Panoplai Virtual Session: Tripadvisor, Group Black and Panoplai Put Black Travelers into Motion with Digital Twins

Tripadvisor, Group Black and Panoplai Put Black Travelers into Motion with Digital Twins 

Editor's note: This article is an automated speech-to-text transcription, edited lightly for clarity.   

Panoplai teamed up with Tripadvisor and Group Black for a session during the March 12, 2025, Quirk’s Virtual Sessions – Consumer Reset series.  

Adam Bai, chief strategy officer and chief client officer at Panoplai, Sarah Chaten, VP of insights and analytics at Group Black and Ryan Gillis, associate director of research and insights at Tripadvisor walked through the research they completed on Black travelers.  

Using a mixture of traditional research methods and new methods, the teams learned a lot about this underrepresented segment that ultimately helped Tripadvisor, and their corporate partners better serve the Black traveler community.

Session transcript 

Joe Rydholm 

Hi everybody and welcome to our session, ‘Tripadvisor, Group Black and Panoplai Put Black Travelers into Motion with Digital Twins.’ I'm Quirk’s Editor, Joe Rydholm. 

Before we get started, let's quickly go over the ways you can participate in today's discussion. You can use the chat tab to interact with other attendees during the session, and you can use the Q&A tab to submit questions for the presenters during the session. And we'll answer as many as we have time for during the Q&A portion.  

Our session today is presented by Panoplai. Enjoy the presentation!

Adam Bai 

Hey everyone, thanks for coming.  

My name's Adam, and this is going to be a recorded talk, but with a really dynamic conversation and a Q&A session at the end. So please stick around the talk called “Black Travelers in Motion with Digital Twins.” It is a really cool panel of folks, I guess me excluded.  

I am Chief Strategy Officer and Chief Client Officer at Panoplai. We also are really lucky to have Ryan Gillis, associate director research and insights at Tripadvisor. An organization I'm sure you've all heard of, and a site you've probably used a billion times.  

We have Sarah Chaten as well, who's VP of insights at Group Black. Group Black, I'll let Sarah introduce, but it's a super cool agency and media organization.  

Panoplai is a next generation audience discovery platform for marketers, innovators, researchers and creatives. You can use Panoplai to do a lot.  You can ask any question, find any audience and, of course, generate end-to-end surveys that are incredibly powerful.  

You can also upload anything. Any market or audience discovery data from any source from NPS to social, to surveys from other platforms to really get a panoramic view of the market and of your audiences. You can uncover behavior, emotions, purchasing decisions, etc.  

This is what we're going to talk about towards the end of the discussion today. You can harness industry leading AI, synthetic and digital twin capabilities to bring your data to life, engage with the data and help you directly with the outputs that matter most to your organization and to your working life. 

What did we do? Well, we wanted to correct a really important gap in data online. That gap has to do with Black travelers.  

Of course, Tripadvisor is really focused on understanding evolving traveling dynamics, needs, habits and emotions.  

Black travelers have about $100 billion in purchasing power annually. They're changing and evolving really quickly in terms of their needs, behaviors and emotions. They're an incredibly internally diverse group of people, right? It's absurd to say that all Black travelers somehow want the same things or travel in the same ways or spend money the same way.  

So, we wanted to work on that together with some really high quality first party data where we're going out to real people and asking how they feel, how they think and how they act.  

There's another aspect of this talk as well, which is getting the balance right between traditional research methodology and AI powered innovation. And that doesn't mean a zero-sum choice where you choose one and not the other.  

It means a really well thought through hybrid approach where we're building a foundation of high quality first party data. Then using really cool cutting edge generative AI power techniques like digital twin synthetic data to extend the value of that known fundamental deterministic data that we're gathering using all of the traditional forms of care and methodological rigor that we believe in this industry. 

I will hand things over to Ryan now and he is going to talk about Tripadvisor, some of the goals associated with this research project and some cool stuff Tripadvisor is experimenting with when it comes to AI.

Ryan Gillis 

Thanks Adam. Hi everyone. I'm Ryan Gillis and I lead the America’s research and insights team at Tripadvisor.  

For those that don't know, Tripadvisor is the world's largest and most visited travel site, home to more than a billion user generated reviews each month. More than a quarter billion people globally visit our site seeking travel guidance and to share their overall travel experiences.  

As a company, we're dedicated to making everyone a better traveler. In order for that to genuinely resonate, we need to ensure that we're doing our best to serve all travelers.  

We found that a lot of research on travel more generally tends to flatten an experience where a lot of nuance exists. Understanding the unique needs and travel behaviors of historically marginalized and underserved travel audiences can ensure that we're creating a product that helps all travelers feel safe, seen and respected along their journey.  

