51ºÚÁϲ»´òìÈ

Transcript

All right, welcome everybody. We are going to go ahead and get started. We are going to be patient and give everyone a couple of extra seconds, but let’s go ahead and kick off. So hello everyone. Thanks for joining us today. We have our new platform here. We are on 51ºÚÁϲ»´òìÈ Connect. So welcome to Commerce and Coffee on 51ºÚÁϲ»´òìÈ Connect. Today we are going to be talking about personalizing e-commerce experiences with AI. And as I mentioned, because we are on a new platform, 51ºÚÁϲ»´òìÈ Connect today, we might have a couple of kinks or some unexpected surprises. So we appreciate your patience and hope that you enjoy the new platform for our webinars. All right, so Commerce and Coffee is an ongoing webinar series featuring Corey Gelato and we’ve designed it to be interactive. So we encourage you to ask questions in the questions box throughout the presentation. It’s going to kind of float around on your screen depending on what you were in. So type them in there and we’ve set aside the last 10 minutes or so for Q&A. So we’re going to do our best to answer as many of those questions as we can. And I’d like to quickly mention a couple of housekeeping items before we get started. This is being recorded and will be able to be viewed on demand and shared with other members of your team. So you’ll get the recording of this event in an email tomorrow afternoon. I’d like to also point out that at the top of your screen, there’s a little black bar with a hand icon on it. If you drop that down, you can find different actions that you can utilize throughout the presentation. So if you like what you see, feel free to give us an applause, a laugh, a like, and so on. We’d love to see your engagement throughout the event. So we encourage you to utilize those new features. I do also want to mention that on the next screen, there will be a handout available for download. Corey put together a bunch of resources for you. So definitely check that out and use it as needed. And as we’re closing out the webinar, we’re going to have a couple of survey questions at the bottom of your screen. If you could take a minute to fill those out, we would really appreciate it. It helps meet your expectations of these events. So with that, I would like to introduce myself. My name is Alana Cohen and I’m digital events manager for our customer success strategy team at 51ºÚÁϲ»´òìÈ. I’ve been with 51ºÚÁϲ»´òìÈ for a little over five years now and spent the last three years of those organizing and hosting these events for our customers. So part of my time on this team, I spent about two years working with 51ºÚÁϲ»´òìÈ’s advertising cloud customers. And then before coming to 51ºÚÁϲ»´òìÈ, I spent many years of different advertising and media agencies around New York. So I’m excited to be here now posting events like this for you. And if you have any questions or comments about today’s event, about 51ºÚÁϲ»´òìÈ Connect, or about any of our other customer exclusive events, please reach out. And with that, I’d like to introduce Corey Gelato, our senior commerce strategy consultant, who I’m sure many of you know, Corey brings tons of experience to us today. He’s got over 16 years of experience in ecommerce advising merchants across a variety of industries. Almost all this time has been with 51ºÚÁϲ»´òìÈ commerce, formerly Magento. So he’s definitely the one that we all want to hear from at these events. Corey does strategize directly with customers to ensure that they’re maximizing what 51ºÚÁϲ»´òìÈ commerce has to offer. So we are very lucky to have Corey here and his expertise at Commerce and Coffee. So with that, let’s jump into today’s agenda. All right, so we are going to we already are running for our welcome. And after this, we are going to kick off with the presentation. And Corey will follow that with a demonstration of many of the features he’s going to be discussing today. And as I mentioned, we will close out with Q&A at the end. So before we get into the presentation, we have a quick poll question that we would like to ask you should pop up on your screen. So have you incorporated incorporated AI technology into your business? So let’s see the choices here. Yes, we have implemented AI across various aspects of our operations. Maybe no, you have not yet incorporated AI tech into your business or some of you might be in the process. So let’s see, we’ve got a kind of like an even split here, although the fewest have actually implemented. So we’ve got a mix, an even split of not yet, and in the process of so alright, that’s good, Corey, that is helpful for you to know what I imagine. So let’s kick off the presentation. Corey. Awesome. Appreciate it. And thanks, everybody. That was fantastic to kind of get started with the poll. I always like to just kind of get a good idea of, of kind of who’s here, what you guys have been doing. And it’s really kind of aligned with a lot of the strategy sessions I’ve been doing. But first, let me take one step back. Welcome, everybody. Welcome to 2024. Right? The longest month of the year is now down. I always feel like January, I don’t know if everybody else feels that same way. But January always always feels like it’s just a very long month. But it’s good to be here. I’m excited for really 2024. What kind of the digital landscape looks like what e comm looks like, what trends are going on. So we got a lot filled in for today, but also throughout the year, too. So definitely keep an eye out for some additional invites that are going to be coming for commerce and coffee. But thanks again for joining us today. You know, I do want to talk about a lot of different things with personalization, mainly kind of focusing geared towards AI today, the demonstration is going to be going through a lot of the core native capabilities with 51ºÚÁϲ»´òìÈ Commerce as it pertains to 51ºÚÁϲ»´òìÈ Sensei. So we’ll kind of get to that. But for now, I don’t want to start here, you know, talking about personalization at scale and AI’s role in that. So the role of AI in enhancing customer experience is truly undeniable. But it’s also crucial to ensure that personalization efforts remain relevant and appealing to customers. AI driven customer data serves as a powerful tool for e commerce businesses to craft personalized experiences that resonate authentically with individual customers. leveraging this data involves a multifaceted approach. First, businesses can harness AI algorithm to analyze diverse customer data sets, including browser history, purchase behaviors and interactions to identify patterns and preferences. Utilizing these insights, personalized recommendations and tailored marketing campaigns can be curated to enhance customer engagement. Best practices for continuous adaptation in this dynamic environment encompasses agile learning models that involve with updated data, regular A B testing to refine strategies and proactive engagement to solicit incorporate customer feedback. By combining AI driven insights with a proactive approach to adaptation, e commerce businesses can create authentic and meaningful experiences that evolve harmlessly with changing customer preferences in this dynamic landscape. I like to kind of break things down. I think you guys that have joined these in the past, you do see that. So you know, while this this may not cover all facets of AI and personalization, here’s some really great points to think about as you start or curating your personalized experiences. So let’s take a step back. While today is focused on the econ aspect of personalized experiences, we need to be sure that