0:19 Hello, and thank you guys all for joining today's personalized webinar on how contextualization is transforming online shopping. We're thrilled to be speaking with you today, but before we get in, I'd like to do a quick introduction. 0:31 My name is Christine Lee, and I'm the vice president of our global retail team here atazar Voice. And today, we're really gonna be covering how we can make sure the contextualization continues to transform that online shopping experience. 0:43 We get started in the content, I wanna do a couple of housekeeping items. We'll be doing a couple of full questions as well as wanting to make sure that you know how to actively engage with that Q and A functionality. 0:53 So throughout the presentation, if you have any questions for us, please make sure to log them there. And Jeff and I will be able to answer them. And with that, I'd love to introduce you to my today, Jeff Lawrence, who is the founder and previous CEO of Granify, and who is now the, excuse me, vice president, a product at the czar Voice. 1:11 Everyone. Excellent. To kick off our session today, I wanna throw it out to you all. 1:20 What are the biggest challenges that you're seeing in creating a personalized e commerce experience? We're gonna have a poll that's gonna be shown here in a moment. 1:29 I would love to hear kind of like what that is for you all. And then while we're doing that, there's a lot of challenges we've heard anecdotally from our customers and from some of the people in the industry that we've heard on kind of what that seems to be for them, whether that be kind of how to create those experiences, whether that be content, not to give you guys the answers to the questions or also just data and regulatory concerns are also extremely difficult. 1:56 And if we have a good amount of poll answers, let's go ahead and push those answers. Alright. It seems like those are gonna be more popular. 2:04 Hope, we have some limited internal school resources. Awesome. We'll have a couple of these more, votes coming through and we would wanna make sure that this really informs the questions that you're asking us going forward and hopefully how we can continue to help you to understand how contextualization can be a really good gap to fill with personalization. 2:27 And what I just wanna share is that you're not alone in some of the challenges that you're facing. So according to research that we've done in partnership with WBR, we see that eighty seven percent of e commerce retailers are saying that their current personalization system cannot accumulate intelligence over time to provide those personalized experiences they're wanting. 2:46 Similarly, eighty three percent of e commerce retailers are considering AI limitation for contextualized experience as a significant challenge. 2:54 And only twenty four percent of e commerce retailers currently employ AI driven contextualization technology So there's a huge opportunity. And that's really where we enter. 3:05 And we're thrilled to announce that the contextualization solution granted by is now bizarre voice contextual commerce. But instead of just hearing about it from me, Jeff, I'd love to ask you a little bit more about what inspired you to start Granify and how did it ultimately develop into what it is today? 3:25 Yeah. It's an interesting story, and as I mentioned, I founded Granify in in two thousand eleven, up till that point, I had spent my entire professional career, which was about thirteen years at that point. 3:37 Really just working with data and finding ways to turn data from something that's, you know, not worth something just data. Into something that has a lot of value. 3:45 So that was across, you know, capital markets, advertising technology, social gaming. And I knew I wanted to do that. That was my and so I was, you know, figuring out what I wanted to do next. 3:57 I was, you know, looking into all sorts of things and really had an a moment around AB testing. So AB testing at that time was really, becoming a standard and adding a lot of value. 4:08 And I started really but dissecting and thinking more about what that actually meant and how it worked and what that how that impacted consumer experiences. And My sort of aha moment at that point was when I thought about the simplest a b test of, you know, a red button versus a blue button on the site, And if we think about how that works, you know, let's say that the blue button, sixty percent of people like, and the the the red button, forty percent of people prefer, with AB testing, you'd test it out and you'd go, okay. 4:37 Well, the blue button's better. Let's now show the blue button on our site, and you'd have some incremental lift versus if you'd shown the red button. But if you if you dive a little bit deeper into that, the reality is you're giving an optimal experience to the sixty percent of people that prefer the blue button, and you're giving a suboptimal experience to the forty people that actually prefer the red button, then you're now gonna see the blue button. 