Tiffany Serbus-Gustaveson 0:18

Happy Tuesday, everyone. I'm Tiffany Serbus-Gustaveson, a digital strategist with BWG Connect and we are a network and knowledge-sharing group, we stay on top of the latest trends; challenges whatever is shaping the digital landscape. We want to know and talk about it, we will have done 500 of these virtual events this year, due to the increase in demand to better understand the digital space. And we've done 100 In person small format dinners this year as well. So if you happen to live in a tier-one city in the US, feel free to shoot us an email or check on our website bwgconnect.com. For upcoming in-person events. These dinners are typically 15 to 20 people having a discussion around a certain digital topic and it's always a fantastic time. We spend the majority of our time talking to brands that's how we stay on top of the latest trends would love to have a conversation with you. So feel free to drop me an email at tiffany@bwgconnect.com. And we've been at some time on the calendar. It's from these conversations we generate the topic ideas we know people want to learn about and it's also where we gain our resident experts such as Yogi who is with us today. Anybody that we asked to teach the collective community has come highly recommended for multiple brands within the network. So if you're ever in need of any recommendations within the digital space, please don't hesitate to reach out. We have a shortlist of the best of the best and we'd love to provide that information to you. Also note that we do partner with a talent agency Hawkeye Search formerly BWG Talent that we can put you in contact with as well should you have any hiring needs and a few housekeeping items. First and foremost, we want this to be fun, educational, and conversational. So drop those questions, and comments into the Q&A, the chat, and we will get to them or you can always email me at tiffany@bwgconnect.com. As we move along, and we started five minutes here after the hour, rest assured we're probably gonna wrap up at least 10 minutes before the end of the hour to give you ample time to get to your next meeting or destination. So with that, let's rock and roll and start talking about the 2023 eCommerce trends and what they mean for the upcoming 2024. I can't believe 2024. The team at Yogi have been awesome partners and friends of the network. So I'm gonna kick it over to our panelists. If you can give an introduction on yourself, that would be awesome. Then, we can dive into the information. Thank you.

Sogyel Lhungay 2:21

Sure. I can go first. Hi, everyone. My name is Sogyel Lhungay. I'm head of Insights here at Yogi. I've been here for a little more than four years. My background is in CPG M&A. And here at Yogi, our team is essentially at the cusp of the professional services team. We have a lot of enterprise clients and we and industries range from everything from personal care to pet care to electronics, really just the gamut.