we’re able to get shoppers and buyers to the site. AI can really help drive marketing efficiencies by analyzing customer preferences and past purchase history for crafting highly targeted campaigns. This ensures that promotional content resonates with the individual customers or buyers, increasing the likelihood of engagement and conversion. When emails and other marketing campaigns are curated, it’s important to ensure their synergy throughout the customer experience. leveraging AI for dynamic content generation, tailoring product descriptions, emails and website banners to specific user segments. By delivering content that aligns with each user’s interest and preference, we enhance the overall shopping experience driving higher levels of customer satisfaction. Revolutionizing the shopper experience with AI driven search to create a more relevant search and browsing experience which helps shoppers find what they want, as well as what they didn’t know they wanted. And honestly, it’s quickly to any commerce or in 51ºÚÁϲ»´òìÈ Commerce. This is delivered through live search powered by 51ºÚÁϲ»´òìÈ Sensei. And part of customer experiences is likely always going to be experimental. A B testing is a great way to ensure that businesses are delivering experiences the most efficient and effective way. AI can learn from these experience and evolve as experiences change. Tools such as 51ºÚÁϲ»´òìÈ Target include an easy to use interface for creating and running omni channel tests, audience segments and content targeting. So let’s talk a little bit more about the impact that AI has on efficient operations or on operations themselves. Often, during one to one strategy sessions that I have with merchants, I’m asked about this, about how or if AI can help with business operations. Efficiency is crucial for ecommerce success, especially for merchandisers and marketers trying to keep up with dynamic customer preferences. AI tools serve as invaluable assets for ecommerce operations, offering a pivotal role in enhancing efficiency and responsiveness to evolving market trends and customer behaviors. These tools leverage predictive analytics to analyze vast data sets swiftly, providing merchandisers and marketers with actionable insights into customer preferences, purchasing patterns, and emerging market trends. By employing AI algorithms, businesses can automate and optimize various tasks, including inventory management, dynamic pricing adjustments, and personalized experiences. Additionally, AI facilitates real time decision making by swiftly processing and interpreting data, allowing merchandisers and marketers to make informed decisions promptly. With AI driven tools, they can and you can adapt swiftly to market changes, ensuring that there are strategies aligned with the latest trends and customer behaviors, ultimately enhancing your competitiveness and success in a dynamic ecommerce landscape. Now, as per the other one, kind of the same thing, kind of want to spotlight on a few different things here. So let’s walk through some of the areas of operational efficiency and how this will enhance your shopper and buyer experiences. Kind of the first kind of thing of this I’d kind of say, ensure transparent communication about data usage and prioritize user privacy, adhering to ethical practices in collecting and using customer data, upholding privacy and transparency is foundational, clearly communicate to customers how their data is handled and ensure ethical practices are followed in data collection utilization. This not only builds trust, but aligns with legal and ethical standards, establishing a solid foundation for all AI driven operations. You can do things like integrate AI powered chatbots for real time customer support, providing personalized assistance, product recommendations, and order tracking. And similar to previous slides, employ AI to craft targeted marketing campaigns that resonate with individual customers considering their preferences and purchase history. This not only boosts the effectiveness of marketing efforts, but it also optimizes resource allocation, ensure promotional materials reach the right audience with greater precision. Foster continuous learning by implementing AI systems that adapt and evolve with user interactions. This ensures ongoing refinement of personalization process. The ability to learn from user behavior enables us to stay ahead of changing trends, approving the relevance and accuracy of personalized recommendations over time. In conclusion, combining these AI driven technologies, ensuring privacy and transparency, implementing chatbots for real time support, crafting personalized marketing campaigns and fostering continuous learning enhances operational efficiency and e-commerce. And by embracing AI, we not only optimize processes, but we also deliver a more personalized and efficient experience to our customers and buyers, setting the stage for substantial and sustained growth and success. So AI’s impact on predictive insights, right? So predictive insights are becoming increasingly vital for e-commerce businesses to anticipate customer needs and preferences. One striking example I often think about and really kind of involves this personalized recommendation. AI driven predictive analytics analyze vast data sets to forecast what customers might purchase next based on their browser history, past purchases, and even behaviors of similar shoppers. This precision enables e-commerce platforms to curate tailored product suggestions, significantly boosting customer engagement in sales. Additionally, predictive analytics help optimize inventory, preventing stock outs or access of inventory by forecasting demand accurately. For instance, companies like Amazon have leverage predictive analytics to implement anticipatory shipping, sending products to distribution centers near customers before they even place an order, ensuring faster delivery and enhancing the overall customer experience. These real world applications highlight the power of AI driven predictive analytics and not just meeting or preempting the customer needs, leading to improved experiences and increased sales for e-commerce businesses. And as you guys could see my trends here, similar to what I’ve been doing, kind of want to spotlight a few different things here. So to dig deeper for how AI can help with predictive insights, I’d kind of like to cover the following. Implement AI driven recommendation systems to suggest products or services based on past behaviors, preferences and similar customer behaviors. With 51ºÚÁϲ»´òìÈ Commerce, this could be done through product recommendations powered by 51ºÚÁϲ»´òìÈ Sensei. This will enhance the customer experience and increase the likelihood of customer engagement and conversion. Leverage AI algorithms to segment customers based on various factors such as behavior, preferences and purchase history. This enables targeted strategies for each segment optimizing the overall customer and user experience. Stay ahead of the curve by harnessing predictive analytics powered by AI. Analyze vast data sets to predict future buying behaviors, trends and preferences. This enables businesses to proactively tailor their offerings, ensuring a personalized and timely approach to customer needs. Tools such as 51ºÚÁϲ»´òìÈ Analytics using machine learning and advanced statistical modeling to analyze customer data. Find patterns and predict future behavior. It allows data analysts to take advantage of huge data sets that otherwise honestly might be wasted. Predictive insights driven by AI transform ecommerce