We’re kicking off another episode of RETHINK Retail with guest Brian McGlynn.

Brian is the General Manager of E-Commerce at Coveo, a market-leading AI-powered relevance platform that injects search, recommendations and personalization solutions into digital experiences.

Brian is a long-time tech industry veteran with 20 years of experience building and hyper scaling organizations. Prior to joining Coveo, Brian held leadership roles at Intershop, Hewlett Packard, Deloitte and IP.com.

Join us as Brian reveals how every day retailers can compete with commerce giants like Amazon—and the tools they’ll need to do it.

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Hosted by Julia Raymond Hare
Produced by Gabriella Bock
Edited by Trenton Waller
Social Media by Madison Freeland

TRANSCRIPTION

Julia Raymond Hare:
Hi, today we’re kicking off another episode of RETHINK Retail with my guest, Brian McGlynn. Brian is the General Manager of eCommerce at Coveo. They were founded in 2005. They’re a market leading AI powered platform, and they inject search recommendations and personalized solutions into digital experiences, which of utmost importance as we all know today.

Julia Raymond Hare:
So, Brian, you’re a long time tech industry veteran with 20 years of experience building and hyper scaling organizations. You have a super impressive background prior to your role at Coveo. You held leadership roles at Intershop, Hewlett Packard, Deloitte, and IP.com. So I’m so happy to have you here today to talk a little bit about AI and where retail’s going on both the eCommerce and brick and mortar side.

Brian McGlynn:
Great. Well, thanks Julia. Glad to be here as well. And certainly excited to talk about the space. I can’t think there’s been anything that’s changed more in the last two years. Even in 2019 lots of things running away, but you go back and forward to now, and where we are at this point, so a lot of great things to talk about. So thanks for the invitation to come in and chat today.

Julia Raymond Hare:
Absolutely. It’s great to have you on the show. I think the one thing that stands out for me is the expectations consumers have are astronomical now, when it comes to retail.

Brian McGlynn:
Yeah. I mean, you look at it and very good point on that. You go back to even 2019, where we would really… When I joined Coveo, and even what brought me to Coveo was a managing company in America, it’s called Intershop, an eCommerce platform. And just the expectation that customers were even then starting to look at, competing with the likes of Amazon, competing with the likes of, you think even the ones that influence our lives outside of some of the eCommerce parts, such as Netflix or what Uber and the others have done, is really the way that clients expect to use something eCommerce, to use something online. They expect things to be better than the in-person aspect. And we saw that in 2019, and then as 2020 came along with COVID, that shut down the in-person channels for most of the world. And what it did is it really outed to those experiences that were good, and those that were subpar.

Brian McGlynn:
And just recently we looked at our part, we did a relevance report, where we surveyed I think upwards of 2000 shoppers and others certainly that use the service out there. And we found is that 90% of consumers, that’s 90% expect the online experience to be equal or better than in-store. And from that part, certainly a large area from there. So you look at grocers, we look at others that are in the home hardware section as well. People wanting to go in and get that experience has just been a big thing for us.

Julia Raymond Hare:
Wow. So 2000 shoppers were surveyed and 90% said better or equal experience digitally as in-store?

Brian McGlynn:
Yeah, absolutely.

Julia Raymond Hare:
Wow.

Brian McGlynn:
And it’s tough to go into, and you think about it. We’ve got to go in and break down what it means to be a great shopping experience. And in many cases, that it’s a matter of, you think about the analog world, where someone goes in, that walks into a store, a sporting goods store. They want to get or they want to, really a couple things. They want to, whether it’s a shopper that’s on a mission, directionally going in, find something, buy it, bring it out, or someone that’s going in there for inspiration. But what they expect is they’ll find what’s relevant to them. They expect to find service staff that can answer their questions, answer them efficiently. And ultimately, even a part as well, you look at specialty stores that are competing with the likes of Walmart and others in the analog world, were going in where there’s inspiration and knowledgeable staff, in many cases as well.

