He Analyzed The Entire Website Visitor ID Industry And Now Thinks It's A Complete Scam — Larry Kim | How Visitor ID Tech Works, Why Bad Visitor Data Is A Disaster For Your Marketing, The Impact Of Bad Data, How To Test Your Visitor ID Provider

He Analyzed The Entire Website Visitor ID Industry And Now Thinks It's A Complete Scam — Larry Kim | How Visitor ID Tech Works, Why Bad Visitor Data Is A Disaster Unknown Speaker: Hello everybody and welcome to the Ecommerce Coffee Break podcast. I'm Claus Lauter and you're listening to the podcast that helps you become a smarter online seller. In today's episode, Larry Kim, CEO of Customers.ai joins me and he has analyzed the entire website visitor ID industry and now thinks that it is a complete scam. So, let's find out why. Hello and welcome to another episode of the Ecommerce Coffee Break podcast. You likely have seen visitor ID tech that helps turn unknown website visitors into sales opportunities. But are these tools really effective as they claim? Today's guest, Larry Kim, has put them on the test and uncovered some very surprising results. Larry is the founder and CEO of Customers.AI, a marketing technology company specializing in website visitor identification and AI-powered customer acquisition. He's also the founder of WordStream, a leading PPC software company managing over $1 billion in annualized ad spend for tens of thousands of agencies and businesses globally, which was acquired by Gannett in 2018 for $150 million. Speaker 1: Let's welcome Larry back to the show. He was here before and dive deep into this very interesting topic. Hi, Larry. How are you today? Speaker 2: Doing great. Thanks for having me back. Speaker 1: Can you explain for listeners who haven't heard about website visitor identification what it is? Speaker 2: It's a relatively new emerging technology that's been around for a few years and the promise that they are making a claim that they can do is that by installing a JavaScript code on your website that ID providers can claim to accurately identify the identity of the person who is visiting your website. And of course, the value prop here is potentially very high because You know, conversion rates are stubbornly low, like they can be like mid single digits typically. And if you can know people who didn't convert with organically, you could then, if you were able to identify those people, you could You can follow up with email or ads if you have their email addresses or other identifiers. So that's sort of the premise of visitor ID tech. There's quite a few vendors in the space today, and Customers.AI is one of them. Speaker 1: Now, obviously, this is a very promising technology, finding out more about your website visitors. But you found out or you realized that there is a problem there, and we want to dive into this. What brought you to the conclusion that you might need to dive deeper into and find out what is going on? Speaker 2: So, recently, well, about a year ago, it came to our attention that the way that we were sourcing data was meaningfully different from how other vendors were doing it. And that just uncovered kind of a rabbit hole of us wanting to do We did a data accuracy test on not just our data but also the other vendors in the space and what we found was that the whole industry is basically a big fraud. Seriously, these ID vendors are just producing crappy shit garbage data and selling that to you. It's not 0% correct, it's correct maybe 3, 4, 5% on the low end. To as high as like 25% on the high end. These things are wrong like 70 to 95% of the time. Like when they give you an ID and say like this is so-and-so on your website, it's actually the wrong identifier. The vast majority of the time is what we found. And we repeated these tests across like Every possible data vendor that we could try, and we believe they're all pretty awful. It's not 100% wrong. There's a small amount of signal in there, but it's mostly wrong. Like it's 1 in 20 is correct or 1 in 10 is correct. It's pretty bad. And we believe that the issue here is that these Companies in this space are all sourcing your data from the same, you know, toxic waste pile data companies. And it doesn't even matter. The data companies that are being used are typically like co-reg networks or DSP data companies. And they're just kind of trying to work with that data. That data is designed for, you know, high accuracy type I'm the CEO of Ecommerce Coffee Break. Mostly right. Nothing is 100%, but we do see that when we run the same data tests on our data offering that the accuracy rates are mostly right. So it goes from mostly wrong to mostly right. It's typically like 65, 75, 80% correct. The important thing is you don't actually have to Just believe me, just verbatim, there is a way to do a little bit of analysis on the data being provided by Whatever data provider you're using, you can kind of arrive at the truth. Speaker 1: I want to dive a little bit into the implications that that can have for an online seller or somebody who has an online store, thinks now he has to collect data from website visitors and obviously gets data delivered, email addresses. What can happen to your own email marketing, for instance, or