strategy from predictive or from really reactive to a proactive approach. By incorporating recommendation engines, behavior analysts and predictive analytics, businesses position themselves to anticipate and meet customer needs in real time, ultimately enhancing customer satisfaction and loyalty. So before we get to the demo today, I thought it would be good to take a look at last year a little bit. And during the holiday season, 51ºÚÁϲ»´òìÈ did a survey and we found consumers were leveraging or planned to leverage Gen AI or generative AI during their shopper experience. So while this survey wasn’t finalized, when I put this all together, I did want to at least highlight it to showcase that in the middle of kind of the December timeframe of last year, this is what we were seeing from that survey from consumers. So one in four consumers use Gen AI at that point while shopping online. One in three plan to use chat GPT or other Gen AI to aid in holiday shopping. And then consumers plan to kind of turn to generate AI this, you know, kind of that during the holiday season and it was looking at best deals, quickly find specific items and brand recommendations and similar items or brands to ones that they already knew. So I often get questions around if you do have, if your business itself does in fact have your peak season during the holiday season and it’s more of like a quote unquote gifting season, AI definitely still plays a huge factor in that. So it’s not where AI is only trying to deliver a one to one true one to one experience. It could be a one to a gift set of experience as well. So it’s kind of good to highlight that. And with that, we are going to turn to the demo. So just give me one second. I’m going to start sharing my screen. Okay, perfect. Then we should now see the demo environment. So there’s a few things I’m going to highlight today. So I want to walk through product recommendations powered by 51ºÚÁϲ»´òìÈ sensei. I’m also going to go through live search powered by 51ºÚÁϲ»´òìÈ sensei. And I’m going to go through category merchandising, which is also powered through 51ºÚÁϲ»´òìÈ sensei and it’s within the live search capabilities. So we’re going to walk through each of those today. And I like to kind of start really at the start of kind of the product rec side. So I hit that a few times. And I think it’s important for us to start walking through that. So product recommendations powered by 51ºÚÁϲ»´òìÈ sensei. This encompasses throughout the customer journey throughout the customer experience. And it delivers in a few different areas to which we’ll look at in just a second on the other side. But it’s thinking about popularity ones, it’s thinking about things like high trends, it’s thinking about things like a one to one experience, etc. So there’s a few different segments or few different areas where we kind of see that. So as you kind of see this here, I’m going to scroll down. So my first one and if you guys have been on commerce and coffee before you’re very accustomed to the Luma branding. So in my fictitious business, I hit a few different fitness type people. So I look at it as like, weightlifter or runner, a yoga enthusiast, and then just kind of a general fitness enthusiast as it is. So my page on my homepage, I have a few areas where I’m delivering more kind of personalized experiences. My top rotator is one of those my my banner that’s here, my recommendation or my products that are here for most popular products actually do this in static, but I use customer segmentation to curate that slightly just based on specific types of groups that I have within my business. Like I mentioned, I do have categorization of customers. But if I keep scrolling down here at the bottom, you’ll actually see my best sellers. My best sellers is driven through product recommendations. So product recommendations delivers it dynamically, right? So as my changes happen within my business, so I sell more, I sell less, etc. This will essentially adapt and it will change that. So it will change the customers, basically what they’re going to see. So in a one to one setting, this might be a little bit different. What I’ve done in this category, category side of it is I’ve done that in much more of a you’re going to see what most customers are buying right now. Now, if I go into things like, let’s say my I’ll go into one of my PDPs. My PDPs I have the frequently purchased together. So the frequently purchased together is utilizing bought this bought that. Again, this is something we’ll actually walk through on the admin side. But now you can kind of see what that’s built like. Now, I’m also using related products. So I do have static products in here too, that I just basically want to always showcase there. But kind of a little tidbit here, what I’m doing is I put those to the below my content. So instead of it being above it, like the product recommendations are, because this is dynamic. So this is following trends, it’s following what users are typically doing. And that’s kind of what I’d be showcasing there. Now I have it throughout the customer journey too. So if I add this to the cart, and then I get to the cart as well, we’ll be able to see this on the cart. I also have this on my order confirmation page. So those of you that have done, we’re all consumers here in one point or other. So as you shop for something, when you get through checkout, and you get to that order success page, that’s a very powerful tool to see what other things have been purchased or things that are similar to that. In this, you can see the bought this bought that I kind of highlighted that again, but I’m just highlighted on the cart now. So again, it is throughout that customer journey. And they are set up a little bit separately in each instance. So on the admin side, what you could see here is just kind of the first page of it, which just shows us really impressions, views, clicks, revenue, viewability, etc. for everything that I have that’s active right now. So where product recommendations is just to highlight that click, we go into marketing, you’ll see product recommendations here. So this is the page that you will land on, you could see anything that is active to or anything that’s not active, basically any recommendations you have set up. So if I go to page two, you’ll actually see, thankfully, even though my business is not that busy right now, because it’s fake, we can see here that I have the bought this bought that on the PDP, when we see that we are generating revenue, we are seeing that there’s viewability and that we have a click through rate as well. So this is a really kind of good way to look at it. This is also based on the last seven days, we can look at the last 24 hours, we can look at the last 30 days to kind of see what this looks like. Now, instead of going through one that I already have, which is super simple, and I’ll show it just really quickly. If I wanted to edit the one on the homepage, I can click into this, we could see what this looks like, we could see when it was created, we could see when it was last edited, we could edit it, we could deactivate it, we can delete it. But instead, I want to show you kind of how quickly we can incorporate another one on the homepage. So in this instance, I’m just going to go and hit create a new one. And in this one, I’m just going to say CNC, let’s do commerce and coffee demo. And in this side, so select the page type. So this is basically saying which types or which page I want this to show up on. And in this case, we are going to use homepage, but I just want to show you