This organizational imperative on our end has driven us to sponsor or undertake research that dives deeper into travel experiences of those underserved groups. That obviously includes this work with Panoplai and Group Black, but we've also done a lot of work over the last few years. Undertaking studies related to the Hispanic travel experience, the experience of differently abled travelers, as well as the experience of LGBTQ+ travelers, looking to get a better understanding of how each of these groups travels and what we can do as a platform to ensure that we're catering to and tailoring their experiences as they show up on Tripadvisor for this particular piece of work.  

In short, the brief to the team at Panoplai was to help us conduct a piece of research that would allow us to gain comprehensive insight into the experiences of the Black traveler. We really wanted to get a better understanding of their travel habits, attitudes and key sources of inspiration. Additionally, we wanted to contextualize those behaviors against a general population sample that would help us really understand and gain insight into what makes the Black traveler unique.  

But, I think also most importantly, we really wanted to hear from Black travelers in their own words to help us better understand the difficult realities that they face as part of the overall Black travel experience. Just some of the particulars of the research that we undertook here as well.  

Leveraging the Panoplai platform, we conducted this study, which was a mix of qual and quant data from a sample of over 2,000 respondents. We split that sample in half with 1,004 Black travelers which is census representative. As well as 1,029 general U.S. travelers, also census representative. We leveraged the Panoplai platform to really give us a nuanced look of gaining insight into these experiences from Black travelers in their own words and leveraged all that the platform has to offer to help us with that analysis.  

Overall, the study revealed really compelling data around the Black travel experience in general. Some of those data points are on this slide [7:22 in the recording], but what those data points really did was help us come up with a storyline in a narrative coming out of the research that can help brands that we're looking to work with as well as ourselves, at Tripadvisor really connect authentically with Black travelers.  

The overall findings that we segmented into four overarching categories or themes, and I'll go through each of those quickly. 

The first was culture driven.  

We found Black travelers seek out trips where they can connect and engage with the Black community and are oftentimes turning to others within the community when looking for recommendations. 66% actively look to support Black-owned businesses when traveling. 57% rely on recommendations from other Black travelers when selecting destinations and 51% seek out destinations where others look like them.  

So, the importance of the Black community, both in the representation within destinations that Black travelers are looking to travel to, but also as a source of reliable and trustworthy information when seeking out travel recommendations was genuinely important to them, along the travel journey. 

Comfort. When we asked Black travelers what their biggest challenges are in travel, those unique issues facing black travelers are genuinely stark and honestly feel more existential than the typical more mundane elements of travel planning.  

Black travelers are much more likely to report feeling discrimination or worrying whether or not they'll be welcomed at a destination they're traveling to. Whereas the general population is more concerned with the typical mundane elements of ensuring that travel logistics are in order or keeping the costs of a trip down. Whereas black travelers are much more concerned with far more existential elements of the travel experience. And it's something that's much more likely to rise to the top of their challenges or barriers that they need to overcome as they plan their travel.  

As a result of that, we see that Black travelers naturally turn to destinations that are racially diverse.  

When we ask Black travelers to verbatim share the destinations where they would feel most comfortable traveling to, we saw that cities in the United States with large black populations really rise to the top. Cities like Atlanta, Washington D.C. and New Orleans all rise into the top of domestic destinations where Black travelers feel most comfortable traveling to. 

The third C that we came up with here was curated. 

For Black travelers, travel is a measured and intentional activity, which we found very interesting in that travel is something where black travelers are more likely than the general population of travelers to employ specific saving strategies. They're less likely to list managing costs as an issue because it seems to be something that they're already taking into account very early on in the travel journey. Whereas the general population of travelers is less measured and considered with their travel approach and are potentially less likely to be consciously considering the costs very early on. 

But, we also see as a result of this measured savings approach, if you will, Black travelers also spend on a variety of different categories prior to travel as well, from beauty to electronics. They're spending to show up at their destination as their best selves. 

Then communal. So, lastly, the Black travel experience is genuinely a social and communal one across both digital and physical spaces. Black travelers are more likely to travel with their friends, they're more likely to value meeting new people over the course of travel and they're also more likely on the digital side to turn to social media and influencers for travel recommendations. 

Lastly, I would say AI as a company isn't new to us. We've been leveraging our data, especially in the context of personalization and search results, for well over a decade. But today, we're well into our journey to push heavily into generative AI capabilities.  

Early in 2023, we piloted and then launched many features like an AI trip builder and AI review summaries. You can now see AI integrated pretty fully across our site, including a newly launched AI assistant.  

But, I think this work with Panoplai really has the potential to help us bring AI into our research work as well.  

The Panoplai platform allows us to scale our most valuable survey responses and open-ends without losing the nuance that makes them so important. We're able to quickly uncover hidden trends in the data, leveraging AI to help with our analysis. The digital twin element of the research really does help us allow for research to be a living and breathing document as opposed to a static report.  

