Operator: Broadcast is now starting. All attendees are in “Listen-only” mode.

Renee Wyckoff: Hi. Good afternoon. I’m Renee Wyckoff, Research Design Engineer at L&E Research. We’re so glad you could join us today for the first in our webinar – in a series of webinars to be hosted by L&E in 2020. Our webinar series focuses on information and tools that can be used to support qualitative research. Today’s webinar will focus specifically on market research technology with two of L&E’s valued tech partners. We’ll be sending out a recording of this webinar should you be interested in revisiting it or sharing it with your colleagues that couldn’t attend. Before we get started, I wanted to mention that we’ll be taking questions and answering them at the end of the discussion. So, please feel free to go ahead and fire your questions off. We’re just not going to answer them until the very end. Let’s kick things off and get things started with meeting our partners. We’re so pleased to have Brianna Boyer, Director of Research at AYTM and equally as pleased to have Nihal Advani, Founder and CEO of QualSights. Hey, Brianna, welcome and thank you so much for joining us today. Can you tell us a little about yourself and your role at AYTM?

Brianna Boyer: Sure. Thanks, Renee. Hi, everyone. My name is Brianna Boyer. I’m the Director of Research at AYTM, also known as “Ask Your Target Market.” For those of you who might not be familiar, AYTM is an online survey platform that helps simplify and streamline the traditional process of conducting quantitative research, helping our clients drive agile innovation for their companies. In my role, I assist clients in executing their own research studies, particularly those involving more advanced methodologies such as choice-based, conjoint, max diff., and turf analyses. When I’m not working I can often be found at home – especially these days – with my three dogs who hopefully won’t make an appearance today. My husband who runs a recording studio out of our home. Normally, I wouldn’t talk about myself and say that I can be found on the couch most nights watching whatever’s in season – hockey, baseball, football. But, that’s – that’s a little tough right now.

Renee Wyckoff: Yeah. That’s a shame. And that – no shame in that, really. Same. Yeah. I enjoy that, too. Equally as pleased to have Nihal Advani. Nihal, thanks to you as well. Can you tell us a little bit about yourself and what keeps you busy at QualSights?

Nihal Advani: Sure. Thanks for having me. So, I’m Nihal, the Founder and CEO of QualSights. And my – my background is, I used to work in [INAUDIBLE sounds like – sales] for several years in both marketing and data roles across the research and display side of the business, prior to launching this company. A fun fact about me is, I used to be an internationally ranked tennis player. I used to play for India back in the Juniors. And that’s what actually got me to the U.S. and I played college tennis here but ended up – instead of going pro – getting into technology because I have a passion for that, too. And what keeps me busy at QualSights is I’m spending a lot of time – as the CEO I’m kind of into everything, a little bit of this and a little bit of that all the time. However, [INAUDIBLE] deploying technology continuously, as well as building relationships with our biggest clients.

Renee Wyckoff: Got it. Thanks, Nihal. So today we wanted to get started with something fairly simple. And let’s start with you, Brianna. What is it about the services that you provide that you feel lend something truly unique or different to the way your clients do qualitative? Now, I want to preface that with knowing that AYTM, obviously, is more of a – is a quant platform. So, let’s just throw that out there. Today we’re discussing mostly qualitative obviously. So, in other words, what is it that gets you really excited when you talk to your clients about your platform? Brianna?

Brianna Boyer: Sure. So, while AYTM is primary used for quant research, there’s still plenty to get excited about. We built a platform geared toward the DIY researcher. A growing role is –we hear more and more about how corporate researchers are being tasked with doing more for less. And, you know, what does that mean – “geared for DIYers”? At AYTM that means a few things – streamlined interface from programming to reporting, including a survey experience designed to be mobile-friendly in this ever mobile-moving world, automated advanced research tests, reducing the burden of programming, task design and analysis to simply populating basic inputs and letting the platform take it down there, making choice-based, conjoint and max diff. more accessible than ever to researchers who, maybe, historically have wanted to do those types of tests but didn’t have the knowledge or technology to actually conduct them. And, most critically, fully-integrated sample built on our own proprietary panel and key partners that extends to over 60 million wonderful humans worldwide, removing the need to source a sample vendor in addition to your platform or implement and test tricky redirect links. You can jump into our platform, set up your survey, click “Launch” before leaving the office and dive back into final data when you sit down at your desk the next morning. On the qualitative side, we do offer a few kind of more qualitative question types for those times when you need a bit more open-ended feedback. In addition to your standard open-end textbox format, we offer image and video response questions as well. With video response in particular, you can set up your primer and, additionally, put talking points for the respondent to go through. So, it’s like a little self-guided discussion guide, if you will.

Renee Wyckoff: Got it. Thanks. And, just curious – what is the – what’s the learning curve for a researcher like to get on and use AYTM?

Brianna Boyer: Sure. So, it’s very simple – or, it can be. It depends on what you want to do. It’s very straightforward, a very simple platform. You just jump in, pick your question type for our list. You have your standard radio and checkbox questions, you have grid formats, open-ended questions, video response – that kind of thing. And you just simply put in your question text, put in your answer options, and you’re basically ready to go. If you have more advanced logic that you need to do, we do have our kind of AYTM Logic System that you can use to program basic logic all the way up to pretty complex things, and include an “Auto-Complete” to help guide you through adding those types of logic.

Renee Wyckoff: Got it. Thanks. Nihal, what about QualSights? What kind of services does QualSights provide and what are the ones that get you most excited when talking about it?

