0:00 Hello, everybody. We're gonna get started in just a minute. Welcome in. Let us know where you're joining from in the chat. 0:08 As we go through today, feel free to drop your questions in as they come to you. We'll be answering those throughout the session, and we'll have a little bit of time for q and a at the end as well. 0:19 But we're so excited. I'm Joe Callahan. By way of introduction, I lead our product marketing organization here at Bazaarvoice. And I'm so happy. 0:28 We're gonna talk today about optimizing your digital shelf for AI shoppers, and really AI and shoppers, because we're gonna talk about how to balance the two. 0:37 And I think that this this to me is not only one of the most important topics that we're we're talking about in the industry right now. I it's one of the most exciting. 0:46 I am personally incredibly excited about what's happening, and we're watching everything so, so closely. But it also presents some challenges for brands. 0:55 And so what I what we wanna do today is really get through what's happening, what's shaping consumer behavior, and give you all a a blueprint to help crack this code so that you all are as brands and retailers are being surfaced by agents, AI agents, and shoppers. 1:13 I think it's really, really critical we start to talk about both of those together. Just just a quick story before we start because I'm thinking through think about the last time that you searched for a product or had a challenge. 1:25 I was thinking about this this morning. I went into chat GPT, and I don't know if any of you are are plant lovers. I've I certainly don't have a green thumb, but I certainly do really enjoy having plants in my house. 1:38 And so I have plants. My family would argue that I don't have a green thumb. So one of my challenges is that some of the leaves were starting to turn yellow and brown at the end. 1:47 I knew what species plant I had. I knew that I was having a problem. I didn't know what was wrong. And so I went to ChatGPT, typed in the problems that, you know, I'm I'm having a challenge. 1:57 Here's the here's the species of plant, and and here's what's happening. I didn't go in with a with a product question. I didn't go in with, you know, any any information. 2:07 It was a query around a challenge I was having. And what what the engine started to do immediately was start to diagnose the issue and then and then recommend products. 2:16 And so found out I was overwatering, of course. I can't go in easy on anything. And then recommended watering globes to help give me the peace of mind that I'm not gonna overwater and that the plant is gonna get the the the water as it needs it. 2:28 So what was really interesting to me is how all of that came together based on a challenge that I had in this conversation, conversational query that I posed, and how product recommendations came to me and something I may not have even thought about. 2:40 I discovered something something new. And so we look at this consumer behavior. Think about the last time you searched for a product here. Are you using same methodology? 2:52 And what we're seeing in the industry is that consumers certainly are. And when you do search, are you digging through pages of blue links, or do you glance at a AI generated summary at the top to get exactly what you need? 3:04 And so if you're leaning toward that sort of AI summary answer, you're part of a massive shift that we're seeing in the industry. We know that nearly sixty percent of searches now result in zero click. 3:16 And if you think about that, that's not just a change in technology. It's a change in expectation, and it's a change in consumer behavior. And then here's here's the deal, though. 3:25 It's not really about optimizing for AI as a technical tax. Optimizing for AI also helps you optimize the consumer experience as well. 3:37 And so when you structure your data for LLMs and when you structure your data for the model, you're simultaneously building a better product filter, clearer descriptions for your shoppers as well. 3:47 And so when you win the algorithm, you're actually winning the human as well. And I think that when we talk about optimizing for AI shopping, it's also thinking through how we optimize for the human shopper as well and balancing the two. 3:59 And so we'll talk about that today. I think the one question before we really dive in here, the one question we can we just continue to ask ourselves, as brands, as retailers, as we start to see this shift in the industry is how do you stay discoverable? 4:16 How do you stay relevant in this era where AI is rewriting the rules of consumer behavior? And so we'll talk through a lot of what we're seeing in terms of the AI driven commerce shifts, what why it matters to your business right now, and really how you can get started and think through all of the elements that you need to stay discoverable and relevant in this space. 4:39 So let's dive in. We're gonna do a quick history lesson, and I love this because if you've been in this industry long enough, you have seen a ton of shifts. 4:47 So think back for a moment. The shelf has changed many, many times. First, we saw brick and mortar world expand into online storefronts. 4:56 Different shelf, new shelf, expanded shelf. And then with with social media, you know, when when social first came around and we started we started seeing shifts as we've transformed from these intent based searchers into inspiration driven browsers. 