0:00 Good afternoon, and welcome to Beyond Click, converting contextual awareness into commerce wins. My name is Matt McCusker. I'm vice president of sales, of contextual commerce for Bazaarvoice, and I'm thrilled to be moderating this sec this session on contextualization and specifically on, a product that we're very excited about called Bazaarvoice contextual commerce. 0:20 Joining me today is Frank Deck. Frank leads product management and Anne Taylor in the loft and has personal experience in rolling out contextualization strategies and specifically in in deploying Bazaarvoice Contextual Commerce. 0:33 I'd like to thank Frank for joining us today. And with that, we'll jump right into, the agenda. I'm gonna kick things off by giving a quick overview of contextualization in general and, specifically, some of the capabilities of Bazaarvoice Contextual Commerce. 0:49 Then I'll turn things over to Frank to take us through the Ann Taylor journey, starting with the challenge that they were facing, how they map their the conversion journey for their consumers, how they address the challenge. 0:59 And then we'll talk about the impact and results that Ann Taylor saw from Bazaarvoice Contextual Commerce, which are quite impressive. Lastly, we'll wrap things up with some key takeaways and what's next for Ann Taylor. 1:11 Before we jump in, I thought we'd take a couple of minutes just to frame the conversation around contextual commerce and dive in on our product, which is aptly called Bazaarvoice Contextual Commerce. 1:23 I'm sure most everyone is doing some form of personalization today, and there's no doubt that personalization has proven to to drive incremental revenue for your ecommerce traffic. 1:32 One of the challenges with personalization, however, is that you need to know the personal data of your consumer. And a good portion of traffic is often anonymous. 1:42 We've heard from our customers that could be high as high as seventy to eighty percent of traffic is anonymous, whether that's new users or known users that simply haven't signed in yet. 1:53 That makes it difficult to deliver a personalized experience, and what happens is sometimes these users who are anonymous get a generic experience. 2:01 And as we know, cart abandonment in that section of traffic is quite high. What contextualization allows you to do is work in conjunction with personalization, so they are complimentary. 2:11 In fact, they're very synergetic partners. And while personalization allows you to deliver a personal experience based on what you know about your consumer, contextualization allows you to deliver a personal experience based on what that consumer is doing right now. 2:26 So the AI technology behind Bazaarvoice Contextual Commerce actually analyzes five hundred data points per second looking at that consumer's behavior on-site, mouse clicks, movements of the mouse, what pages they're viewing, what searches they're doing, and then makes the decision to deliver a very specific optimized message that motivates that seller to add to cart and convert. 2:48 And we do this without blasting out, tons of messages. In fact, only about thirty percent of your consumers will see messaging from us. That's the strength of the AI technology. 2:59 Frank, if we move to the next slide, in a nutshell, what Bazaarvoice Contextual Commerce does is help you unlock more revenue from your ecommerce traffic with minimal effort on your part. 3:10 And, what's great about it is you only pay for the proven results that you see. How do we do that? There's three advantages to bizarre voice contextual commerce, and the first is that it has the most advanced AI technology on the market today. 3:24 It's based on thirteen years of machine learning, literally looks at one point five trillion data sessions per month. And this is truly the secret sauce of of, the contextual commerce product. 3:36 This is how we only have to message thirty percent of the time and still get significant lift, which we'll talk about in just a moment. The second, advantage is the fully managed service, that we offer to make this effortless for you on your behalf. 3:48 There's a team of Bazaarvoice strategists whose sole job it is to help you drive incremental revenue. They they help you launch the initial campaigns. They fine tune those campaigns. 3:58 They work with you to launch additional campaigns, and they wake up every morning purely focused on helping you drive incremental revenue. And the last advantage is that we don't charge based on how much that team works or the campaigns that we run or or the page views, that they see. 4:14 It's all based on the results that that that contextual commerce drives from an incremental revenue standpoint. I've been doing this thirty years. I've never seen a product that that delivers such an impact in short amount of time, and the best part is that it's very quantifiable. 4:27 You'll know exactly the revenue that's coming from contextual commerce. This slide represents what our customers have seen from a sales lift standpoint, over the last twelve months. 4:37 So anywhere from four percent up to thirteen percent. And on average, we see a seven point three percent, lift. Now that four percent, on the left hand side is generally when you first launch. 4:50 Right? So we launch the initial set of campaigns. It's usually a subset of eight to ten to twelve campaigns, and then we build on that over time. 4:58 If you go to the next slide, you'll see that growth. And this is the long term value of the bizarre voice contextual commerce product. And it it is this type of of, growth over time for two primary reasons. 