Nihal Advani: Sure. Yeah. So, at a high level what QualSights is is a platform to get dramatically faster qualitative insights from people anywhere in the world with the same level of depth. So, basically, not compromising on the depth and authenticity of insights, but still being able to get fast and cost-effective qualitative insights. And we have a platform that supports various different methodologies from digital [INAUDIBLE] focus groups and some [INAUDIBLE] in-person fieldwork. But, more importantly, contextual methods like mobile ethnography, diaries, video surveys, concept tests and more. And, really, what sort of gets me excited is, if you think of, until recently, any kind  of qualitative – when you were trying to do qualitative remotely, the problem was that you didn’t have anything that matched the depth of what you would be able to do in-person. But with our platform we’ve kind of addressed that. And that’s because of two key reasons – one is, when you’re trying to do things until recently, remotely, you’re either left with one of two options. It’s either you’re doing digital IDIs or focus groups which is sort of depth [INAUDIBLE] not necessarily built for research, so it doesn’t have the quality you need, or you’re using a platform where you have short videos and it doesn’t, again, map to what a consumer’s natural behavior is when they’re doing an activity like cooking or cleaning, shopping, et cetera. And our platform allows you to actually get that contextual feedback but do so live. So, you can choose to do live conversations with people as they’re in the moment cooking, cleaning, shopping, eating, et cetera, so that you can probe them almost like you were there, but doing it from a desk. And, if you’re not doing it live and you wanted to do it unmoderated, you can do that as well with no length limit and have them follow a series of tasks and questions that ensure that they are basically giving you complete responses, even in an unmoderated setting. So, [INAUDIBLE]

Renee Wyckoff: Got it. Thanks. And, I’d like to follow up with the same questions that I asked Brianna. So, what’s it like to get on and use your site? What’s the learning curve like?

Nihal Advani: Oh, sorry. The learning curve – it’s – it’s very straightforward. Our platform is kind of built to be very easy – it can be used DIY. It may be so basically, you can kind of login quickly, get a project started and launch something same day. You are also able to get – even though it’s qualitative – you are – we are able to get to your quota quickly, as well as capture that data, many times. Even if you’re doing, let’s say, a diary study where it’s multiple different activities, you can [INAUDIBLE] results and the whole analysis ready to go for you on – on the Monday. And so, essentially, you can cut down the amount of time it takes to do qualitative. We’ve done projects that are one-day projects, depending again on the activities required, to projects that are done all weekend. But, it’s really about being fast and easy. It’s very simple to do this either DIY or with agency partners.

Renee Wyckoff: Got it. Thanks. Following that – and, after hearing about what your platforms do – can each of you give an example of a unique research challenge that a client came to you with? Tell us how your platform was able to help your client overcome that challenge and how they were able to turn that into an actionable insight. Brianna, let’s start with you on that.

Brianna Boyer: Sure. So, I think a lot of times it’s easy to default to, “We’re going to do qual then we’re going to do quant,” or, “We’re going to do quant then we’re going to do qual,” or even take the approach of, “We’re just going to do one. Which one makes sense? Which one do I need?” In reality, a blend of those two that’s a little bit more fluid can be kind of the secret sauce. A global technology – or, a health technology company came to us recently looking for a quantitative partner that could fit seamlessly into their newly-adopted lean startup approach as it related to conducting research for new and existing offerings. A key tenet of their lean approach was the “Build, Measure, Learn” framework. And broadly speaking, just an agile and iterative way of building and refining their offerings based on customer feedback and needs. They were conducting qualitative research with various specialized medical professionals but needed a way to step back and validate ideas and needs among broader audiences, such as the consumers who would be on the receiving end of their offerings in a way that didn’t take weeks with a traditional quant provider. With AYTM, they were able to take that key step of testing ideas and measuring needs with quant research efficiently and effectively. The decision about if and when to use qual and/or quant was driven by the research objective – not a time or budget constraint. Being able to bounce back and forth as needed was key to success for them. And, remember my anecdote earlier about launching the survey before leaving the office and analyzing data the next morning? That came directly from this client, who was able to run a survey overnight to consumers to take not just qual findings but also quant back data into their meeting with leadership the next afternoon. And I know they’re not the only ones who have done that.

Renee Wyckoff: That’s amazing. Thank you. Nihal, do you have an example that you can give us?

Nihal Advani: Yeah. Sure. So, we basically – right now with the environment – with the Coronavirus situation – there’s a lot of companies scrambling to find options to do digital research. And so, that’s one of the things we’re seeing – is where finding a way to do effective qual is something we’re helping a lot of these clients navigate through with our platform. Not just being able to convert their in-person work that perhaps was a focus group or an IDI into a digital one. But, also being able to help convert shopalongs or things that were more in-person ethno, for example, in nature. Helping them convert – convert those and kind of do those in an effective way, even in this rapidly changing new environment. Beyond that, another kind of challenge that we’ve kind of seen in helping several clients towards is, many large companies have actually come to us with the goal of trying to embrace more DIY qualitative. And what we’ve been able to do is provide them a roadmap and the capabilities that allowed them to bring more research to them in-house when it made sense in a manageable way.

Renee Wyckoff: Got it. Thank you so much. So, Brianna, following up on that just a little bit – again, with AYTM being a quant platform, what are some of the other ways that you can help supplement a client’s qual research, or even do an entire qual project? And, from your perspective, what are the benefits of having a quant piece in your qual research?

