Adobe Digital Insights: GenAI Traffic Update Q2 2026

Transcript

Oh, sorry, Vivek, I think you might have to share your screen again. Okay.

Before I let people in.

I can, I had it up just a second ago.

That’s there. And then I will share the screen that should be up coming now. There it is. Is that sharing okay now? I’ll do it to full screen once we get into the session. Thank you.

Okay.

Okay. Am I good to let people in? Yep.

Cool.

Hi, everyone. We’ll be starting in just a couple minutes here. We’ll let a few more people file in and then we’ll be starting with a presentation.

Giving it just one more minute.

And to some of the new people who joined, we’re just going to get started in just the next minute or two here.

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So everyone files in.

We’ll get started. So I’ll load up the screen.

Hi, everyone. Hope you’re all doing well. My name is Vivek Pandya and I’m the director of Adobe Digital Insights. And my team runs both our Digital Economy Index, our holiday report, and many of our generative AI trends. And we’re really looking forward to getting into some of the insights we’re seeing so far, what we’re anticipating for the rest of the first half of the year. And we’ll have a lot to cover. But before we get into that, I also wanted to introduce our co-host. So Marta, do you want to also introduce yourself? Sure. Hi, everyone. Thank you for joining us, Marta Fertini. I lead industry strategy globally for retail at Adobe. I’ve been in retail 20 years myself prior to joining Adobe and work across our retail accounts on their digital transformation strategies.

Awesome.

And go ahead, Marla. Oh, no, I was just going to say I’m Marla Mims. I’m going to be facilitating at the end some of the question and answer portion of this webinar, which you all are. We’re pleased to see you here at this Adobe Digital Insights Gen AI traffic update where we will be covering not just the AI traffic update. There will also be some Q2 retail guidance from Vivek and Marta who will incorporate information and insights on what this means for retailers like yourself. Throughout any questions that you have, please use the Q&A box to enter those questions, because at the end, we will have some time to facilitate a bit of Q&A, go through those questions and make sure we get you what you’re looking for. With that, Vivek, I’ll turn it back over to you. Thanks so much, Marla. And yes, we’re so glad so many of you are kind of joining us to get into these insights. If you’re on this call, you’re one of the first to see many of the insights we’re going to be sharing today, especially in terms of our Q2 guidance in the first half of the year performance. But for those of you who don’t know how we develop our insights, we look across over a trillion visits through the Adobe Analytics platform, and we’re able to then leverage that data to get a really dynamic view of the digital economy and see what sort of trends are impacting it, be it buyer journeys, generative AI, being able to understand how consumers are shifting based on various price sensitivity factors and how that looks across categories. So a lot of big implications here. It’s a very powerful data set that underpicks everything you’re seeing. A lot of the data you’re going to be we’re going to be walking through is going to be from this data set. So real data, dynamic view data of actual transactions, actual visits. So pretty powerful stuff.

We have a lot of trends to get into today. We’ll be diving right in, but we’re going to be looking at what we’re anticipating for the rest of the quarter, the first half of the year overall. We’ll be talking about generative AI and where we are with the trends that we’re seeing there and also touch on marketing channels and the broader strength we’re seeing, especially for certain categories.

Shift right over here. So when we look at where we are here in terms of what we’re anticipating for Q2, so especially looking at from April to June, we’re anticipating about $301.4 billion to be spent. And that will account for about 11.9% year on year growth. Now, many of you may be thinking, okay, well, what is inflation’s impact here? Because we do see online inflation appearing not as strongly as we’ve seen it in other sectors of the economy, but we do see online inflation kind of in the 2 to 3% range currently. And so when we think about real growth, that’s likely to fall into that 8 to 9% range. But again, a good amount of volume happening online and a decent clip of growth even when you account for inflation. So there is definitely a clear sign that consumers are leaning on the broader online sector and digital economy to manage costs, to see more favorable pricing. And we see them absorbing a higher share of online than they have in previous years. So again, a lot of opportunity there for e-commerce players. And one of the reasons we’re anticipating this growth to be so substantial is because the Prime Day event has been moved into June. So previously Prime Day would fall in mid-July during the summer. We saw it a little earlier in July last year. And we’ve seen it go into becoming a four-day event instead of a two-day event. And that has big ramifications for how we think of almost summer sales moments, back-to-school shopping, the motivating factors, the eventized shopping that can get consumers to spend given the broader economic headwinds they’re facing. So the fact that we see this Prime event moving into June, we see strong growth for it when we compare Prime performance year on year. And obviously, if you look at purely June strength, when you have a Prime event now encompassed within it, we’re anticipating about 23% year on year growth there. So that’s pretty staggering in terms of the step change June’s going to experience this year. And the opportunity many retailers have to provide really strong promotional discounts to take advantage of that higher buying propensity that consumers will be capitalizing on given the Prime Day event opportunity. So that’s what’s informing a lot of our guidance in terms of Q2.