generally in marketing if you're using false data? Speaker 2: I think it's catastrophic, Claus. The issue here is that if you're just using crap data for ads, I mean, it's not necessarily the end of the world because like Facebook can kind of do some, you know, auditioning of your ad to see who's interested. But if you're using it from an email perspective, The risk is catastrophic, like an existential risk to your business essentially. You know, clearly email marketing is a very, very important channel for D2C e-commerce retailers and if you're using these You know, ID providers that have like, you know, 5, 10, 20, 25% accuracy, that means that the inverse of that, you know, 95, 90% of this data is wrong. That is going to torture your email deliverability, your email reputation. The current spam, you know, threshold for being classified as a bulk sender is 0.3%. So, like, you know, imagine if you're randomly emailing people and this is not an ID provider. These are worse than cold emailing systems. Like, even with cold emailing systems, like, What you can do is you can get certain people with certain job titles or certain demographics, you see what I'm saying, and then just email them out of the blue. Here, when these data providers give you a wrong ID, it's not just like, oh, it's another buyer. You know, and we're close, like this is somebody who, I don't know, was on the same IP address as someone else, you know, at the same time. And the the data provider that they're licensing, you know, has a thousand of these people on the same IP address. And they're saying, like, oh, let's just let's just include them all. OK, so, you know, it's like it's like going to the wrong person in line at like a Starbucks or something like this. And it's not just a little bit wrong. It's completely wrong. And so You know, the negative email engagement rates, so like unsubscribes, complaints, bounces, it's going to be inversely proportional to the accuracy. So if the accuracy is like, you know, single digits or low double digits, those complaint rates are going to be sky high. And you might be wondering, well, why, if this is true, Why hasn't everyone been kicked off their Klaviyo? Well, first of all, we've heard many stories of people being kicked off of Klaviyo because of compliance and deliverability issues when you start pumping this toxic waste into your ESP. But secondly, it doesn't happen all at once. It's like being poisoned slowly. So imagine you're in a business and you have a lot of visitors. The thing about these visitor ID solutions is they actually provide a lot of IDs. Like you might be getting like a thousand new emails a day or something like this at say 10% accuracy. So that 90% That's off of the thousand new and an e-commerce store might have half a million emails in their Clavia or ESP like on day one. Okay. So that 90% error is then diluted by the fact that their domain is doing a lot of first party emailing that that's kind of like diluting away the toxic waste. The problem with this is like if you Stay a customer of one of these crappy shit data ID providers. The problem kind of just, it just poisons your ESP over time. Like so at one month, you know, in this example, you're at 30,000 emails it not at three months you're at 90,000 emails like that's you know percent of your of your half a million emails and if 90% of that's wrong like that it's just like it's just Chipping away at your deliverability, and it's just a matter of when, like maybe it's like three, four months down the road, like at some point, or if you're a smaller brand that's just starting and you're using this, like that tipping point from when your ESP is mostly like garbage, that'll happen very quickly, like it could happen in the first week. So it's just, It's just a really dangerous situation that all these vendors are using toxic visitor ID data, not really having an understanding of how that data is created or how to test and understand what the accuracy of that data is. Speaker 1: It makes perfect sense. I like the example that you mentioned with Starbucks. I work at a lot of coffee shops. So basically, I go to an online store and then everyone sitting around me, because we're all on the same IP address, one of a sudden shows up in your database with their email address as far as they can reach through. Obviously, very bad implication. So obviously these providers and these database providers give the whole industry a very bad rap. And we were mentioned in the pre-call also that you can see it from your conversion rates because you're not really targeting the right clients. Tell me a little bit on how that reflects in conversion rates. Speaker 2: So, we've done case studies with major brands and one such case study is with a retailer called Jordan Craig and one vendor gave 14,000 emails. And generated 24 purchases. So that's like a very, very tiny conversion rate. Like remember, it's not all wrong, but it's mostly wrong. So 24 out of 14,000, that's like .04% or something. It's a fraction of a fraction of a fraction of a percentage. Customers.ai gave approximately 6,000 emails, so like less than half the number of emails, but it generated like 224 purchases. So that's eight times more purchases