5:13 And so think about the way that you've discovered products within the social space recently within your own behavior as well. And as all this is happening, and if you've and if you if you remember maybe, like, you know, ten, twelve years ago, the desktop experience all of a sudden shrunk into our pockets. 5:31 And so mobile first was born. We started to see user behavior and even, like, media inventory started to overweight on on device. 5:39 And so mobile first was born. So different shelf, smaller shelf, physically smaller. And then today, we're entering another evolution. 5:47 There have been so many evolutions in between. You've seen changes in search, retail media, all of these pieces. But today, we're entering this evolution that I think is just massively changing our industry in a way that we probably haven't seen in decades. 6:03 It's not just about changing the interface. This isn't about real estate. This is about upending the very nature of discovery, and that's what makes it so exciting. 6:12 So the who is discovering your products is actually changing, but the how you win them is simpler than you think. I know some of it can feel a bit daunting when these massive shifts take hold, but I I actually have a a ton of optimism around this space, and I'm sue I'm very excited about what's happening. 6:31 And we used to talk about this as the future state, but if we look at some of the data coming out of IAB, for example, we know that nearly forty percent of US shoppers are already using AI to shop. 6:42 And if you look at this last holiday season alone, AI was said to influence over two hundred and sixty billion dollars in commerce. 6:50 Those are incredible statistics. And I think with that opportunity comes a challenge. So not only are we rewriting discovery, these models are becoming drivers of discovery, but they're also becoming gatekeepers in a way. 7:03 Because when you surface a handful of brands, if you're surfacing three to five brands, if your brand isn't surfaced in those results, you're effectively being you're effectively invisible in the search. 7:14 And so I think we really have to ask ourselves again, how do we stay discoverable? How do we stay relevant in this environment? And this old model that we've we've played for for so many years as marketers with high baseline brand awareness, media spend were enough to keep you visible, it's no longer the case in in many ways and especially within within this environment. 7:38 And so we think through what are the things that matter. It's trusted content. It's reviews. It's other UGC. Those are the currency that are being valued within the models. 7:48 And so we'll talk about how how that plays a role in a really big way. And AI shopping is really a culmination of three phases of evolution, and all of these are happening simultaneously. 7:58 So we've already talked a little bit about AI summaries. You know, you've seen Google AI overviews are appearing in in twenty five percent of searches generally, and then for, like, forty percent if you have more high research categories like science or health. 8:13 We already talked about sixty percent of total searches are now zero click results. So consumers are not scrolling. They're click they're not clicking through. 8:22 They're reading the AI summary, and they're making decisions. Is your brand surface there? How is it being surfaced? These are all the questions that are that are starting to arise. 8:33 And so the second piece of this is really around AI assistance and that you see retailers like Walmart, Home Depot, Target. They're deploying AI assistance within their app environment. 8:44 And with this move, they're really moving toward more conversational commerce. And so these assistants are acting less like a filter within the app environment than acting more like a knowledgeable store associate. 8:56 They're they know about the product. They've read the reviews. They know what the consumer sentiment is around a product, and they can make those recommendations from a highly intelligent lens. 9:08 And that's really important. Forty eight percent of shoppers say those are going to improve their experience, and seventy five percent of retailers are are saying that AI agents are essential in twenty twenty six. 9:19 So these two elements plus this third one of agentic commerce, which is really what we're starting to see with ChatGPT in app shopping. 9:28 Last month, the announcement from Google at NRF around the universal commerce protocol in native checkout for Gemini. All of these means that all of these all of these announcements, all of these shifts in the in in the technology means that shoppers are now able to discover, compare, buy across retailers within the experience. 9:50 And they never have to they never have to leave the site. And so what's becoming really, really interesting is you're seeing all of this culminate into this to this AI shopping opportunity for consumers. 10:02 And it's really where AI stops just assisting humans and starts buying on behalf of them. And so what we're gonna start to see is not only this collapse of discovery, consideration, now conversion. 