The other key piece here, and we’ll talk more about Prime events, but what we’ve been seeing across categories and what we’re anticipating going forward. So when you have that type of motion, those types of sell events that try to get consumers buying beyond the essential goods, that benefits overall non-essential categories, the durable categories as well. So apparel, 10.2% growth, electronics, 11.8%, furniture, 9.9%. These are quite accelerated levels of growth that these categories are not usually expected to see around this period. But because we have, again, the Prime event that will power a lot of June gains that will help these categories overall. These categories also see a bit of inflation. Electronics used to see a lot of deflation online, year-on-year price decreases. But due to chip shortages, demand for computers and the pricing and what we’ve been seeing in terms of the global supply chain, we’re seeing electronic prices up about 2 to 3% year-on-year. And that’s different than what we’ve seen in previous years when electronic prices were down about 4 to 5% year-on-year. You do have some inflation powering that growth, but there’s still a lot of significant overall growth, real growth happening within those individual categories. So a big opportunity there. Cosmetics has done pretty well even in Q1, especially with the sales events, Valentine’s Day, real heavy utilization across that period. And so we anticipate that to amplify further going into Q2. And grocery has been a consistent performer. Again, grocery had the highest online inflation about a year ago. We still see grocery prices ticking up about 1 to 2%. But a lot of that 12% growth shown there is really indicative of consumers leaning into the efficiency of online grocery, the convenience, the ease. And the latitude online grocery gives them to maybe find better pricing for different types of essentials.

Now, when we think about that trajectory again, we started off the year pretty slow. We had quite the holiday hangover. You see categories like apparel, electronics down about 2 to 3%. As I said, online prices were about 2%. So that’s about flat for apparel and electronics and home and furniture, toys and very, very mild growth for cosmetics and sporting goods there. So it was pretty challenging in January. And when we got into February, we saw a bit more momentum get unlocked because you had a little bit more excitement around the Super Bowl. We’ve seen the potency of events like Valentine’s Day. We’ve just had Mother’s Day. Consumers kind of pulling back on non-essentials and really leaning in on them when the event comes around to maximize that experience of a really great Valentine’s Day event. Or something like that that holds together as an experience, which is an area of the economy that’s seeing a lot of growth and, you know, making sure they get what they need for those events and those moments. So eventizing the sales has also been important. Cosmetics has done a good job driving some great promotional sales in Q1. And we anticipate that momentum, that growth that they unlocked in Q1 to persist into Q2. And I’ve just been saying the E word quite a lot here. Events, events, events, events. And so what we were seeing was the spring sales really kicking off. Many, many retailers took advantage of Easter sales. And as a result, that helped shake off some of that price sensitivity on the part of the consumers where they were, you know, they were a little more willing to take part in some of these sales moments. And spend a little more freely, especially online. But that it took those sales events, the spring sales, the eventized sales in order to generate some momentum there.

And when we look at the boost that we saw, as you can imagine, flowers, jewelry, greeting cards, fragrances, all doing quite well for Valentine’s Day. And then for Super Bowl, really stocking up on the chicken wings, the chips and dips. It really is indicative of the amplification that these events can drive because you essentially go from a goods based purchase that’s now powering an event based experience. So tying the purchasing of goods to really profound experiences is key, especially when we think about the sort of trillion dollar experience economy unlock that’s happening right now.