Brianna Boyle: Definitely. As I brought up earlier, I think keeping a more symbiotic and less at-odds relationship between quant and qual is a key to success. The world is ever-changing. We’re seeing large-scale shifts right now that no research three months ago could have forecasted. So being able to move quickly in both types of research and set up for an iterative approach when it makes sense is crucial. To fall back on a classic analogy, quant should be a tool in your researcher toolbox, not just qual. That said, the traditional post-qual/quant study to validate and quantify findings has stood the test of time for a reason. Being able to deep-dive with consumers in a qualitative manner is so useful and should maybe be considered a bit more by hardcore quant researchers. But having a larger sample size, yielding robust numbers behind takeaways from qual is equally useful and important. I once heard a really good talk at a conference about an in-person follow-along done with an individual in Asia with regards to how they were doing their laundry. The insights were really powerful and moving, but the talk abruptly ended with, “So we revamped our line of products because of this experience.” And I couldn’t help immediately wonder, “Was a total product line overhaul conducted off of findings from one person’s journey?” So, having a quantitative study with a much larger and more stable sample size provides further credibility to qual findings. From a qual execution standpoint, in addition to fielding surveys among our integrated panel, you can set up and launch a list survey to your own respondents. So if you have a list of potential participants from your own panel or source, you can use an ATYM list survey to collect preliminary information as it relates to the topic of research, and vet respondents for recruitment into a larger qual study. On the backend, sometimes you need to collect very rote data or quantitative feedback from participants. Like rating a product that was tested as part of an IHUT, which you can use an AYTM survey to be that piece to collect that data as part of the broader qual study. And, again, qual elements can be implemented into more traditional quant online surveys through the question types I referenced earlier. Like the standard open-ended question, image and video response, as well as questions like heatmap which, while possible to quantify, I would argue at its rawest form is a type of qualitative data.

Renee Wyckoff: Understood. Thank you. So, Nihal, with all of the advanced features that QualSights offers, which feature would you say is the most useful to your clients, and which is the one that they use the most? Which is the one I would say that is the most user-friendly and gives them the most impact?

Nihal Advani: Sure. It’s kind of hard to pick one feature, to be honest, because we are one of the broadest qual platforms that supports any visual method and we do a lot of innovation on the capturing side. But, that said, as you all know, capturing the data is just one half of the battle. It’s basically the analysis that’s equally challenging. It’s, in fact, very cumbersome, traditionally, with qual, when you – especially when you’re doing video and things, it’s all kinds of unstructured data. And to be able to kind of get through all of that is quite a challenge, if you didn’t have what we offer, which is a powerful suite of AI tools that lets you navigate all of that. So, that’s the one feature, that every client, no matter what methodology they’re using, gets the benefit from, which is this powerful suite of tools that does things from the basics like transcribing and translating in 100 different languages to being able to automatically generate keywords and topics and video code. Everything for you – show you sentiment and emotions, show you even object and scene recognition so you can find the moments that matter, both based on what was said as well as what was seen in these videos. Automatically video clips things for you so you can drag and drop and put them into a presentation. And so, it’s that AI piece that makes that second half – the analysis half – of that qualitative project much more manageable and keeping that end-to-end process much more efficient.

Renee Wyckoff: So just to ask a little follow-up question on that, with all of the data that’s coming out of a project, how does that make it – how is it easier for, say, a client of yours to navigate around that and to extract what they need out of that? Obviously, you just mentioned many different things that they could use as far as sentiment analysis and wordsearch and things like that. Is it basically one-stop shopping? What do they have to do to get that out of your platform?

Nihal Advani: So, it’s all automatic. By default, within minutes – or, within 10 to 15 minutes of any video being completed, all of the AI I just talked about is available. And, not only that, it’s not available just at, let’s say, one video, or one sort of session or activity level. It’s available at the aggregated level. And so, you essentially can have several different activities or several different participants in a project, for example, and be able to look at these insights from an aggregate view so that you can, for example, see how many different participants in your project were answering a certain question or what were the top keywords and top themes that were seen across the project or for any different activity – if there was multiple activities in the project. And very quickly be able to find those moments by just clicking a button here or there. And so, all of these are sort of bubbled up and made available for, basically, taking away a lot of that grunt work. The AI that we provide is not meant to replace what a human does by any means. It’s meant to take away all the grunt work and allow that human who’s, of course, much more nuanced than AI can be to be much more strategic in what they do and, therefore, get to that insights and get to those findings much faster, without having to worry about all the cumbersome process that would have taken them and otherwise taken to have searched through all that.

Renee Wyckoff: Understood. So, with that said, Brianna, what does it look like for a client to do the same with AYTM as far as extracting out that data that was just collected?

Brianna Boyle: Sure. So, our stats pages or reporting portals on a survey are available as soon as a survey is launched. So you can be watching the data come in, in real-time. So if you have things like image response or video response, you can look at the images coming in. You can look at the videos and start to glean insights from those. And, you know, obviously, once a survey is completed, they’re still available as well. From the open-ended side, we do have kind of word clouds and an interface to interact with open-ended text. It’s really neat. On the word clouds, you can click on a word and drill down. You can also have it filter out common – common words that are not going to be helpful in your word cloud. And we’re actually working on some really neat, more robust analysis tools as it relates to open-ends, but I can’t spoil anything, unfortunately.