10:14 All of these pieces are happening with it can can happen within the within the agent. And so all of these are happening now. It's important to talk about each of them, but we will get into more around how you can optimize and think through your operating model so you're optimized against against this new environment. 10:31 And so I think I'm gonna start with a a quick poll here. I'm curious where we land. How have you all interacted with AI agents for shopping in recent history? 10:42 Are you personally using an AI tool to shop for products in the last ninety days and recent history? We've talked a little bit about my experience with my plants and trying not to kill them. 10:52 I'd love to to hear from you all. I'm gonna stop sharing for a minute. We'll get those poll, those poll results up on screen. Alright. Great. 11:01 Really nice really nice results. We're seeing nice overwhelming response on the yes, a few a few noes. And, honestly, if you've done a if you've done a Google search recently and used the AI summary that appears at the top, that's a that's an AI assisted search. 11:15 And so really, really interesting to see the results here as well. Alright. I'm gonna get back into it here. 11:24 I wanna dive a little bit more into the technology that we're seeing. Let me just get back to where we were and start to demystify some of the elements on the back end here so that you guys have a clearer picture on what's happening and then how to win. 11:41 In terms of the technology itself, I like a I like a very, very simple analogy. And so we're gonna think of the AI crawlers as harvesters and the LLMs as chefs. 11:54 So the AI crawlers go out into the field. They go out to the web. They harvest and gather all of the raw ingredients. So wheat, vegetables, spices, those are your product pages, your reviews, your q and a, your website, third party. 12:08 They are they are going out, and they are finding everything that they can about your brands, about your products, about your retailer. LLMs are the chefs. 12:18 So they're going to take all of these raw ingredients. They're going to understand how they work best together. You're not going to be eating raw flour or a handful of salt. Of course, if I cook, you probably will be. 12:28 But they're going take all of these amazing raw ingredients and prepare a finished meal. That's the coherent answer. That's the response to the query, the response to the challenge. 12:38 Remember my plant example. They're going to come back, and they're going to say, hey, listen. I think this is what's happening, and here's how I'd recommend a solution. 12:46 And so that's going be tailored to your specific taste. They're going to digest this data and turn it into answers. And so that's Chek Chi P T. It's Gemini. It's Perplexity. 12:55 These are the chefs. They're the ones making the meal. They're making the answer. Here's the part that should get your attention. And this is this is where the challenge lies, but it's also where I am most excited. 13:07 If your content is thin, if you have sparse reviews, if you have unverified claims, if you don't have contextual details, you're So this is more than a technical problem. 13:18 If you're not landing brand attributes with depth to give the models more to work with, you have to give them more to consider and surface product recommendations. 13:29 You might be invisible in the search. Remember we talked about this handful of brands that's gonna be surfaced in the results. It's really important that AI has the information it needs to have the confidence to recommend you. 13:41 And that impact to discovery is ultimately an impact to revenue. But when you feed it rich, verified, contextual consumer content, the LLM is gonna reward you with visibility and recommendations. 13:56 This is really a supply chain. You control the inputs. You influence the outputs. So it's really, really important to have all of that rich data and information about your about your brand, about your products, about your retailer. 14:09 So in terms of execution, we like to think of this through our triple a framework. This is what we call the triple a framework. 14:18 It's through authentic, trusted content and lots of it. That's what you need. Simple as that. Brands and retailers are gonna stay relevant in this space. 14:29 Remember we asked, how do you say discoverable? How do you stay relevant? Content needs to be accessible. It needs to be authentic, and it needs to be abundant. 14:37 And it needs to be the content that models trust. So put simply, what's being weighted in the models, ratings, reviews, other user generated content. 14:49 And so your content must be accessible so the machine can read it. That's the first piece. It has to be authentic so the machine can trust it, and it must be abundant enough to give confidence for the recommendation. 15:02 So this is the new mantra. We're gonna talk about the three of these in detail. Get all three of them right. It's gonna put your brand and your retailer in a strong position to be discovered, but let's let's dive deeper into each one of these. 15:14 And I think by the end of this, you should be able to guess which which a is my favorite. The first a is accessible. So your content has to be visible and structured so crawlers can find and read it. 15:27 Remember, if the crawler cannot harvest the content, the LLM cannot prepare the meal. Remember, our harvester and our chefs. 