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Transcript

Hi everyone. If you’ve just joined us, we’re just giving everybody a few more minutes to join from the lobby. So we’ll get started in about two minutes with our material.

Okay, hello everyone and thank you so much for joining. I know that we’ll probably still have a few people joining in from the lobby as we continue on in our discussion, but I just want to get started and kick us off. Thank you for joining today’s webinar. Our Q2 webinar is all about the state of digital and Gen AI adoption. There’s a specific focus here on the retail and consumer goods vertical as well as travel and hospitality. So with that, I’m going to go ahead and introduce the hosts for today.

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Thank you so much, Matt. So again, welcome to all of you guys who have joined us today here. My name is Meredith Goodspeed. I’m an ultimate success leader overseeing our retail and consumer goods vertical. Joining me today, we’ve got both Matt and James from our ÃÛ¶¹ÊÓƵ Digital Insights group and the wonderful Julie Hoffman who oversees global industry strategy for our travel and hospitality vertical. We’re going to hit on a ton of exciting topics today, primarily on the state of digital and Gen AI adoption across retail, consumer goods, travel and hospitality verticals. But before we do that, I wanted to take a moment and hand this off to James and Matt to go ahead and take us through what the ADI team does. So you can understand a little bit more about this powerhouse that’s within our ÃÛ¶¹ÊÓƵ ecosystem that has helped bring these insights to life for us today. And is a fantastic resource for you as our clients within the ÃÛ¶¹ÊÓƵ group. So after that orientation, this group is going to bring forward some of these insights that we found recently. And we’ll get into the specifics around the data that we found particularly interesting for you guys on the line. So with that, I will go ahead and hand it off to James and Matt and we’ll get started.

Thanks, Meredith. So ÃÛ¶¹ÊÓƵ Digital Insights is the data driven thought leadership arm of ÃÛ¶¹ÊÓƵ and a leader in real time economic and digital experience insights.

ADI provides unique, actionable benchmarks and recommendations to the biggest brands through deep data partnerships and decades of industry experience.

Our calling card is the annual holiday report and we’re frequently featured in top media outlets. You may have seen us on CNN, CNBC, Forbes, Wall Street Journal and other outlets. We also produce digital economy thought leadership globally and other customer experience thought leadership, such as the data in today’s presentation.

Next slide.

So we recently analyzed over one trillion visits to US sites and over 100 million skews and noted for prevailing trends we want to share with you today.

We’re going to talk through observations, insights and key takeaways for each of these trends. So as a quick preview, first, personalization is facilitating more efficient experiences and consumers are spending less time on any one website to make sure that they are not getting too far.

Second, the steady march toward mobile continues and consumers are continually shifting toward mobile across categories. Third, social traffic is growing but remains inefficient.

Growing, the engagement conversion rates are just remain low. And fourth, Gen AI referrals are surging across categories and we’ll talk a bit about this. We all know that the use of Gen AI is exploding and we’re seeing that traffic is doubling nearly every two months and conversion rates increasing over time.

Julie.

Yeah, so I’d like to just add a little nomenclature on her. We’ve done a few different research trends in terms of loyalty. And there was an interesting anomaly that came out in our last research and looking across all the different cohorts, Gen Z, Millennial X and Boomer. And they all value time as a resource. It used to be just for your high end luxury consumer that really valued time, but every single cohort now really values time. So we’ve hit a turning point in personalization. More brands are now more mature. And what we’re seeing is that the gap between like the hype and the reality is closing. I think what this really means is that, you know, we can anticipate needs for customers, but we also give people their time back. Which is very valuable. And the data shows that we’re actually making some real strides here. Mobile still remains a very strong channel for travel, always has been. And I think we’ve done a great job of overhauling it and becoming a lot more effective. Social, although it’s in flux, it’s really high on inspiration, especially in travel. But it’s low on conversion because it’s due to unclear next steps. Oftentimes people land on something social related and they want to go instantly to the product or the offering that connects with that. And I think when we get better at that, it’s going to improve. And I think Gen AI is stepping in at the right moment. Travel planning can be very overwhelming. It can be very heavy and time consuming. And I think it’s helping to simplify those decisions and guide action, meeting a real need, especially for the space. So I just wanted to add that in because across this is retail, consumer goods, travel. Every single cohort really wants their time back. So we’re doing a good job.

Great, thanks, Julie.

All right. And a quick note on our methodology and how you should read through the graphs and the subsequent slides. So we’ll try to call out highlights on each page. But the short version is that you’ll be able to see year over year changes for each of the metrics and also broken down by industry. If you have any questions, please just post them in the chat. Now, these charts should be viewed more as a weather vane. So don’t get bogged down by the exact number in any one industry or for any one metric. What we’re trying to do here is capture the overall trend and focus on that. But there are questions again. Feel free to use the chat where we can bring up in Q&A. And with that, I’m going to turn it over to Matt to discuss personalization.

