, Carlos. Very interesting path entering into the sensory and consumer science field. Well, let me jump into a different topic, sensory digitalization. So it's a hot topic nowadays and we clearly see a big trend in companies going towards digitalization. And we understand that we are focused on updating and optimizing our global sensory methodologies for digitalization. But what do you understand by digitalization? It's a very broad term, right? So if you could share a bit of your understanding of that and what would be the main changes you see with digitalization?
Carlos: I think it's a big topic and it's a very broad topic and we can see it from different angles. I don't know, maybe you might remember there is a picture of this, this is a joke on which make faster digitalization in your company if it was the IS department or covid. And it's true that after covid, we see digital things in a different way in terms of sensory evaluation and one example is a presentation that someone from the US, an editor of Food Quality and Preference, he did in Pangborn about, for example, a driving bot, which is something that could be, I think it was a very nice way of doing that so we don't stop sensory measurements. And this driving bot, I think was a good option for the US. It could not be an option for example, where I live, I mean, I live in Paris and most people don't have a car, so they cannot go driving or the panels that we do in India. Many sensory scientists, what they did is they just started making digital online sensory evaluations so they send the samples to the panelists simply in a digital form, they just put a zoom call and send the samples and get the information from the panelists. In our case, we have blind panelists. When covid started I was still in Mexico so we have a blind panel. So we needed to start working with them via zoom and get the information from them and be sure that they were evaluating the same product all in the same order. So it was just some basic things that we needed to do. For example, we label all the samples. For example, if they were evaluating five samples, then we put a sticker in each of the samples of different colors for us so we put them to put the camera just in front of them so we can see which were the samples, and then we just tell them like well perfect, you have the samples in the correct order or you just need to move the samples. And that was something, mean, it's a very simple thing on the digital part and I think that is one thing on the digital changes for sensory and consumer. And I think besides that, one of the things that many companies are starting to do is to use all that data that you have because currently, well in the past the sensory data lived in excel files in the sensory manager's computer and it happens to me that someone asks you like oh, have we done the profile of this product? And then I just needed to remember and say yes, we did that profile about a year ago, and then we're just going to search so either you have fees and then you search it. But I don't think many companies have, for example, a data visualization software as simple as Tableau or any other software. Well now PowerBi, which is simple as PowerBi for Microsoft Office, a lot of companies are moving into uploading all that information into a data lake and then having Tableau or PowerBi accessing that and give it more use. That's a simple way of accessing the information. But there are some bargains because when you show that, for example, if you do a dashboard with this type of software and then you show it to someone, for example, a developer they are not familiar with that. So I think we need to change the way we present the results and move into this traditional PCA and Spider plot into maybe a more digital way of presenting the data. That is one thing that many companies are starting to do with digitalization.
Vanessa: Yeah, that's interesting. Yeah, the database is really important, right? Because in many situations we see companies getting insights from their data after collecting their data, but the historical data can really help you answering business questions that you may have, right? So it's something like really, really powerful to store your data properly, to standardize our data, and to pull historical data to answer business questions.
Carlos: Yes, and that's something very basic. If you go to other types of companies, they have done this for years. In sensory and consumer departments, I think we are more traditional and still, much of the research is stored as excel files and PowerPoint presentations and I think that I mean, there are many things that are changing. For example, all these online surveys we have seen that they have changed a lot so people don't question anymore the validity of making online service and now that change open the door to other digital tools. I think that one digital tool that I like is for example mobile Ethnographies. So there are several suppliers that can, for example, have an app where you can track the consumer. So instead of going to their house, you can use different apps. For example, there is one app called Indeemo, it's an Irish app for ethnographies, and mobile ethnographies. So there you can give a task to the consumers and then you can have pictures, you can have videos and you can make things that you cannot do in a traditional ethnography. For example, if you want to understand more about how a teenager is eating. So you can give the app several tools and use the app throughout the day. And then see this teenager is having lunch and then sharing lunch with his friends, what type of food is being shared? You have all this type of information in mobile ethnography. So that's something digital that is changing, which I think mobile ethnographies are something new. You don't see a lot of publications on mobile ethnographies actually.