With half as many emails being produced. So, you know, it's 16, 20 times higher conversion rates. It's not just a little, it's like more than an order of magnitude difference here. Another vendor was even worse. It did like, you know, a similar number of emails, like 8,000 emails, and it produced one sale. So that's like 0.01%. And then another one did three sales off of 10,000 emails or so and it's almost worse than just randomly generating emails and sending them out. There's just a lot of error. Can we talk about how to test the data at all? Speaker 1: Yeah, of course. Yeah, sure. I would be interested to hear. Speaker 2: So, I think that the challenge for all these unsuspecting customers that are using all these agencies, like, oh my god, agencies are using this stuff and not even knowing what it is. The issue here is it's a little tricky at first to understand if the IDs being provided by the ID vendor is correct or not. There's an assumption that it's true because that's what they're saying it is. Most of the discourse in the space has been revolved around like match rates. So like, oh, we can match 20% of your visitors and someone else comes up, another startup comes up and says, we can do 40%. Like it's the match rate is kind of a joke because like, I can double maturate this by generating more phony, fraudulent emails. The way that you can check to see if the guess provided by the ID provider is correct or not is to establish a baseline of truth. That baseline of truth is typically your first party data. So if somebody actually purchases from your store, at that instant in time, you should have a very, very high conviction this particular session is Claus or this is Larry. You'll know exactly who that person is because they just purchased. And so what we've done is we've just made it easier for people to then rewind that session to see what the guesses were. By, you know, any of the available visitor ID providers and they're usually wrong. Like, it's just, you know, and you look at the emails of who they thought it was and who it really was, they're not even close. It's just like, what? You know, it's a random person who was routed through the same You know, network at the same time or, you know, has a similar browser configuration like it's just completely wrong the vast majority of the time and this is a This is a big deal, Claus. People aren't testing it. And what we've done is we're making it easier for people to see this by offering a free data testing service. Speaker 1: Now, obviously, at Customers.AI, you do something different because your results are far better than anyone else in the market. So where's your approach different? Speaker 2: Well, we do this fundamentally differently from everyone else. Just the whole premise of how our ID graph is constructed is completely different from how everyone else is doing it. Without going into all the details, what I can tell you is that the founders of the companies who do this kind of ID graphs are definitely Yeah, they have that panache and they're like, you know, you've met some of them uh, they have this panache and they're like Really just like good at hyping things like like really None of them that we've looked at have any serious engineering abilities like there's we'll see like a like a sales and marketing kind of go-to-market where we're different is that customers AI is an engineering company like we you know most of our company are engineers my background is in electrical engineering and we just have a approach the problem from a I would say in the last 18 months or so, we've been approaching it from a meaningfully different angle than from what the industry is doing. I think that the way that the industry is doing it right now is ridiculous because none of those sources that vendors are licensing are just black boxes. They don't even know what's in that data they're licensing because it's just like a feed. You didn't have anything to do with how the ingredients were packed, packaged, or anything. It's just like, here it is. It's like, OK, I'll use it. We control the build and the sources at every stage. This is very different. And I think that the fact that none of these other companies have I've done anything to fix their data. It leads me to believe that it's just not possible for them. Speaker 1: Obviously, somebody who's using these systems and you said you're providing a free data accuracy test so people can go and really check on the quality of the data they get from any provider out there. How does it work? If somebody comes to you, how can they run the test with you? Speaker 2: It's pretty simple. Most of these ID providers have a way of either exporting or sending the data somewhere. If you happen to have some other ID provider, we can just work the data and connect the dots. It's important to understand that the data tests that we're providing here It isn't necessarily something that couldn't be done by any individual brand because the brand knows who the real purchasers are and what data is being provided by these ID vendors. We're just doing a better job of matching them up. To see like, you know, were they right or wrong? And this is something that they could do if they have