Brian McGlynn:
We’ve got, for example, one of our customers is actually in the DIY business. And actually, the fourth largest DIY store in the world. They came forward, and part of their whole site redesign was to bring in, not just the point of, “Hey, I want to go in and buy a barbecue. I want to go in and buy nails,” or something like that. They wanted to get where they can go and look for videos about how to use barbecue smokers and other parts like that. So as customers go in, they can go in and not just acquire, but also be inspired by the various different parts that are out there as well.

Julia Raymond Hare:
And that’s huge. I know you said your client is the fourth largest DIY store in the world. And we can think back last year when everyone was really bored in their house, looking for activities and just how bad a lot of the sites were compared to today. I mean, they’ve made huge changes over the last year and it’s so needed. And I think that there’s a cross section, when you talked about the shoppers, how they want that experience digitally and in-store, when we shop in-store, we’re also using our phone most of the time as well. So there’s no way of escaping that side of it. You guys work with Famous Footwear and Polaris and some amazing brands. What do you think some of their takeaways were from talking to them in the past few months, now that we’re midway into 2021?

Brian McGlynn:
Well, we’ve certainly seen, like for example, you have Famous Footwear, one of our customers that came on board along with part of the Polaris family. They went through a pretty large redesign and worked with us across that, replacing some legacy technology and modernizing their experience. And part of it is, the challenges for online that often get left behind is first of all, retail. But 50% of the traffic, that goes to a site, in some cases in B2B it’s upwards of 90%, but in retail, it’s about 50%, is the search. And I always say, anecdotally, “You don’t Yahoo something, you Google something.” So it’s a matter of where those wars were fought 10 years ago, 20 years ago. And clearly, the public is really having that question and answer, we’re attune to that, just like walking into a store, asking an associate where something is located, where something is. People like to ask questions to get answers to that.

Brian McGlynn:
And site search is one of those unsung heroes in a lot of cases. And you look at Amazon, that is the primary interface and others, is where people will go in, pose a question and look for something to come back. And that’s really when we look at with being able to provide that best in class experience, it’s a thing where people go in, they expect that, to where they type in information, whether it’s on their phone, if they’re in a store shopping for something or others. And that’s the case with Polaris, where the focus was getting an experience to go in, where people could look for inventory that would be inside their location. They could do based on the size, based on models, in the various different shoes that they’d be selling.

Brian McGlynn:
And at this part, being able to go through and really being relevant to that. So where a sales associate’s not showing you something that they don’t have in your size or in what you’re looking at. These are things that seem trivial when you think about it in the analog world. But when you go online, there’s a lot of tech limitations and other parts that have really precluded early technologies from being aware of inventory, being aware of location, being aware of taste, color, and other items like that, to present really to the user, what they’re looking for or what they might be looking for.

Julia Raymond Hare:
And you touched on Amazon a little bit there. I know Wayfair as well. They’ve set the bar high when it comes to site search and not customer experience necessarily in terms of discovery, but for search, if you know what you’re looking for. But for the everyday retailers, maybe midsize, maybe mom and pop, do you think it’s possible for them to compete with the big giants or how should they be thinking about the competition?

Brian McGlynn:
I think they absolutely can. And we’re seeing this a lot and really play out in many different cases in the B2B world, around marketplaces and certainly in retailers. You think about Main Street, the big box stores came in and did a number on Main Street. And now Amazon is kind of the next phase of the big boxes that are out there. But we’ve talked about some of our customers that have come in and really looked at a content rich experience.

Brian McGlynn:
So Lee Valley, actually a Canadian hardware retailer. It’s a big Coveo customer. They’ve gone through an embarkment initially to bring in and fix site search. So if you’re searching for a glue gun, you get a glue gun versus a nail gun. And these are the things that are common and rampant with site search. Once again, over 50% of their site search or site traffic goes in. Part of it is really going to that next level to be relevant. In this case, where they specialize in tools, they specialize in really aiding users to work on their houses and other items like that, where companies certainly competing with the likes of Amazon can one, use the technology to equalize, to go in and get that same kind of a search technology. And two, use the ability to go in and augment really know how, enrich content around it.