Vanessa: Yeah, interesting. Yeah, it's amazing to see how covid and this whole situation has been pushing, right? Like collecting data remotely, all that stuff. Maybe before covid, many were like somehow afraid of doing that and now things are really moving on. So yeah, really interesting.
Carlos: And you have a lot more suppliers that have moved to the traditional agency to a more digital approach. For example, this app is Indeemo, but you have more suppliers that can support you on more ethnographic approaches so you do Ethnographies online. There are more tools that can support or you can see a lot more suppliers in sensory and consumer conferences where you don't see fees, I don't know if we can say brands, but everybody knows some of these things on sensory and consumers. So let's say fees. If you go to a sensory and consumer conference, you no longer see only fees, you start seeing more suppliers and more suppliers that can give you information about culinary information. It's available online. So we have suppliers that we work with suppliers that capture that information. On social media also see more suppliers that are getting closer to sensory and consumer and they are based or they are originally from the tech industry. So that's quite interesting.
Tian: I think this is a very important topic. So I think the world, as I was trying to see the world going to future, we're at this stage that we're trying to make everything digitalized. All the experiences, our data previously, lots of on paper just as like printing kind of expedite the whole world cultural industrial development. Now we're in this stage, we want to get every data into the digital world and then I think the most attractive part of this is after the data getting into digitized enables you to use the data in another level. That's when people are saying artificial intelligence, like machine learning models could be sitting on top of all this data. That may great like make those things smarter and smarter. People put smart on everything. So do you have experience with using artificial intelligence with sensory and customer data?
Carlos: Not myself, but we collaborate. I mean, we don't have a team dedicated to artificial intelligence within the sensory and consumer. And some of the things that Firmenich has published, it's actually if you share on the Firmenich.com site, you will see several initiatives that are towards artificial intelligence. One of the things that the company published in the newspapers and in the site was how the company built the first artificial intelligence flavor and it was a savory flavor for plant-based products using artificial intelligence. And one of the objectives of artificial intelligence is to help the flavor to do faster their work and be more assertive in their work. So it's not about cutting the creative team because you're using a machine, for example, when you're a flavorist, it's a very technical person. So you get a lot of experience working with raw materials and not all regions to have the same raw material. So maybe a flavorist working in Latin America might have some raw materials available versus someone working in Asia. And when flavors start working, they get experience in certain types of flavors. But it's until you have a flavor that is more experienced, then it's easier for them to maybe create the flavor more rapidly or understand some interactions. And one of the objectives of putting more artificial intelligence information to the creation team is that maybe you can have a younger flavorist that will access the same amount of information as a senior flavorist. I think that's an interesting thing if you think about flavor creation and artificial intelligence and it would happen the same in other areas. I don't think in the following years we are going to work the same as sensory and consumer insights. Just to give you an example of how it's moving, the agencies that we work with, I had an agency in Mexico that still was making this questionnaire by paper, and then in the timeline, you see, well, this is the time of the study and then this is the time where I put all the information from paper to excel and then I send it to you and I said to them, you have one week of putting all the information and then that person of the agency, she told me, yes, you're right, so I'm going to put more people working on that, but I just need to charge you more so I can have more people working in entering the data. That doesn't make any sense because you just need to move to more digital things. So those agencies that are working in this past way of using the data, they're not going to be successful in the market anymore. If we think about all the digital data that will be available, it's interesting from an artificial intelligence point of view because we can input all the data into a model or several models, but it also depends on the quality of the data. So this old idea of the statisticians that bad data will give us, for example, for regression, the teachers tell us that in school, bad data is going to give you a bad regression model and it's true in sensory and consumer. So one of the things that we do and how we interact with people working in artificial intelligence is to share data that has quality of the data. So you cannot mix data from a very small consumer study, let's say 30 consumers, and then share data from another study that you did that has hundreds of consumers. It will not have the same variation. So our work as sensory and consumer scientists is to check that all the data that goes into the people actually working in the models are good quality data because what people working in the models, are statisticians or data scientists so they don't have the sensibility of that. It's our job to tell them, well, this is good, this is not good, this makes sense and this doesn't make sense. So that's more or less how I've been approaching artificial intelligence so it's not a project that I'm working in, it's a collaboration that we do with that.