Thanks, James.

So first key point, first thing that we pulled out was we’ve been noticing that personalization seems to be facilitating more efficient experiences. The first part of that is that we’re finding consumer web interactions are getting shorter. So if you compare 2023 to 2024, we looked at the industries that we have across the board. So financial services, mean entertainment, software and services, in addition to retail and travel. And we’re seeing that there are fewer page views per visit and less time spent per visit just about everywhere, including retail and travel. You can see the call outs there minus 3 percent for retail and minus 14 percent for travel. But it’s really a prevailing trend. And that’s the first part of the story. And then when we drill down to e-commerce categories, so looking now at, say, apparel and footwear, health and beauty, consumer electronics, we’re seeing a similar trend.

Page views per visit tend to be down. Time spent per visit is also down. So just reinforcing what we saw on the last slide, this is something that we’re pretty much seeing across the board. Also things that we’ve seen corroborated in other sources across just experts in the field. However, the important flip side of this is that these consumers are converting just as often across the board. So when we’re looking at the CTA’s just actually purchasing an item in e-commerce, we’re finding conversion rates are often going up. And the trend overall for retail and trend for travel is that conversion rate is actually up year over year. And that’s even though average order value is increasing. So it’s not like there’s some external trading down factor that’s impacting this conversion rate going up.

Meredith? Yeah. So when we were thinking about this from a retail and consumer goods standpoint, this reinforces something that we already know, and that’s that customers are wanting to buy, but they need you to meet them where they are as that attention span is really limited. This really emphasizes that critical importance of personalization. This also emphasizes the critical importance of really stitching together that online to offline experience to make sure that when they go into your e-commerce site and they are there and ready to buy, their experience is truly meeting them where they’re at with regard to their holistic journey with your brand. So a few things that we’ve been talking about in the past, just reinforcing the critical nature of a personalized experience and really letting your customers know that you know the experience they’ve had with your brand thus far.

And you’re ready to meet them at that place and show them that you know them and that you’re willing to support them in their purchase cycle wherever they may be.

And I would add on travel that we’re definitely converting better thanks to smarter segmentation. We have a recent study that will be coming out that shows that on average, all sub verticals are around 15% for sophisticated segmentation. And there’s still obviously a lot of room for improvement, but that’s a huge improvement from where we used to be. Average order value actually shows a couple of trends for us. Competitive pricing is driving decisions. So pricing right now is in flux and travelers are eager to still travel, but they are making some trade offs. They’re choosing lower tier options, different transport modes, or they’re shifting to different brands to get more value out of there. And of course, a lot of this is due to those macroeconomic trends.

Great. Thanks, Julie. So moving on to high level observation number two, the steady march towards mobile continues. This is a long standing trend we’ve seen over years and years. People are using mobile more in place of desktop and that continued from 2023 to 2024.

So you see that across the high level industries, mobile visit share is largely up. Up across the board, it’s up in retail, same in travel and hospitality.

And then again, looking at mobile revenue share, revenue share tends to be up when we’re drilling down into the e-commerce subcategories.

However, mobile engagement still lags desktop and engagement. What we see here in the graph is basically we’re trying to compare page views per visit on mobile to page views per visit on desktop. So, for example, in telco, page views per visit on mobile for telco are about 85% of page views per visit on desktop or about 15% fewer page views per visit on mobile than desktop. So we are finding that pretty much across the board, there are fewer page views per visit on mobile than desktop.

That ranges from 85% in telco to 56% in financial services. Both retail and travel are about 0.8 that ratio.

So engagement is still trailing.

Julie? Yeah. So the big question for me is, well, how can you actually improve mobile performance? And my answer would be to invest in a unified customer experience. So being seamless between one channel to the next, physical to digital, really helps to save people time. And it’s actually really comforting from a consumer perspective. If I ended my search or my journey on one part of the experience and then it’s reflected back to me in another channel, it actually speeds up my process for actually completing what I was designed to do or what I was intending to do.

Although they may view fewer pages and conversion actually increases, overall, we’re going to see is higher level success. We saw from a cross-channel consistency that it really drives a lot of impact in travel. In particular, we had an airline brand who made that conversion of having this unified experience and they were driving about a million dollars a week by connecting mobile and desktop experiences. That’s a lot for one use case. And for cruise brands is another example. Decisions are very complex and they oftentimes will move between desktop and mobile. So how can you make this alignment even more effective, even wrapping in the call center too as well? Yeah, and I think what we’re seeing is that brands are doing that. Mobile experiences have continued to catch up in e-commerce also. So looking at the e-commerce subcategories, there’s been an increase in mobile’s time spent per visit and conversion rate relative to desktop. So it’s still trailing. You can see it’s still pretty far behind in some instances, but for the most part, it’s been getting better. The experiences are catching up because of some of the things that Julie mentioned.