Brian McGlynn:
So shopping online is not so much an experience of, hey, I want to find a doorknob that does this, but also learn about what it is. Okay, well here’s how you use a router to go in and add a doorknob or add a door jam. In this point as well, here’s a router you should look at and here’s another particular item. And have it all be inventory ready such that when a person would go to a local store, they’d be able to go in and have it all pieced out at this part.

Brian McGlynn:
And that’s something that where, to compete with the likes of Amazon, it really comes down to is that curated experience and being able to do it. We look at, at Coveo, one of our biggest, really our item we take out there into the market, one of our phrases is we we’ve democratized AI. And that’s really what we’ve looked at is you take, for example, Wayfair. They have 2,300 different developers on staff working with the furniture. It’s massive. So a company that’s going to go through and literally, if you’re not in the tech part, if you’re a furniture reseller, your core competence is around getting furniture out to the market, procuring it, getting the best mixes for your customers. Not necessarily writing code and developing artificial intelligence.

Brian McGlynn:
So what we’ve done is really take it, not for our own purpose, but take all of those particular learnings, a lot of the research, and make it available such that a home hardware reseller, or a footwear supplier, or an auto parts supplier can go in and use that intelligent search and product recommendation and personalization items to drive that experience such that someone gets really that kind of a white glove experience that they would expect at an in-person store.

Julia Raymond Hare:
And it sounds to me like this is the… It’s here now, but it’s also the next era of search and having that curated experience.

Julia Raymond Hare:
So it’s like, “Okay, you’re looking for this type of dress. You could dress it up or dress it down and here’s some examples of models doing that.” And it’s a video, it’s not just static. It’s something that is going to take the experience to that absolute next level for customers.

Brian McGlynn:
Yeah, I think altogether that’s really the inspirational shopping aspect. We acquired a company called Tooso about two years ago that develops a really interesting vector technology and knowledge graph technology with that. And knowledge graph, really, it’s a fancy way of describing a relationship between products. To know that, well, here’s a particular bag, here’s a set of shoes, here’s the dress. These are all related items. They’re different, but they work together.

Brian McGlynn:
The whole idea with that is that then you couple that with natural language processing to understand what someone’s intending. So the hard part, you go in and you take, for example, going into your phone and doing a search saying I’m in New York, I’d like to buy a dress at four under $500 in color blue. Can you help me find it? And being able to do that. So looking at dress, $500, looking and taking those strings of texts and converting that into actual meanings and words, it’s not an easy thing to do from computers. It has to understand what each individual token means and what it means in context. Well, this is a price field. This is a color field. This dress is an item. And then going in location. New York. Is it New York City? Is it New York state? Then being able to go in and pick up all those clues that are either explicit or implicit and use that to go into what can be millions of individual items between colors and variations and what’s available in different sizes, and bring that out to where you can express it.

Brian McGlynn:
Whereas if you’re dealing with a personal shopper, if you’re dealing with someone at that part, sure, it’s easy as a human being to say that. Our brains are processing that. But it comes down to a very difficult problem for technology to go into.

Brian McGlynn:
We’ve done an enormous amount of research on that. We’ve published several papers. We have products that are coming to market around that as well. We either call discovery tags, or are we going with we call it personalization to go. And the whole idea is being able to look inside the product space, the catalog space, understand those interrelations and bring that.

Brian McGlynn:
We definitely see a lot of trends. We’re in the space, we’ve seen other companies going into this as well to really, with us, complete the look or really just understand what it is. What it is is people want to do two things. They certainly want to retain the customer and make certain that the customer’s satisfied, otherwise they bounce out very easily from one digital experience to the other.

Brian McGlynn:
The other is to extend that relationship. So, okay, here’s a [inaudible 00:13:58] wallet. What can we do to augment the look or augment what somebody is looking for if they happen to be in fashion? Or in the DIY space, the same thing. Being able to augment and say, “Okay, well, here’s what we have for additional tools. Here are DIY videos. Here are other components that are there,” and string that together to where the benefit to the customer, they don’t have to go shopping at different locations. They can get inspired and really feel really happy about what they’re going to.