And we’ll circle back on Prime Day here and give a breakdown. As I said, we anticipate it being a four day event. This could be subject to change. But for the time being, this is the trajectory we would see it landing. Stronger powering spend levels on those first two days, a bit milder on the back two days. But given the level of June Prime event activity, this will be pretty powerful in terms of its contract detail space, not just for Amazon driving it, but many of the retailers taking advantage of the stronger buying propensity here. And in terms of discounts, there’ll be discounts, as you can imagine, that will be fairly competitive with where they were last year. We don’t see them being much stronger than they were last year, which, you know, as I said, the online economy historically for the past five to 10 years has been characterized as being deflationary and offering consumers year on year price decreases, especially when we had more and more retailers entering the online space, both domestically and globally. It gave consumers a lot of value. So now we’re in a position, especially with where we are post tariffs, where we are in terms of the world events, that there are limitations around how much more favorable the discounts can get. We’ll see the implications here for the Prime event and where these land and what that means for the holiday season in the back half of the year and how responsive consumers can be at these sorts of promotional levels. So as you can see, apparel pretty strong in the 20s in terms of 20 percent average discounts, weaker on the computers level, where computers, the discounts are only mildly better.

It’s going to be important for computers to be able to unlock more value and more innovation so that consumers are more willing to spend at these more elevated prices.

Again, the top performing categories, as you can imagine, travel experiences will power luggage and travel goods, kids apparel.

What we still bank on is consumers using this as a back to school shopping motion, just as they did in July. It’ll be a little earlier in June having to think about back to school. But again, the nature of prices right now will prompt consumers to try to get some of that early back to school shopping done in that June Prime event. So kids apparel will be surging refrigerators and freezers for college, college, back to school. That will all be influencing some of the product category trends we’re seeing here. Few other trends we want to highlight, because mobile is now at 56.4 percent share.

It’s not breaking news that people are spending on mobile devices, but we do want to really reassert that mobile conversion rates still lack a lag laptop desktop conversion rates. So improving those, you know, ensuring that they’re scaling at a time where this mobile velocity continues to ramp up. There’s still a lot of upside. You know, we have parts of the world where mobile share is 60, 70 percent or sometimes, you know, you think about India, China, places like that, it can get even higher. So there’s upside here of mobile adoption and importance for retailers to compete heavily on a mobile vector.

And mobile spend will get to about 58.2 billion by June.

So you really see that scaling happening with the Prime event. So making sure the mobile experience is aligning well and activated well on mobile surfaces, updating your consumers through text notifications, through app updates, that these sales are coming, especially to coincide with Prime will be key. The other couple of areas that we watch out for is Buy Now Pay Later. Buy Now Pay Later had strong, strong growth over the past few years. It’s now oscillating at about 4.7 percent, still growing and still pretty significant.

Where we were in March, it was up at, you know, 8.3 billion. We’re anticipating about 21.1 billion full on from Q1 means that we’ll see, you know, continued momentum in Q2 for Buy Now Pay Later. So it’ll still be differentiated. But you do have more credit instruments coming onto the scene that are also gaining a lot of popularity and consumers are leaning on credit cards pretty heavily in this environment. And then the forecast for Buy Now Pay Later lands it such that we’re anticipating the first half will be between 43 to 43.4 billion dollars, which will amount to about three to five percent year on year growth. So still over indexing in terms of overall credit instruments that are out there. But it’s important to think about Buy Now Pay Later as a space that’s kind of in a place that’s where you have the consumer base that’s using it. But it’s not as accelerated as it was when it was first coming onto the scene in 2023, 2024, where we had double digit growth for Buy Now Pay Later.