4:58 So even though you know, an incremental improvement, you're actually giving yourself optimal experience to a huge portion of users. And so I really thought you know, what if we could use data to ultimately figure out who should see that red button, who should see the blue button and give everyone an optimal experience? 5:14 So it was kind of the the the stub of an idea at that point. And, obviously, over the last, I guess, thirteen years now, we've taken that thesis and really you know, still still aiming at the same thing and going, let's use all this data, this stream of data, and be able to optimize an experience to give everyone what they want. 5:33 And that obviously translates into value to retailers, values, value to shoppers in terms of the experience and You know, it's been a it's been a great journey so far. 5:44 Well, we think so too. I'm so, pleased to hear that though, because one of the things that's so core to Bizarro is ethos is we are really passionate about creating radically transparent shopping experiences and ultimately excellent shopping experiences for the end consumer. 5:58 And so I love the the application of how you can think about a the red versus blue on making sure that every shopper has that opportunity. This can be great for them. 6:08 But in that, like, Jeff, I'd love to understand a little bit more practically, like, in a few sentences, can you help us understand how Granify helps or non contextual commerce helps clients achieve that success? 6:20 Yeah. It's really working with them. You know, we go on the website. Sort of embed ourselves. And ultimately, what we're doing is pulling in all of that information about, you know, what a shopper is doing with their objective. 6:33 And then how do we dynamically optimize that experience? And we'll show some examples a little bit later on, but, really, what we're aiming at is are there little micro opportunities to increase the chance of someone converting on a site? 6:44 And by taking advantage of those, you know, able to increase conversion rate, reduce card abandonment, you know, increase repeat visits and and really look at, optimizing and enhance seeing the expected value of of every single shopper that visits one of our customer's websites. 7:03 That's awesome. Well, with that, I guess let's get into the meat of it. Those on the phone might be asking, okay, but what exactly does contextualization mean? 7:13 And what we see is that contextualization is just the next evolutionary step in personalization. And it's the ability to use machine learning to analyze that shopper digital body language, to be able to tailor a shopping experience to them without the use of third party cookies or personally identifiable information. 7:30 So let's explore a couple other of the differences. So personalizations, I'm sure a lot of you guys are familiar with, is what many companies are relying on today for those dynamic user experiences. 7:41 It has a manual set up of shopper segments and tags and potential triggers, It also has groups of people who have to take a specific action or have a specific characteristic to be able to, put them into a cohort for personalization. 7:55 And also, and lastly, it relies on PII, which really only works for customers that you already know, those known shoppers that are coming to your site. 8:03 Whereas the inverse on contextualization works for both known and unknown shoppers, which is a true differentiator. So instead of focusing on who you are, contextualization is focusing on the behaviors that you're taking that indicate what state of the shopper journey that you're in. 8:19 And what mission you're ultimately on. And so the engine can identify when a user is ready to purchase or leave the website and then The way it does that is by looking how a person searches for products, analyzes the behaviors as they scroll through a product page, and understand the way that they interact or potentially don't interact with content to be able to ultimately understand and anticipate shoppers' needs, which will then provide whichever engagement method will be the most impactful, whether it be recommending product information, recommendations, providing a social proof message, keep shoppers engaged and to be able to address their concerns and desires. 8:57 So let's take a quick look about if I were a shopper coming to a site that I'd been to before. I might be coming to a site. I'm a return visitor, but I wanna see what's new for me. 9:07 So I go ahead and click And on this site, I scroll down. I see some cute items, but then I'm given a module where I see, some recommendations on some new items based on my fit and style. 9:19 Based on my previous browsing behavior. And when I see here, I see this like FlexPant and floral crop top, which looks cute based on what I'm searching for and what I want. 9:29 So I go ahead and click into that. And when I click into that, I start to go into research mode. So I'm deciding what I need to have to make a decision. But at this point, I might be hiring and humming about, like, it's Q Top, but it's early in the spring. 