15:35 And if the harve and if the if if the chef's not preparing the meal, the shopper's not gonna see it. Right? This is the discover this is the discovery issue. So a few things that that from Bazaarvoice perspective that we're doing to help with accessibility. 15:49 One, Google syndication. Syndicating to Google means your reviews flow daily into Google's shopping graph. That's a big one. 15:57 The second is around retail syndication. So if you look at our network, our retail syndication network is massive. When reviews are distributed across thousands of retailer sites, it means more touch points and more AI discovery opportunities. 16:11 That's the scale, the reach piece. Gives AI more to work with. And then AI review summaries. So these LLMs absolutely loved chunked detailed content, especially summaries that can distill hundreds of reviews into clean, scannable insights to save processing time. 16:27 That's another one. And then q and a context. So this is where things get really interesting and really exciting. Traditional search was four words. Four words. 16:37 LLM queries are forty words with context. So does this run true to size? Is this good for sensitive skin? These contextual answers match long tail queries. 16:49 This is getting a little bit deeper into how we need to show up as brands, And that context is the currency. So remember we talked about not having thin or sparse content. 16:59 The LLMs really, really appreciate this this depth and this contextual relevance. And these tools don't just help AI find you. 17:09 They help humans find you faster too. And so this better structured content means better product filters for shoppers, and summaries help them to decide faster. 17:19 So more on this in a minute, but as you remember, we're talking about AI and shoppers. How do you win both? How do you think about both? This is really important. 17:27 The second a, as we're going through here, is authentic. Why does AI care about authenticity? This is such an interesting question, especially in the age of AI and the way that content is being generated and what is being prioritized. 17:46 AI is going to prioritize authentic, genuine content that comes from humans because AI is inherently trying to act human, and it's gonna value the things that humans value. 17:58 And that is the trust and the recommendations of other humans. And so it wants to avoid hallucinations to fill data gaps. 18:08 It's trying to look for these trust signals. So it's trying to look for context, and it's trying to look for context from trusted sources, and those are other humans. 18:16 And if you look at a lot of the major AI models like like Google, for example, they're looking for technical optimization of content that follows the model with experience, expertise, authority, trust. 18:28 These are all the things that they're gonna value. And so when you think about indicators like verified badges and our intelligent trust mark, these may play a role here. 18:37 They're gonna act like green lights for algorithms. They're gonna tell AI the data's reliable. Our fraud detection tools are monitoring for harmful content, protecting brand integrity, and ensuring that the review is authentic and human. 18:51 All of these pieces are so critical, and here's the reality. This is the differentiator. We have to differentiate ourselves from some AI posing as UGC. 19:00 We have to we have to differentiate ourselves from fraud and inauthentic content. And so the source of this data is real people. 19:08 Human networks networks creating authentic UGC, and we're leveraging human authenticity to feed the machine. And so that's the competitive advantage. 19:16 It's our competitive advantage. It's now your competitive advantage. And, again, it helps humans too. When shoppers see verified badges, they convert faster. 19:26 Trust drives both AI preferences and the human conversion element. And so there are so many things that play here. Again, win AI, win the shopper. 19:37 Alright. We're gonna roll into one more poll before we dive into the third a. I wanna set the stage for context. 19:48 Before like, when we're thinking about the opportunity to provide context for your brand within this space, which elements of your brand DNA play a role in providing that valuable context? 19:59 Is it brand equity? Is it unique brand attributes? Are they brand differentiators? Or is it all of the above? I'll stop sharing, and we'll get into that we'll get into that poll. 20:07 Alright. Let's see if these answers are rolling in. Yes. All of the above. Nicely done. Really nicely done. 20:16 Let me roll back to where I was. Alright. Yeah. You're right. It's all of the above. And I'm so happy you guys nailed that because this is what gets me most excited about the space. 20:27 I think that in the in the industry, we've moved away to, you know, very fast turn performance metrics and in a in a a lot of ways, very quick turn signals. 20:41 And I feel like at the expense of brand equity, landing those brand attributes, those differentiators, and really talking about who you are and what you stand for as a brand, that's gonna be so, so important in this environment. 20:53 And so that's what gets me very excited about the shift. Alright. So let's talk about this third a. This is around abundance. So abundant means value. 