And with that, I’ll kind of hand it over to Marta to kind of get a bit into the implications there. Yeah, thank you Vivek. Great stats as usual. And I’m so excited to see your team help all of us forecast what’s ahead of us. So you touched on a lot of these. I think the three things that really stand out to me that I want to make sure everyone is aware of and pays attention to what we had into Prime Day. And how do you manage through heavily promotional periods and events like that? First of all, I think you said it right in the market in general price sensitivity will remain persistent. And this is true for events and not events. So it goes without saying, ensuring you have competitive pricing. But I think what we are seeing more and more is also retailers really trying to target their offers and be more mindful on who sees what. Because obviously, it’s also a very margin challenge, margin compressed environment, right? So you do want those promotional hooks to drive your customers in, but you want to be mindful on who actually takes advantage of what. And then we are really seeing consumers value, looking at value beyond just discount and pricing, right? Is this the right value for what I get? So the seamless experience, being able to find a product you’re looking for, delivery and logistics, in-store inventory, all of that is just as important. The second thing I always think about when we think about events is the relevancy, right? We all in retail have our journeys running, campaigns running, etc. But when you think about an event and a customer behavior around that, people actually start to browse and build their wishlist and see what’s out there, often way before the event, right? So you want to look at your triggers, you want to look at your journeys and optimize around that timeframe. On one hand, you want to be obviously as real-time as possible, but on the other hand, you want to extend look-back windows of your browser and about non-card campaigns, as an example, to make sure that you are capturing the people who were kind of like building up their wishlist.

And the other thing is making sure that as much as possible, those journeys are very personalized, that if they were looking at specific products and categories, those are pulled into your campaigns and journeys, and the message is really personalized to what they were looking at, because we also see consumers browse across multiple sites and retailers during event times, right? And then the third aspect, which I really think is where retail is making the biggest strides and accelerating the most, is real-time.

We are really seeing more and more brands focus on experiences that capture the intent, are more predictive of what is the next best thing I should show you, and apply what used to be your traditional CRM tactics to anonymous shoppers as well. In a matter of couple of clicks, you can understand what a customer is shopping for, well beyond just product recommendation carousels. And so how do you think about adjusting the experience based on what the customer is shopping for in the moment? Not just in general, but even more so during events, because no matter how much you know about a consumer, what they are shopping for in that moment, in that promotional moment, may not always be what you know them for, right? Like I may always shop women, but during an event, I may be a lot more interested in stocking up on gifts or stuff for my kids or stuff that I need in the house. So you need to account for that and overwrite profile information or complement product information with real-time signals.

And then I wanted to take a quick look at what do we see happening in the industry more broadly, both on the consumer and the marketer side. And this is, I think, really helpful. At Adobe, we do a lot of research to complement what your team looks at from just a data and Adobe Insights perspective, right? So from a consumer perspective, we are really seeing that growth is being shaped by customer experiences. We all know that the bar of customer experience expectation is growing. Relevance is a baseline. The vast majority of consumers expect to easily find what they’re looking for and that retailers know what they’re looking for and personalize for them. So the attention is fragmented. We are seeing that over half of consumers only give promotional content about two to five seconds to actually capture their attention, right? So repetition, relevancy, again, super important. And then the importance of those moments and experiences is huge. In our consumer research, we see that it only takes just over two bad experiences for a consumer to leave a brand. It takes almost seven positive experiences to actually build that loyalty. So the importance of really maximizing and optimizing every moment and every touch point is huge. And yet only about 16 percent of experiences are deemed exceptional by the consumer, right? So there’s a big gap that I think companies are really working towards filling. And I think the big change we’re seeing is with AI, obviously, there’s a lot more momentum and a lot more intelligence coming into how we manage some of these experiences and campaigns.