5:09 First, that team of dedicated strategists whose sole job it is to help improve the campaigns and continue to drive that incremental revenue, but, also, the AI technology gets smarter over time. 5:20 It's self learning. So we start with data from thirteen years of experience, but then it gets to learn your consumer behavior and gives better recommendations based on the learning that it that it gains over time. 5:33 My last slide talks about what's coming, and the the best part is the best is yet to come. So we are now integrating, contextual commerce with the the other Bazaarvoice products. 5:43 Here you see some examples of bringing in ratings and reviews into some of the contextual commerce messaging as well as social content. What this means is we're building upon your existing investment in BizarroVoice to deliver curated on time messaging, which further motivates these sellers to to add to cart and convert. 6:01 We're very excited about where this product is going, and I'd love to turn it over to Frank now to take us through the Ann Taylor journey. Hey. Thanks, Matt. So hi, everyone. I'm Frank Deck. 6:11 I am at Ann Taylor and Loft, which are sister brands, ann taylor dot com and loft dot com. My team, I head up a team responsible for website optimization, which is really about taking the customer journey once they arrive on our digital property and then optimizing that to be the most engaging, most interactive type of customer experience, ultimately to support my company's revenue and long term profitability. 6:38 So what a little bit of background about Ann Taylor. So we are in the retail fashion space. Our target market is professional women. 6:48 These are people who are looking for value of course and have a sense of style, have a sense of getting something that fits their specific use case needs. 6:57 And then like we talked about, where I come into this is really optimizing that online experience to make it as seamless, efficient, engaging, and personalized as possible for every customer who comes through our digital storefront. 7:14 So the big challenge, what we're trying to solve for is quite simply how can we make the most out of every single visit on our website. 7:25 You know, every year, I'm sure just like most of you, we have revenue goals. We have things we're trying to accomplish as a brand. 7:34 We had done some initial testing before we started our engagement with Bizzare Voice where we had done some, urgency messaging and actually saw some good results. 7:45 It was great, but the problem was it wasn't scalable. It was only a one off bespoke solution, and there was only so much we could do with it. 7:54 Furthermore, we couldn't really make it a contextually aware type of message. So really everybody got it whether you needed it or not, which meant just another thing on our website all the time that everybody sees that now is competing with all the other messages on the website. 8:09 So we were really looking for something that could give us a better experience with what we had while still keeping the website clean and performing. 8:21 So as we worked with Bazaarvoice, we, in cooperation, really mapped out that journey. And what it really looks like is figuring out the best touch points at every step of the purchase process. 8:35 I'm sure all of you have seen some version of this as far as the ecommerce funnel over time, but really it's how can we make them aware of the products? 8:44 How can we make sure that they are aware that this is the right product among the products? How can we make them feel good about that purchase and then ultimately get them to do that final click and buy that item to take it home? 8:57 So we worked with them. We came up with a game plan. And I'm gonna show you some of the tactics that we used in partnership with the b b team. 9:07 The important thing to note here is there are two things going on. One is presentation style and the other is the message itself. 9:15 So for all of these, you're gonna see two different cells. One's a little higher volume, one's a little lower volume. And then we'll talk about the specific messages also. 9:24 These can happen in any combination, and it really it's not that all of these are being shown to every customer. Just like Matt mentioned, it's a machine learning model determining the right message at the right volume for that customer based on their journey, Even if sometimes it means not showing anything at all. 9:42 If the customer doesn't need it, they don't get it, it gets out of the way. So the first of these that we partnered on is carding frequency. 9:51 And I should mention we did this for both brands as a separate split test on our site, an AB test. We did it for the Ann Taylor brand. You'll see some images for the Loft brand also, which has a slightly different customer base, but some meaningful overlap too. 10:07 So one of the first tactics that we partnered with is part of our first batch is carting frequency, which is really giving social proof to show what other people are doing as far as adding to cart, something that showed up on our product detail pages. 10:22 You'll see a slider treatment right here, which is more of the higher volume message. And then similarly, you'll see something for Loft with that higher volume message with a slider that pops in, that really just highlights how many people are adding this to cart, which can both give some social proof but also give some urgency to say this could sell out. 10:46 Similarly, we did purchase frequency. So same type of messaging, but now it's the people who have bought. So with this, you'll see a much smaller message. 