each of these. So personalized cross cells, and up cells popularity and high performing cross cells and up cells, there’s a reason why this is not showing anything, it’s because we’ve designated that this type is going to be on the homepage. If I go into PDP, you’ll see that cross cells and up cells now populate. The reason why that’s happening is because we do have a specific product that we’re on that page that you’re on is a specified product. So you can do view this view that viewed this bought that etc. But when we’re on the homepage, right, we don’t know if there’s products there in specific businesses, you might not highlight any products besides what’s going to be in a recommended product. So you can kind of see as you kind of click through this now popularity most viewed most purchased, this is again cross, you can see what’s high performing view to purchase conversion, view to cart conversion. And then you also have, as I mentioned before, that personalized one. So personalized is going to deliver that one to one experience. If at any point in time, you’re looking to get a little bit more information on which each of these do, you can actually go here, click learn more, you’ll see what that looks like from our user guide. But again, in this case, we’ll just do on the homepage, what I’ll do is I’ll do recommended for me as well. And what we’ll say is recommended for you keep it simple. And what I’ll do is I’ll keep this at the five products for now. And I want to show this at the bottom of the content well, so we can do this at the top. So maybe I’ll do this top for now, just so we can see what this looks like, and maybe go back and change it. Really cool thing about this too, is you can include or exclude specific products. So let’s say for instance, you showcase out of stock products, right, you offer back orders, you offer sign up for restock alerts, etc. With a product recommendation side, this is more kind of strategy, you typically do not want to show out of stock products within a product recommendation tool, right? Customers are clicking on that to go to that product to be able to purchase it. So if you’re delivering them and out of stock product, it just could disrupt that experience. So maybe in that case, you’d want to go in here and go to add a stock, you’d say you want to enable it and basically say that you’re excluding that same thing for including, let’s say that you have a specific product that you have an overabundance of, so no matter what or who that person is, right, because this one, as we’re doing, we’re in this case, we are doing recommended for you. But let’s say for every single person, we do want to showcase a specific product. So you can actually define one product, two products or three products within the five products that you’re showing. And then basically, the extra products that are showing in there are going to be based on that consumer or that shoppers behavior, or buyers behavior. So in this case, I’m not going to add any inclusions or any exclusions right now. We’re going to activate this, we could see that the demo is now activated. So this is our new one, if we go to page two of this, here’s our new product rec. If I go back to my homepage, I’m just going to do a quick hard refresh here. Now I do have exposure, I have experience on the site, meaning I’m registered here, I’m logged in, there’s behavior data on me already. So it kind of has a good idea of what I’m shopping for when I get to the site. So you can kind of see that that’s curated it. Now two things. One, as I’ve done that, and I’ve activated it, this is awful placement, I would not do this here. So what I would want to do is I want to go back in and say, okay, now they see this activated, I’m just going to go back in here, going to edit it, let’s put it at the bottom of the content, right, we’ll put this here, we’ll actually make the best sellers be just above it. So you can actually change the sort, we could see the two that are active there. And I’m going to save those changes. We’ll go back to that front end, do a quick refresh here. Now we could see the content side of it, we could see the banners back brought up to the top, we could see if we scroll all the way down here, here’s our best sellers one that was there before, and now we could see the recommended for you. So this is mostly just giving you context of how quickly you can change that, how fast you can do it. So this kind of gives you all that kind of insight to that. So product recommendation wise, kind of super straightforward. Now if you wanted to go back into this and say, okay, at the same time, what I want to do is I want to edit this and I want to exclude a certain product, maybe again, we’ll use exactly that out of stock again, go into this, we’ll say, let’s exclude out of stock, let’s enable this. And we could see that the preview again, results on the storefront are going to vary occasionally, right, we’re not, we’re doing a personalized recommendation here anyways, but we could see enabling this filter will exclude that out of stock product now. It’s kind of a good way for you to kind of see what that looks like. Let’s see. So that’s really product recommendations in a nutshell, super straightforward, super simple. I want to jump into live search and the live search is going to be really kind of the bigger part of the demo. But for product recommendations, you guys have questions, feel free to drop them in there. We’ll get to them at the end. But let me get to the live search aspect. So live search wise, and I’ll use mine for right now, I have two of them that are up because I want to show a few different things. But for live search, those that are on 51ºÚÁϲ»´òìÈ Commerce or previously been in the Magento ecosystem, Elasticsearch is kind of the main search provider that’s in there. So that’s the native solution. Now, live search powered by 51ºÚÁϲ»´òìÈ Sensei is now the new cutting edge search solution. It is no additional cost for 51ºÚÁϲ»´òìÈ Commerce customers. So I like to get that out of the way really fast. But essentially what it does is it provides an intuitive AI algorithm, a data-augmentated behavioral augmentation type of experience and delivering more of the one-to-one exposure in search, but also providing quick search results too. So I’m just going to type in pant here. I’m going to show you what this looks like quickly. You could see even that pop over, sorry, I did click through that pretty quickly, but even the pop over that’s here is all driven through live search. So everything that you see within here, anything that you see on this side of it too. So what you see within these results is all driven through live search as well. I like to kind of show this one specifically because I do have a rule around it. So we’re going to look through that, but basically anything that you have here. So even if we did like video, anything you could kind of see as we’re typing in, it starts bringing in different types of results and it’s based off of a lot of a few different factors. Obviously again, your name of your product itself is absolutely going to be part of that, but it’s also the attributes that you’ve set to being filterable and searchable, et cetera. So those will also be factors in there too. The left-hand navigation here, as you guys kind of know it, the layer navigation, we consider this and call this intelligent fasting or fasting within live search. It essentially gives you that ability to ensure you have specific filters that are available, either pin facets or dynamic facets too. So pin facets means they’re