Spencer Kelty 2:51

Yeah, yeah, absolutely. I'm Spencer, I'm Head of Marketing at Yogi. I'm really, you know, I've got a background in working with eCommerce brands for technology solutions, really finding ways to modernize that customer experience. I see a lot of familiar faces in the audience here today. We've done quite a few of these this year. So I appreciate those of you who've come to a few of these as we talk about different topics. Today, we're going to get into kind of a big overview of a lot of the trends that we've looked at throughout the year. Some things that we've touched on here with BWG, and some of these calls, and some things that we've covered in our insights, wires, newsletters, and some things that we've done a little bit in the backend, some some trend analysis that we've discovered. So let's just get into it. I'm going to start by just kind of intro in a little bit of the data that we're looking at, and a little bit of what Yogi does, just to kind of give the background and the basis for where this information is actually coming from. So Yogi is a platform that helps consumer brands, aggregate and analyze their reviews. So basically any public source, Amazon, Sephora, target Kroger CVS, sources like that we can pull those reviews in. And we use AI to break down those reviews into concepts of themes, attributes, and understand the customer sentiment behind each. So I think we've got some metrics here for the number of reviews and and things we've analyzed here. 20 million written reviews analyzed in this last year alone on the Yogi platform for an average rating of 4.28 stars. This is across 75,000 products and 300,000 URLs that we've ingested, crossed 250 sites and 50 countries. So basically, this is to say A we're looking at a lot of data, we're always in the data. And I'm really excited to have Sogyel here to help us dive deeper into that and really bring it to life. So, you know, what we're what we're seeing is, brands and retailers are getting more and more data-focused, and prioritizing your views as a core data source. So, you know, one thing that we're going to talk about here in just a minute is the way that retail sources have started using it to enhance the customer experience, which really kind of highlights that importance. So brands should be taking that same data and using it to answer questions about their, oh, we can go to the next one to get to know worse, to answer questions about how they should be speaking with their customers, to change their PDP, optimize their marketing campaigns, you know, understand how they should be evolving and iterating their products to create better product roadmaps and improve their positioning. But you know, also do things like innovate new products around the white space and around the consumer trends that they're seeing. So that's kind of a big overview of the types of things that we're going to look at today. So with that, let's get into our first our first trend here. Cool. And this is one that I'll talk about, because I've been talking about this for most of the year. And it's just something I'm still really excited about. We've done, I believe, a total of four webinars this year on different AI topics. And the big one, that's really the big trend this year that's relevant to all of us here is retailers prioritizing AI tools from a review perspective. So what we're looking at right now is Amazon review summaries on the left. This is Amazon's first consumer focused generative AI push. And they're using reviews as a data source to generate this. Earlier in the year, we were just seen this come out as something that was focused on a couple of categories. And a couple of skews. These were mostly at first high value, high-cost electronics. Some of them are somewhat niche, things that would target to, you know, perhaps higher earners, big spenders, things like Dyson air filters, that was one that we saw really early on some somewhat niche, high end, like pet focused electronics, things like that things that people would be very likely to leave a thoughtful review on, because they'd put a lot of money into it a lot of time into it or a lot of emotional energy into it. So Amazon was a be testing this, it was one of those things where, you know, we did internal surveys inside yogi and also did it with some some audiences outside. And we found that, you know, depending on the product somewhere between, you know, 20 and 40% of us, we're seeing it in the early days. And it was just something that your account might not even been part of the part of the test group. So a lot of people didn't see this for most of the year. But some people have been getting these review summaries on their product pages on Amazon for quite a while. And as the years went on, it's expanded to new categories, new products, it's went from dozens to 1000s of SKUs, which is clearly showing that the early tests are proving that by breaking down these hundreds and hundreds of product reviews, and using generative AI to create this summary, tight content that highlights the core positives and negative experiences about the product and the consumer sentiment behind it. They're increasing their conversion rates. So now's a good time to really quickly talk about what these actually look like. You can see an example on the left here, it's a little bit small. But generally they follow a somewhat templated format, they're going to pull in a couple of positives, a couple of neutral or negative themes that people aren't super excited about. And then whatever that lowest sentiment theme is whatever people are liking the least. Basically the idea is is that you should be able to look at that piece of content and understand in 10 seconds if this product is right for you just based on those top themes. Moving on really quickly to another big sign of this trend of AI from trained from reviews is is Google's shopping guides. Now this is something that is still in the early stages much earlier at this point than Amazon review summaries. It's not being rolled out to everybody yet. But if you search certain things and you're part of the test group on Google, you might see something like this on the right, where you get a shopping guide built for you and your specific question. These use generative AI, to pull data from reviews and from PDPs to understand what these products are going to provide for your specific needs. So in this case, the example is a five-mile commute that has hills. So they're looking for products that match the description of a bike with good ratings. But it's also going and trying to find ones that have positive customer sentiment in their reviews, around commutes, maybe even five-mile commutes, and doing well with hills. So it creates this this mixed media experience where they're seeing something about the types of bikes that they should be looking at, they're getting information that's going to help them make a better decision. Even if they don't go with one of the bikes that are listed below. Google is clearly focused on educating. But then they're also giving you examples of the bikes that they think you're going to be most happy with purchasing. So CL I think I saw you wanting to say something a minute ago, no, okay. So basically, all of this is to say is that the platforms that consumers are using the most to research and connect with products are already leaning heavily into reviews as a data source. And obviously, since we're in the review space, we're really excited when we see this because we see the power of reviews every day. And not everybody gets to experience that on such a frequent basis. So we're really excited to see this trend. We've been really excited to talk about it all year. And I'm sure it's going to be a trend that continues into 2024. As reviews get more and more important and inform that consumer experience in very direct and impactful ways.