Brian McGlynn:
And from the brand’s perspective, it’s the ability to really get a person, not just to be a single transaction, but develop a relationship where they spend time and work with the customer on a long period of time as well.

Julia Raymond Hare:
Mm-hmm (affirmative). And Brian, you brought up great points. I think everyone who’s listening and think of a time when they had a really bad search experience or bad app experience.

Julia Raymond Hare:
I love Instacart, but I’ll just throw one out there. I purchased little chocolate wafers called Knoppers from Aldi, and they delivered baby wipes. That was the recommended product substitute. I was like, “I don’t have a baby. Do I have someone else’s order?” So that was something I kind of laugh about, but it’s also just it comes down to whatever database or relational suggestions were in the engine. It just did not pan out. And I think what you said, retailers don’t have the staff and the money to have incredible developers and data scientists working on this. So you really do, in a lot of cases, need to outsource this if you want to have that good experience.

Brian McGlynn:
Absolutely. When you bring up, it’s funny. I mean, it’s comical. It’s not comical probably when you opened it at first expecting Knoppers and then end up with baby wipes. Well, you can’t eat them. Maybe clean a few things off or whatever. It’s crazy. It’s comical and you look at it from the outside.

Brian McGlynn:
We did our relevance report and we certainly found that difficulty finding information is huge. 42% of the respondents found that was actually a big turnoff at this point. Actually, from a revenue opportunity perspective, 43% said they’re willing to pay more if they find things in just a few clicks. It’s interesting that just relevance and being able to get there, it’s such a quintessential part of every experience.

Brian McGlynn:
To your point is that you can have the most beautifully designed user interface and flows and even check out, even deliver something in a short period of time. If it’s baby wipes when you were looking for cookies, you have a major fail at the whole experience. And that’s where you see 90% of people will churn out from an experience that way. It’s a non-trivial thing to fix.

Brian McGlynn:
For Coveo, since 2005, these are the sorts of things we’ve been fixing. And we’ve been going through and working on that and getting things set up and just going in from there. We have some good stuff that has been going in. We’ve got some good items that are really going in there. And that’s just the key part from what we see on different parts as well.

 

Julia Raymond Hare:
Cool. I think that’s a good one, right? Because it’s usually the high ticket items that are the most ridiculous when they’re recommending them again. Yeah. Okay, cool. So Brian, when we talk a little bit about recommendation engines, they’ve been around for a while. What are some of the biggest faux pas you see even today, knowing that this technology is advanced?

Brian McGlynn:
Well, It’s definitely, we look at a couple of things, misreading the customer. When you think about recommendation engines, a lot of it is to do it from a customer journey centric perspective, versus a product centric perspective. This is more when you’re in the product space, you really have to go in and look at marrying the aspect of the user, understanding your user space, understanding the product space and putting them together. So going in for one, looking at a 4K monitor. There’s a few things and just one, it’s not always the high ticket item, it’s the high margin item to look at as well. And understanding the user that there’s there’s a difference of a person that may go in and look at buying a $200 stapler versus a $1,000 laptop. These are signals that we’d look at to see that these are items that okay, someone has a propensity to buy high margin items, and they’re not necessarily as price conscious, they’re more performance conscious.

Brian McGlynn:
So we’d understand those vectors about what a user would be looking at and then as well, looking at, “Okay, well, if they’ve looked at 4K monitor and they’ve purchased one in the past and they’ve gone through, let’s recommend a soundbar.” And at this point we can start to recommend items that may be higher in margin or better propensity for a person to buy. As opposed to having to drive them down into, “Well, you clicked on this, therefore you’re in this segment, therefore you’re in this segment, this segment.” Doing that in an automated manner to where it scales. And that’s the big thing, being able to go there is to an end-user dealing with a human walking in, talking to a person. A good sales person can go and engage what their interest is in. And at this point as well, seeing recommendations that are there, some of the cases we come in they’re off the wall, or just totally irrelevant. You’re buying kitty litter and it’s recommending wine at this point as well, or other particular items.