So third key observation, we’re finding that social traffic is growing, but it remains a relatively inefficient channel.

So to start off with a big overview of marketing channels across the high level industries, we can see that more traffic is driven by direct and search pretty much across the board. Social traffic is still not that high, although it’s fairly big in retail.

One of the key trends that we’ve been noting in general is that direct traffic and search traffic are the two channels that have been growing more than any other, and those are the more mobile associated channels. Mobile, social, it’s obvious you’re browsing social media on your phone. You click on a link. You’re on the website.

Direct, part of that, a big part of that is actually app traffic. So being in that consideration set in advance and someone being able to just touch on that app. Meredith? Yeah, so this was interesting to me when I looked at this, understanding that I also look at it with kind of a critical focus on retail and consumer goods specifically. Notice that one of these is not like the other, and it is retail. If you look at the tail end of that chart for retail specifically. And this is in alignment with what we reported out on last quarter with regard to results around the holiday season. Social and email are really critical channels for retail specifically. Retailers are looking to these channels to inspire their next purchase.

Retail overall, as Matt mentioned, is overall seeing more traffic from social, but it is still struggling with regard to engagement similar to these other verticals. So we really have the opportunity within the retail vertical to capitalize on that higher traffic and focus on that social conversion strategy more so than other verticals and really pave the way there. So it’s something that we mentioned again during the holiday report, during our Q1 webinar, but it is critical to focus in and understand what is our social strategy? What is the conversion component within that social strategy look like? And then how are we also incorporating an affiliate strategy too, as we know that the conversion rates coming over from affiliates are pretty strong in comparison to other channels. So an area to consider and definitely should be a critical focus for retailers to make sure that there is strength in their email, social and affiliate strategies.

Great. Thanks Marta.

So drilling down now into social, we said social is growing, but visitors coming from social are not very engaged. The first part of this, you can see social visit share is growing across the board, but the relative engagement is pretty low. So social to overall sort of same story as the metric with mobile to desktop on the previous, on the earlier slide, we’re seeing social to overall page views per visit rates being at about 0.6, 0.5 and then time spent per visit 0.5 to 0.4. So engagement on these channels is engagement from social pretty much across the board is pretty low.

And then if we’re drilling down into the e-commerce sub industries, they saw big social growth too, but moving from engagement to conversion, the relative conversion rate is really low. So as a result, the social visit share from this channel from social tends to be way higher than the social revenue share because the average, the overall social to overall conversion is about 20% in retail and only about 10% in travel.

So overall, actually what we’re seeing from social is that traffic looks more like patterns we might see from display than patterns we might see from say search.

Julie.

Yeah, so I always say that in travel, we like to study what retail is doing. Thank you, Meredith.

And retail is ahead of the travel space often in many ways, especially when it comes to performance. You know, one of the things that I find interesting is, you know, there’s a very natural crossover.

You know, both categories are highly visual, lifestyle driven and impulse influence. So we have a lot of similarities, you know, kind of looking at the breakdown here, apparel and footwear brands using social, I think is a place where we could lean in from a travel perspective to learn what’s working and what’s not for that subcategory. You know, it’s smart, it’s fast moving, it’s full of lessons, you know, and a great example is OnRunning. You know, they built this incredibly engaged audience across social and much of their traffic comes from authentic influencer partnerships with athletes and creators who reflect the brand’s values. And I think that that model very much can work absolutely for travel brands, especially when paired with like high quality experiences. You know, I think that’s an area, especially because we have such a dynamic industry and there’s so much excitement around it. We can look for those partnerships in particular. And I think that’s a big area of growth for travel in 2025 is how do you actually find those partners and align and leverage that natural social influencer? Great. Thanks, Julie.

So let’s move on to one final broader observation that we had when we looked at the e-commerce categories. We’re finding that price point shouldn’t form engagement strategy across devices and channels. So the first thing that we’re seeing, we’re looking at the average order value within a subindustry and then we’re comparing it to certain KPIs. So in this case, we’re seeing average order value versus conversion rate. And we’re finding that a higher AOV categories have lower conversion rates. So higher consideration, higher research industries like consumer electronics and home, you see their conversion rates are lower, about 1%, 1.3%. Whereas verticals like apparel and footwear, health and beauty, those are up closer to 3%. Julie? So I would say that this is always a hot topic in travel and hospitality. What are conversion rates? We get asked a lot and I’m oftentimes working with the ÃÛ¶¹ÊÓƵ Digital Insights team and how can we share those information in a more holistic manner. So this is a great chart to say, OK, what is it? What’s happening? You know, with high average order values, travel generally performs well, even with those longer decision cycles. They are considered purchases, though. So customers take their time, they compare options, they weigh value. And I would expect that those lower price products, you know, they convert at a faster rate. But I think the key is isn’t comparing across the whole industry. It’s really benchmarking against your own product complexity and price point. So think about the product complexity and price point instead of, you know, the vertical at whole and say, you know, again, in travel, especially for airlines and cruise lines, the call center remains a very critical part of the conversion journey and often serves as a final nudge for someone who’s close to the customer.