Renee Wyckoff: Yeah. I mean, I think the open-ends are probably the toughest to get through as far as extracting that data. But, I’m sure that it – we’re all interested to find out what’s going to come out of ATYM with that. Thanks for sharing that. So, moving on, I always like to ask our panelists, not something so specific about their company, but in general – being in the industry – what are some new trends that you’re seeing in qual research? And you can even touch on quant if you’d like, Brianna, since ATYM does mostly quant. But, what are some new trends that you see in market research in general, and what’s been on your radar lately as far as something fairly new on the horizon? Nihal, let’s start with you on that one –?

Nihal Advani: Sure. So, in fact, I know we’ve touched upon this a little bit, but there is definitely a blurring of lines between quant and qual. As time goes on and as technology advances, it is possible to get much faster insights even on larger data sets, if it was more qual-heavy versus quant. That’s definitely a trend we are seeing, where sample sizes, even in qual, are going up because of the tools and the AI that’s available to kind of help you get through stuff. One of the things that we’re doing – in fact, you know, you talked about some of the new things that we have on the horizon. One of the things that we have is, actually, a video surveys product. It’s something that we’ve recently launched, where it kind of flips things on its head in that it blends. You think of the just – if I step back for a second – and you think of the problem, right? The overall problem with quant and qual is that quant is where you – it’s fast, it’s easy, it’s scalable, it’s great in that sense. But it tends to lack depth and context at times, or it tends to have challenges with survey bots or with disengaged respondents. While qual, on the other hand, gives you great depth of insight, but then lacks the speed and the agility and other things of quant. And so blending the best of both is what we can offer in something like a video surveys product where you can actually see somebody on video the entre time, therefore, authenticate that this is a real person, make sure they’re engaged because this is all visible, and then have them answer questions along the way, both a mixture of qualitative open-ended as well as quantitative questions, but on video the entire time. And allow the AI to help you with the analysis, even if those sample sizes are larger. They need not be thousands like in a traditional quant study. But they need not be 15 to 30 like in a traditional qual study – so, somewhere in-between. And that’s one of the trends we’re seeing and that’s why we launched our product.

Renee Wyckoff: And that actually – that actually made me think of something to ask you, Nihal. So, we – here at L&E, we did kind of an experiment or a little bit of research on sample and “depending on where you get your sample from.” One of the trends that we’ve seen – or, that I’ve seen – is clients that are – because they want that “quick and dirty” or they want that fast research, they sometimes will use a quant panel for qual research. So my question to you is, “Have you personally seen that? And do you think that using a quant panel for qual research has any impact on the results or what comes out of it in the end?”

Nihal Advani: Yeah. That’s a great question. You know, there’s – we’ve done that. We’ve seen that done, as well. And we’ve seen mixed results. And the reason is – if you don’t do it a certain way. And so, when we’ve had clients that have come to us who have tried using quant panels for qual and kind of – it not having worked out. And I think one of the key things that we’re missing – and what we put in place when that needs to happen – when you’re doing a quant sample and having to have some subset of them do qual or kind of blending the two as we talked about, but still leveraging a quant sample, it is extremely important to be able to add additional filters and additional context to the panelists, so that they know what they’re getting into. So I think the best practices around that is, first of all, making clear to panelists that, “This is not just going to be quant” – if they move on, it’s going to be quant plus qual, and therefore they kind of know beforehand. But, that side, actually adding in additional kind of layers to ensure quality before they get to the qual piece, whether that be – in our case, one of the things we like to do is a video articulation question. So, rather than just an open-ended sort of articulation, doin a real video articulation so you can not only see how engaged they are, but also hear them out and have them kind of speak and really see if they are good at describing their thoughts and feelings. So, you have to have some strategic questions in there, but that’s a good way to then ensure that those who have made the cut to get into qual are of higher quality. Because, otherwise, if you don’t to that, what tends to happen is you’ll basically have people who didn’t expect that and weren’t necessarily looking for that and were comfortable with a short, quick survey where they had to tap around, but weren’t necessarily a fit – or didn’t want to be doing more. And that’s where you start to see quality issues if you do that.

Renee Wyckoff: Right. So –

Brianna Boyer: And to piggyback off that –

Renee Wyckoff: Yeah. Go ahead, please –?

Brianna Boyer: We’ve seen something similar on our side as well, where clients have said, “Hey, we’ll want to follow-up with some people for IDIs or some type of qual research that gets a little bit more depth,” in the space that they’re testing. And I 100%, agree. And this is something that I would kind of qualify as a trend across research in general – is just being really transparent with respondents and treating them like you would like to be treated, right? That classic saying. And letting them know that, “This is or could be more than just this survey you’re taking,” like Nihal said. And, I think it’s really interesting what you were saying about using video responses or some kind of more qualitative measure to understand how engaged this person is, if they would make for a good in-depth interview, or if there may be somebody who’s giving you answers to get – not necessarily just to get through it – but they’re not overly elaborate, right? So, you wouldn’t necessarily get a lot out of them in qual research. But, definitely, quant as a recruiting tool for qual we’ve seen recently, as well, and definitely have some best practices around that. Mainly, being very transparent with people and respecting their time and if they’re willing to do that.

Renee Wyckoff: So, just a quick, interesting kind of question – or something that I thought of, Brianna. So, the flipside of that – so, I know with AYTM you can use your panel, or you can use your resources. Or a qualitative company like ourselves can kind of import our database in there and kind of run a survey or do something like that. Do you find, on the flipside of that, that people who are in a qual database, when they get on to or into a quantitative experience, that it might not run the same way as if you were just to hit your panel with it?