Brian McGlynn:
Maybe there is a relationship to it. Probably not. They listed something as ultra-personalized. If it was personalized, “Okay, yeah. I’ve got a kitty and then went in and I needed to get some Rose at the time.” But chances are for someone who’s going in cold start, there’s usually some kind of a relationship in the journey that we want to stitch together. And that’s by understanding that the actual product space in the user, we can come up with more relevant recommendations along those lines.

Julia Raymond Hare:
Excellent. Yeah. I was thinking about all the single cat ladies out there who are getting their wine.

Brian McGlynn:
Yeah. Kitty litter and wine.

Julia Raymond Hare:
Crazy cat ladies. No. I’m just kidding.

Brian McGlynn:
You never know.

Julia Raymond Hare:
And Brian, outside of churn, are there any hidden benefits that retailers you work with don’t think of initially when they partner with you that later they realize, hey, this really helped having a best in class search capability because now I’m experiencing these other benefits?

Brian McGlynn:
Absolutely. We’ve made it certainly a good business, helping retailers along those lines. The ROI, we look at other business items as well. When you buy an e-commerce platform, it’s kind of a do or die. You install it. There’s areas where it needs to work along those lines. Where you go in, and we’ve worked a lot with retailers as well helping their customer service, where we’ve gone in reducing unnecessary calls by helping people find solutions to problems online.

Brian McGlynn:
For us, where we go in with search through recommendation and personalization, there’s a very, very strong ROI. We’ve seen some of our clients anywhere from 20, 30, we’ve seen some that have claimed up to 300%. But we definitely see things in the 20% and 30% increase in conversions on products with search. So we see it where, time and time again, we install…

Brian McGlynn:
… on products with search. And we see it where time and time again, we install and very quickly we see a bump, and then it just continues to go up after that as well.

Julia Raymond Hare:
That’s amazing. It’s the small incremental fixes and improvements that really do make a big impact, so it’s exciting to hear that. And as someone who works in this field, are you seeing any other e-commerce trends that are exciting you that are definitely tied back to artificial intelligence, or anything you could share with our audience that’s the next thing?

Brian McGlynn:
The big thing we’re looking at really got a lot of people scared, I think more than anything else. You look at-

Julia Raymond Hare:
Oh, boy.

Brian McGlynn:
Especially retailers, anyone in marketing technology is… I mean, there are the threats of Amazon coming in. They’ve been there. We certainly see that. It’s interesting, is even with COVID, Amazon was really… The brick and mortar actually had stronger growth, many cases, those with e-comm. So we’ve seen the benefits on it. Part is with Google and Apple, and certainly others are bringing in restrictions on cookies that people are going to be installing, and really first and third-party data where a lot of the traditional personalization engines require to do that. And what I mean by traditional, personalization engines and others would use collaborative filtering, other particular technologies where they’d look at thousands and thousands of transactions, try to find similarities with that, and use that to create recommendation models, but required either additional data…

Brian McGlynn:
And it required a substantial amount of interactions to get to a point where things would go in. When that shuts down… And Google announced it. They made a pause, but they’ll certainly bring that up. Retailers, and anyone doing personalization, needs to really look at it and go through and understand things better, and really look at different technologies. So we introduced something called personalization as you go, where we looked at products as opposed to going through and looking at what people have bought in the person space. We actually attached a lot of machine learning and artificial intelligence to the product space. [crosstalk 00:20:06] product space, what it’s done is it allows us to build intelligence into that. And give you an example what it would mean is a person walking in with cold start, just investing in our technology, turning it on.

Brian McGlynn:
We’d be able to go in where someone would search, for example, like you would if you go into a store. Suppose you go into a sporting store, and you go in into the golf section and pick up a pair of pants. And then the associate comes by and says, “Hey, can I help you?” I say, “Yeah, I’d be interested in some gloves.” Well, if you’re in the golf section, it’s very easy to really make that connection. Online, it’s very difficult, unless you’re looking at it from a map of the products or a map of the content. And that’s something that we’ve been able to do, is go through and provide that means for people to go in and navigate through the various different sectors and space at that point, such that in a short period of time, you go in, you look at golf pants, and then you may say, “I’m looking at a club,” or, “I’m looking at a ball.”