So, I think leveraging the AI driven analysis capabilities of the Panoplai platform really help us extend our usage of AI that's showing up very consistently within our product to our research work as well.  

With that, I will pass it to Sarah.

Lisa Hancock 

This is Lisa from Panoplai, stepping in for Sarah from Group Black.  

Group Black is the first of its kind media collective and accelerator rooted in the advancement of Black owned media properties. Its mission is to foster an inclusive media ecosystem by amplifying diverse storytelling and deepening the investment pipeline for diverse owned businesses.  

In October 2024, Group Black collaborated with Tripadvisor to release the Black Travel report. This report underscores the importance of safety, community and cultural representation in shaping travel decisions among black travelers. The report was published in multiple places, including a feature in travel and leisure and a landmark report on the Tripadvisor site.  

Now, I'll pass it back over to Adam who will wrap us up.

Ryan Gillis 

Ryan and Sarah have already presented to you in a really powerful way about some of the impacts of this foundational research with real people that we did. They've also talked through some of the experiments or initiatives in AI that Tripadvisor and Group Black are really investing heavily in.  

But what I want to talk to you about right now is the ways in which we've applied really cutting edge techniques powered by AI around digital twin, synthetic data and AI persona chat to bring to life that foundational data to allow users to with that data and to really drive directly to more effective engagement, audience building, etc. 

So, the first thing that we did together was actually create an AI persona chat opportunity.  

Think of it this way. Say you send a survey out to 1,000, or in this case 2,000 people. You thought one of the respondents was really interesting. Rather than going out and paying a ton of money to that person to bring them in for an interview, we structure a conversation with a virtual extension of that individual. When we ask them questions, they answer those questions in highly realistic ways that represent the ways in which that real person would answer those questions.  

You might ask, how is that possible? Or you might say, can I just do that in ChatGPT? Why do I need you guys?  

But we believe that approach is simply not enterprise grade, where you're relying on the large language model to simulate one person based on a few data points or even a segment of people.  

Why? Because we're building these personas on a really powerful, stable three-legged stool.  

One leg is 20 plus known demographic characteristics. We know exactly who this person is, where they live, income, religious affiliation, etc. 

Number two, we know how this person answers questions, how they speak, how they feel, how they emote in a particular context. We've sent them a survey.  

Number three, there's tons of Panoplai clustered data. We're good at this. We've done this 1 million times, and we know how to bring people, like data to bear, on a conversation with one kind of person. 

Then finally, we're pre-processing all of that data on the Panoplai side. We're sending out a series of calls to optimized large language models that we are then asking for responses to be generated from. You end up creating a really concrete lifelike chat with somebody that feels real, and not only that it can help you ideate or test ideas. But even more importantly, we are also generating conversations with interrogations of, analysis of precisely targeted audience segments.  

So if you think about the organization that you work for and the segments of the audience of customers that you care about most, and you think about how much work went into defining them, the segmentation analysis, the cluster analysis, the performance marketing data, etc. Now imagine the ability to actually take that segment of the market and have a conversation with them and with all the data that you know already about that segment.  

In this case, we were looking at different segments of Black travelers. As I said, it's an incredibly internally diverse group, and there were really important themes and differences relative to age.  

Younger Black travelers tended to be even more interested, for instance, in traveling to locations where they saw more people who looked like them and they had different kinds of priorities when it came to comfort, when it came to adventure. 

All of these themes can come out of a conversation with these segments.  

Not only that, but I could also test a new tagline, a new idea for innovation, a new engagement strategy against the needs, expectations, etc., of a very quantitatively precisely targeted segment of people. And I could get instant feedback that could help me just in the course of my daily working life, innovate more quickly and effectively, come up with sharper taglines, etc., all without the need to go back to real people every time.  

Now, this is all based on a foundation of real data from real people, but this obviates the need to keep going back over and over again, spending a lot of money, multiple waves of research, etc. 

The other thing that we do and we'll do in the context of this study is what we can call a virtual recontact survey.  

Imagine you send a survey out to a bunch of people and either you forgot to ask some questions or you are further along in your innovation journey or your marketing strategic planning process, and you now know the right questions to ask. The cool thing is that based on that foundation of real data, we can send new questions out to the entire sample set or part of the sample set via virtual extensions of that existing audience.  

So, this survey was sent, the real survey was sent to about 2,000 travelers. Here we're asking a follow-up question about actions to take to minimize potential discrimination while traveling. No real people were asked this question, but at the same time, we're getting really concrete, rich, statistically accurate responses from the entire sample or rather virtual extensions of the sample that are usable.  

That can really accelerate the research journey and allow us to move much more quickly from wave to wave, from phase of the innovation process to a new phase of the innovation process. 

I got one more for you now with Panoplai, and we're really excited about this one. You can actually bridge data gaps with what we call Multi-Study Chat. 