essentially going to show no matter which search results that you’re showcasing. So things like price and maybe even categories would be something to pin there at all times and showcase that. Now others might be something like color, size, right? If I’d searched for the video that I was showing before, basically something like this, color size might not matter. It might not be applicable to the results that are there. So dynamic fasting is really going to kind of showcase that and I’ll show that on the admin side in just a second. Now benefit of what you get with live search. So if you use a third party search provider, typically what they need to do is they need to go in and they need to redesign or to design your search results page because they essentially are taking that over. What live search does is once it’s in place, it’s going to utilize what you have as your style sheet for your PLP. So it’s going to use your fonts, your colors, what your PLP looks like. So you can kind of see mine. I have the swatches that are here. I’m utilizing the swatches for thumbnails specifically that go into there. So you can kind of see what this really does kind of look like from this side of it. Same thing with like buttons and if I have anything that’s enabled from like wishlist, compare all those aspects, that’s also going to showcase into here as well. So what this looks like from the admin side. So I’ll show it in two different instances. So underneath marketing, go here again, you’ll see SEO and search, live search will be here. So I’m going to go to mine specifically just for the search merchandising rules. I just want to kind of walk through what I have set up here, but I’m going to go to another instance here just so I could show you kind of everything totality. This is one of the other demo environments that we have. It just has some fake data in there. So that way you can kind of see what performance looks like. So unique searches, the zero results and popular results. I typically whenever I’m doing any sort of like strategy session, I say like popular results, zero results, you can really curate that. You see that that’s coming into there. So beyond what analytics is going to show you with these search results and what this performance is showing you, maybe there’s a synonym that you want to create around it. Maybe there’s a search merchandising rule you want to create around that. So I’ll walk through those in just a second, but that’s really kind of what this is for. You can look at specific date ranges. You also can export this into CSV as well. So just kind of seeing what that looks like. For faceting, so really kind of straightforward. We kind of highlighted it before. I touched on a few of these, but you essentially have the ability to do pin facets and you have the ability to do dynamic facets. Again, just to think about what that breakdown looks like. So pin facets are exactly as they kind of sound. You’re pinning these facets. So no matter what happens, no matter what the result is, you always want categories and price to be shown here. So that’s a really good indicator or a really good type of an attribute that you might want to show is your categories and your price in every single search result. Now, the other side of it is the dynamic facets. And if you actually highlight over these little icons, they’ll tell you what they look like and what they’re specifically for. But essentially dynamic facets are the flip side of that. So anything that is part of the data set within those results. So if you have close outs, if you have education recommendations right here, these are my attributes that are part of my product taxonomy, but you essentially have these where you could showcase them. So if size is applicable in those results, it will show in the layer navigation. If color is applicable in there, you’ll see the same thing. Now sort type, just to talk about this quickly, sort type is essentially what you see within that layer navigation. So I’m going to show you just another version of this. Let me actually just drop this in the US dollar and let me do the same. I’m actually going to do the same exact result. This is a good example of showing you the styling too. So two different, just to give you a quick example, these are just showing you two different look and feels, even though they are the Luma branding, you can see from mine, I just do a little bit differently with my PLP versus this other demo environment that’s here. So essentially what that means is for that sorting option. So color was one of those ideas or one of those examples on intelligent fasting, the dynamic facets. This one is actually set to alphabetical. So you see black, blue, brown, gray, green, et cetera. Now if this was based off of the other side of it, which is count, this would showcase count being at the top. So climate, for instance, you could see indoors is showing up before cool or even before all weather because it has a higher count. So you could do it based on count or alphabetical. So it’s entirely up to you what you’d like to do to keep it really straightforward. If you click on these three little dots, you hit edit, you’ll actually be able to change this. You could say color or count or alphabetical, et cetera. So that’s kind of this page itself. Now to add new facets to this super straightforward, or even to remove, I just showed you kind of clicking on those three dots. You could say, just delete this from this, but to add new facets, you simply just go into add facets at the top here and anything that’s not activated. So like ribbon compatibility, store amps, et cetera, you can basically add this into this. So if you’re saying, I want to add this as a dynamic one, you could see here is that test color attribute now added. If we wanted to pin this, you just click on the pin. You’ll see that at the top here. Now for the sorting options of the actual available attributes, we’ll say it that way or available attribute or facets, you essentially have for pin, you can change the order of these. You could say, I want price to show up first, category to show up second, so forth, so on. With the dynamic facets, it’s going to be relevant to typically what’s in those results. So what do people, what are your consumers, your buyers, that behavior, what does that look like? Are folks typically clicking on color when they go to something that has color variants? Are they clicking on size when it has different dimensions and so forth, so on? So based off of that, the AI tool will understand that and start showcasing and displaying that order a little bit differently on the front end. So again, with pin facets, you have control over that. With the dynamic facets, you kind of do still have the control over it, but the AI tool really is doing that algorithm based off of that. So that is the faceting side. Synonyms, super straightforward. This is a really easy thing. You basically just have a one way or two way. So for anything that’s basically being searched, you want to showcase specific elements here. So for instance, with the first one that’s here, going like two way, you have blue. So if somebody searches for aqua, you want to show blue. If you somebody search for blue, you’re going to show aqua. Same thing. If you kind of look down here, we look at a one way. This is a good example of this as well. If somebody searches for shirt, you might want to show sweatshirt as well, but if somebody searches for sweatshirt, you don’t want to show shirts, right? That makes perfect sense. That’s typically what you would do. So synonyms, really