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In this episode of the Customer Service Secrets Podcast, Gabe Larsen is joined by Jay Hinman who’s a pro at understanding what it takes to optimize search results to the fullest. It’s important for customers to find exactly what they’re looking for, or else they’ll most likely abandon a brand that doesn’t fit their needs. Tune in to learn more about how you can maximize your web presence with the right search terms.
We’ve All Been There
Picture this. You’ve got a big event coming up, perhaps a wedding or company dinner. You need a very specific outfit to look and feel your best, a nice green dress will do. The more you search online for the perfect dress, the more options you’re inundated with. Narrowing the search to, “long sleeve green dress, v-neck, short cut,” might do the trick, but yet again you’re met with far too many options to decide on just one. Finally, you find the right dress, but what about the size? What if you order the dress but it’s too big and can’t order the right size in time for the event? Talk about stressful!
VP of Marketing at Lily AI, Jay helps companies channel customers to their websites through optimizing search results with the right words. By doing so, it eliminates a lot of the stress for the customer by using specific words like green, v-neck, dress, and formal to lead them to the perfect product, meeting each of their needs. Brands like Gap and J.Crew have adopted this mode of marketing and have seen significant increases in customer follow-through purchasing. The intersection of CX and marketing can certainly produce fantastic results!
Digital Transformation Makes a Difference
Using a resource such as Lily AI requires brands to go through an immersive digital transformation and Jay finds that many leaders aren’t quite ready to do so, even though they’re totally capable. He uses the example of the ol’ reliable Google Sheet, which is so easy to use and broadly known across industries. When new software comes into play, some leaders freeze and can’t seem to move forward with the changes even though they’ll be helpful in the long run. This is often the case with companies that don’t know their product attributes or understand their customer context as well as they should, so undergoing a digital transformation is quite intimidating. Jay explains, “We’re kind of now in a world where the success of an e-commerce customer discovering what they’re looking for is really rooted in making sure that the retailer has a deep understanding of both their own product attributes and their ability to predict that customer’s intent.”
Fixing Your Search Results with These Three Changes
Jay gives leaders three tried and true tips for boosting search results that are easily applicable for any leader. The first is to, “Recognize that a product that is bought online has a lot more attributes than you might think and that you can capture this long tail of buyers by ensuring that you capture as many of those as possible.”
Second, Jay suggests acting on customer context and intent. For example, this means tracking if a customer likes mid-century modern furniture and suggesting furniture that suits their taste and their needs. If they search for a blue chair, this can be optimized to the customer’s taste by showing them a blue chair with mid-century accents like wooden tapered legs and a minimalist cushion design. This chair just might be the thing the customer ends up buying, even though they didn’t know they needed it in the first place.
Jay’s final piece of advice is to create an experience for your customers that is visually attractive because after all, we are visual creatures. “More than 85% of respondents respectively put more importance on the visual information, the stuff they could see, than the text information.”
To learn more about boosting search results with AI, check out the Customer Service Secrets podcast episode below, and be sure to subscribe for new episodes each Thursday.
Listen to “Understanding Search Results and Consumers | Jay Hinman” on Spreaker.
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Full Episode Transcript:
Boosting Your Search Results with Jay Hinman
Intro Voice: (00:04)
You’re listening to the Customer Service Secrets Podcast by Kustomer.
Gabe Larsen: (00:10)
Welcome everybody to the Customer Service Secrets Podcast. I’m excited. We got a special guest joining us today. His name is Jay Hinman. He’s currently the VP of Marketing at Lily AI. And today we’re going to be talking about product and customer intelligence, specifically focused on this kind of retail and e-commerce space. So before we get into that, Jay, thanks for joining and how are you?
Jay Hinman: (00:35)
I’m great. Thanks so much for having me, Gabe.
Gabe Larsen: (00:38)
Yeah. I pushed Jay just to the other day to join us on this podcast and he was kind enough to jump on. So I’m excited to hear the talk track. Tell us just a little bit about yourself doing what you guys do over there at Lily.