21:04 AI needs the volume and depth to build recommendation com confidence and add value to your product. So having five glowing reviews is not gonna be enough. 21:16 You need a large volume of detailed contextual reviews that give AI the confidence to recommend you over your competitors. And the reality is AI isn't just looking at your website. 21:27 So, you know, we've talked a little bit about the different sources, the different ways that a like, the the crawlers are harvesting information. You need this large volume that sits not only within your owned properties, but also within third party properties as well. 21:43 It's not just looking at your website. According to Mackenzie, in many categories, over sixty five percent of the sources AI uses to build answers are user generated content and third party sites. 21:55 They're not your brand website. So brand website plays a role, but other sites play a role, and user generated content plays a massive role. So if your brand isn't generating a high volume of social proof, you're running the risk of being invisible to the algorithms that are now curating the modern consumer shortlist. 22:11 And research from Columbia and Yale, you guys may have seen this study, it's confirming this new reality. This is fascinating. AI agents are prioritizing products with high ratings and high review volumes even more aggressively than humans do. 22:25 So the study found that simply doubling the number of reviews, I think it was going from a hundred to two hundred at the time, a brand could increase price by seventeen to thirty seven percent and still maintain its status as top recommendation. 22:37 If you think about how sensitive consumers are to price and you think about the weight now that ratings and reviews are holding within the recommendation engine here, this is incredible. 22:50 And so when we think about this ladders back into what we were talking about earlier around AI trusting other humans. It's trusting the recommendations. 22:59 It's trusting review content, and it's trusting star rating and the review volume to help provide the weight for its recommendation. 23:09 And that's that's really incredible. So it's a quality and quantity of review content. And if your social proof isn't landing context and brand attributes, you're less likely to surface. 23:18 So remember, we're talking about volume, but we're also talking about quality. So what is the depth like? So you have more reviews, and that's gonna provide natural language data points for AI to parse. 23:29 And it's really about allowing the agent to match specific user needs. So is it natural ingredients? Is it best for small apartments? Is it going to help my my plants from not dying because I'm overwatering? 23:40 Is this a good product to help give me the peace of mind? It's really landing those product strengths, those attributes within this content that are gonna help drive drive the engine. 23:52 And so let's talk about how we execute this. What does it look like when we stop optimizing just for keywords and we start optimizing for context? 24:02 So I had a former mentor, a boss and and mentor who used to say, if content is king, content plus context is king Kong. 24:11 That stuck with me. I think that's an amazing it it works in media. It works across search. It works across the AI environment. Context is absolutely critical. 24:22 And so when we think about having clear, concise, relevant content, this is easier for the system the AI the AI engines to source when answering a specific query. 24:33 So if you think about how users are searching, help me find a gift for my sister who likes running and lives in a rainy tropical environment. 24:41 Right? AI is not looking for running shoes. It's looking for context, details like water resistant, like running shoes, comfortable, etcetera. 24:52 It is it's looking for something that's gonna help it construct an answer within the context of the query. And so to do that, it needs to source specific detail from your content It needs to find and cite structured concepts like water resistant, breathable, good for humidity. 25:10 And within your reviews, if that content doesn't exist, if you don't have other consumers talking about how these things are good for these scenarios, it's not gonna surface, and it's gonna move on. 25:21 And so this is where we can start to pull in things like our AI content coach that can help guide real reviewers, authentic reviewers to leave specific rich feedback about the product. 25:36 Doesn't sway sentiment. It it puts things into more of a contextual lens so that the the review content becomes much more detailed and helps AI and shoppers. 25:49 So these are things that we can start to look at. And when you look at doing sampling programs, connecting your products with engaged consumers to collect these quality reviewers, that's gonna drive scale. 25:59 So there are a number of ways that we can help start to lift and shift all of the the perception, add the context, add these deep layers, and help AI understand who your brand is, what it stands for, what are the product's unique attributes, why does it make sense in this particular query, why should you be surfaced as number one. 26:18 And then one more example before we wrap up too. Imagine this. A shopper tells their AI agent, I need to restock my pantry with healthy snacks for my kids, some protein bars for myself. 