So if you go to the next slide, we also talk to about 500 retail leaders globally about several topics. And I think I was mentioning AI before, and I think this year is probably the first year where we see this real momentum. I think when we always talk with executives, we actually saw a declining confidence in being able to actually meet customer expectations in the past few years. And that trend has reversed in the past year with what AI has unlocked and agentic capabilities for retailers in really being able to personalize and predict. We now see that that gap is closing. And we see that retailers once again feel that those breakthrough customer experiences are possible. And in particular, when we look at where are they looking at AI to help with some of that, these are a few areas. I think the first three are the more obvious ones, more personalized experiences that anticipate and respond to the need, the end-to-end journeys that better deal with identity resolution and consistency across digital and physical points, and then AI power recommendations and service that feels like human and closes that gap between the service you get in store and the experience you get on digital. The fourth one is kind of like a bit of a new frontier, and I think it really bridges with how consumers are also doing research, which you’re going to go into right after with AI traffic and tools. But it’s really that idea of AI power conversational experiences, not just on Chudgipity, but how do I bring some of that contextual conversational experience on my own property and website? And then by the same token, we see the role of marketing also change, right? So if we go to the next slide, these are some other stats and points that become clear from our research with leaders. As I said before, the industry is striving for profitable growth, right? So definitely a quest to increase sales and conversion while also increasing efficiencies. I think that one of the most interesting points for me that I hear over and over is how the role of marketing is expanding. We thought about how growth is driven by experiences, and marketing leaders more and more are expected to directly contribute to revenue, but even more interesting, they are less of just brand stewards and more and more owners of the end-to-end customer experience. So we are seeing our customers think about how do I organize about that? How do I boost cross-functional collaboration between my teams, etc.? And then AI, the buzzword, right? And I want to touch on it from both sides of the equation, the marketer side and the consumer side. On the marketer side, we are definitely seeing strong adoption and progress, but at the same time, ambition still is ahead of adoption. We saw before how 70 to 80% of retailers are investing in AI. They expect that AI will bring significant benefits, but we are also seeing that over half of the companies we talk to are kind of stuck in this pilot mode. Last year, they have driven a lot of new initiatives, a lot of power from AI, but it’s hard to move from pilot to scale. There’s still fragmented data and systems, there’s still a lack of measurement framework, and very often weak organizational alignment around that. So one start that stood out to me is that of about 100 AI use cases that teams bring to life and propose, only 15 see the light of day. And so I think it is really, really important that companies are intentional around aligning AI use cases to strategic priorities, ensuring that they do the not fancy work of preparing your data, your brand guidelines and all of that as they deploy AI and the measure results. And we are happy to partner on any of that and share more as follow-ups, of course. And then the real change is what goes through consumer adoption. Like the AI mediated consumer is absolutely here. Majority of consumers have now turned into AI tools to really help during their buying journey, particularly in that discovery phase that we see on Chajipty, Perplexity, et cetera. So I’m really excited to dive more into some of the stats you are seeing on your hand. I think that’s a great segue, Marta. I don’t think we can beat that segue. And I know many of you are curious to see what we’re seeing on the generative AI front. And we’ve been tracking this data for a couple of years now in terms of traffic coming from generative AI platforms to retail sites. And it’s continued to surge. We’re seeing that traffic up 393% year on year. And when we think about what happened in April where Chajipty started making all brand mentions linkable, it really lifted up that traffic. So the opportunity to kind of leverage and meet the consumer where they are, given that they’re using these generative AI platforms and about 40% of them are using it through some part of their buying journey. It’s very important to ensure that you have strong visibility across the platforms and that you’re ensuring that when consumers are in a space where they’re thinking about different use cases, different items they need, that you’re amongst the consideration set. So generative engine optimization is more important now than ever. And we are seeing, Marta was talking about measurement frameworks. That’s kind of what we do on our side. And we are very heartened to see that the conversion of traffic coming from generative AI platforms is now, that type of traffic is converting 42% better than non-AI sources. So non-AI source traffic at first was overperforming generative AI source traffic. Now that has flipped on its head a year on. So we’ve seen a huge amount of change in just the span of about a year. And when we look at our survey data, we see that consumers are saying they trust the generative AI results. They really feel like it’s helping them get what they need and it’s providing that ease. So it’s this adoption that’s scaling on the part of the consumer, the traffic that’s moving, generative AI introducing itself within the purchase decision-making process, and then the performance being even stronger once it hits your sites. That’s a really high value level of traffic that’s coming through. And when we look across multiple metrics, we see the same story. So revenue per visit, you can’t think of a more critical metric in the e-commerce space. And that is up 37% compared to where it was a year ago. So it’s very exciting to see this type of scaling happening where you have that non-AI source traffic continuing to make its gains incrementally, but now this AI source traffic is driving a 37% higher revenue per visit. So the stakes are pretty high in getting this type of user to come to your site versus going to someone else. So as I said, we looked at this across categories, we looked at it across products, and we see the adoption across many categories, and these many categories experiencing a boost. So 55% of consumers say they’re using generative AI for ideas and research and inspiration. So that benefits all these types of categories we’re talking about here, like apparel, sporting goods, electronics. You think about electronics and the complexity there about RAM and memory, it becomes important for that to be synthesized for the user so that they know what they should buy. And we’re seeing again, strong AI referral growth as early as March for cosmetics, for luggage, home decor. And so when we have the events, we also see the uptick happening. So be it Super Bowl or where we were with President’s Day sales, Memorial Day sales that we have coming up. It’s consumers jumping onto the generative AI platforms and saying, where can I get what I want? Where are the cheapest prices? And really leaning on them for different use cases.