straightforward. Adding them also really straightforward. You just go into this and you say either two way or one way, enter the term or phrase. You could do the terms comma separated so you don’t have to do these one by one or anything like that. You could showcase that here too. So you can kind of see what this looks like as well. All right. Now for search merchandising, I know synonyms is really quick. I like to highlight it though. Search merchandising, I’m actually going to go back to mine just here for a second. I want to kind of walk through what I have set up. So I have a few different rules that I’m doing with the same kind of concept. So I’m doing boosting as well as pinning and a few other elements to this one. So I’m going to showcase mine specifically. You can also look at the details of it where we’ll just kind of break that out a little bit, but I’m going to go into the edit page itself. So what I’m doing here is I created a rule that if somebody searches for pant, right, and that’s exactly what I showed you on the front end too, you could see my pant. I’m seeing exactly the pinned options that I have here. And then there’s an augmentation of the rest of the ranking of these products based on, again, AI algorithms. With this specifically, there’s a few different types of things you could do with the conditions. You can do search query contains, you can do search query is. So if you drop this down, you’ll actually be able to see that search query contains, is, starts with, ends with, et cetera. You also could say if it matches any, if it matches all. So your conditions can be multitude as well. So you don’t have to have it as just one. Below that is the intelligent ranking. I’m going to come back to this in just a second. I want to go through just the pinning aspect first, and then we’ll walk back to this one. Just as a little tidbit here, intelligent ranking was later released within the live search capability. So when live search first came out, the search rule was just kind of with the pinned and so forth, so on. But the intelligent ranking did come afterwards. That’s been out for some time now. It’s been out for over a year. So just give you some context. We’re always developing, always looking at different new ways to be inclusive within here as well. So looking at the manual ranking now. So this is really where those rules come into play. Now for strategy sessions that I’ve had, I typically call out a few things here. So I have merchandisers talk to me all the time and they say, hey, there are specific products we have to have pinned within our results. We want to showcase these, when anybody’s doing a search. And this is the best way to do it. You do it through this pinning, or you do it even through boosting. So if you want specific products to showcase, you could pin them just like I’m doing here. Now pin basically means that whatever position you pin that in, it will show in that position. Doesn’t matter what you have. And I know I said I was going to mention it before, but it doesn’t matter what you’ve set as the intelligent ranking. These will always show in those specific pinned elements or positions. Now boosted, slightly different. So boosted is just going to boost that product up, but the AI, the augmentation of the behavior is going to determine and dictate where products are going to lie. You’re just saying, you know, for instance of mine here with Ether, I just want it boosted towards the top, but any of these other products that don’t have anything where it’s a pin, bury or anything like that, basically can overtake this at any point in time. It just means that it will show up within maybe my first page of my results here, just boosting that up. So that’s the difference between the boost and the pin aspect. Now you also have the ability to hide a product, which you could see here, I’m hiding this Karina basic Capri, I’m hiding this product and this could be for various reasons. I could be hiding this product because I have low stock in it and I know I’m going to have low stock in it. So I want to push that down and I want to hide it. The other aspect you have is burying products. So this Thorp Track one, if I load more of my results, you can actually see that this is buried down. This same concept would be on the front end too, so if I go to the next page and so forth so on, you’ll actually be able to see that that’s actually pushed down on my list too as well. But you could see all the other ones that I have where it’s pinning them and so forth so on, if I go back just to the front end for just a second, you’ll see that that’s following exactly what I have on the admin side, what you can actually see. So it’s changing certain ones, it’s changing products specifically around different types of things, but essentially is again, everything else that’s between there, it’s changing those rankings based on AI. Now this is where I want to talk about the intelligent ranking. The intelligent ranking really gives you that next cutting edge to this, where instead of it being just kind of all for everybody and it’s set up through AI, obviously it’s still going to be a behavioral basis and it could be based on popularity and so forth so on, where the intelligent ranking really comes into place is you can make this recommended for somebody specifically, you could say it’s most viewed, so recommended for you is going to be one to one. So as I search, if I purchased similar products in the past, those are going to rank separately than what maybe my counterpart here, Alana, maybe Alana is searching for the same exact kind of concept, but she’s going to see different products than I will. Now for most viewed, you would see something where it’s within the last seven days, you can actually see this here too, it says recommended the most views within the last seven days, most purchase is also within the last seven days, and most added to cart is within the last seven days. Really kind of good to call this out because this doesn’t get stale then, it’s not showing from a year ago, two years ago, it’s showing in the last seven days. So as we were kind of talking about before that dynamic aspect, that’s the dynamic aspect, that’s the learning capability that’s really coming into play there. And then trending, it’s based on the last or the product’s recent momentum across the site. So you can actually change this for the last three days, 14 days, 30 days. So you do have the ability to kind of change that and fluctuate that. So we said we want this to be recommended for you, you could see just changing it. As you get to the front end, it will dictate, it will kind of showcase those results and it will show it on the front end based on what you’ve said as your intelligent ranking. Then you also have the ability to just basically do none. So this is going to be based on relevance. AI is still part of this, but it will just be based on relevance of what was searched. It’s not going to be dictated by any sort of behavioral basis for that specific result beyond what you’ve done as pinned and boosted and so forth, so on. So it’s going to just based off of that rule. So again, you could do it where you just have this manual ranking be set to one thing where you’re just boosting one specific product. You could boost multiple, you can hide, you can pin. And I kind of did all that here. So you could see these are the options that you have, boost, bury, pin, and hide a product within a rule. And you could create multiple rules too. So just because I’m showing you one doesn’t mean you only have the ability to do