9:41 Do I need it? Then I'm given this visual prompt. This slider that pops out and shows me that this is the lowest price that this item has been in the last thirty days. And because I'm a very savvy shopper, I'm like, well, a good deal. 9:52 I absolutely need that, and I go ahead and click to add it to my cart. And when I do that, it helps to make sure that I'm getting that nudge to get over that in and out mode of whether or not me as a user would have chosen to add to cart and complete my purchase versus actually a band aiming site. 10:09 And each of these examples that we have are designed to delight different types of shoppers depending on their intent. And so there's a couple of different use that Jeff would love it if you could speak to them, and kind of talk through what they look like. 10:24 Yeah. Absolutely. So the The first category really is around surprising and delighting shoppers. There's a lot of these examples that we have. 10:33 It's really a lot of times it is using data that we have and and presenting it in a way that, you know, does actually just provide super value. And couple examples of these are if you're browsing a shot or a product, you know, you show high high engagement, high intent, and then you don't buy it during a session. 10:51 If you come back and it's dropped in price, we can let you know that proactively. So say, hey, this product that you, you know, previously viewed is now dropped in price. 11:00 So obviously is is a great one for shopper experience. Another one would be if a product has sold out in your size or or something that you looked at, and you know, you return to the site again and it's back in inventory, we can alert you to that. 11:13 So just really things that give you that, that moment of delight as a shopper. Then the second category is obviously right at the heart of what, you know, bizarre voice has has always done, which is the social proof and user generated content You know, one of the ways that we can really help together and one of the exciting things about, you know, this acquisition overall is we're able to amplify things. 11:36 And and one of the great things that we can amplify is the ratings and reviews and letting someone know that a product that they're viewing or having their cart is something that people rate really highly. 11:45 We can even amplify, you know, the the positive re reviews themselves. So, obviously, that's at the core of of online shopping in general. 11:54 Another great example of social proof is letting people know that a lot of people have viewed the product or have purchased the product, you know, just letting them know that that validation part of it as well. 12:06 And then the third one is driving urgency. So sometimes you just need that, you know, that nudge or that kick in the butt to to move across the finish line and, ways that we can do that is just emphasizing that a product a high sell up risk, you know, has low stock, you know, various other ways to to drive that, that urgency and get people over the finish line. 12:30 And then, you know, we have all these experiences, but really, the biggest thing with with contextual commerce is is knowing, again, what what to show to someone that moment to increase the probability that they'll convert. 12:45 So I'll walk through what we call the Granify brain, which I guess is now the, the cocoa or the kind of different brand. And so step one of that is, you know, once a shopper lands on a retailer's site, we're ingesting a massive amount of of information about that shopper, and it really starts with, high level kind of macro information that doesn't change during a session. 13:07 So that would be, you know, what what page of the shopper land on? What's the source of the traffic? What device are they on? What's the operating system? Sort of anything that we'd know as soon as the shopper lands and and follows them throughout that, that session. 13:20 And then we go into, micro behaviors, which is really what they're doing while they're navigating the site, and that can be page sequences, search terms, all the way down to the smallest most movement how someone's interacting with a product image or a product or, you know, their click stream. 13:37 So we're really tracking everything we can about a shopper to pick up digital clues are what we call digital, digital body language at Granify. And then we're pulling that into the Granify brain. 13:52 And with that, we're looking at at that information and that stream of information and data compared to everyone else that we've seen. And at this point, we've optimized over twenty billion sessions. 14:03 And so we're really looking at commonalities around patterns of of that data to go. Is this person gonna buy? Are they not gonna buy? And if they're not gonna buy, is there some way that we may be able to to increase that probability that they will? 14:18 And so with that, every second, we're pulling back that information and the Granify Brain is making a decision on whether there is some opportunity to increase the probability of conversion. 