And when we think about what the implications could be there before we get into marketing channels, we’re seeing people use them for financial services, for travel. We’re seeing them really think about it in terms of how they can orchestrate multiple events, multiple motions, all in kind of one workflow essentially. So what do I need? Where can I buy these goods for this type of event? All of that’s getting answered by the generative AI platform. And we find that brands that are being cited well across things like Reddit, YouTube, social media platforms, listicles, top 10 lists, all that is helping these brands get that visibility. The other piece of this, and I’ll just go back over here for a second, is about a third of content on your websites, on retail sites is not machine readable. A lot of this content and site development happened in a pre-AI era. So it’s important to lean on LLMO optimizer tools to understand how you can improve your machine readability across your site. In fact, a bit of homework. If you go to the Google Chrome store and look up Adobe LLMO tool or LLMO visibility tool, Adobe, you’ll find a free plug in there that you can install on Google Chrome and you can get readability scores across your pages, across your sites. It’s hugely valuable. And we do see certain retailers who are doing a really good job in terms of machine readability and many that are kind of lagging. So you essentially have an opportunity here, much like you did when SEO was a big deal 20 years ago, when social platforms came onto the scene 10 years ago. So really take advantage to meet this sort of GEO LLMO opportunity and you will see some really strong upside.

And we do want to continue to emphasize some of these strong marketing channels that we’re seeing continued growth on, that we’re expecting to see continued dominance. Paid search has been quite strong. Affiliates, especially social media influencers are driving revenue share. We do see natural organic search seeing a bit of growth, but that’s not as strong as it’s been in the past. And the opportunity of that growth by marketing channel is actually kind of down for organic search and it’s up for social networks and it’s up for affiliate partners. So while some of these shares are kind of holding on a little bit, the overall growth now is concentrated on things like social networks. Affiliate partners are much more what we define as social influencers now. And I know many of you brands have been investing across your social influencer base and you should be seeing some pretty good upside there. We’re seeing on our side that social media affiliates are able to drive a 12x higher conversion rate than regular traffic coming from social channels. So it’s absolutely important to engage these social media influencers, the micro influencers, because they’re trusted by their audience base. So especially when you have these big sales events, maybe bespoke sales events, making sure all those promotions are feeding through those influencers to ensure that your audiences see that. They see maybe promo codes, additional discounts, and that will be incentive enough for them to say, OK, I want to buy at this very moment. Really drive that impulse shopping because seeing a 12x higher conversion rate is a big lift and it’s really indicative of how consumers are discovering products, i.e. through social media influencers, trusting them through things like reviews, the validation there, and then those promo codes, those little perks that help get them over the edge and help them buying through those influencers. So we continue to assert the big opportunity and upside here.

The other key area that we do keep an eye on still is buy online, pick up in store. And what we’re seeing is that is still holding at about 15.8% and essentially order share. And it’s primarily driven by grocery now. That category had strong momentum through COVID and it’s holding where we are now. So ensuring that you’re supporting BOPAS, especially for grocery retailer, is still worthwhile. And thinking about ways to further differentiate in this environment where maybe there are higher costs at a shipping level, maybe there are higher costs at a product level. BOPAS can still be favorable in that type of motion. So that’s BOPAS right there. And now I’ll hand it over to Marta to get into the implications.