Jay Hinman: (00:50)
Yeah. So, I mean, as you said, I lead Marketing at Lily AI. We are based in California and we are a customer intent platform for e-commerce retailers. And really, we are focused pretty much on fashion and apparel, home goods, and beauty retailers. And we count Bloomingdale’s, the Gap, threadUP, J. Crew, and others among our customer base. And what they do is they use our product intelligence platform to help improve their site search, their personalization, their recommendations, their SEO, SEM, et cetera, really based upon making the customer experience better. And then we also have a customer intelligence solution that personalizes the shopping experience for every unique shopper based on –
Gabe Larsen: (01:30)
Those are the words that I think everybody’s talking about these days. Individualization, personalization. So you’re definitely right on that track. Excited to hear more about that as we jump in. One more question before we do, I always like to embarrass people. So outside of work, anything you’re passionate about? Hobbies, embarrassing moments, things you’re working on that you’d like to share with the group here?
Jay Hinman: (01:55)
Yeah. I think my problem is I always have too many hobbies, so it’s actually juggling those and going to work and being a father and a husband. But I try to run a lot. Running’s important to me, but I also write about music on the side and I have for many years, and I’m also a really heavy film snob. So that’s kind of what I’m spending my non-work time doing,
Gabe Larsen: (02:15)
Film. You got to double click just real quick on the film snob.
Jay Hinman: (02:21)
Film snob means that for years, even dating back to the dawn of cable, I’ve always dug into super kind of obscure films and underground films. And I just, I watch a lot of them and I love it and world cinema, it’s just one of my passions.
Gabe Larsen: (02:36)
Wow. That is, I do a little bit of Netflix when I can find the time, but it sounds like you’ve taken that way further.
Jay Hinman: (02:42)
The pandemic definitely helps.
Gabe Larsen: (02:44)
Right. I think we all spent a little more time in front of the screen. Alright. Well, let’s jump into this idea. Let’s start big picture. You obviously, I love this idea of retail and e-commerce and those companies, it’s been interesting over the last little while. What’s going on? What’s not working? Let’s start there.
Jay Hinman: (03:02)
Well, I think it’s dovetailing really with customer experience. We’re in a world now where it’s very hyper-personalized. Customers have been trained by the Amazons and Netflix of the world to expect to be shown what they want online, even before they know they want it. And so we had this like digital transformation going on in e-commerce that really was rapidly accelerated by COVID. And it’s now like two to five times bigger than it was even in 2019. But you find that these retailers are often, they fail to digitally transform and they don’t really keep their customers and those expectations really at the center of the experience. So what we often see at Lily is that the retailers we work with have some pretty outdated e-commerce stacks. They do things like they rely on simple tools like text-based keyword search and spreadsheet-based demand forecasting, or what they often do is they’ll take whatever product attributes that come over from the manufacturer of the product and they just kind of put those straight into their e-commerce sites. And so for simple products, like a consumer who’s looking for an all black men’s large t-shirt, which is pretty much all I wear, that’s fine. Men’s large black t-shirt, boom. But what about the consumer who’s looking for something like a floral print boho chic dress with lacing, right? We want to make sure that she finds what she’s looking for. So these thin and inconsistent product details lead to poor search results, non-usable data for demand prediction, but really, and most importantly, it hurts the customer experience and revenues.
Gabe Larsen: (04:30)
But it really is…the crux of it then is some of the underlying systems and technologies. I think I’ve said this on the podcast before. I love it. But one gentleman said, Gabe, I feel like I have this Frankenstack. We’re a 20 year old [inaudible] and but we’ve just kind of duct-taped this and wired here and stitched together this and it turns out to be a monster, basically. You mentioned the spreadsheet. It’s like we, I think people know where they want to go, but there have been these inhibitors, and sometimes it kind of starts and ends with this process/systems. Is that correct?
Jay Hinman: (05:07)
I think that is where it starts and ends because often the very first thing that happens is the item’s set so somebody gets in something from a manufacturer, they set it up, they input that stuff into their systems, and that’s where the problems start. Because if you’re only putting in those three attributes, let’s say it’s size, fit, and color. But your customer is the long tail of consumers who are actually searching for things that go well beyond that, they’re going to put in a search term, whether it’s for apparel or something else, and they’re going to get 78 results and two might be relevant, and that’s really frustrating and we’ve all been through it, right?