26:31 AI remembers past purchases, knows dietary restrictions, checks reviews, compares prices, places the order in a future state, all without the shopper ever visiting a website. 26:47 And I think what's incredible and we talk so much about the collapse of the funnel here and how you can go from just discovering a brand and driving conversion very, very quickly, almost as if consideration was cut out. 27:02 And I think about it too, but the reality is consideration still exists. All of that research evaluation, is a product right for me? It exists. 27:10 It just changed hands. It just exists within the AI environment. The the a the the models are helping you do that help do that for you. 27:21 And so I think what's really incredible here is that as we are moving rapidly from AI systems that help answer questions to more of an agentic AI, an AI shopping environment that performs tasks, we really have to win the AI agentic commerce environment by doing three things. 27:45 And that's one, being discoverable by AI. So your content has to be accessible. We talked about that first a. Has to be accessible across all crawler types of platforms. 27:55 Needs to be trustworthy. Your reviews must be verified, authentic, credible, so AI feels confident recommending you. 28:03 And then you need to be preferred. You need the volume, the ratings, the contextual richness that makes AI choose you over competitors. It needs that confidence to know that you're the right brand, product, etcetera, that's gonna provide the solution to the query. 28:20 And so I know we've covered a lot today. I wanna bring it home with what you can do right now. The first thing is audit your AI visibility. 28:29 Now there are tools out there, but the easiest thing to do, go to Gemini, go to ChatGPT, search for your products, use natural language queries. 28:38 Help me find the best x product category for x specific use case. Ask it a question like I did with my with my plant situation. 28:47 See if your brand shows up. See what AI says about you, or see who's winning the recommendations. That's where you start. 28:56 Really activate your AAA features. That's the second that's the second piece here. If you're already a Bazaarvoice client, you likely have access to the tools like Google syndication, AI review summaries, content coach, and the intelligent trust mark. 29:11 If you're not using them, we can activate them. If you're not a client yet, you can reach out and let us know about how you'd like to get there. And then the third is really scaling authentic content. 29:23 So launch a sampling campaign to build that review volume. We know that review volume matters. Do it for your hero products. Do it for new product launches. 29:33 Implement review request emails for recent purchaser purchasers. Turn on q and a to capture those contextual details. 29:42 That's an amazing place to start to land those brand attributes that we talked about being so critical for context. 29:51 And make abundance your competitive advantage. Land this everywhere. Consistency is key, and it's absolutely critical. Alright. So let's recap. 30:02 AI generative AI has already been shaping what consumers see, believe, and buy. It's here. We know it's here. We're using it. 30:11 The consumer all of our consumers are using it, and it's really critical that we we understand the different components that are leading to this type of behavior. 30:20 The brands that adapt to this shift very early by building trust, relevance, and authenticity in content foundation are gonna win this this next era of digital commerce. 30:32 This is a defining moment for our industry. Shoppers are already embracing it and remember the mechanics. Second piece, crawlers need ingredients to harvest. 30:44 So we talked about, you know, the analogy of the harvest the crawlers harvesting and the LLMs making this amazing meal. 30:52 If your content isn't visible, it's not on the menu. If it can't be found, it can't be made into the answer. If it's thin, if it's, you know, if it's sparse, if you don't have verified content that the engine's gonna trust, you're handing that that that small shelf space, that handful of brands that's being recommended in the results to your competitors. 31:16 And then finally, the AAA framework. That's how you make the content more nutrient rich. It's how you add the depth and the content the context for the algorithm. 31:27 That better data structure helps everyone find what they need faster. And so I hope this was useful. I'll do a couple of questions. 31:36 Thank you again for the time today. I wanna open it up and see what what what's on your mind, what what you guys have going on too. 31:47 Let me just get into that. And let us know what you thought about today's session too. If there are things that you want us to dive into deeper in the future you know, I will dive into context all day. 31:58 I absolutely love this third a. If you didn't guess, that's my favorite. I feel like we have this incredible moment in the industry where driving equity and landing our unique brand attributes. 32:09 And that context of why our brand matters and who we are has resurfaced. And I'm so excited about that opportunity. 32:17 It's back to the the magic of magic of marketing, and I just I'm I'm just absolutely thrilled that that we have this opportunity as marketers. 