And then you know, for those high average order categories like cruise or amusement parks, customers often research online, but they purchase offline, making a strong omnichannel experience and attribution tools essential for the team. And for those lower average order value categories like short haul airlines or budget hotels, personalization and loyalty become key to capturing attention and driving repeat business. So again, I would think look at your product complexity and price point and think very carefully about what that journey reflects because it isn’t standard across travel and hospitality. And I’m just going to just sorry to jump in here, but just to build off of what Julie said, I think the same very much goes for retail. When we think about complexity, let’s say within apparel, there are multiple different sub verticals within apparel. Some are more complex than others. Some take a little bit more time to think through what you might need or the sizing might be more complex than for example, a shoe is going to be a little bit easier to size than something that might run big, run small or undergarments, for example, might need special sizing. So that what Julie just said really rings true for retail as well. And I do think it’s really critical to benchmark yourself against other apparel or other retailers that are within a similar sphere as you. But make sure that you’re also setting your benchmarks against yourself and the goals that you’re trying to achieve within your own organization and really bring in that complexity that the consumer might be facing as not all one. It’s not a one size fits all, if you will. No pun intended in apparel.

I could make a size joke there just for fun, but I won’t. The joke’s already been made.

So moving on to mobile.

We’re also finding that mobile is used to buy lower ticket items at a higher rate than it is to buy these more complex items. So you’re looking at consumer electronics, home, travel, mobile revenue share is a lot lower than the mobile revenue share and maybe the less complex, the less expensive categories. So apparel, beauty, merchandise. And then we that’s in part, but in part due to having lower mobile visit share. But not really. The mobile visit share is a little fairly similar across the board. What we’re really seeing is that the mobile to desktop conversion rates a lot lower. So if someone is browsing on their phone, they’re going to be way less likely to pull the trigger in the home category when they’re on a home or consumer electronics website than when they’re on a health and beauty category on a healthy beauty site.

So that same pattern, more complex purchases are going to have lower mobile revenue share and similar to engagement. It’s about the conversion rate more than anything else.

We also see that social performance is better for the smaller AOV categories.

So relative engagement rates for more complex purchases are lower. So traffic from social does not drive as much engagement or conversion, whereas in the less complex, the less expensive categories, the relative conversion that it drives is better.

Yeah. And I think that is it for this general section. I’m going to pass it off to James to dive into Gen AI adoption.

Thanks, Matt. All right. Going on to our fourth prevailing trend, we’re talking about Gen AI adoption and the surge that we’re seeing now. You’re going to hear me refer to Gen AI. What we’re really talking about is Gen AI LLM platform referred traffic. So if you’re Gen AI, Gen AI adoption in these terms, we’re really referring to is referral traffic from platforms like chat, GPT, Claude and Perplexity to your sites, to retailers, travel, banking. Those are three you will really focus on today.

So the first major thing we’re seeing is growth surging across industry travel leading the way. Traffic to retail travel and banking is surged. We look back from July 2024 through February 2025. The share of traffic is doubling approximately every two months right now. Travel has seen the biggest surge with Gen AI visit share up over 1700 percent since July.

And finally, Gen AI visit shares up over 1200 percent in both banking and retail.

Yeah, and I would add here, I mean, I love that travel is leading the way. And I understand that deferred traffic or traffic that’s going to Gen AI and not coming direct to the traffic to this website can be considered a red flag. But there’s actually a real opportunity here. You know, with AI usage accelerating travel, this is a chance to learn from how customers are searching and what they’re asking for, because there is a gap. Oftentimes, we’re you know, brands are very hyper focused on the actual conversion and the actual booking itself. But most consumers are looking for help with inspiration and with planning. When I was a practitioner, I actually would personally scrape social comments and use that language to redesign landing pages. And it would completely shift our performance and even helped us reposition into the luxury space when I was working at MGM resorts. And something that had been a challenge before, especially for like the city center properties like Aria. So in a bit, we’ll dive into how travelers are actually using Gen AI and what that tells us about the types of content that we should be creating next to help support them.

Thanks, Julie. We’ll start with a dive into retail.

Now, Gen AI shopping boom is a trend that we believe is here to stay. The amount of traffic here is nascent, but the growth is exponential. It’s growing rapidly.

39% of consumers are reporting that they are already using AI for online shopping.