14:29 So most times, the answer is no. If you show something or you change the experience, it's gonna create friction and friction reduces conversion rate. 14:38 So most of the time, the answer is just let the shopper keep going. But when there is a moment that the brain determines that it's mathematically optimal and it'll increase the chance of conversion, then we'll automatically step in and dynamically you know, optimize that experience and and provide information to the shopper that helps them, you know, feel better about the purchase and ultimately pull the trigger. 15:01 And then the real cool part is with every shopper that comes through, we have another data point. And so, you know, every time a shopper lands on the site goes through the experience and whether or not the interaction changes their behavior, that feeds the model. 15:14 So it gets smarter and smarter both you know, on your site and then across the overall network. So when we see a new customer come on right away, there's positive results. 15:23 And then over time, we see that trend trend up that we're getting we're delivering more and more incremental value over time. So really, really powerful. And then this is just a quick overview. 15:36 Granify's, implementation is already quite light. But if you're already a bizarre voice customer, then it gets even lighter. 15:44 Two pieces of the three that we require are already taken care of. So that's really, the JavaScript snippet and then having access to a product feed or product catalog of some sort. 15:54 So if you're a Starbucks customer, that's already taken care of. And then the last step really is just around validation of results. And so you would just need to accept events into your analytics providers that that's you know, Google or or Adobe or or really anyone. 16:09 And then you're able to ingest the information about, you know, who we're interacting with and the the overall session splits, which people are in the Granify group versus a control group, and that allows you to validate your results, which we always want our customers to do so they know that the incremental revenue that that, that we're driving is truly because of us. 16:29 Thanks, just so much for walking through that. I think that This really gives completely users on our webinar today an understanding that contextualization is really able to fill those gaps, especially with the unknown shoppers, on how they can continue to drive an optimal site experience. 16:44 But I just wanna reiterate that those traditional personalization needs are extremely reliant on these data segments that we're seeing like PII, name, age, etcetera. 16:54 But again, with contextualization, you don't need all of this information. But even if you do have this information about a shopper, it might not be relevant because what I was focused on yesterday and the shopping experience might not be what I'm focused on today. 17:07 Like, I could be shopping for my partner or loved one, or I could be just ultimately browsing today for a bigger purchase, maybe like furniture versus an impulse buy. 17:16 So I think that if you're already even having a robust personalization strategy, contextualization is still a really great way to augment for those unknown shoppers and potentially use cases that you're using today. 17:28 With that being said, let's talk a little bit about why you should choose bizarre voice contextual commerce specifically because we do have unique differentiators. And what we think sets us apart more so than anyone else is our service and ultimately our proven results. 17:43 So our team from an implementation and service perspective handles all of the heavy lifting. Consider us as service as a service with a little bit of machine learning learning magic on the side. 17:53 You don't need to have an entire personalization team to manage our performance. And our experts on the team are working so closely with our clients that we're basically considered an extension of our of our clients team, which we love. 18:05 And then from there, we are a fully pay for performance technology. We believe in this product so much that we only make money when you do. 18:16 We don't believe in grading our own homework. And we wanna make sure that the results that we're seeing are a hundred percent verifiable based on those technology integrations that Jeff shared. 18:26 We're gonna be integrating with those existing analytics providers that you're working with, and we're only going to be charging for the revenue that we can prove was generated by the contextual commerce solution. 18:37 And the results really do speak for itself. On average, we see eleven percent conversion uplift for new visitors. 18:45 We also see a forty one percent increase in the likelihood of a first time customer becoming a returning customer, which is huge. And There's a three month trial period for select customers where you can expect at least a two percent revenue uplift. 19:01 But as the brain continuously learns on your site, We can see that that uplift averages six point seven percent, but can grow to fifteen percent over time. 19:10 And so that's hidden revenue from shoppers that are already on your site that bizarre voice contextual converse can help unlock. And, Jeff, as we're preparing for today's conversation, you were telling me about accessory that we just absolutely had to share. 