32:26 I got a question around The biggest mistake we're seeing with brands trying to optimize AI on their own. What what I'll say, and I said it in the beginning, was really around assuming that the old rules of play still exist. 32:42 So thinking that optimization for SEO is gonna win in GEO, it's it plays a role. 32:50 But there are there are other things that we need to consider here. And the second piece is really around as brands and and retailers, we've, you know, we've been trained over the last couple of decades that high baseline awareness, media spend, all of these elements are guaranteed to get us surfaced in some kind of result or visibility or increase our share of voice in the market. 33:17 I think what's fascinating to me and the more I work with brands and and some of the biggest brands, you know, the some of the biggest brands in the world is that because the engines are valuing this authentic human voice and who is best at landing brand attributes and who they are, what they stand for, why their product is best for something. 33:43 What's happening is I'm is I'm doing, you know, searches or identifying gaps on brands' behalf is that smaller brands attacker brands, challenger brands brands that normally wouldn't have been in the competitive set are surfacing in results because they're very, very good at landing these things. 34:01 And so I think that I spent much of my career at a very large enterprise house of brands. And the competitors that we looked at may not be the competitors we should be looking at today. 34:16 You know, we should be considering some of these smaller challenger brands who are doing a very, very nice job surfacing in results. And I think that's a really incredible moment on this for this industry. 34:28 And then, you know, again, I talked about the the funnel collapse, and everybody, you know, is is really talking about this collapse of the funnel and the the removal of, like, consideration within within the funnel. 34:39 And the reality is I strongly believe it's just changed hands. Having those contextual elements, understanding how people are are searching for your brand, your category, your products, the queries that they're asking, and making sure that you have the answer structured and in many, many places consistently is gonna be absolutely key. 35:00 And so these are the things that I start to think through because that consideration element is still happening. It's just happening with within the AI models. 35:09 And so it's smarter. It's very, very good at research, and we absolutely still have to show up as brands in every moment that matters for us as brands. 35:19 And so that's what that's that's the shift that I'm most interested in here as well. Alright. Any other questions? 35:28 Somebody's asking about search engines hold AI search engines hold heavier weight to reviews for brand hierarchy and AI overviews. Yep. That's right. Same principles apply. 35:38 The engines are absolutely prioritizing review content, not only star rating as we as we discussed. So it's the the quantity of reviews. 35:48 It's the quality of reviews. Star rating itself plays a really big role and then the depth of the review. So adding those contextual layers. 35:56 And I think what's what's really fascinating here as well as we talked a little bit about depth and context, it's easy to brief for a brand asset. 36:06 It's easy to brief a creative creative agency and say, hey. Listen. We need to land these brand attributes. Go. I can brief that. I can evaluate that. That's very clear. 36:15 Within review content, that's a challenge. You wanna make sure that a reviewer stays authentic, still lands all of those amazing brand attributes and differentiators that you've worked so hard to land in all of your outgoing messaging. 36:30 And when I look at some of the tools that we have at our disposal with content coach and helping helping, create the opportunity to nudge in different topics. 36:45 It talk about flavor, talk about taste, talk about texture. Anything that is relevant that is going to help drive those deeper, richer reviews, that's an amazing opportunity. 36:55 And it's an amazing opportunity to have this content work as hard as all of the content within your suite. 37:03 So I find this an amazing opportunity for brands. From a from a reviews perspective, these are, like these are these are these are really hardworking assets in this environment. 37:16 Alright. I think we've answered a lot of these questions. I think if there's anything else let's see. Make sure I didn't miss anybody. Alright. That looks great. Well, listen. 37:26 If you guys have any other questions, always feel free to reach out. And we will we will also try to get to anything we missed within the chat, within the q and a. 37:36 I really hope this was useful. I am really excited about this opportunity. I'm excited about this space. More than happy to dive into any of these elements deeper. 37:46 Let us know in your feedback if you want to hear more about a certain topic. We are we are absolutely here to help you navigate this industry shift. 37:57 Again, one of the biggest ones in in decades that I've seen since I've been in the industry and and absolutely fascinating. Thank you all so, so much for joining, and we hope to see you on the next one as well. 38:08 Thanks again.