Tiffany Serbus-Gustaveson 11:59

And it's so cool to as somebody who was a vendor on Amazon, those reviews, I just couldn't handle when a review was put in on our product. And it was because of the shipping. It was things logistically that was out of our control, and they love the product. But they gave us one star because it arrived late and nothing to do with us. And what I've noticed with this AI tool on Amazon, and definitely if people are seeing differently put in the chat, I'm not seeing that summary include anything about logistics, it's really solely focused on the quality of the product, what people are saying about the product, and omitting all that other noise, which is great for a brand because you're truly putting the spotlight on the product and not the other minutia that comes along with obviously, the delivery of the product sometimes. So that I think is very cool to watch. And to hear so many people this year use AI for holiday shopping, myself included, like now it's like another components of your holiday shopping experience. And research is now using AI tools. So definitely see that grind, very cool questions, comments, put into the chat that q&a, and we will get to them.

Sogyel Lhungay 13:09

Great, thanks. So the next trend that we're gonna look at is more actually, I think interesting for the marketers in the audience right now. So this is probably my favorite kind of funny insight that we found this year, it was around how consumers are talking about your product. And specifically we're looking at, at pasta, that spaghetti spaghetti. So we looked at three major pasta brands sold on amazon.com and looked at the reviews. And what we noticed was there was increasing an increasing number of American consumers just referring to spaghetti as noodles in the reviews. However, several well, two major Italian-based brands or Italy, based brands, actually don't mention noodles in their product title. They don't mention it in the PDP. But their consumers are using that language when describing their product. Right? They're like good noodles, you know, etc. So I think this is really interesting, because this is this is not like a new trend for 2023. This is something that's existed a problem that's existed forever for marketers, which is like how do you how do you talk about your product? How do you talk about it more like the way your consumers are already talking about it? And there are like tangible benefits from these things like having ranking better and SEO or was a high ranking higher in Amazon results as a result of of actually describing your product in the way that your consumers expect you? And I know this is this is I'm sure offensive to any Italian cuisine fans in our audience. But it is. The data doesn't lie. Our next one is something that I saw a big uptick in this year particularly so over this year. I think we're about five times that we got a question from our from From a large enterprise client, where the focus was really not on a product that they currently sold, but the questions were around a product that they're around a market or a space that they weren't in already, like they were either wanted to expand to an adjacent market, or they were looking at maybe an m&a acquisition target that they that they were considering, oh, how is how is this? As part of their due diligence? Can we look at how customer feedback for this product line is? So? And in addition to looking at data, we all they also want to know, well, if, if I, if we decide to move into this new market, how should we position ourselves to take advantage of existing gaps right now. So this is an example was a real example really of a of a customer that has a health supplement, it was a basically like a health supplement company, and they're looking to expand into like an herbal, more of a niche herbal digestive supplement. So one of the ways we looked at that was just by looking at the shape of the customer conversation. So this chart over here kind of describes this as a tree map that describes the the most common themes in reviews for this product set, they looked at 12 major competitors in this space that have already been there, some of them for a few years, some of them for many years, longer, like decades, we see that, you know, things like flavor and taste are it's the most common talked about topics at that almost a quarter of all reviews mentioning it, we also look at things like how effective it is at nausea relief, or at the impact on digestive health. And so that actually is really important, because one of the other questions folks have is like, what if we're going to introduce a new product, we have to understand what are the claims we want to want to make for this product? And how do we prioritize those claims, you know, when what is the problem that customers are most having right now. And so therefore, it needs to be spoken to the most. And so some of how we get to that is by doing keyword analysis. So we could take a look at the themes that we're talking about effectiveness of the product, and about using the product and we can see certain terms come up more often. This is part of a much larger analysis that got into very granular into different like symptoms, and which ones to sort of like classify as as the main claim, but it is a very practical and and and a novel use of of, of you know, reviews and user feedback. I think the the other point that this makes is essentially that you you have at your hands as a as a brand manager as a as a marketer, you have basically this like giant, this, this huge wealth of of essentially like an instant focus group out there when you have product reviews, because you've got your own products out there. But you've also got competitive products you can look at historically. And it just becomes like a it's sort of like a source of data source that is as close to the pulse of the customer as you can get. And it is constantly evolving. So you keep getting new new reviews every day.

Tiffany Serbus-Gustaveson 18:04

Absolutely. That's what I was thinking, I think this is the ultimate focus group, no longer need to get people in a room and ask them questions, you have 1000s that the bigger fingers.