And 53% of consumers plan to use it this year for shopping within the retail space. And of those who have used AI for retail, 55% of respondents report using it to conduct research. 47% report using it to get product recommendations. 43% to find deals. And others to ideate on gift ideas and generate shopping lists.

Meredith.

Yeah, so this is something that we’ve been discussing since January at NRF, if anybody was present for that. And so this trend only continues to uptick as we continue through the year at what you can see is a pretty fast rate. In the past, we’ve kind of spoken about this in terms of there needs to be a new way to think about SEO when it comes to Gen AI. And that was actually the bulk of the questions that I got after presenting about this at NRF. There was a lot of questions that we got in Q1 as well. And now some leading researchers are actually starting to now coin this area as a generative engine optimization GEO. And so it is here. It is a new way to strategize around your SEO or now what we’re calling GEO. And it absolutely needs to have a place in your strategy. Thinking about it now before the holiday season hits will be critical. And those who will thrive in this space are going to be the ones who are starting to build out a strategy now so that they can be successful in this space come October, November and December. Because we expect shoppers to really be leveraging this for inspiration, for prioritization during that critical shopping time. We’re going to have some key takeaways at the end of this presentation, specifically around GEO, since it really is a critical building block to incorporate into your strategy this year. So if you have more questions about that, feel free to use the chat pod. We’ll be providing those key takeaways at the end here. But this is one of my favorite topics this year. It is absolutely important to understand how do you show up in these Gen AI search engines? How do you use them as a referral source? And how do you really leverage the different opportunities out there to drive traffic back to your site through these inputs? So more to come here. But this is a big one and probably my favorite topic of the year so far.

Thanks, Meredith. All right. In terms of engagement, we’re looking at bounce rates within the retail space to measure this right now. And what we’re seeing is consumers referred by Gen AI sources are less likely to bounce among retail sites. So bounce rates for Gen AI referred traffic have declined throughout 2024, more or less stabilized in 2025, suggesting that AI users are finding recommendations more useful over time. Those recommendations are improving. Between August 24 and February 25, Gen AI traffic has had significantly lower bounce rates than non AI traffic. Again, indicating relevance and just a higher level of engagement. And finally, in February of 25, Gen AI referred bounce rate was 23% lower than the bounce rate for non AI traffic. Again, just indicating that higher level of engagement when somebody’s already gone through that process of researching or generating a list and then they’re making it to the site, then they are more engaged at that point.

All right. We’ve also found that a Gen AI referred visit is worth as much as a non AI visit in the retail space. This hasn’t always been the case. When we started this analysis, when we look back to July of last year, we saw that a Gen AI referred visit was less than half as valuable as a non AI visit.

There’s been a trend and the value of those Gen AI referred visits has been growing. In fact, in December of 24, a user referred by AI was spending on average more, just over, but more than a user that reached a retailer through traditional channels.

We’re definitely seeing an upward trajectory in this space in terms of, we’re calling customer value or revenue per visit.

All right. Finally, when we look at different product categories and we think about considered purchase, a considered purchase versus a less considered purchase, we’re seeing within the retail space that considered purchases are seeing a stronger conversion among traffic from Gen AI sources. 87% of consumers are using AI for online shopping report that they are more likely to leverage it for complex purchases.

So considered purchase categories, such as consumer electronics and jewelry and accessories are seeing the strongest conversion rates relative to baseline. And less considered categories, such as grocery and apparel aren’t seeing that conversion bump in the space, but it might be used a little bit, but it’s not quite seeing the bump that we’re seeing among considered purchases.

Yeah. So a few key takeaways that have really stood out for me in this past section, aside from the importance of generative engine optimization, which I shared my excitement around a few slides back, is the idea that consumers are really looking for reassurance and their purchase decision. And this isn’t a new concept at all. Before Gen AI, customers were looking for reassurance in other forms, such as customer reviews, influencer suggestions, online forums. I know myself, when I was going to make, if it was, let’s say a consumer electronics purchase decision, I read a lot of reviews before making that purchase and understanding what would be best for me, even when it comes down to apparel, something that might not cost as much to me. I’m looking at how that fits on other people who are reviewing it on, let’s say Amazon or Reddit or what it may be. So customers are looking for that reassurance that they’re making the right purchase decision for themselves. And they’re now finding that reassurance through Gen AI, which is a huge shift. This is supported by the AI-referred bounce rates being lower, the recommendations being more useful. This is also supported on this slide as these more expensive categories within retail or more complex categories are seeing that stronger conversion, as you can see here. So again, helping support the theory that consumers want the reassurance and they are actually starting to find it more and more through Gen AI really reinforces the critical importance of having a strategy around your generative engine optimization and how you’re showing up within this space, because it’s only going to continue to grow, especially getting that nailed down or a strong hypothesis and strategy around it before the holiday season will be very important.