Brianna Boyer: Sure. That’s an interesting question. I don’t know that I have any surveys to draw upon – you know, some hard data. But, my thoughts on that would be, “You probably would see a difference.” One thing that we caution clients against a lot of times is blending of sample in terms of blending panel sample with list sample, because there definitely is a difference in the way that people who are used to taking surveys respond versus those who aren’t. And so I would imagine that people who are signed up with a lot of qual partners, or to do qualitative research and not necessarily quantitative, when put in a quant survey, they might act more like that average consumer that you collect from a list survey and not someone who takes surveys a lot of times and kind of gets in the “survey mindset” or “gets in their groove,” if that makes sense.

Renee Wyckoff: It does make sense. And, Nihal, actually you hit it spot-on because what we found in the project that we did or in the research that we did was that the quant participants needed a lot more – I don’t want to say the word “training” but a lot more preparation when it came to participating in a qualitative project. People who are in a – or on a quant panel, or solely in a quant panel are used to doing those really quick hit, “quick and dirty” surveys where they’re just used to getting in and out and doing it, and not any kind of length of engagement. So it took a lot more prodding and preparation to get those people to follow-through, because it was simply not what they were used to – used to doing. So that’s kind of why I wanted to throw that question out there, to see if you have any personal – yeah – any personal experience with this. All right. So, thanks for that. I appreciate it. So, moving on, can you both tell us some ways that you work with L&E so that our audience might be able to get a better idea of how they can execute a project on a platform like yours? So, what are some of the things you’ve done with us? How did it work out? Brianna, let’s start with you on that one, as well.

Brianna Boyle: Sure. So, I believe L&E has mainly used us as our – as a tool to collect quantitative data for recruiting people. So making sure that they are the people that you’re looking for and then, also, that you can get the right mix of people. That you’re collecting key demos or other type of information so you make sure you get a well-rounded and balanced sample for your qual study. And then, I believe maybe also a little bit of kind of the backend use for – in a qual project collecting a little bit of quant data, but mainly on the recruitment side.

Renee Wyckoff: Got it. So, to follow that up – so, that is, in fact, how we utilize your tool, most of the time – is – we found that it can be, not only as a survey tool, but it can be used as a really effective recruiting tool as well, to do just those things. And then with the ability to be able to use video and stimuli and things like that, it’s been able to add a little bit of spice to what we can normally do as far as recruiting goes. So thanks for that. And then, Nihal, what are some of the things that you work with L&E on, or some of the things we’ve worked with you on? You know, just to give our listeners maybe a couple of examples of how they can work with you.

Nihal Advani: Sure. Yeah. There’s, in fact, a couple of different methods we are typically engaging with L&E. One is, when clients come to us and then they want us to help with recruiting, and depending on, again, their target criteria, their screening criteria and so on, we will engage L&E and bring them into the project. And we work very closely with you guys, of course, and have done several projects with you on that, where L&E then takes over in a seamless manner, takes care of the recruiting and busses back those respondents which are easily – essentially – added into the platform. And then we stay engaged with the person or the project manager on the L&E side throughout the project, where there is a constant sort of connection between the QualSights team as well as the L&E team to ensure that participants are completing, especially when it’s a diary study or an ongoing study that requires that. And so that’s one way. The other way is when we’ve had several occasions where clients will come to L&E and they’re recruiting to L&E, but they haven’t yet picked a technology to use for qualitative, for example. And that’s where L&E will, many a time, bring us in to those projects and then sort of ends up working out the same way. But you can approach QualSights either through L&E or approach L&E through QualSights, essentially. So, those are the key ways.

Renee Wyckoff: Got it. Thank you. So, again, not necessarily talking about your companies, but your personal experiences in working in the industry, what are some of the things that you can recommend to a client to make their qualitative project more successful, in general? So, again, drawing from your personal experiences, when a client comes to you with a project, are there some things that you can recommend to help them – to help their project be most impactful? Nihal, let’s start with you on that one –?

Nihal Advani: Sure. So, in general, regardless of what tool people decide to use, my general theory and general outlook on qual is that we are still doing way too much of focus group qual, way too much of recall-based methods. And while they’re good and they have their place in certain areas, when it comes to behavior, there is no better way to see somebody do something. In fact, many times, people will say they do something a certain way, but when you see it it’s actually different, right? Or, if you ask somebody, “Three days ago when you went to the store, what did you notice first?” they have no recollection because a mind cannot store that level of information for longer. And so, whenever possible, especially when it comes to behavior-based projects where you truly want to understand how consumers or patients or others do something, try to kind of do contextual or in-the-moment methods. And that is something that we always are guiding our customers depending on when they bring a project to us and if they still haven’t their methodology. Or sometimes even when they’re thinking of doing something a certain way, we’re not shy to tell them, “Hey, have you considered doing this, this way?” And it doesn’t have to be one method picked over the other. In fact, nowadays, what we’re seeing more and more often is actually a mix and match of methods, even within qualitative. So, on one end, in a broader sense, you can mix and match quant and qual in multiple different ways. But you can, also, within qual, actually have a mixture. So, for example, let’s say you’re doing a diary study, right? You do a diary study, let’s say, with 30 participants over a week where you kind of see, let’s say, “A Day in the Life” based on a certain topic and have them do several different activities. You can choose to do an IDI follow-up with a subset of those participants to go deeper and have that face-to-face conversation, digitally, again, with them if you’d like. And that’s where – those are some of the things we’re sort of guiding our customers to try and, whenever possible, if not the whole project then at least a portion of the project, wherever it makes sense around behavior, focus on in-context and non-recall methods as much as possible for those types of studies.