10:55 This is the low volume version, which is the inline. Either of these can be either version. Another one to boost that confidence in the product itself is ratings amplifier, tying in with the other Bazaarvoice suite, which we also partner with. 11:10 Being able to pull in those ratings, and if it's a good product and people like that product, highlighting that, putting the best foot forward for that to say, you should notice this. 11:19 A lot of people like it. Maybe you should consider buying this. And then also for a customer who's perhaps a little bit more promotionally minded, a savings amplifier message. 11:32 So instead of, hey. This is great. It's saying, this product is on sale. Let me do the math for you. You're saving exactly this many dollars for this. 11:40 So, you know, the customer can already see that there's a lower price. But with this, they're able to see exactly how much they're saving. And for some people, the ML model is showing, that makes a difference, and it's a meaningful message for them to really drive home the value of the product they're buying. 12:00 On the urgency side, limited inventory is one of the tactics we partnered on. So this is really driving home the fact that this product, it is inventory aware. 12:11 So it's able to say, this is running out. If you like it, you better go ahead and make a decision before you run out. And then also a kinda neat one which is hidden gems. 12:22 This is interesting because what it does is it looks at products that maybe have a lower view count, but a higher purchase rate to say, like, not many people see it. 12:31 But when people do see it, they buy it to really highlight those and give almost a little bit of a sense of accomplishment for those people when they're looking at that product. 12:41 Again, it's all about driving urgency, feeling good about the product, feeling good about the value. So all of those were part of our first batch of tests. 12:51 We ran this as a split test, and all of these were available for the machine learning model to choose to show or not on a one off basis. 13:01 Like Matt mentioned, it's low volume, but we actually were able to see some pretty substantial results. So for our Loft brand, what we were able to see was a five percent lift in revenue per visit, and that was across all visits, not just a subset. 13:20 On our Ann Taylor brand, we were even able to see a six percent lift in revenue per visit. So for all visits, all of a sudden, it was great news for us. 13:30 We were generating substantially more money with those customers, driving more purchases, driving higher satisfaction, and really driving that conversion. 13:41 The really great thing about this was the scalability, which this was something we were able to do. Like Matt mentioned, the service really did all of this build out for us. 13:52 So it's not something where we can make more money, but we need to add five more team members. We were able to do it exactly with what we have today without having to add anybody else to it and really let the machine learning take care of the presentation. 14:07 Let their services take care of the build out. So all in all, we are very happy with the results that we saw with this, and really saw the value of these contextual messages and really tailoring them to a specific customer. 14:23 But our journey is not done. So what's great is we're partnering. And now that we've launched this, whereas maybe some of the other partners we've worked with, it's like, you know, you sign the contract, they say thank you, and then, you know, you have an allotment of hours and, like, good luck. 14:39 Hope you're doing okay. It's really a partnership ongoing where they've looked at our performance and have helped to create a roadmap of enhancements to their own product to support us. 14:50 And what we're gonna be looking at for our own roadmap is continuing to optimize both for the messages, including how we message, maybe the frequency cadence that we message them, whether we're talking about something that happened just in the last day or the last thirty days, really testing to see what resonates with our customers. 15:11 Testing the placements Is our low volume message, what's called the inline message, below the photography better? Or is it above the photography? 15:20 Or maybe alternating between them. All of these things are things that they're fully aligned on and partnered on to be able to split test with us and continue to drive that value for us, which is really great. 15:33 And then on the medium horizon, also tying in with some of their other things, the UGC imagery that we're also partnering with them on, to be able to pull those in too and just create a really nice cohesive experience that really drives the overall engagement and ultimately conversion. 15:52 So all in all, I'd say we're really happy with this partnership. It's been really great to work with them and to go on this journey. 16:02 We're really excited for the future that we can continue to drive value. And, of course, it's helping to drive our bottom line, which makes us all very happy. 16:12 So with that, I wanna say thank you and best. Thank you. If you do have interest in, learning more about contextual commerce, please reach out to your account executive, account director, or CSM, or you could reach out to me directly. 16:26 Thank you.