19:23 Do you mind walking us through that? Yeah. For sure. And, lot we have lots of success stories. This is one of my favorite ones. 19:33 So with this one, we started a a pilot for two months and it was with a global fashion retailer. We have a lot of brands. 19:41 We started off with two of them and the success criteria during the the the POC period or POC period, was two percent lift was what we're targeting. 19:49 So two percent lift on their overall online, revenue for the two brands. We hit that within two weeks. So a really good great start. 19:58 They were blown away. And during the six day period, we ended up getting over three point six percent, lift for those ones. They were again, they sort of mentioned to me that that was the best pilot that they'd seen during their their testing careers And from there, we expanded that to include all of their brands, which was over ten websites. 20:18 And now we also added recently their iOS app. And so, you know, starting off with that performance of the as I mentioned, the two percent, two weeks, three point six percent over sixty days, and then now through the relationship over three years, the revenue, per lift is, six point four four percent increase, and we've delivered over four hundred and seventy seven million of incremental revenue. 20:41 So just a fantastic win win for for for everyone involved and, you know, one of my favorite success stories. Absolutely. That's absolutely insane. 20:51 And then here's a fun quote that, you know, from from that brand, and emphasizes, obviously, what they've seen, but I think also really highlights the white glove service that we provide and how much our our customers value that and love that. 21:05 That's fantastic. Okay. So next, I'd love to share a quick demo from one of our team members, Trey, to get a better sense of contextual commerce can look like in more of a real life scenario and inaction. 21:18 So I've resolved was our contextual commerce solution formerly known as Granify takes a unique approach to helping retailers solve this challenge. 21:27 For one, we're using shopper's real time behavior data rather than personal or PII data. To power these experiences that we deliver to your shoppers, this enables us to create tailored experience to both anonymous and known users while not having to worry about data and privacy regulations. 21:46 Secondly, We've leveraged AI and machine learning to ingest and analyze millions of data points to identify when and when not to engage with shoppers This allows us to deliver the right experience at the right moment in order to maximize the conversion opportunity that each shopping session brings to your site. 22:06 Lastly, we're pairing our technology with white glove service to each of our clients. This includes dedicated experts focused on creating a strategy that's catered to your business and creative and development resources that are responsible for executing on that strategy. 22:25 Now that we've provided the context in contextual commerce, let's get to the fun part. For this demo, we're going to walk through a sample site together, imitating a standard shopping journey. 22:39 So you all can see the various ways we have at our disposal to engage with shoppers at various points during that shopping session. 22:48 As we look at the home page here, of our site. Normal shopping experience indicates that, you know, the the shop or journey will begin landing on the homepage and trying to spot something that generates interest. 23:02 As we do that, Contential Congress has the ability to hop in at this ideal moment. Here, showing this jump back in module to our shopper. 23:14 Now quickly, let's talk about why this particular module might show up. As a shopper comes to the site, and we see them navigating down the homepage more and more. 23:26 That could indicate to us that they're not finding something that they're explicitly interested in. They're showing us by their behavior that they haven't found something that they're interested in. 23:37 So because of that hesitation, Let's personalize the homepage with a module to help guide that product discovery process. 23:46 Let's help move that shopper down the phone from product discovery to interests. And by leveraging information that we might have about them. 23:58 In this case, we're looking at somebody who's probably a returning user that we have previous purchase data on previous data about their interest. 24:09 We can curate products that we feel they might be interested in. Now as we hop back into our shopping session, let's say this pink turtleneck sweater really is something I'm interested in. 24:23 As I land on the page, you'll see that we have this social proof messaging that appears upon landing above the product title. 24:31 This one's highlighting the fact that fifty five shoppers had purchased this product today. Reason we weren't showing this is to validate the interest of shoppers had made them feel good about the fact that, hey, not only did I find this, but a lot of people are finding this and are really showing interest. 