All right, we’re going to change switch industries, talk about travel for a little bit. As mentioned on the previous slide, we’re seeing tremendous growth, the most growth within the travel space in Gen AI-referred traffic. Now, 29% of respondents have used AI for travel. We thought that was exceptionally high. And 87% expressed interest in the future. AI advancements within the industry. That includes Gen AI and other AI technologies. Now, of those who have used AI for travel, 54% of respondents report using it for research, 43% report using it for inspiration recommendations, and others report using it for budgeting and with packing assistance for trips.

Yeah, and just to reframe again, the deferred traffic. As more travelers turn to Gen AI, although it is less or loss of traffic, it’s more a shift in behavior. So we can really learn from this and build generative engine optimization or geo as Meredith was sharing. And so if you look at this planning, inspiration, budgeting, packing help, these moments show where we can actually become smarter with the types of content that we have.

One of those could be, what is the best cruise for solo Gen Z travelers? We’re going to be talking about generational trends here in a moment. But in general, 75% of Gen Z and millennial are traveling alone in solo. So how do you actually meet their needs for the types of inspiration and planning that you’re doing? So these pieces of content are really designed to surface directly in AI power tools. And this can help travelers earlier in their journey and also position your brand as helpful, not just promotional, which is really what they want. Back to you, James.

Yep. And then we get to looking at the value of a Gen AI referred visit versus a non AI visit, we’re finding that in the travel space, AI visits, Gen AI visits are 80% more valuable than non AI visits. This is a stark contrast to retail where we saw maybe bump up to be as valuable as within travel, we’re seeing it. These visits be 80% more valuable than on AI visits. So in December of 2024, specifically, the value of a Gen AI visit was more than double that of a non Gen AI visit, again, just showing the exceptional research and preparation these customers have done in getting to that point and the value that that they potentially have for you. And I would just add is that travel planning is exhausting. If you are the travel planner in your family takes a lot of time. And so I think these results very much speak to the gap in the industry is that customers want help with that process. They want to be a lot more simplistic, they have specific things in mind. But oftentimes, the way we create content is very centered again, around the booking versus centered around that inspiration and planning. So I look at this as a huge opportunity. I think brands who lean in first, they’re gonna see a lot of success with this. Great, thanks, Julie.

All right, finally, some insights into the banking space. Much like travel and retail consumers are turning to AI for finance. We talked about the growth rate previously here. Just about keeps up with with retail. 27% of survey respondents report using AI for banking and and financial needs, and 62% are expressing interest in future AI advancements in the sector. Not quite as high as travel, but still a lot of interest in what in how things can improve. And we had in our in our survey, we saw that 93% of respondents trust AI to provide financial recommendations, and 49% reported that they would follow its advice completely. Now those who have used AI for banking, respondents report using it for for a number of tasks, including recommendations for checking in savings accounts, explanations of complex financial financial topics, personalized budgeting insights, investment advice and tax advice.

Now we looked at engagement within the banking space. In this in this case, we looked at time spent per visit. Since July of 24, time spent per AI Gen AI source visit has increased 46%. In January of 25, AI driven visitors spent 45% more time on banking sites than those that arrived from other channels. Finally, application start rates within banking. So application start rates from Gen AI referred traffic eclipse that of traditional traffic for the first time in January of 25. Again, showing that preparation that research that’s going into it and that engagement we’re seeing from from users.

Alright, now, who’s using this? Who’s on who’s on the other end of driving these trends and we’re seeing that young affluent users are driving Gen AI referrals, but not exclusively and we’ll and we’re going to look at that.

So Millennials lead the AI assisted shopping spree. Younger generations.

Excuse me, younger generations are leading to AI with Millennials leading to charge and both adoption and expected use. We’re seeing that 28% of consumers report that AI assistants are their primary source of product research.

Yeah, so yeah, just to add on here, we are in the process of publishing a white paper on customer acquisition in travel and hospitality specifically. And what we learned is that 82% of brands have either no generational strategy or only have an ad hoc one. Like they’ll do it for a campaign. It’s really not cohesive. So one major gap is low Gen Z participation in loyalty programs over half of the loyalty programs. And so the ability database was showing up as active like 54% but of that the cohort for Gen Z was only 14%. So creating content that surfaces in in those AI assisted shopping. Could be a huge and smart way to actually reach and engage this audience, especially as their digital behaviors evolve. And, you know, now that you know, we’re at the time that we’re in both Gen Z and Millennials are an area where we need to spend more time capturing those customers as Gen X.

Alright, speaking of some of the age categories, we’re seeing that baby boomers are lagging relative to the others, but they are catching up. So more users have adopted Gen Z across the across generations. And we have found a 22% increase in consumers using AI for online shopping compared to the five months prior. Now, over 85% of users in each generation have said that AI improves their shopping experience. I find that one to be exceptionally high. And finally, baby boomers are the least frequent AI users currently, but they are seeing the largest growth. They’re showing that the most significant increase in adoption and also reporting positive, the most sorry, the highest positive experiences with Gen AI over the last five months.