Renee Wyckoff: Got it. Thank you. Brianna, what about you?

Brianna Boyer: Sure. And so I really – just stepping back and going to a higher-level research approach, because I think this works for qual or quant, it’s just to be very mindful of the current climate and current events that might be affecting things like behaviors. And then just be very clear and intentional with your research. So making sure you’re reaching out to the right people, you’re picking an appropriate mode to measure or observe the behaviors or attitudes and preferences that you’re looking to learn more about, just like Nihal was saying. And last thing, I would just say, consider quant for validation. Start mixing modes and making sure that you’re understanding, not just the “Why?” and getting deeper, but also quantifying and being able to prioritize and get that more robust sample behind some of these findings.

Renee Wyckoff: Understood. Thank you. So, finally, we’ve heard – we’re seeing some questions coming in, and we touched on it briefly – but, kind of addressing the elephant in the virtual room, what are some impacts that you’re both seeing on your business during this epidemic? And is there any advice or guidance you may have for others in the industry as far as how they can alter their research to meet the latest challenges? Brianna, let’s just continue on with that. What are you seeing – are you seeing any impact at AYTM with what’s going on in the world right now?

Brianna Boyer: Definitely. The world is changing. Current events are changing everyone’s habits and behaviors, as that affects attitudes and preferences, those kinds of things – both personally and professionally, right? Our company, while fully remote, there are people that sometimes get together because they work – or they live close to each other. And we’re not doing that anymore. So, whether you’re doing B-to-C, B-to-B, it really doesn’t matter. You’re going to be affected by what is happening right now. So what we’ve seen is honestly something I’m very proud of. Our clients are asking us not to stop research, but how to be more mindful in the research they’re continuing to conduct. Or, “How can they pivot to make sure that they’re accounting for what’s happening right now?” So, that’s kind of the two places my mind goes. Is, one, be mindful in how you’re asking questions, like I hit on earlier, behaviors are definitely changing. Like I mentioned kind of at the beginning of the call, there was no research that was done a few months ago that could have predicted what's happening right now, right? So being agile, being able to pivot, run something quickly, get some data, is really good. And just that you should embrace research right now. Don't be afraid of it. Like I said, and repeatedly said, things are changing, things are different. And the companies who choose to try to understand those differences are going to have a major advantage over those who are fearful of conducting research to understand what's happening and that want to pause and wait. Certainly there are clients who are pausing, at least some of their research, and it completely makes sense. But I don't think that's a good mindset to start from, is, "We shouldn't do research." I think it's the opposite. I think you should learn the differences, embrace this time, because right now, this is the new normal. And we don't know how long the new normal's going to last, and even if it gets back to default mode, or what used to be normal, there will be lasting effects from this. So understanding the differences that are happening right now is really important.

Renee Wyckoff: So when you say be mindful of asking questions, or how you ask questions, what do you mean by that?

Brianna Boyer: Sure. So if you want to ask about behaviors, and certainly recall has limitations, but find ways to ask about it in a specific time frame. So instead of asking something like, "How do you prefer to purchase, or how have you most recently purchased a product?" maybe ask, "Over the past six months, how have you you typically purchased a product?" Right? Because if I'm asking about their most recent toilet paper purchase, I'm probably going to get very different answers than if I asked that two, three months ago.

Renee Wyckoff: Very true. Very, very true. So Nihal, what are you seeing?

Nihal Advani: Yeah, I mean, to be honest, it's been – it's been nuts. It's unfortunate that it's happening this way, but it's blowing up for us. We are getting a crazy amount of inbound requests, now, because anything that was physical is all being converted to digital. And so we are actually seeing a tremendous increase in projects at qual sites, just due to that fact. And so there's some of the simpler stuff where you have an IDI or focus group in a facility that's now being converted to a digital IDI or a digital focus group. So that's fairly straightforward, but then then there's other things, like an in-home ethnography or an in-store shopalong and other things that are also being converted to digital. And luckily, our platform, because of us having several different options, both in context and otherwise, are able to help them convert those projects and still do that research. And I agree with Brianna, where this is not the time to pull back. It's the time to actually understand this new normal, and trying to really figure out. And we've in fact got multiple projects right now about corona. We have multiple clients doing projects already to understand consumer behaviors during this pandemic. And so that's really where we're seeing it, and, yeah, I think it'll be interesting to see how long that lasts. But I think now is the time where they can both convert things rather than canceling stuff, they can still be converted and saved and done in the same level of depth even though it's remote, and they can also use this time to understand consumer behavior. It's not just here in the US, but also around the world and how those are changing due to what's going on.

Renee Wyckoff: Got it. So if I understood you correctly, I think you said that there are – and you may have even touched on this as well, Brianna – that there are projects that are popping up from clients to help understand consumer behaviors during this time, and during this pandemic, and what's happening right now?

Nihal Advani: Absolutely, yep.

Brianna Boyer: Certainly, yeah, both in studies that were in the design phase are now being either modified or having additions made around what's happening, and have – asking people to report how their behavior might have changed. As well as people popping up and saying, "Hey, we need to go find out what's happening right now." And as a minor shameless plug, just – as people who are big fans of research and interested in consumer trends and behavior changes, we're starting our own internal survey that we're going to run periodically to kind of keep track of how behavior changes, and just – yeah, keep a pulse on this, because it is important.