24:48 And so in a lot of cases, This can be a good way again to validate that interest and move that shopper down the phone within that session. 25:00 Now it's important to note that we aren't showing this on all product detail pages across all products. Our technology, again, allows us to understand when it makes sense to show messages like this. 25:12 So we're not overusing them. We are pinpointing the exact time this makes sense. Now, a typical shopping session might have this user shopper looking at product images, reading the product description, getting a better feel for this product. 25:30 Ultimately, we're gonna say for this use case that added the item to their cart indicating to us that they have explicit interest in that product. 25:39 However, we're not gonna quite check out yet. We're gonna continue browsing through the site and try to see if something else sparks our interest. 25:49 Based on that behavior, contextual commerce can indicate again, there might be an opportunity for us to help with the shopping session and allow this user to find or enable this user to find what they're looking for. 26:05 In this case, We have our currently trending module, which will highlight popular products in key markets, especially when we're talking about fashion, And as I click on the different areas or metros, you'll see those product results will actually update really fun and engaging way for a shopper to, again, find something that sparks their interest. 26:31 For the sake of this experience, we're actually gonna not click on a product here, but let's say those results actually piqued my interest in a particular type of product. 26:41 And so we're gonna search for specifically sweaters. Now as we search for that on site. We land on the search results page here, and we'll begin looking at those search results. 26:54 Now, You can see that once again, we've identified a really good opportunity to engage with the shopper. Think it makes sense though to explain why here, why now. 27:07 So in this case, a user has given us explicit interest in that type of product, the category product, in this example, sweater. 27:16 So in order to help avoid something like analysis paralysis where we see maybe even hundreds of results from a given product especially if we're talking about a more broad search term like sweaters. 27:30 Let's help guide them down the funnel, help them find what they're looking for. So by prioritizing the key search terms that they've entered and leveraging shopper data that we have across to site. 27:47 We can highlight the products that are most popular that have been purchased the most frequent based on that specific search term. 27:56 This is a really good way. Again, to use social proofing, right? Different than maybe what we think about with social proofing, but this in fact is leveraging social proofing by highlighting that, hey, people who have looks for his letters frequently purchased these products. 28:15 Now, this shopping journey, we're gonna say this yellow fuzzy sweater in the middle of that module really piques our interest. As we get here to the product detail page, we can find another fun way that we can engage with shoppers to, again, validate the interest in that product. 28:34 This time, instead of showing an inline social proof messaging, we see that we have an overlay badge on the product image. 28:42 Now this is different from a lot of overlay badges you've probably seen because it really only expands when the user hot or hovers over that product image that we have data that shows us that we've tested various ways of showing different messaging like this, and our data shows that this is a really effective way of engaging with the shopper. 29:04 For one, it's not intrusive by hiding product imagery, which you've undoubtedly spent and invested a lot of money in. 29:12 But it also piques the interest of the shopper by seeing that icon and then watching the message expand over the image is a really just fun and engaging way to capture the attention of a shopper. 29:24 And again, not be overly intrusive. So in this case, we're gonna continue the shopping journey by adding this particular product to the car. 29:34 We really like it, but we're going to continue browsing once again. This time, we're going to look at the outerwear category under width. 29:47 So as we land on the category or product listing page and start reviewing the results. We get down rows and rows. And after enough time, the contextual commiss brain indicates that this is a good time or there could be a good time for us to step in and engage with the shopper. 30:06 Now let's talk about why this particular placement, which is a slider and a messaging. So for starters, we've we already know that this shopper has multiple items in the cart. 30:18 They've shown us explicit interest in those products. Right? Now, If delayed by browsing and browsing and getting sidetracked from those products, we could lose out the opportunity in this session to convert the shopper. 30:34 Not only that, but we might understand that there's time sensitive information about these products that they showed interest that we might wanna highlight to the shopper. 