Alright, and then some of the income breakdowns higher income segments are leading the adoption within the retail space. Now, in general, higher income higher income consumers are more likely to use AI to make retail purchases. Gen AI is assistance, LLM platforms. Usage is highest among higher income Millennials, with adoption steadily increasing as income rises, exceeding 50% usage for those that are earning $70,000 or more. And Gen Z shows the strongest adoption at lower income levels, but usage caps out higher income levels just under 50%.

Alright, and now, as we were going through this presentation and putting all of our thoughts together, we asked ourselves, what does the future look like? And we’ve been discussing how AI platforms are shifting, how users access information, how they’re researching how they’re how they’re purchasing. And one of the questions came up was, what are our traffic expectations in the wake of Gen AI LLM platform adoption? Now, Ev Fedorenko is an associate professor at MIT. And she studies the internal architecture of the brain’s language of the brain’s language system and neural networks. And she was recently asked, where’s AI headed in the next five to 10 years? And she gave what I thought was a very common sense answer. She said, I think we will learn to put big air bars in our predictions of how things unfold. And as we explored over the, over the previous slides, a growing percentage of consumers are reporting that they’re using Gen AI.

Google’s AI overviews, chat, GPT, other platforms are reducing traffic to informational content, and decreasing the need to visit external websites. We’ve also seen decreases in the share of share of traffic for search in various industries. Now, we don’t expect all of this to translate to loss of business, but rather there is an emerging consumer behavior that will be seen as AI ultimately influencing conversions that occur later through change in the future.

Again, big air bars around this, but that’s where, that’s where we’re anticipating in terms of traffic. Now, the path of least resistance, whether it’s planning for a trip or creating a list of gift recommendations, there’s clearly a segment of customers who are finding tremendous value and efficiency with Gen AI tools. Gen AI LOM platforms are reducing the friction for consumers to find information. As this field continues to develop, we may ask ourselves, where in the customer chain do brands create value? Where do brands connect with the customer? It’s more important than ever to acquire and maintain high quality first party data, and have things like a strong mobile and have things like a strong mobile app adoption, or a great email program. These are the types of durable assets that can help weather the shifts in this evolving landscape. Finally, generative engine optimization. This was alluded to earlier. To follow up on this, the goal is to ensure that AI models can easily understand and position your brand as an authority in AI generated answers. Gen AI LOM platforms are designed to synthesize and prioritize quick and comprehensive responses. This is also why we see a decline in traffic to informational pages on websites. These pages remain critical for the same reason that they’re actually receiving less traffic. Now, some of the recommended optimization tactics currently include using relevant keywords, citing relevance, sorry, citing reliable sources, adding qualitative data and statistics, quantitative data and statistics, including expert quotations, use of clear and concise language, incorporating technical terms.

And perhaps most importantly, is publishing authoritative content and thought leadership. And finally, being listed on external sites such as best of lists for your brand or your product. With that, that’s the end of our presentation today. And we’ll turn it over to Q&A. Yeah, thanks, guys. And thank you guys for joining. I’m going to go ahead and move over to the Q&A chat pod in a moment to answer a few questions or field questions for the team. Before I do that, I just want to let you guys know that this content will be shared. This will be shared out to everybody who registered for this webinar. So over the next few days, you can expect this to hit your inbox. If you don’t see it for some reason, maybe this was forwarded to you so you’re not on the original distribution list. Feel free to reach out to me. I’m happy to share it with anybody who would like to see this content and feel free to share it out with other individuals within your organization. So if that was your question, the answer is yes, you will have access to this content. And even better, you’ll have access to this recording so you can listen to us like a podcast if you want. Okay, so let’s talk about the first question. What are some of the most effective ways Gen AI is being used by industry leaders to drive qualified traffic and improve engagement on customer-facing websites? So I’ll give my two cents first. And I think that the team kind of hit on this throughout the presentation and really there at the end, James did. But one of the things that we’ve been talking about is knowing how LLMs work and understanding where they’re going to source this information. How can you partner with authorities within your space to really show up in places on the internet so that when it is doing that scraping, it is pulling you in? So an example I’ll give there is let’s say from a shopping perspective, I’m looking for a really great summer wedding guest dress that is light and breezy. This is just for example sake. How can you partner with influencers, with publications such as InStyle, for example, or other authorities within the topic in which you’re hoping to drive your influence in to be listed as some of the best options within the space? So you have to think back in terms of what do we want to show up as? How are our customers going to be searching for us, if you will, within the Gen AI space? And then from there, where can we partner with other authorities outside of our realm that show up within along the internet to really be pulled in and scraped in? So that’s one example for retail and consumer goods. I know there’s multiple answers to this regarding the vertical one. So I’ll ask Julie and Matt and James to add to that. But that’s just one way to think about it within retail and consumer goods. I would definitely add on to an authority figure. If I think about travel and dining, those are two hot topics for all of the content creators that are out there, the social influencers.