Thank you, Vivek. And you shared some of the amazing numbers in terms of growth and conversion. I think the other thing that our team’s collective track that I think is quite interesting is how our consumers from their perspective using AI and generative AI tools for shopping. And I think what’s interesting is like that first start of research, which is a very like top of the funnel type of behavior, it used to be north of 70% just a year ago. And I think that ties really well to what you were saying about conversion and revenue per visit. When we look back one year to 18 months, we see that that traffic was not high intent. It was people who were experimenting with AI and curious about how do these new platforms work. Today, we see a much more even distribution between top of the funnel, mid funnel and lower funnel and very high value, high intent. So how consumers use AI today is yes, it’s still top of the funnel research and initial ideation. A lot of product recommendations, whether that’s what is the best type of running shoes for a beginner or whether that’s comparing two specific products and brands to each other. They’re definitely using it for finding deals. Again, it could be who has the best price on a specific product I have in mind, but also more generally. And as we head into things like Prime Day and Memorial Day, who has the best offers on Memorial Day, who has the best Prime Day promotions, etc. And then ideating for lists, whether it’s gifts for others or shopping lists for themselves. We are seeing a very intent driven type of shopping, like what do I need for a themed birthday party or what do I wear for a wedding? As we look at the world of GEO, you don’t just control what GEO shows through your own website. You were talking about social before. So if we click to the next slide, it’s really this idea that LLMs decide what to really show based on your site. And maybe more importantly, based on what others say about you, whether that’s our media, whether that’s PR, whether that’s social content. So what you were talking about before we optimizing social media influencers and some of those sources for commerce and shopping specifically, the same is true in terms of how those then in turn influence LLM results. So definitely pay a lot of attention there. And then when we look at what does it take to win in this environment? Let’s go to the next one. And we really think about what does an end to end GEO framework looks like. And it’s not just GEO, it’s GEO and SEO. And I’m sure many people on the call have heard about a couple of weeks ago, the Adobe acquisition of SEMrush was finalized. And we’re really excited to bring SEMrush into the family. And it makes these extremely powerful. And when we think about GEO end to end, what do you really need? First of all, do you need to have that intelligence on the traffic itself? It’s not easy to track AI driven traffic all the time. Different tools and different platforms behave in different ways. So you don’t need estimated model traffic, you need actual data and tools that can capture and quantify that traffic.

And then you need the intelligence. So it’s not just about am I visible and how visible I am. But it’s like, what are the recommendations behind me? What is my share of voice compared to others? How do I compare to competitors, etc. So a lot of the things that were done in the traditional SEO world are still true in a GEO world. And then you need optimization. And optimization is different, right? We talked about how important third parties are and what people say about you. And we always had backlinks and those concepts. But it is so, so important in the GEO space. And it’s optimization that is both technical. It’s about content. It’s about social presence. It’s about earned authority, etc. And then you need the closed loop measurement. So you want to use tools that actually allow you not just to optimize, but to also quantify what those optimizations are worth. How is referral traffic moving? How is conversion changing? How is revenue changing based on the optimizations you’re doing? And we are doing this with our retail customers who are piloting or using LLM Optimizer with us today. So we do see some of those results and learnings that I’m going to go through next.

So we see real lift in visibility and real lift in citations. And part of this is this is not something that you can solve by just throwing human capital at GEO. You need the tools to also support, as I was saying, the measurement, the optimization, the quantification. The other aspect I think is so interesting what you were mentioning before about this is still a not so crowded space. Right. There’s a lot of even very big retail brands that have not done the optimization work. So if you are in that universe, there is a huge opportunity because the growth and the visibility when you do do the work pays multiplier and dividends back. Because, again, there’s still a lot of people out there that are not doing the work. And then if I go through some of the learnings in the next page is what we hear from a lot of the customers we work with on optimization is a few things. First of all, you’re moving from traffic to trust. Right. So you’re not just measuring how many times do I show up in an LLM world.

How the LLM represents you is just as important. Is chat GPT talking about my brand positively or negatively? Am I actually being understood and represented correctly and appropriately? Or do I need work to actually change and influence what the narrative is about my brand and what the understanding is? From keyword to prompt is the other big change. Right. It’s really understanding in an LLM world and in an AI based world, what are your customers looking for and how are they searching? And what do you want to stand for as a brand? What do you want to be found for as a brand? Those kind of like extended queries, like question based queries, intent based queries are really important to track and understand. And then from pages to system. These, I think, in retail is maybe more critical than in other industries. You talked about how so much of the content is still not readable. So first of all, it needs to be readable. But then we are an industry that is so brand proud and brand aware. And it is really important to understand that you will continue to build beautiful product pages and beautiful websites for the human user. That will not go away. But you are now serving a dual audience. So you also need to make sure that your content is machine readable, your product metadata schema, everything is set up correctly for LLM to be able to understand and retrieve. And also that you are feeding your product information directly to the LLM to be able to show up there because they may not always be landing on your site to crawl it. You also want to make sure you’re building and setting up feeds into the LLM themselves.