one. You could do 50, you could do 100 of them. So you do have the ability to kind of showcase multiple different types of rules here or different types of things that you have. Okay. Last part of this. I know we’re going through things and we’re recording this so you guys can feel free to come back to it. There’s a lot of different things within our user guides around this too. But category merchandising, super awesome, released at the end of last year or during last year. The category merchandising is really, really cool guys. This is where you kind of like, I get jazzed up about this. But this is what I’ve had so many merchants come back to me with. Even though the search results are very powerful, right? I will never kind of note that or denote that the search results are going to be a higher converting. So it’s important that you do have relevant and fast search results and that they’re augmented and dynamic and based on that actual customer experience. But those that are shopping, if they go to categories, they’re looking at categories, the ranking of products within there, instead of it just being static, as you guys probably have done in the past, category merchandising is the new cutting edge. This is AI driven and you have the ability to also do rules. So I’ve had merchants come to me and say, well, I have to be able to showcase specific products, but I also want the sort to be different by each individual. Category merchandising does that. So in my fictitious business, here’s all the categories that I have available. And I’ll show this just from the front end. You can see I’m going to actually focus on the watches side of it for right now. It’s a simple category. I don’t have that many products in here, just so you guys could see everything in its totality. But I’m going to put one that’s on here. But essentially everything that you see from this front end side, all the different categories that I have available, that’s exactly what’s here. So within here, you can add new rules. You can say what you’re specifying, which category, or I like doing it this way. This is my preference of this. I actually go through it this way. I say, okay, here’s my watches category. We could see here I have most viewed on gear already. I have most purchased on, sorry, on the gear category than I have most viewed on the fitness equipment. We could see if it’s inheriting specific ranking too. So really cool factor is that you can inherit from another salute or another category that’s within there. So if I wanted bags, fitness equipment, and watches to inherit from the parent category, they would basically all go down to most purchased. So you can also rank it based off of that. Now, if I go into watches here, I’m going to go and click on the three dots here. I’m going to say add rule. And in this case, you could see here is the category rule. So similar to what you saw within Live Search with the intelligent ranking, we can do the same thing here. We could say what’s recommended for me based on my previous and onsite behavior, what’s most viewed in the last seven days, what’s trending, so forth, so on. So similar to what you saw here. You also could see apply intelligent ranking to subcategories. So if there was subcategories here, I can actually do this and it would be applicable to everything that’s sub below me. Now I’m not on an actual subcategories or I’m already on a subcategories. It’s not showcasing that. The manual ranking side. So here’s that same concept again. I could say no matter what I want the Clambr watch to show here or actually instead I want this Summit watch. So I want Summit to show and I want that to be position one. So I’m going to change this to position one. I’ll change this to position two. It’s already doing that for me. So Summit watch is going to be position one. So position two is going to be the Clambr watch. And then what I’ll do here is I’ll just say recommended for you too. So based on my behavior, I’ll save and publish this. We could see once this is saved and I just click this down again, we could see that that’s now effective here. Now if I went into a different one, let’s say I went into the men’s top category, which we already have one on there. All right. So this is actually already doing it, which is perfect. So it’s already doing this for the sub elements. But let’s say I even want to do this at the top, top level and I wanted to add a rule here. So I just wanted to show you can apply intelligent ranking to the subcategories. We could see what’s being overwritten right now too, which is really cool because we could see, you know, ones that already have that on there, but you can essentially apply the intelligent ranking to all subcategories as well. So kind of a good way to facilitate this in a lot faster of a manner. Now let’s just go back to the front end. Remember we did Summit watch to the first one and then Clambr watch to the next one. So again, what will change here is the recommended for you. This is based on a one-to-one experience, but at the very least what I’ve done is I’ve taken these two products. So kind of, again, we see that through there and that’s it. That’s the category merchandising. It’s an awesome tool, really, really amazing. And what it does to be able to do this intelligent ranking on category pages, but that’s as simple as it is. So with that, I am going to turn this back to Alana. We’ll get to some questions. I always laugh when you’re like, that’s it, it’s that simple, Corey. You’re making me laugh. But that was awesome. Thank you so much for that presentation and demo. And before we get into Q&A, I want to quickly pause because we are going to some very exciting stuff, be launching a new spinoff series of Commerce and Coffee called Behind the Brew. At these sessions, we’re going to be taking a deeper dive into the more technical side of things. So our first session is going to be a spinoff of this one on Thursday, February 29th, where one of our technical advisors, Tapan Sotagar will spend the session sharing more information on how to implement live search on your site. So it’s going to be a much more technical session. But please let us know. There’s a little poll in the corner if you’d like to receive a special invitation for that. Also, feel free to click yes if you’d like the invitation to pass along to your partner or to another internal colleague as well. So let us know there. I’ll keep that up later. Put that back up later in the presentation as well. And then quickly, I want to make a quick plug for 51ºÚÁϲ»´òìÈ Summit. It’s coming up March 26th through 28th in Las Vegas. Some highlights that will take place at Summit is keynotes from 51ºÚÁϲ»´òìÈ and customer executives. There’s going to be strategy keynotes, including demos and deeper dives into our solution. There’s Summit Sneaks, which provides us a sneak peek into some of our potential new innovations, which is really exciting. Hundreds of breakout sessions and hands-on labs and, of course, networking opportunities with people from all over the world. So definitely check out 51ºÚÁϲ»´òìÈ Summit. There’s a link up ahead in the presentation for more information on that. All right. Keep it going, Cory. You ready? Let’s pop open our video again. Awesome. Waiting for you. And then we’ll get started. Great. Okay. So let’s jump into it because we have only a couple minutes left. Oops, lost you on the camera there, Cory. Should be there now. Hi, everybody. Does this work for a B2B environment and how do we feed the AI with our product information so that I can know what to really recommend? Yeah. So