Sogyel Lhungay 18:15

Yeah, and focus groups aren't cheap. So this is like significantly cheaper way to get to that. So in a way, it's also efficient. So that those are two themes that I think I want to hit throughout this is really just about prioritization and about being being like efficient with your with your funds. So this next trend is really around this Insights Wire that we put out this year. If you heard earlier insights wires, our like newsletter that we send out weekly, you can sign up for an online. So in one of our most popular insights wires this year, we showed we highlighted how targeted AI review analysis can be. So I don't know if you are familiar with this brand luminae. They make natural, like chemical-free like deodorants that you can use on your whole body, not just on under your arm. So if you look at this blue line over here, this is the average rating for the product over time for these last few years. This was a company that was bought by Harry's I think in the end of 2021, so maybe about two years ago. And you can see that it's really been in decline this whole time. It's gotten into this really like dangerous area in the sub three-star rating, right? However, if you look at it, if you slice it up a little bit more and look at actually the themes of what people are talking about, you can see in this groups in this green line, that when folks are talking and talking about the how well the product controls your sweat, they're actually giving it relative like better reviews, it's still pretty low, but it is on average better than your average rating is for this product. So it's it's so it's giving like an ops you know, like an upward momentum towards the reviews. And then and then on the flip side, you You have downward pressure coming from the scent of the product. Now this is the actual scent of the product, like how the how the deodorant smells not like how good it is at controlling odor, that's a separate theme. But by being able to like, isolate themes you can just look at when someone talks about the scent of your product, what kind of rating are they giving, and, and then you can kind of like get way more like surgical with with what to work on next. So that's that's what I'll talk about in a second. But just to sort of drive the drive home the point, these are some of the verbatims for this product. You have folks describing it, smelling like dog food.

Tiffany Serbus-Gustaveson 20:32

Like dog food. Wow. It's before you're applied on your body. Wow. Fascinating. Exactly. Button belt. Yep. So this is fascinating. Because in traditionally you would be like, Hey, do we just remove it from our assortment. And just phase it out? It's been a lot of good around this product is simply if you tweak one area, which happens to be the center, it could become this stellar five star product at once. Who has a capability of becoming? Yeah, yeah, totally cool.

Sogyel Lhungay 21:08

Definitely. Yeah, and there's, there's definitely a lot of different things at play here. It's not just these two issues. But but these are two of the main issues for this particular brand, right?

Tiffany Serbus-Gustaveson 21:18

Do prices ever change?

Sogyel Lhungay 21:22

The price probably did change, I don't have it in front of me, it definitely would have changed when after like Harry's bought it, it might have actually gotten cheaper honestly, to so that it can reach a large audience. But the main pitches that it's you know, it's like kind of chemical feed, and you can use that all over your body.

Tiffany Serbus-Gustaveson 21:39

That's my dog food.

Sogyel Lhungay 21:41

Yeah. So so. So like sticking with this particular example, I want to talk a little bit about what the evolution of have review analysis is going to be like for next year. So like I said, it's going to be more important as ever to prioritize where your funds are going. And you can do it by listening to the customer. So this chart, let me just explain this real quick. So the 3.15, that you're seeing on average for all of these, that is the average rating for this product for the last from May to May of 2019 to now. So what we're projecting here is essentially in the light green, this is the conservative case, for the star rating improvement that you would have if you address the issues around product sent. The dark green is the sort of the Reach case. And so somewhere in between here is what we estimate is like the bump up, you get if you fix this, this core issue, and people are no longer leaving negative reviews about this, and they're actually leaving positive reviews about your products as a result. And because we have human team analysis, and usually we will divide, you know, any kind of data set into at least a dozen to 20 Different themes. I've just highlighted four of the most dramatic ones here you've got products and concern sensitive skin skin concerns, sent duration concerns, and swept controls where control was at one from the prior slide that was the the green. So it makes sense that there was the least amount of impact from fixing that issue essentially, since essentially it's, it's already doing pretty well. So from something like this, you can now prioritize, oh, I really need to fix the product scent, or we need to reformulate it or we need to change some of the wording around how it's maybe we need to make it clear that the scent is for a certain type of person, or it's like unscented or whatever. So from here, you can see that there's almost an entire star upside from fixing the product sent concerns. And so I think this is like sort of the next stage of, of how to think about review analysis. And then really, once you have the star rating amount, you can actually then make even further assumptions about ROI. So looking at this from $1 standpoint, and we used some some estimates from various sources of sales data to estimate what their monthly sales of this of LUMION. So these are like directionally correct, but not they're not from the company. So it's not exact, but you can estimate based on the amount of ratings lift how much impact it's going to have on your eCommerce sales from in like an annual basis. So for this for address addressing products and concerns, you get anywhere between 30 32 million to 47 and a half million increase in annual sales. And this is just for one product. Obviously this is a product that is it's one of their standard, their best-selling products. It's their standard, one of their first product flagship products, but they have other products as well. So you can see if you do this in a systematic way you actually have a way to impact your bottom line.