So last, we wanted to leave you with a few resources.

Vivek mentioned before the plug in for the readability score. So we will share the deck as a follow up. You can definitely at that link find the plug in itself if you didn’t find it in the Chrome store already. We have some information about the Adobe and SEMrush partnership and what you can really get out of that as we supercharge our own capabilities. And then please do feel free to connect with Vivek or myself or your customer success manager, your Adobe team. If you want to at any point go deeper into any of the data, the research, what we are seeing in the industry and even possibly get data on your own brand.

So well said, Marta. And yeah, I would I’d say the other capability we drive as a team is these benchmarking reports, and they really allow you to see how you’re performing on conversion rate, bounce rate, many of these key metrics in your industry. How do you do relative to your competitor peer set? And it can be super valuable because then you’re not looking at any of these metrics in a vacuum, but understanding how you’re scaling them relative to your broader industry. So thank you all for being with us today. I know we packed a lot of these insights in. We spanned everything from the opportunity to retail, generative AI trends, what Marta was able to get into the broader strategy and the implications there. And so we hope you got a lot of value from this session and we will be sending a recording. You’ll get these slides. As Marta said, don’t hesitate to reach out and we’ll leave it there. Thank you all for joining us. Oh, Vivek, wait. Oh, sorry. Did I miss questions? We did have, we had one in the Q&A. Good. Thanks. Thanks, Marta. No problem. Are there pages that are better to optimize for LLM readability than others? For example, should the homepage be more readable than a product detail page? Do they carry different weights? It’s a great question. And again, I’m glad you cut me off before I signed off there. But yes, I would say that home pages are important in terms of how quickly you can pass out the information. But I would say FAQ pages. We’ve seen a lot of importance there given by the LLM’s help pages, because that allows you to essentially put the content down in a very structured kind of bulleted, pointed way, clear headings. So I think you can use the homepage to drive some of that domain authority back to the LLM’s. But the LLM’s are just as fast kind of working through some of your FAQ pages and some of your dense pages that answer questions. So the generative AI platform and the LLM bots are looking to really tap into understanding the answers to these users’ questions. And that can be trickier to do on a homepage when you’re trying to showcase the brand a certain way, position. So you can get some of that information on the homepage, but you are in a strong position if you leverage your help, your FAQ pages, and some of your other product pages to really get into that detail so that an LLM can do their sort of comparisons and provide the user with the guidance they’re looking for.

Yeah, I completely agree on that. And I think the other thing I would say is when I think about product pages and category pages, obviously it’s impossible to optimize all of your pages at once, right? So a couple of things I think that are what we see when we work with brands is there are structural optimizations that you have to think about. For example, how you’re surfacing reviews, how are you surfacing like size charts, how are you surfacing some of the product specs, etc. There might be technical aspects behind it that are an easy change that updates across the board. And then the other dimension to that is what are your hero products and categories you really want to stand for? And that’s really where you should focus some of the optimization. The other thing I would say, which I think ties to what Vivek, you were saying for FAQs, is what do you stand for as a brand? I think brands have content pages that have very often been deprioritized historically. We work with a brand, for example, that is extremely sustainable, stands for sustainability, yet they were not showing up in any query related to sustainability because the content wasn’t readable and wasn’t like LLM optimized.

And so those are some of the things that used to be, unfortunately, often on the retail sites because we had to have them, but we were paying a lot more attention to merchandise hierarchy and shoppable pages. And I think that’s changing in the LLM world. But again, because you cannot optimize the world at the same time, what are you standing for as a brand? And make sure that that is clearly communicated and readable.

That’s great. Awesome. Thanks. Any other questions, Marla? No, that was the only question that we had today. It was a very good one. Thank you, Megan.

Awesome. Well, then I think we’ll sign off for real this time. Thanks again for everyone who joined us. And don’t hesitate to reach out and we’ll leave it there.

Thank you all.

Thank you. Bye.