Renee Wyckoff: I would agree. And thanks so much for sharing what's going on in your world in response to COVID-19, especially since, and as we've heard from both of you, especially you, Nihal, since moving to online research has become so important in the past weeks. With that said, and being made very aware of the desire for consumers to participate in research more now than ever due to social distancing, we have heard that people are quarantining themselves or are shut in, so we've heard that engaging in something like this is certainly more attractive than ever. With that said, I'd like to take a moment to briefly touch on something that our audience may not be aware of. L&E has been a leader in the virtual workforce for over a decade, with over – with a team of 30-plus project managers and nearly 200 recruiters that have been working from home for over a decade as a result of our proprietary technology that enables us to work remotely. So we've been doing this all along, as you have, Brianna. So our zero disruption from COVID-19 quarantining and seamless work-from-home abilities, coupled with our experience with working with partners like QualSights and AYTM, means that we are easily ready and able to help researchers out there with their online research needs. So please feel free to reach out to me directly after this webinar to discuss how we can guide you on moving your in-person research to online. So at this point, we're going to move on to some questions. We have a few. Brianna and Nihal, I want to thank you so much for helping us get to know you a little bit better today. We're going to take questions, but first, I'd like to thank Focus Forward, our transcription partner, who so graciously volunteered to transcribe this webinar for free. As you certainly know, Focus Forward is just one of our technology partners that we've partnered with to bring complete qualitative toolkits to our clients. We'll be emailing out the recording of this webinar, and you can view this webinar, or download a copy of this free transcript at our website, as well as learn about all of our exciting technologies offered through L&E Solutions at www.leresearch.com. So let's get started with a few questions. All right, so surprisingly, as I mentioned, some of the questions coming in are specifically aimed at what's going on in the world. So this one is interesting. So there's a plan by President Trump to spend one trillion to fight COVID-19, to keep Americans healthy. Do you feel there is a need for market research there, to make sure that the money is well-spent? So if – let's pose the question this way, Brianna, if we were to have a conversation with President Trump right now, what are some suggestions that we could make to him to make sure that any research he's doing on COVID-19 gets the money well-spent?

Brianna Boyer: Sure, so that would be an interesting conversation. I think that research could be used to reach out to the average consumer, right? I think that a lot of people may feel that there is a disconnect between people in political office and your average American and their needs. And so I think doing a survey to get the pulse on how people are feeling, what are their concerns when it comes to financials, both on kind of loss and their outgoing expenses. What is the priority? What problems are they having when it comes to healthcare? I've heard a lot of stories about people who are concerned that they are potentially carrying this virus and aren't able to get testing. So where are they going for these, where are they being turned down, what's the disconnect? So I think that there are a couple different things that if they were interested, they could use market research to inform them when making a decision about how to spend that type of money.

Renee Wyckoff: Got it.

Nihal Advani: And to piggyback on that, I think – and this is the perfect time, actually, to do a quant-plus-qual study, if you're the government, right? You basically kind of do a broader survey around what's going on, find some areas where you need to dig deeper, and then actually really talk to those consumers. And so I do think it will help, and that's perhaps the way I would do it.

Renee Wyckoff: Excellent. So the next one, let's see. Can we discuss how our recruitment efforts are impacted by today's environment? And then also are survey or interview completion rates impacted by the distractions that everyone is experiencing? Brianna, what are you seeing here?

Brianna Boyer: Sure, that's a good question, and one of the ones that we are getting from clients. They are asking about, Well, are we still feasible? Is my fielding time going to be extended? What does it look like from the participant side? So what we've been seeing right now is very little effect on kind of incidence or completion rates. In places that are a little bit harder-hit, we are seeing a little bit of a slowdown, but still feasible. I think, as it relates to online research, a lot of people are doing it from their homes, they’re doing it from their phones, right? So they're less impacted from the social distancing that's happening. We also aren't seeing much difference in panel representation or there's a big loss of a certain group, or anything like that. For the most part, from the respondent side, it's been fairly status quo in terms of reaching them, for ours – for us, at least.

Renee Wyckoff: What about you, Nihal?

Nihal Advani: Yeah, so also seeing not much disruption here. As you pointed out earlier, people, I think this is a time for many people where they may be are not earning money elsewhere and this is a good way, and it's a welcome opportunity, to be able to do some work when they are isolated at home. That aside, there have been – there has been one project that I can think of in the last week where there was a couple unexpected departures, that we didn't expect otherwise. And we do attribute those towards something going on or some major distraction, maybe, in the [INAUDIBLE] family, or something. So it can happen, but it's still a small amount.

Renee Wyckoff: That's good to know. And from our end, same. We have not seen much of a disruption. I think with people, with social distancing, and with people kind of being either forced to work from home, or schools being closed and such, we've kind of found that – I don't really want to say captive audience, but I think it's – participating in something like this is sort of a distraction for people, so we've not really seen any falling-off in participation. And that's been one of the biggest questions from our clients coming in, when they are going to do research, is, "What have you seen? What can you tell us about what's happening? What do you recommend that we change, or can we pose questions differently" – like you were saying, Brianna – "to our participants?" So they're asking us those questions, and frankly we haven't really seen any dropping-off. So let us see. What is our next one? OK. Are the employees of L&E working from home because of the virus? Most employees of L&E have always worked from home, so again, this has been a really seamless thing for L&E to deal with. We've always worked from home, so we – this has not been an issue for us at all. Next one, Nihal, is directed right at you. Can you elaborate on the different contextual and in-the-moment methods QualSights offers, also how QualSights has been quickly moving in-store ethnographic research to digital?