Brian McGlynn:
And at this point, balls pop up, and they’re golf balls as opposed to tennis or baseball or footballs it may be at this point based on the browser’s behavior. So these were areas where we start to limit the negative impacts of where being able to have massive amounts of machine learning models and others, and it’s still taking a mass personalization effect as opposed to really a highly-personalized approach, where based on what somebody’s sector is by truly understanding the data that’s there. And ultimately, once again, really… Well, for us, the gold standard is taking that best experience that you’d see in a store and being able to mirror that back down to the individual with how they go shopping, or how they work inside an organization.

Julia Raymond Hare:
Very cool, Brian. So I think I’m understanding this correctly. In terms of the personalization as you go, what you guys are rolling out, that’s coming soon?

Brian McGlynn:
Yep, exactly. And these are things that we’ve got a couple of customers. We’ve been soft rolling it out, so a lot of customers are using pieces of it, but we call it personalization as you go. And this is something that we brought in to really address that, and so we have other items that are part of it, such as tags to help do discovery. We may search on pants, and it says, “Well, here’s golf. Here’s a dress. Here’s other parts around that.” And by understanding the product data and understanding people’s interaction with it, you can bring these items out, and it really comes down to really mimic, at this point, a personal shopping assistant, whether it’s sporting goods or clothing or going through and looking at DIY, any of these sectors, especially when there’s hundreds of thousands of skews that are in there. This is where we’re really able to derive that intelligence and bring that part back in as well.

Julia Raymond Hare:
That’s excellent. So there’s a quicker go-live time, I’m assuming, because you don’t have to rely on a lot of historical first-party data from your clients. You can get going pretty quickly.

Julia Raymond Hare:
What advice would you give to a retailer who has not yet adopted a similar technology to what you guys offer at Coveo yet?

Brian McGlynn:
It’s amazing. It’s eye opening. We work with customers. Is search… In many cases, clients will go in, and they’ll first become transactional. They go on, they’ve sometimes bought generation-one search for those armies of manual merchandisers out there trying to guess in kind of a whack-a-mole capacity what a user is going to type, and build lots of logic and rules. We’ve had customers that have had six plus people that are out there trying to just guess and manage the search component. You just really can’t guess what people are going to come out with. Not to mention, things change, seasons change, items come out there. So there’s a lot of older-generation tech that’s out there, and what happens is it trips up on a regular basis. So a lot of our business…

Brian McGlynn:
So we had one where a CEO of a large sporting goods store was on his private jet, and had sent an email to the CIO saying, “Search is terrible. I can’t find anything, get it fixed.” So we got called in, and we went in to fix that. And there’s a lot of those items where we’re going through and looking at it, and I think people need to look at it. Even though the search box is a small box, it’s inside a webpage or inside an experience. Especially on mobile, when you start to look at it, it really… Beyond browsing and a lot of that, the search is really the brains and the intelligence, and that window into finding information. So once you’re in there and you’re providing search and you’re looking at it, then you can go in and start making recommendations on content and products and other items, but to really go in and prioritize that…

Brian McGlynn:
And it is actually the lowest-hanging fruit from revenue, being able to go in and say, “Okay, how do I add 20% more revenue to my site? How do I go in and increase the long-term value of a customer, or increase revenue by 10, 20% per session for our customer?” These are ways where very quickly customers can do that, and from a business perspective, grow revenue. From a customer’s perspective, provide a superior experience, where they can interact with the brand. So my biggest thing to a lot of customers to look at is prioritizing things like search, product recommendation, product listing pages, really the brains and the relevance behind it, and look for ways where they can differentiate and stand out up against the Amazons and the Walmarts and the others of the world that have massive amounts of skews, but not necessarily the amount of depth around what they provide in their part.

Brian McGlynn:
And that’s where it’s a case, and surprisingly, for a lot of customers, they find the ROI is very, very strong and very, very quickly realized as well. So that’s one of my biggest call to action for customers to be relevant, certainly going into holiday seasons and others, is to look at just the experience of that, just the information experience that’s out there.