the technical wherewithal and that they could reproduce like on their end independently. But we're just offering to give them a tutorial on how to do that matching up of data just because it's really not that complicated. Speaker 1: I think it's super important because as you said, you're poisoning your data over time. And a lot of marketers are only interested in volume. So if you're sort of blind, if you see, oh, I have a thousand new emails coming in per day, it makes every marketer out there happy. But if the data quality is just not on spot, you're really hurting yourself and you don't want to be kicked out of Klaviyo for that. Speaker 2: It's happening. And the churn rate for a lot of these products is extremely high. It's as high as like You know, customer election value of like three, four, five, six months, which is extremely low. It's just really funny because even when it's complete crappy shit garbage like. You still get these 40% open rates and you still get these like 26% like click rates. It's these people saying like, what the heck is this? Like they open it and they click on it. So it's not immediately obvious what's happening right now, but I would be focusing on things like The complaint rates, which are always higher than 0.3%, I would be looking at the overall accuracy and the conversion rate. If you're getting 20,000 emails or something, there should be more than You know, a couple of dozen purchases. Speaker 1: Absolutely. Let's talk quickly about CustomerAI. Who's your perfect customer? Speaker 2: Well, we love e-commerce companies, 3 million GMB and up is who we're focusing on. Speaker 1: Okay. What's the onboarding process if somebody really wants to move away from a provider that does not provide? Speaker 2: It's pretty simple. We would want you to feel comfortable, so we would work with you to just do a free data test and to see what that is. Spoiler alert, it's going to be shocking. You know, 5, 10, 15, 20. It's going to be mostly wrong. And then transparently, we can offer to do the same thing with our data. And it's not perfect, but it'll be a multiple better. We've seen as high as like You know, 16 times more accurate or two times more accurate, it's somewhere going to be on that spectrum. And then you can decide for yourself, you know, which way to go. Speaker 1: That makes perfect sense. And I think it's definitely worth trying it out because you don't want to break all the data that you have and more coming in by the day. Speaker 2: Yeah. Like, imagine if you're an agency and you're like, recommending the use of one of these ID providers to, you know, a portfolio of like 20 clients or something like this, like, that's an existential risk to your agency. Because like, if you don't, like, You should at least do a test to see what it is that you're pumping into your clients' accounts. You don't have to do anything with the information. You could say, yeah, well, I'm happy with 25% accuracy or something like that. You can make that determination separately, but to not even know what the accuracy is of the data that you're using from your data provider is I think it's quite irresponsible and like as a, you know, you're supposed to be helping them grow and looking out for them, your clients. And so I think this is just like a – it's worth getting a data checkup is what I'm trying to say. Speaker 1: Absolutely. And I think the idea and the technology is there to make it work. And I appreciate that you're helping our listeners in getting to the truth of it and hopefully getting better data out of it. Where can people go and find out more about you guys? Speaker 2: It's Customers.AI and if you go to Customers.AI slash test, you can sign up for a free data evaluation. Speaker 1: Okay. I will put the link in the show notes and you just one click away. I hope a lot of people will reach out to you, not only the ones that are already using another provider, but also the ones that are generally interested in the topic of finding who's on their website, on their store and getting more data from them. Speaker 2: In summary, I just think it's something that a lot of people may have had some suspicions around. It should be doing better. Why doesn't everyone use this technology if it really is the correct ID of all these visitors? This is like a second-generation visitor identification if we can actually do what we're saying we're doing. I think the upside is tremendous. Thank you, Claus. Speaker 1: Thanks so much. Let's keep in touch and I will be interested in how this goes into the future and how more accurate this can get. Thanks so much for your time today. Hey, Claus here. Thank you for joining me on another episode of the Ecommerce Coffee Break podcast. Before you go, I'd like to ask two things from you. First, please help me with the algorithm so I can bring more impactful guests on the show. It will make it also easier for others to discover the podcast. Simply like, comment, and subscribe in the app you're using to listen to the podcast and even better if you could leave a rating. And finally, sign up for our free newsletter and become a smarter Shopify merchant in just 7 minutes per week. 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