Vanessa: Interesting. Yeah. While you are talking about how things are changing fast towards digitalization, it reminds me (well, I'm not that old) but when I started in the sensory field as an intern, my role was to measure the QDA, scaling for rumor and now I can imagine like people are doing that. But yeah, it's quite interesting how things are. Things are changing really fast and still more or less in the same topic, Carlos, you mentioned that we are using more and more different data sources and social media is one of the sources that we are using to get insight. And my question would be what role do you see social media playing in flavor development in your specific field? Do you have like examples?
Carlos: I do, a lot. In the case of social media, it's also very interesting. You can do many things and you can access free software like R and then use that Twitter module. It has huge limitations because you cannot make some restrictions when you capture the data. You cannot select countries or gender, and there are certain limitations that you cannot, but there are a lot more the same. You have a lot of suppliers giving you access to more tools to access social media. You have Twitter analytics, you have synesthesia, you have many suppliers and it's actually every year it's a publication about the top social media intelligence platforms. You can easily access that online and then you see a list of 20 companies. And in social media, you have a lot of information and it's also a lot of information easy to capture. You need to be careful of the topic you are searching for, the objectives of your study, and the regions that you're assessing because not everything can be studied using social media. And also, to give you an example, there was one person, one marketing person, that person had a project with low-income consumers, so they wanted to develop products for low-income consumers in Latin America so there was no budget to do the study, a more traditional study. And she told me, why don't you do just a social media study and see what a low-income consumer might need about a certain product? And I thought this doesn't make sense because people are not using social media to tell. For example, in my case, I am a low-income consumer and I have this monthly salary, so I would need products to be more affordable with better nutrition. They're not going to say that. So that's one limitation. Also to give you another example, I think the worst study I have done on social media, was an example of the data was very good. It was a study done to understand breakfast in Argentina, always focusing on flavors and flavor characteristics, etc. So we made a study, I'm from Mexico so I don't know the details of Argentina but it was very easy because we speak the same language so we did the study in Spanish, so we did the search, we did all the social media filter, we started getting all the information and we put together a very nice presentation about all the information. When we present the results to the local team in Argentina, they were just quite shocked about the information because breakfast in Argentina is very simple. It is just like sweet bread and jam and orange juice. It's very simple. You don't see a lot of variety in terms of many juices, many fruits, and many different types of bread. And the result was, on the contrary, we saw pictures of beautiful bread, tropical fruits, and juices and the lady of the marketing person, she told us that's a breakfast that I have once every year. Just to sum up, the thing is that people are showing and selecting what they post. So they post this beautiful breakfast. So if you saw the results and you're not from Argentina, our conclusion will be people in Argentina, they have a huge, beautiful multicolored breakfast and that's not the case. And I think that was one of the worst. So again, in social media, you need to select which are the topics that are suited for social media. And some topics are very good. If you want to understand more about trending flavors, differences between flavors in different markets, perceptions about products, and attitudes about certain things, for that social media, it's great. And we have presented several things actually we present in the Eurosense. We will present in the following week something on challenges in social media in Latin America. Again, I think the role of sensory and consumer insight scientists is to understand how these tools are useful for us and which type of information we can get out of social media and not everything can be resolved via social media.