Julia Raymond Hare:
Well, I thought of another question now, Brian, because I’m thinking back to my own personal experiences shopping online, and there are some sites where… I mean, huge retailers where you have to put in so many filters as the person searching, because when you searched and nothing really comes up, and you just have to check off all of these boxes. Why is that? Why is it set up like that so often?

Brian McGlynn:
It’s old technology.

Julia Raymond Hare:
It’s a short answer, yeah.

Brian McGlynn:
It’s the biggest frustration. It’s old tech. We spent a lot of time… We have dynamic navigation experience. We actually do this for a couple of our customers, where we’ll limit the number of filters that are there, and we’ll surface the most relevant filters, so that if it’s priced, it may be something. It’s not always the same in every category, and that’s what we look at with machine learning and AI. We’re able to look at it and say, “Okay, what are the filters that people use? What are the ones that are more important,” and surface those out there. Now, that’s one way to do it. The other is, as we mentioned earlier, is with discovery tags or looking at using NLP, natural language processing. We can go through… And that example of looking for a dress and-

Brian McGlynn:
We can go through and that example, if I’m looking for a dress in New York for under 500 bucks. Being able to take that, pre-populate that allows you to even eliminate it. We had a classic case. We go in and demonstrate with one of our electronics retailers, where you type in 4K monitor and “Okay, I get it.” 4K monitor you type that for a computer monitor in 4K. You’d see junk, like HDMI connectors, USB connectors, things that aren’t even a monitor. So being able to break down what is a monitor 4K and you’d see superfluous things like resolution. It’s, “Well, I’ve asked for 4K, why am I seeing a 10 80 by or a 12 80 by 10, 24 resolution, when I’ve already specified 4K?” So really providing that level of intelligence, to go in there and in that, but yet the short answer is, it’s old tech. This is where we can upgrade. That’s where clients need to be thinking about that.

Julia Raymond Hare:
It’s funny that you gave that example because I have had experiences like that and you know what I do, I just go back to Google. I’m ,”Well, I’m going to start over.” Because Google will show me something more relevant.

Brian McGlynn:
Well, actually in your point there, what happens then is customers churn. So Amazon spends a fortune bidding on words. So if you go in, you look at something, go onto a site, you look for a 4K monitor. You can’t find what you want. Go back to Google. Chances are Amazon is going to put an ad word in because their conversion rate is so high, that they can afford to spend more bidding on those particular words. So they’ll outbid the retailers in many cases. So yeah, that’s the issue. Once your search box doesn’t resolve what you want. You’ve lost the customer. They’ve gone to Google and they’ve gone somewhere else.

Julia Raymond Hare:
Exactly. And we can’t give more people over to Jeff.

Brian McGlynn:
No.

Julia Raymond Hare:
We have to have to have some retail left.

Brian McGlynn:
Exactly. We need some other… Exactly. Some other variants out there. I agree, I totally agree.

Julia Raymond Hare:
Well, Brian, you talked about a lot of exciting things today. I loved seeing Coveo at the shows. I’m excited to see you guys, when we’re at NRF next year and how can our listeners, if anyone is interested in reaching out, what’s the best way to do so?

Brian McGlynn:
They definitely go check… We’ve got demos we’re constantly going through and we’ve got blog entries and others at coveo.com. C-O-V-E-O.com and check it out. And by all means you can hit me on LinkedIn, Brian McGlynn. I’m certainly there. And people can reach out to me directly, or we’ve got a lot of great folks on our pages as well where we go through. So, there’s a lot of case studies, other items there to really help either build business cases. Where a lot of our customers ask us, “Hey, I’d love to go in and really improve my UI and my customer experience. Can you help me with a business case?” The answer is, yes. We do this all the time. So we have materials there. We have a team there and we love to talk about what we can do to help your business.

Julia Raymond Hare:
Wonderful. That was Brian McGlynn, general manager of e-commerce at Coveo. Thanks for coming on the show. And I hope to have you on again in the future.

Brian McGlynn:
Well, thanks for having me.