So aligning your brand to the ones that make the most sense so that you can be front and center as a brand. The other thing, too, is I would be actively searching chat, GPT, Perplexity, all these different engines to actually understand what are the things that customers are searching for tied to my industry, tied to my brand itself and understand what those answers are. And then look at those answers and reverse engineer to what would be my solution for that? How do I provide more content either on my own site or through those partnerships so that my brand can be again front and center? They are again performing at a very good rate in terms of the productivity once they actually get to the site, because they’ve already done a lot of their research and planning outside of the site. But if you can provide that content within your own four walls and then it’s more searchable, it can be picked up by these engines, which I think can provide a big trajectory. And of course, for the younger demographics, again, a lot of them are growing into being the top cohort for the travel industry. So understand how do they think, which is different, like what to pack as a content creator? What are the best, again, solo Gen Z trips? What are the most Instagrammable destinations, which a lot of people are looking for those iconic places? There’s a whole thing around destination dupes right now, especially as the economy has evolved and there’s a lot of things going on with uncertainty. When you think about that, the consumer you have today is not necessarily going to be the consumer you have tomorrow.

There will be more localized traffic understanding what they’re looking for. So maybe they’re not going to go to Amsterdam, but maybe they’ll go to Holland, Michigan, or maybe they’re not going to go to Italy this year. But you could direct them to California, Napa, and make the connection for them on those places that will resonate if they make different choices in 2025 and beyond.

Pass it over to the other folks. Yeah, I would just emphasize something that I think both Meredith and Julie touched on. Run these searches, enter these queries yourself, see what results show up, see who’s showing up in the results. Like if you’re looking for, if you’re in apparel, you’re in shoes, you have the good shoes for running, right? Just that someone might search, see what’s showing up in the results. And then also importantly, what those results are linking to now that all these platforms cite sources.

Check to see where they’re pulling it from and where they’re sending traffic to. And that should really help you figure out how to get into the consideration set. Yeah, I think that’s a great call out. I’m going to move on to the next question.

Next question is, I would love to know more about advertising or partnerships in Gen AI LLM platforms. Do you have any details on this? This is one where I think we need a little bit more information about what you mean about advertising or partnerships within LLM. So if this was your question, please feel free to reach out to us directly and we will work to try and understand the root of the question there a little bit further.

The next question is, do we have any insight into the slight dip in Gen AI usage among Gen Z in 2025? I don’t have an answer to that one specifically, but I will throw out a teaser that we are going to, we have the next iteration of our research on the Gen AI front, hopefully coming out very soon. We can work with your account teams and CSMs and everyone to get that out to you. But ideally, what we’ll have at that point is a, you’ll notice that our research to date was through February that we shared today. We’ll have more up to date and we’ll see what that trend looks like for say Gen Z throughout more of 2025 and see exactly what we’re going on there.

But right now that’s further research and we’ll see what comes with that trend.

The next question is, are AI overview results coming into ÃÛ¶¹ÊÓƵ Analytics as direct traffic? Is there a way to see AI overview traffic separately from organic search or direct? I would direct them to look at, no pun intended, direct them to look at the referring domain or referrer to identify this traffic right now. So not under marketing channel.

I’m going to put this in the answer in case other people have similar questions.

Okay.

Do we have any research data on Gen AI repeat purchase trends versus organic search or other paid referrals? We have looked at loyalty a lot, but not in the context of the Gen AI data yet. I think as this space continues to evolve and we have more data in history and everything to review and look at, loyalty will become more of the picture.

I would suspect at this time it would be relatively low just due to the limited amount of traffic under Gen AI.

But that’s a great thing to point out and repeat purchase trends I think should become more of the story as time goes on. Yeah, I think that’s a great question.

Okay, we’ve got about two minutes left and with that I think we’ll go ahead and wrap it up. Thank you all for attending. Thank you for your time today. I hope you enjoyed the content. We will continue to share out information like this evolution of what we’re talking about today into next quarter in future webinars. So please make sure to continue to keep your eye out for opportunities for us to share this information for you. We love bringing this information forward to our clients and helping shape your strategies around the data and insights that we are able to glean every single day from our work. So thank you for joining. Please keep a lookout for the recap to come over. It’ll come over from myself with a link to the deck and the recording. So it should be there within the next few days and I hope everybody has a wonderful rest of your week and great weekend. Thanks for coming. Thank you. Bye. Bye.