it’s a great question. So yes, it does work for B2B. So product recommendations and live search, I’ll kind of double click on that. So both of them are absolutely part of our B2B and B2C. So for B2B, you have things like shared catalog, proprietary or curated catalogs, pricing and so forth, so on. It all works with it. So if you have a specific catalog that is for one company versus another, when they do a search, it’s going to be based on what you’ve created and what you’ve sent as their shared catalog. The same thing with like category permissions, different tier pricing and so forth, so on. That will also be applied to search results and to product recommendations as well. So it’s not like they’re going to see the wrong information to them if it’s already been dictated or if you already had them set up by something. So it’s a great question. Thank you. Awesome. Next question. How much control over user segmentation would a marketer have? And are segments identified via AI or are they predetermined? So that’s a good question. We didn’t really touch on segments too much besides through the slide where. So segmentation within 51ºÚÁϲ»´òìÈ Commerce, for those that are not aware, customer segmentation can be utilized for content curating, so dynamic content for different promotions, so forth, so on. So different ways of creating a personalized experience or a differentiated experience by segment. So question around that, can AI create those segments? So no, those would still be dictated based on the categories you assign. Where I would say the AI does play a factor into that is if you are delivering more of the recommended for you aspects. So the intelligent ranking we went through for live searching category merchandising, the same thing with the PREC side too. If you’re doing recommended for you, it essentially is creating some sort of a segmented type of approach. It’s not just you can’t see it in the segment side. So yeah, essentially you’re creating them manually. Awesome. This next one comes from Gabriel. What’s the minimum size business that can realize benefits from AI predictive analysis? Oh, Gabriel, good question. So any size business to be fair, right? I mean, I know that that’s like an arbitrary answer or just like kind of being politically correct, but ultimately, I mean, really any size business to some capacity, even though you might not think you’re doing it right now, you probably are in some fashion where you have some sort of predictive analyst or analytics involved in your business some way. But yeah, I mean, really any size and if you’re not using it with no matter what your size is, you could be behind a little bit. And if you’re just starting out a business, you might not think it’s important, but you grow from there. The predictive analyst and analysis for a business and data sets, it’s critical for the growth and sustained growth too. So any size, if I answered it a different way, I would be, that wouldn’t be the best way to answer it. So best way is any size to be fair. Awesome. We got time for a couple more. I know you kind of mentioned this, but to reiterate, do we need to use additional plugins that cost extra or is this native in 51ºÚÁϲ»´òìÈ commerce? Okay. So for live search and product recommendations, so great question. We consider this one of our microservices within the 51ºÚÁϲ»´òìÈ commerce fold. So what that means is there’s no additional costs to you at all. If you are an 51ºÚÁϲ»´òìÈ commerce customer, you have full access to using live search and product recommendation. It’s essentially a microservice because there is an extension around it that you install. It’s our extension. No, it is on the marketplace, it’s available on the marketplace. There’s guides that are around this as well. The reason why we kind of separated this or, or I don’t like using the phrase, but decoupled it from the platform is so that when we do make adjustments to it, we can kind of update that without needing to upgrade the entire environment. As most of you probably are seeing, we are doing one update a year for the platform itself, right? That’s kind of what we’re trying to follow is around that. And we’ll do patch releases for security, but you know, two, four, seven is coming out next month. That would really be the only release that we’re having this year. But live search had three iterations last year. It didn’t mean that you needed upgrade the extension itself. We kind of deploy those automatically because it’s a SaaS service. So you already have that available to you. So installing the extension and then everything can be configured on the admin side. So there’s nothing that you really need to worry about beyond that. It is our extension, no additional cost. Awesome. I think we’ve got time for one more from Gunner. How difficult is it to implement the AI? So similar to what we were just kind of walking through it, honestly, it’s just an extension install. I’ll say it from my side, I’m not a developer. What I did is when I had that installed on my demo environment, it took the developers not long at all to get that installed. Configuring it took me maybe 20 minutes and that was creating the API key to. So you do have to create an API key in your account.medeta.com. But beyond that, you basically have everything that’s connected to there and then it syncs your catalog. Depending on the size of your catalog, it could be five minutes to take, it could be a few hours. So it just depends on the size of your catalog. But essentially, once you get that in place, you just saw we even created a product recommendation in real time just now on the homepage. So you saw how fast it was to kind of implement that. And then the data wise, I saw a few questions within here that were around like, how long does it take for that information to be synced? Basically, that behavior is all the time. If somebody’s searching for something, if somebody is looking for something specific one day, but then they change, it’s learning that, it’s augmenting that. So that’s day in and day out that it’s going to learn that. But implementation, yeah, it’s not a lot of time at all. It’s mostly going to be figuring in, like I said, that’s 20 minutes that you’re configuring. And then setting it up took us just now 30 seconds. So I know it’s, I did it in real time for that very reason for somebody potentially asking that question. So hopefully that did kind of hit that for you. Yes, very encouraging. Um, well, that is all the time that we have for Q&A. But I want to quickly wrap us up. So on this screen, there’s a bunch of resources for you in the web links section, you’ll see a link to our past recordings on experience league, another one to our upcoming events, a link to blog post about today’s topic. And then there’s your link for more information on 51ºÚÁϲ»´òìÈ Summit. Also, don’t forget to download the white paper with lots of information and resources for you. And as mentioned, if you have a second to fill out these survey questions, you’ll also see the poll question about our technical deep dive into live search on February 29. So again, let us know if you’d like to join that session and we’ll get you an invite link for that. And if you have a question specific to your account that we weren’t able to address today, please reach out to your solution account manager. And as a reminder, you will receive a recording of today’s event in an email from us in 24 hours. So that’s all that we have for you. Thank you everyone again for attending. Thank you, Cory for presenting and we hope everybody has a great day. Have a good one guys.