Gabe Larsen: (05:41)
So, the end outcome of this is that point you just said. It’s I’m a consumer. I know what I want and your example’s incredible. Lace, black, curly, round, it’s 12 attributes, or it’s something that’s potentially a little more niche and all I was able to do was look at medium shirts.
Jay Hinman: (06:01)
That’s right. And what we find is that because these retailers are kind of making these bad guesses about shoppers and inventory, it’s born out in some stats that are industry-wide, like there’s a 2.4% industry average conversion rate for e-commerce fashion and apparel, and return rates can be up to 50%. That’s also a function of how consumers buy these days. They like to buy stuff, get it in the mail, try it on, send it back. Then also average unsold inventory of 30%. So if you can just improve those numbers a little bit, make a conversion rate instead of 2.5%, 3.5%, because you’re now serving up the products that they’re actually searching for a huge, huge return in terms of revenue.
Gabe Larsen: (06:43)
Oh man, just that small, right? Game-changing. So you’ve got some industry stats. Yeah. I mean, it’s obviously a challenge and you really kind of honed in on conversion rates. Ultimately what this problem is hindering is your ability. I’ve got somebody there. They kind of stopped. They were dead-end. They didn’t convert over. So where do you go from here then? So obviously this is a challenge and not just, I mean, this is all e-retailers. Well, I mean, maybe some have obviously nailed it down, but how do you then help companies to start thinking about overcoming that? Because one of the challenges we face in our own business is this kind of old paradigm, a new paradigm, right? Like as example, tickets versus people. For ages and ages people have always kind of been, they call up, what’s your ticket number? How do I handle it? Now we’re like, how do we shift that moved to this new paradigm of what if someone called up and they were a person, not a ticket? It makes sense to people, but at the same time, it’s new. It’s kind of a new thought. Do you have a hard time getting people to make that shift in paradigm? And we’ll get into the tactics in just a minute, but any thoughts on, and maybe it’s the revenue that they’re losing or how do you get people to kind of get that aha moment to like, oh crap, I better change?
Jay Hinman: (08:10)
Well, I think a lot of it has been exacerbated by COVID and the fact that most retailers have digital transformation initiatives already. So they know that it’s important and then all of a sudden COVID happens and you’ve got this like $2.2 trillion growth in global e-commerce just during COVID alone. And the stats kind of come up like consumers get really frustrated. 94% of consumers say they usually get irrelevant results when they’re searching on retail websites. This is from IRC research last year. Or 76% of consumers say they’ll abandon a retailer after failing to find what they’re looking for. So all this kind of comes together and then they look at their spreadsheet-based demand forecasting and things like that. And they’re like, yeah. This digital transformation we’ve been talking about, maybe it’s time to actually set that into motion –
Gabe Larsen: (08:56)
Probably because spreadsheets are like the best tool ever in so many ways, right? I mean, how many Google spreadsheets do I create a day? I love to just create them and send them out. And oh boy, if they become like the defacto crunch that has ruined all of our business.
Jay Hinman: (09:13)
It’s because we all know how to do it. But honestly, I run my main marketing dashboard on Google Sheets because I know how to control that stuff and sometimes software is a little too taxing.
Gabe Larsen: (09:24)
That’s true. It’s so funny to hear. It doesn’t matter whether it’s just your business, our business. I was talking to a kind of data visualization provider and they were like, obviously, the spreadsheets are the death of them as well. So yeah, everybody, it’s such a great tool, but it’s such a bad tool. I love the stats. I think you’re, that’s the aha. They’re feeling it. COVID has made it worse. I think people see it, they see the digital transformation of their spreadsheets. So how do you start to help them fix it? Where do you start to go to say, “Hey? How do we start to go through this in a way that gets you from where you are to where you need to go to really meet this modern consumer and the expectations they have?”