Spencer Kelty 24:47

I also also just want to what I kind of chime in here a little bit because I think that this is you know kind of a big deal for brands the opportunity to not only be able to determine what themes that consumers are interacting with are going to really impact the way they perceive your products and the way your product is coming across in your reviews, but to be able to assign a somewhat accurate, ROI, impact and revenue impact to making those changes is pretty, pretty insane. Because, you know, I know that, you know, as a marketer, you're gonna hear a lot of a lot of questions about ROI. Anytime you want to change something, anytime you want to run a new brand campaign that changes, you know, something about the perception of your product. And, you know, same goes for product folks, if you're trying to change or reformulate a sense, you know, being able to actually change that product. And, you know, put the time and the money into, you know, making those reformulations. If you can actually come in with actual data, and a relatively accurate band that will show the revenue it's going to generate, that's huge. And I just saw a question pop up. Yeah, talking of are they asked, Are we talking changes to the actual product or changes the listing? Both? You know, one thing that I like to talk about is that, you know, it's a matter of how long down the timeline you want to look at, you know, you want to look at, you know, what you can do in a month, what you can do in three months for a product, that's not where you want it to be ratings wise, you're talking PDP, you're talking marketing language, and that can absolutely make a change. You know, one thing, I don't know a ton of details about lumen, you know, a lot of the details of what's, you know, the issue here, but it's an all natural brand, but it's also a brand that's owned by a major, a major company, it's a brand that's entering new markets, it's pushing more to acquire new consumers, these might not all be consumers that are familiar with natural deodorants and are familiar with the scent being a little different. They might be coming from a you know, a Dove deodorant, or an Old Spice deodorant, something that's very chemically chemically constructed and smells, you know, like detergents, more than natural products. So they might have different expectations, you know, so one thing that we talked about is, it's, it's a couple of things, it's setting different expectations in your marketing language and in your PDPs. And as you set those expectations, that will definitely change what happens in your reviews, partly because people come into it expecting something differently. And partly because some self selection happens, if you're explaining to somebody what they're going to have the experience they're going to have with your products. And it's more accurate to what the actual experiences, people that aren't going to have a good time are going to look at that and understand that they're not the right person to buy that product, which in turn will lead to those higher reviews coming in. Yeah, exactly. Um, you know, you would have to exact you'd have to promote it to to your customers, you'd have to go after, you know, different angles in the marketing side. But then, you know, I also want to talk about that long-term product change, you know, if the scent is actually bad, if it's a problem that people are actually having, and not just an issue of expectations, then after that three-month window, you know, when you look longer down that pipeline, you want to be looking at possible reformulation changes. I'm sorry to hijack a little bit here scale. But I do want to talk about a really quick, quick example that that's really similar to this. We worked with Tylenol, for a product launch that they had Tylenol powder, which was basically something that you poured on your tongue. It was a product that was underperforming where they wanted it to, it was well below the other Tylenol products in in ratings. And after they did some analysis of their reviews, they figured out two primary things. One was that people were using the product wrong or having the wrong expectations of how to use it, they were pouring it in a bottle of water and expecting it to dissolve, because they were used to things like liquid IV or emergency or elements or you know, whatever they're using in powdered form. And the other was that people were talking positively about it, in terms of it being fast acting. So they were able to make changes to the marketing and to the PDP to change. Some of the campaigns that were running on it, changed the PDP language even I believe make a small packaging change. And with those, they were able to raise the rating by nearly a full star. So it's it's definitely not just about product changes. It's about understanding how to match the product experience with consumer expectations, and then match the product and bring it along if it needs actual solid changes to the product experience to bring Up to the expectation.