When we're having a conversation with the data in the Panoplai platform, when we're asking questions about anything from statistical significance to narratives or storylines using simple questions in a chat like interface, we can chat with multiple studies at once. Not only that, but we can chat with multiple sources of data at once. 

So, imagine being able to compare your social data to a series of surveys. Imagine being able to compare different surveys over time or from different providers or different platforms. Imagine even being able to layer in reports with PDFs to try to understand the relationship between your raw data and your analysis of that raw data or third-party analysis of the data.  

To bring this to life, one thing we did is we did was pulled in Tripadvisor’s brilliant report that they worked on with Group Black about Black travelers. Then our system is looking at that report alongside the raw data and we can layer in multiple other sources of data all in one place, all of the data that matters from any source about this audience and about this topic. 

We can compare, meaningfully, both quantitatively and qualitatively to find emerging opportunities and validate whether they're real or just kind of ephemeral. We can figure out if people are in a social bubble or a brand is in a social bubble, or if people are having real-world conversations that align with the conversations they're having in social media, etc. 

It's an incredibly powerful analytical function that gives you a truly panoramic view of everything going on around you when it comes to the audiences and the topics that matter most to your organization. 

So, just to take a step back to close things out, I want to think a little bit about what this means for the future of research. And I think the future of research is a hybrid future.  

I don't buy the argument that somehow gen AI data, synthetic data respondents, etc., will totally displace real research. They shouldn't. Instead, there should be a way forward where we're taking the best of the old more traditional, tried and true approaches and combining them, interweaving them with the best of the new.  

What does that actually mean?  

It means that we're always taking this foundational real data of the moment, data from multiple sources, to give us that panoramic view. Then on that foundation, we're building these constructs that add value to that data, allow us to interact with it, to bring it to life, to get real time feedback. Those are things like the digital twins segment chat, AI persona chat, virtual recontact surveys that I was talking about. 

In this context, we're getting real-time feedback from key travelers and customers. Whether you're an innovator or a marketer, you can always get a suggestion or some feedback instantly. And that suggestion or that feedback will be useful and will be accurate.  

There are direct applications all the way from insight to innovation to marketing to audience targeting, etc. Everything you do can be continuously tested and enriched with real data. This approach is cheaper, faster and more audience focused. 

In the end, we're essentially pioneering an optimal blend of the traditional and the cutting edge. It's an approach that we're testing and experimenting with Tripadvisor and with Group Black. We've proven with lots and lots of Fortune 500 clients by now. 

Lastly, I want to take a step back and talk about tips for any organization. These tips are applicable regardless of whether you're working with Panoplai or whether you are a traveler platform or an agency or any kind of organization. 

The first thing I'd say is that you want to always embrace a hybrid approach that takes the best of those traditional and cutting-edge research techniques. That's going to look different depending on who you are, the kind of data you have access to and the kinds of decisions that you need to make.  

Number two, you need to focus on your data and adoption plan, which is to say processes, communication. When you're applying synthetic data, for instance, versus real data in your innovation process or in your strategic planning for marketing, you need to focus on those things as much as or perhaps more than the technology itself. 

The technology is something that creates a conditional possibility for innovation, for speed, for cost savings, for breakthrough innovation. But if you don't adopt it properly and you don't think about the processes that you're using within your organization, then the impacts won't come and the ROI will never arrive.  

Thirdly, you need to work backwards from business and marketing goals.  

In this case, we're not just interested in understanding Black travelers for its own sake. It's an important goal, but we're not an academic organization. We're trying to engage Black travelers more effectively. We're trying to help Tripadvisor’s corporate partners reach them and serve them more effectively. We're trying to send content to them that feels more targeted, more urgent and more personal.  

So, we're thinking backwards from each of those goals, adopting a research plan and a use of some of these cutting-edge technologies specifically to accomplish those sets of goals.  We are creating a report card and a set of benchmarks, and we're testing relentlessly to make sure that the outputs are not only statistically accurate, but are realistic, they're generalizable, and they lead to measurable increases in speed, decreases in cost, increases in the possibility of breakthrough, innovation, etc.  

Finally, we're building a flywheel where every investment in research fuels an enhanced understanding and impact.  

You really don't want to go back to the days where you're doing that video interview, you use it once and then it sits in the corner gathering dust. You want every bit of research that you're doing, every dollar you're spending on research to go back into that interactive data repository to provide the context, the training data and the insight that you're going to use as your organization moves forward into this new frontier where you're testing plans for innovation, marketing, decision-making, etc. 

I want to thank you all for being here, for listening. I know it's not always that easy to sit through a recorded talk.  

Now we really want to hear what you think. If you disagree with us, let us know. If you think we're crazy, let us know. If you're wondering how all of this might apply to your own organization, let us know. We're here to answer questions.  

Thank you.