Jay Hinman: (10:03)
Yeah. I think there are three things that retailers can do differently. And a lot of them are really waking up with this. But I think the first one is that recognize that a product that is bought online has a lot more attributes than you might think and that you can capture this long tail of buyers by ensuring that you capture as many of those as possible. So as we said, not just color, shape, and size, things like that. Think of your own shopping experience as a consumer. Like I said, searching for something, getting a bazillion different results, one or two are relevant, and how frustrating that is. That’s number one. The other is seeking to act on customer context and intent. This kind of takes it to another level, right? So you’ve got a shopper, maybe she’s searching on a furniture website for something that’s really important to her, like solid beige modular sofa and chase. And she has her own unique take on just what that means. So a really forward-looking customer intent obsessed retailer maybe has an anonymized sense of this person’s buying profile and even her emotional context. They might understand that she prefers a minimalist look because that’s what she clicks on usually, and they’ll present her with results and recommendations to give her a minimalist solid non-pattern modular sofa and chaise lounge set. And she’s like, this is like the sort of like, “Oh, I didn’t even know I wanted that, but that’s what I want.” Yeah.
Jay Hinman: (11:19)
And the retailer might also understand that she’s browsed and purchased similar home furnishings and simple colors besides beige. So they present color alternatives to her in ways that might delight her and surprise her and result in that sale or upsell that might otherwise not have taken place. And then I think the final one, and I think this is an important one, is really to embrace visual search because we’re visual creatures. And so shoppers tend to shop based on what they see. It’s not based on what they type or a description of a product. I’ve got some stats that I think are really important here. Like when shopping online for clothing or furniture, more than 85% of respondents respectively put more importance on the visual information, the stuff they could see, than the text information, which kind of goes without saying but a lot of retailers don’t do it. And then Gartner says that retailers who redesign their websites to support visual search will see their digital revenue increase by 30%, which is a lot.
Gabe Larsen: (12:18)
You mentioned a few different things there. Maybe we can go back through them but the visual is…wow. Yeah, that is so important. I got stuck on that one because I don’t really like going out anyway. I’ve become one of these e-retail shoppers that buy, gets it, tries it on, and goes, but I love the written, but man. If I can’t see it and try it on virtually or put the couch in the corner and kind of see how it looks in my room, I need that across the business, and as a remote person, it seems like it’s even more important. I forgot what point one was. What was your first thing? Say that one more time.
Jay Hinman: (12:58)
It was really sort of the crux of the matter, which is like that every product starts with a set of attributes and most retailers only go for what the manufacturer has given them. So recognize that something that’s brought online has a lot more facets to it than you might think. I’ve been at Lily for only about six months now and there were things I had no idea that exist in this world, like cottage core or boho chic or things that actually describe things that people in the fashion world who are like shoppers of dresses and handbags, things like this. This really means a lot to them. So they want to search for those things and they want to make sure that you serve up a boho-chic result and not just a black handbag. And so this means a lot to them and that’s how you convert people from two and a half percent –
Gabe Larsen: (13:41)
For someone who’s not an expert in that, to your point, I’m kind of thinking…well, man. How deep could that rabbit a hole go? I mean, you got size, color. I mean, isn’t that about the gist of it? Is it, I mean, what is it usually like? 15? What’s the number?
Jay Hinman: (13:54)
Yeah. I would say you can go up to around 15. You can even go up to 20. But just think of a jacket, right? It’s going to have a certain type of neck shape. It’s going to have a certain type of lapel. It’s going to have a certain type of belt on it. It’s going to have fabric. It’s going to have a feel. It’s going to be part of a style. It’s even going to be part of any occasion. So is this for a party or is this formal? And you start capturing things like formal versus party versus informal versus loungewear. That really makes a difference in searches as well.
Gabe Larsen: (14:25)
Yeah. That shows you my basic mind, but it’s funny. I think it’s fairly basic, but then, you’re right. When I go on things and it’s not just clothes. I mean, you’re buying a TV, and all of a sudden it’s like, I needed this, this, click, click, click, click, click. Pretty soon, you’re down ten characteristics.