Tiffany Serbus-Gustaveson 30:02

Good point, and great questions. So keep them coming. That's awesome. And the low-hanging fruit, like if you have r&d money, and you're going to focus on doing something that doesn't make sense, looking at this data, maybe you do tweak a few of these items that are on the cusp of doing, you know, amazing volume with your r&d spend, and I would assume to it's bringing teams together that normally maybe haven't collaborated in the past. Yeah, breaking down those silos, because the data is pretty much it's an aerial view of the whole organization. So it's very cool. All around. Awesome.

Sogyel Lhungay 30:37

Yeah, I totally agree with that. Like, there was a Spencer, when you're talking about this, this example about like, quantifying it from, let's say, the marketing team quantifying it for the R&D team. This is something that comes up all the time. Like, there's, there's often often like r&d will tell, marketing, this is an actual example. Like, there was a shampoo company, we worked with very, very, one of the major CPG brands, and then they, they were having issues with their ratings, their product wasn't selling, they had dropped, they had like a significant drop off after two, like two years ago. And there was basically like, this year along, you know, kind of a disagreement between pro between product, I mean, between R&D and marketing. And each was saying it was because of the other reason, right? And so we were able to do a very like deep dive analysis until looking at when certain when when basically when a reformulation happened basically, like the r&d side was saying like this, Rhian formulation, reformulation only improve the product, whereas marketing was saying it had a negative effect. And so we looked at, like the specific times that that the reformulated product was hitting the shelves and looked at the impact on ratings at that those periods and you could see a drop. And so then marketing was able to go back to r&d and say it actually is your concern. And yes, I understand that those are very, like we're now we're talking about in the span of multiple year-long fixes. But you know, I think that's where the quantifying part comes. Because you might find that there is there's a threshold over which you would be willing to go ahead and make that change, right. And so now you can put some dollars around it, as opposed to just saying, Oh, I think this is the number one problem. And I just don't know how much that you know, what the impact would be of fixing it.

Tiffany Serbus-Gustaveson 32:20

Yes. In an emotion.

Sogyel Lhungay 32:22

Exactly. Yep. So this, I think this is actually the last slide. So there's wanting to go into q&a from here.

Tiffany Serbus-Gustaveson 32:31

Okay, awesome. Let's see, we're gonna circle back. So regarding and when we started talking about AI and Amazon, this is true that yes, maybe they aren't talking about the shipping issues, or if there's packaging issues within that AI summary. But it does not change your star rating. So the star rating is still going to formulate how it traditionally has. But that AI, which I'm seeing more and more becomes your more your source of truth, because that's becoming the spotlight of what people are going to is going to amplify the positive and negative of the product only feedback.

Spencer Kelty 33:06

Yeah, let so let me let me answer how it is now and how I kind of think it's going to move. Yeah. So right now, you're not going to see shipping, handling those kinds of more transactional elements, they're not going to pop up in the the Amazon review summary. We also don't really see mentions of price come in, there are some value items that come in sometimes. So you might see something like, you know, maybe consumers are neutral on the value of the product compared to other options. But you're never going to see something directly about the price something directly about the seller directly about the shipping, anything like that. But yeah, it doesn't affect the rating. And obviously, rating is still 160, all I'll kick it over rating is still incredibly important, that's still going to have a major impact on where your product shows up on Amazon or any other retailer. But it's important to say that Amazon's not stopping here on the way that they're using AI in the shopping experience. I used to work with a company called constructor. And one thing that they did was basically take the way that consumers interacted on a website and match them to products that fit their consumer profile. And that's the kind of thing that Amazon is going to be doing more and more with this, like this is the product side it shows the product elements that have positive and negative sentiment. Once they're looking at that on the consumer side as well. And using the same sort of AI analysis for you as a consumer. It's not a big leap to say that those ratings as an absolute number are probably going to not be as important as they're more looking at what you as a specific consumer are going to care more about. So if you're a consumer that has shown in there in your past that you don't necessarily have a problem with long shipping, or you have more of a tolerance for, you know, damaged products and shipping and having to, you know, go and get a new one, or something like that. And there's a product that's rated lower than its competitors, but only because it has those types of problems otherwise better, you might get paired with that product more trend, it's a very clear change from when they implemented those, it was, like I said, nearly a full star rating increase. So it's something that is very trackable, it's, it's very consistent, it doesn't mean you're always going to get something that dramatic, but when you look at the ranges, it's going to be in that rage.