Vanessa: That's really interesting. Yeah, for sure, like social media, you can get very important information, and important sites, but you have to be careful, right? Those days I was reading, I even shared on LinkedIn, like how to deal with social media sarcasm. So there's an algorithm that people invented in the US. I forgot, the name of the university, but yes, to deal with the sarcasm because people on social media don't really see their expressions, right? The way people are talking, you don't hear the sound so you need to be able to capture it somehow because sometimes they are saying the opposite. It's not really what they mean so it's quite challenging.
Carlos: We did another study on whiskey that we present in the Pangborn in Scotland and it was a perception of whiskey and mescal in the UK and in Mexico. We did only the textual, I mean the analysis of the text from Tweets and Instagram. You kind of get similar results and that didn't make a lot of sense to us. So when we started working were in the analysis of images in social media. So we took a set of images and we just analyzed it using more like the methodologies of art history and we analyzed the composition of the image and what was the meaning of the image. I still have not seen any good tool to analyze automatically images because the things that we have seen that other suppliers have presented are more like these digital tools, it's more like automatic things to categorize that in the picture you have a dog, a bear, a brand, food, etc. But you don't have the symbolism around the image. And I think that's very important and we're actually going to publish a book chapter on the analysis of the image in social media and we take an approach very into the art history methodologies and yes, that's because I'm married with someone who is working on art.
Vanessa: Oh, interesting.
Tian: Yeah, this is very interesting. I feel like going into the future if we can somehow get images, analyze more images out in a more interpreted in a more sensible way, and connect those things, that will enable us the great power going to the virtual world with the sensory components as well. We can't believe this is already close to 30 minutes of the conversation, right? We can talk forever. So, for the last question, we usually ask our guests what you would recommend for the new young sensory scientists just coming into the field. Do you have any suggestions, or recommendations for them?
Carlos: I do have and I think it goes into the same direction of that it's our responsibility to guide these people working on more artificial intelligence or big data analysis, that it's our responsibility to guide them into what makes sense and how we measure things and does it make sense to mix data or not? One of the things that I think it's very important if you are thinking more as a consumer scientist. My recommendation to someone is to get closer to having an advisor like your Ph.D. advisor in psychology because of many of the publications you will see now or maybe in the past five years. We have like a boom in publications on emotions and when you see the work that some people do on emotions or it's published in certain journals closer to the sensory domain. It's actually going into the other way that journals of psychology and again, to give you an example, we have TDS as a methodology, (Temporal Dominance of Sensations) and you measure the dominance of the attributes across time and there are publications called Temporal Dominance of Emotions and while it makes sense in terms of data because if you ask consumer they will give you a response. But if you think about an apple or a beer, how much it changes your emotional state when you drink, it will not drastically change the way you feel. So actually maybe some alcohol consumption could change your mood over time, but it's not like a drug that definitely will change rapidly your mood over time. So it makes a lot of sense. So in this type of methodologies of methods, I think we need to choose correctly where does it make a change to measure temporal emotions? And I think there might be, but not all. So if you get close to someone in psychology who tell you, well, this is an emotion. Emotion is part of the effective phenomenon and gives you all the background, it will be very good. We understand the principle of the stimuli of the emotions so that will be my basic recommendation. I didn't do it in the past to get closer to psychology, and I do it now so maybe for consumer researchers, I strongly recommend that they took psychology courses, read, or get closer to a psychology advisor. It will be very helpful for their career.
Vanessa: Yeah, that's a great piece of advice, Carlos. Well, to wrap up our conversation, what's the best way for people to get in touch with you?
Carlos: Well, my Twitter and LinkedIn is my full name, so it's Carlos Gomez Corona. Also in academia and research gate and there's my account and my publications. There are some publications that are linked to my current work, and they are more proactive.
Vanessa: Okay. Yeah, we're going to add the links to the podcast. Thank you so much, Carlos. It was a great pleasure to have this conversation with you.
Carlos: Thank you.
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