30:44 It could be pricing related. In this case, it's more inventory related. And so what we're able to do, again, all in real time is understand how much inventory is available for the products in the car. 30:57 In this case, we're looking at the pink turtleneck sweater. Have we seen that the purchase trends on the site this particular product tell us that this could sell off sooner. 31:09 So let's make that aware to the shopper because last thing we want them to do is miss out on a product that they have indicated to us they have interest in purchasing. 31:18 So by bringing this type of police and a message to their attention, we can make sure that they are in fact converting within within this session and they don't miss out on the opportunity to buy this sweater. 31:35 You can see that we clicked on the continue checkout call to action, which navigates us to the cart page. And then pawn landing on the car page, we see this great message at the top in our billboard placement indicating that you're saving forty two dollars by purchasing these products today. 31:52 Obviously, that's something that's gonna resonate with almost all shoppers and makes you feel good because you you feel like you're getting a deal. You are getting a deal by purchasing these products today. 32:02 Now, that messaging, if a sale or price savings, cost savings is not relevant to this particular session. 32:11 Could read something like nice, fine. This is gonna look great on you. Think about, you know, the parallel of shopping in store and having the cash, your compliment, the order, the purchase, the products that you have, and you're you're purchasing at that moment, is it going to change your mind? 32:29 Maybe not, but it's gonna make you feel good about that purchase. It builds up that engagement between brand and consumer. And again, just makes them feel good about this purchase that they're making with you today. 32:41 Awesome, Troy. Thank you so much for sharing that demo. I wanna thank everyone for joining us on this webinar today. Jeff and I have time for any questions from the audience, and we'll go ahead and open it to Q and A from you all. 32:56 As we're waiting for some questions come through. If you do have any follow-up questions from today's materials, please reach out to your Starbucks account director or client success manager, or you can feel free to reach out directly to me. 33:09 I believe that I had my contact information in the invite. But really wanna make sure that if there's questions that you have, we can make sure to answer them. 33:18 One question that we did see is How do we make sure that contextualization messages align with each brand? And, Jeff, this is one that comes up quite a bit, I think, because you wanna sure that the experience of all these opportunities to contextualize the site is really on message. 33:35 And so I can take a first stab, but then we'd love to hear from your perspective as well. But one of the things that I know we do is that we're looking to see what is the current brand examples and brand look and feel. 33:46 And then anything that we're doing from the new placements or campaigns. So it would be running and getting approval from the brand to make sure that it's on on target for what they are trying to accomplish and really is looking to be an extension of their existing experience versus, kind of abstraction her off off brand so to speak. 34:03 The job, is there anything else that you would wanna add there? I think he covered it. You know, we take their brand guidelines, and make sure that it's both in the look and feel, you know, fully within the the brand guidelines itself. 34:15 But also within the tone. And then there will be a final approval process for for everything before it goes live on-site. So, there's always that control. 34:23 Okay. That's awesome. And then we have one other question. It says, would the results continue to improve over time? 34:32 When they reach their full potential. Jeff, I think that one might be more for you around the brain. Yeah. For sure. So, right out of the gate, there's no cold start period. 34:42 We obviously have analyzed a lot of shoppers. So right out of the gate, you're gonna see good performance. And then as we learn the nuances of your site, We're gonna get better and better at, you know, being accurate with the the messages, the right moment, and lift will go up improvement. 34:59 And then from there, you know, we are always adding new capabilities, you know, through our r and d. And as we introduce new things, goes into the brain, and then we have another tool in the tool kit that ultimately continues to drive lift higher and higher over time. 35:12 Very good. It looks like we don't have any other questions. So I'll go ahead and wrap and say thanks to everyone who joined us. 35:21 I really appreciate the time, and we look forward to seeing how contextual commerce can continue to grow our retailer and brands businesses. Thank you so much. 35:30 And Jeff, thanks so much for co presenting with me today. It was a pleasure. Thank you. Thanks, everyone. Bye.