Tiffany Serbus-Gustaveson 38:38

Awesome, and it paid off. Question here, which sales platforms does Yogi integrate review analysis with?

Spencer Kelty 38:46

So I'm gonna I'm gonna make some assumptions here on on what they're they're talking about for sales platforms. Basically, any public review source, the reviews can be pulled from automatically. So if the reviews can be accessed publicly online, without a login barrier, they can be accessed. That doesn't mean you don't need a you know, doesn't have to integrate your Shopify account or anything like that. It's just directly off offline. If you are a DTC brands, obviously, your owner reviews are completely accessible. If you're using a bizarre voice, a power of use something like that, we integrate with those and can pull those in as well.

Sogyel Lhungay 39:27

Yeah, and also had we there are also aggregators that already exist like Google Shopping, or Google Shopping reviews. So we also pull stuff like that as well like third-party aggregators.

Tiffany Serbus-Gustaveson 39:37

Okay, cool. And what are the teams that usually work with if you're gonna onboard with Yogi who are the stakeholders that are in the room?

Sogyel Lhungay 39:50

I think the the titles that I see most are like brand managers are marketing managers. Definitely, folks in new product development and R&D, tend to be interesting, but that's I'm interested but that tends to be very company-specific. And some companies that are indeed like does not want to talk. And other ones they're way more involved in actually like the end product. Sorry, the end is like selling of the product. What are some other titles? I think we obviously we get like any analytical like customer insights, customer experience type of type of title as well. But I think product managers, probably the most, or brand managers the most common.

Spencer Kelty 40:29

Yeah, I'll, I'll add on that just kind of on broad themes. Anyone who is doing analysis on consumers or competitors, anyone who is doing anything to do with messaging, it's very impactful to anyone who's doing anything involving product creation or evolution. So to cast a very broad net. And a couple, one thing I wanted to mention because Siegel's example actually really highlighted this is you know, M&A, for example, is an interesting case that we're seeing more and more engagement with cases that are not about releasing a new product, they're about entering a new space, or purchasing a company and analyzing their products, one of the cool things that we are able to do is because we're using publicly available data, it's not just your products that you can analyze, it's the entire competitive space. It's a company that you're considering acquiring, it's a company you're considering entering their space as a competitor to them, you can go in and hijack their data to.

Tiffany Serbus-Gustaveson 41:37

Okay, so Insights Wire, you guys mentioned that where can the audience subscribe to that?

Spencer Kelty 41:44

Here. Let me drop a link in the chat. I'll do that in a second.

Tiffany Serbus-Gustaveson 41:52

You guys can subscribe to that newsletter.

Sogyel Lhungay 42:01

Yeah, and then M&A piece to what we've been seeing is it's not just like corporate development folks at companies or like, like the CMO or the CEO, the CEO like sort of ecosystem, but it's also like folks that are like in that are part of VCs private equity firms, like third party marketing agencies, they're interested in this in this information as well.

Spencer Kelty 42:27

Tiffany, it looks like for some reason, I can't drop a message to everybody I just sent it to us can you possibly drop it in?

Tiffany Serbus-Gustaveson 42:34

So yes, if you want to sign up for the weekly Insights Wire that is done by Yogi, you can sign up via that link, and start getting that newsletter, which be awesome. I'm sure. Like always, the media is always delivering awesome insights. Every time we have a webinar, I'm always learning something like ah, like, I was like, Oh, I wish I had that when I was working with Amazon would have been amazing. So Sogyel and Spencer, thank you so much for your time, and the expertise you've shared thanks, and everybody for joining today. And we hope to see you on our next webinar. And we definitely encourage follow-up conversations with the yogi team because they are fantastic at what they do. So with that, it is a wrap for the day, happy to be going into the weekend and happy holidays in New Year. So take care, stay safe, and we'll see you next time. Thanks, guys.

Spencer Kelty 43:23

Thanks, everyone.