Jay Hinman: (14:44)
Right, right. Like I think something like a basketball, you’re not probably not going to do much with, but things like fashion and apparel, beauty products, and home products, these are kind of what Lily focuses on. These all have a wide range of attributes.
Gabe Larsen: (14:58)
Yeah. Yeah. That makes sense. People always like stories of how this kind of translates in reality. Love kind of the principles, the three things you think retailers need to kind of think about in order to make that change. Any stories come to mind to help illustrate kind of how somebody or a brand did make that transition and where it ended?
Jay Hinman: (15:16)
Yeah. I think my favorite one is with threadUP. ThreadUP is a Lily AI customer. And so if people know what threadUP is, it’s really cool. It’s a resale platform basically online and they have 35,000 brands on their platform from Gap to Gucci. And then 10,000, no, I’m sorry, a hundred thousand unique items come through and are processed every single day.
Gabe Larsen: (15:37)
I’d say that’s a couple, right?
Jay Hinman: (15:39)
That’s a lot. But on the site, you’ve got 2.4 million items listed at any given time because it’s all resale stuff. So like how does threadUP make sense of it? So what they did is, as I was saying, they embraced visual search and social commerce at the same time to make it really easy and fun to shop on threadUP and really embrace where customers are at today. Customers are on social, they love influencers and they’re often inspired by the clothing that’s worn by these influencers. So threadUP, we’re in a unique position to take images that were submitted by their own customers and they’re using Lily AI’s AI to visually scan and tag these images and then kind of put all those attributes out there. So Lily AI identifies threadUP items that are similar to an item in a photo. So it’ll scan a photo of an influencer and say, “Okay, these are dresses that look like the dresses that she’s wearing.”
Jay Hinman: (16:25)
These are handbags. These are shoes, these are whatever. So they call it thrift the look and it’s right there on their site and it is seriously one of the coolest shopping tools I’ve ever seen, even though it’s not explicitly targeted at my quote-unquote demographic. But it’s yeah, thrift the look. If you can check it out on the threadUP site. And so we’re now tagging 275,000 images for them every single week. And it has boosted threadUP’s sell-through by 15%. So I think it’s a great example of embracing visual search and social commerce at the same time and having really great results with it and a lot of fun too.
Gabe Larsen: (16:59)
Fun. I like the example. It’s called thrift the look? I’ll check that out. We may put in the show notes for the podcast. Okay, well look. All good things must come to an end. Really appreciate you taking the time, Jay. Fun story. Like the problem, like the solution. Maybe I’ll do this before we wrap. We did hit on a bunch of stuff. What would be kind of your closing arguments here? Your summary statement? We hit on a bunch. What’s kind of the takeaway for these leaders who are maybe just recognizing this problem? Starting to take the change? How do they get going? Where do you direct them?
Jay Hinman: (17:36)
I think like, well, I would certainly direct you to Lily.AI if you want to learn more about it. But I would say like the closing argument is we’re kind of now in a world where the success of an e-commerce customer discovering what they’re looking for is really rooted in making sure that the retailer has a deep understanding of both their own product attributes and their ability to predict that customer’s intent. And so when the retailers are actually investing in this stuff, understanding customer context and intent, they’re going to have that increased conversion, the larger order sizes. And they’re going to make sure that the customers return to the e-commerce sites over and over again.
Gabe Larsen: (18:11)
Yeah. Like that. Yep. Okay. Makes sense. Alrighty. If someone wants to get in touch with you to learn a little bit more about this, where do they go? How do they do it?
Jay Hinman: (18:19)
Yeah. So check out my LinkedIn. I’m Jay Hinman. H-I-N-M-A-N at Lily AI, and then just come to our website as well: lily.ai. And there are plenty of resources there that sort of outline some of the stuff that we’ve talked about. There are webinars you can watch and so on.
Gabe Larsen: (18:34)
All righty. Well, Jay. Really appreciate your time and for the audience have a fantastic day.
Jay Hinman: (18:40)
Thank you so much, Gabe. Appreciate it.
Exit Voice: (18:46)
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