Nihal Advani: Yeah, that's a great one. So I'll address the first part first. Basically, yeah, there's several different in-context methods that we support. Mobile ethnography, any kind, whether that's in-home or in-store, related mobile ethnography, truly kind of seeing consumer behavior. Mobile diaries is another very contextual – so unlike a traditional online diary, a mobile diary is mentally completely in the moment, where they are set up with different kinds of activities, it doesn't have to only be video, it could be a combination of video, photos, audios, other kinds of activities that they are doing over the course of a few days. But it's, again, contextual and in-the-moment, so you can see things like they are. And also video surveys is mentioned, which is our newer sort of quant-plus-qual that is still in context because they're still using a smartphone and still mobile and still able to show you things along with answering that survey while they're on video. Now, that second part is actually even more interesting, because we've seen a lot of that. So there are some in-store projects that are converted to digital or were digital from the get-go, that are still being done, and – but being done, perhaps, maybe if there was a longer activity, maybe shortening it up and only making it when someone is planning to go make a trip. But more often what we're seeing now is, what is the real behavior? And real behavior now is shifting digital, just it is the nature of what is going on. And fortunately, from a research perspective, we actually have digital insights piece in our platform as well. So our platform allows you to actually capture the screen of somebody, the smartphone screen, in fact, while they are researching something online or even shopping for something online, so you can do an entire digital shopping activity where they're sharing their screen and being able to talk through the thought process as to how they're shopping, whether that's Amazon, Target, or wherever else, because it'll capture anything on their screen. And this can be done both recorded, where it's unmoderated and you just have them kind of show their activity like it is and talk about it, or it can be done live, where you can be connected to them in real-time as they're doing this online shopping activity, either through an IDI, so on their computer, or through a smartphone-based system, where they're sharing their screen and you're being able to kind of talk to them and actually probe them as they're doing something in the digital world. So that's how we handle that second aspect.

Renee Wyckoff: Excellent. So the next question asks, How do both companies export data? Nihal, since you were talking, why don't you tell us how you export data from the research that comes out?

Nihal Advani: Sure. There's a couple different ways. So first of all, within our platform, we have a full presentation capability as well. So the stages are recruit, capture, analyze, and present, and both analysis and presentation is available into the platform so you can very seamlessly kind of create a presentation and then export that into PowerPoint with one click, where you have slides and embedded videos in each slide, for example, or you can share that digitally. Now, beyond that, if you want to export data, whether it's just for data retention and kind of deleting it off perhaps the cloud and keeping it on your own system, you're completely welcome to do that, and there's one-click buttons for you to be able to download everything. And so that's the two different forms of exporting, either exporting a presentation or exporting data just to store.

Renee Wyckoff: Thank you. Brianna?

Brianna Boyer: Sure, at AYTM, from the raw data perspective, we have a variety of options for exporting data. There's various Excel formats, both coded and labeled, depending on your preference, SPSS and Jump, if you use either of those softwares. From a kind of reporting side, you can export to PowerPoint, both the default report, which is just every question, and then if you do some custom work, if you want to add what we call virtual questions to customize a visual or remove some questions if you want to build an executive-summary-type deck, the export on the PowerPoint will reflect whatever you've set up in your custom online report, if that makes sense. And when it comes to things like image and video response, you're able to export the raw data – or the raw image or video formats for those as well.

Renee Wyckoff: Got it, thanks. And we have time for one more question, and this one looks like it's geared specifically at you, Brianna. So it says, there's been some really great feedback with survey design and best practices, especially during this time of COVID. Are there more resources we can have, articles, or blogs, from AYTM?

Brianna Boyer: Sure, that's a great question. So, at least internally, we've put together a document, and we've been circulating that with clients, as it relates to questions that they've been bringing to us about how to continue with research in this time, or considerations they should be making, and also addressing questions about, are we seeing any drop-off in participation among respondents. And I'm not exactly sure what the plan is for releasing that more publicly, but I'm sure that we are going to be producing a blog at least today or tomorrow with some of that information, if not all of it. Definitely this is something that, like I said, we want to keep a pulse on. We are starting our own little tracker right now to follow the trends in consumer behavior, and preferences and concerns and worries and those kinds of things. So it's something that we are very much on top of, and want to stay on top of, and of course want to share findings with others in the industry to help them conduct good research.

Renee Wyckoff: Excellent. Thanks. One thing I'd like to address, it's not necessarily a question, well, they were questions, we had quite a few people ask about demos from either AYTM or QualSights. My contact information has been shared directly in the comments, so if anyone would like to arrange a demo with either AYTM or QualSights or any of our tech partners, for that matter, please feel free to reach out to me directly, and I will connect you with the appropriate person for a demo. I've mentioned previously, we’ll be emailing out a recording of this webinar, and you can view this webinar, as well as learn about any other technologies offered through L&E Solutions, at www.leresearch.com. Thank you so much for joining us today, and thank you so much, again, Brianna, and Nihal, for joining us today. And please be on the lookout for an email invite for our next webinar we're hosting in this series. Thanks so much again and have a wonderful day.

Nihal Advani: Thank you.

Brianna Boyer: Thank you.

Renee Wyckoff: Thanks, guys. 'Bye.