We are delighted to share the latest interview from Napier’s Marketing B2B Technology Podcast.
In our latest episode, we interview Steve Zakur, CEO & Co-Founder of Solosegment, which provides software that drives engagement and leads with anonymous data and AI.
Find out more about Solosegment and the meaning behind anonymous personalization, by listening to the episode here.Â
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Transcript: Interview with Steve Zakur – Solosegment
Speakers:Â Mike Maynard, Steve Zakur
Mike: Thanks for listening to marketing b2b tech, the podcast from Napier, where you can find out what really works in b2b marketing today. Welcome to the latest edition of marketing b2b technology from Napier. Today, I’ve got Steve zaika from solo segment. Welcome to the podcast, Steve.
Steve: Thanks very much, Mike.
Mike: Thanks, Steve. So, you co-founded Solosegment, can you tell me about your career journey? And how you got to the point where you decided to found the company?
Steve: Yeah, absolutely. So I’ve been kind of a technology person by trade for a long time, although I’ve never written a line of code. You know, I’ve often been that person who is at the interface of Business and Technology, whether it was back in the days when I worked in finance, I moved into operations. And then in the late 90s, kind of caught the startup bug, I really was excited about the opportunity, especially the way the internet right at that time, was really changing and transforming how business was done and worked for a startup for about two years. And like many startups, that went when essentially nowhere, but I had the good fortune of getting hired by IBM at that point, because this was now late 2000, early 2001. And they were, you know, hoovering up all of these, anybody who could spell.com they wanted to hire and so had the good fortune to get hired at IBM, and then spent 15 years there, in a variety of executive roles, primarily focused on what I like to refer to as fixing broken toys, a lot of work, you know, looking at products, projects, customer relationships that have kind of gone awry, and helping us to write those.
And last couple of years that I was with IBM, I was working in there, I was responsible for their sales and marketing technology. And it was a pretty hefty responsibility. And of course, being an executive, your job is to take the pain that other executives throw at you. So it really gave me a keen sense for, you know, what were the gaps and opportunities, especially with regards to marketing technology. And early in 2016, I was at our Astor Place location, and I was walking through the halls, and I ran into Mike Moran, and Mike, who was one of the cofounders solo segment. He was the guy who hired me went back in November of 2000. And into IBM, we had lost track for about 15 years. And, you know, literally, he was back doing some consulting, we had a chat by the elevator and said, let’s have a beer because I’ve got this idea. And that idea was soul segment, you know, did he had just gotten started with some development of software that that helped improve website search. But it really was that was the starting point. And, you know, a lot of our early conversations before I joined him, were very much focused on this gap, right? This this where the, you know, marketing executives, you know, weren’t getting often the value they could out of the existing technology, and how could we bridge that. And so, you know, my journey to solo segment now spending four years building solo segment and from, you know, I guess what you classically think of as a startup into an actual business that operates is, was really focusing on that those gaps that we saw. And honestly, you know, of course, like any good company listening to, you know, your customers and finding, you know, the nuances and the pain so that you can make sure you’re addressing what’s important to them.
Mike: Amazing. And is the founding team. Are they still with the company?
Steve: Yep, they sure are. Yeah, Tim Peters, the third member of the founding team, Tim is our marketing leader. He’s, he’s a marketing technology person, as well, has a lot of experience in financial services, hospitality and into the tech industry as well.
Mike: Wow. So you’ve got the classic sort of CO marketing and technical trio family company. That’s cool.
Steve: Yeah, it was. And honestly, that’s one of the things that drew me there. I mean, you know, I know that, you know, from my prior experience, you know, that early team is really important in not only the vision, but you know, it’s very easy for individuals to make to go astray. But when you have a solid team that you really, that keeps you honest and keeps you focused on the customer value, it’s very helpful, but more than anything, you know, we fill each other’s blind spots, right. And that really was the benefit. The early benefit was, you know, we all had very unique but distinct points of view on the business opportunity.
Mike: Amazing. I think I’ve got a blind spot that I need filling so. So the segment describes itself as anonymous personalization. Can you can you just unpack that and explain what you mean by it?
Steve: Yeah, you bet. So I mean, traditional personalization. I mean, it’s in the name, right. You know, it’s all about understanding something about the person. And so when you look at how personalization technology emerged, and again, this rewinds all the way back to the late 90s. And especially when you think about what Amazon was doing early on, you know, really under Standing patterns and behaviour. And there were lots of other companies that did as well. But Amazon, of course, is an exemplar in many ways. In the consumer space. You know, a lot of effort was put into understanding data about the people. And as marketing technology and marketing processes, embraced digital, almost everything we do focused on the person, everything from how the technology identifies people to cookies related to computers, which are related to people, logins. Now that data gets that first party data get sold as third party data.
So basically, you can buy information about anybody on the planet, that that root of the personal data in personalization is deeply, deeply embedded in how we think about web engagement, right, it’s knowing something about you. And then using that information, to help you engage with social conversations that might interest to you to help you find products that might be interesting to you. In the b2b space, it’s a little bit different, the challenges were a little bit different. When you look at the profile of a visitor to a b2b website, a very small portion of them are actually identifiable three to 5%. So why is 90 95% of the traffic on identifiable for a variety of reasons. First, often what you’re doing at work doesn’t relate to what you do in your personal computer, although in COVID, land, right, you know, everything is the same. But but in kind of a traditional view of things, you know, what you’re doing in your personal life, or what you’re doing your business life are very distinct. So there’s not that data trail, that kind of translates really well. So if I’m on Amazon in the morning, buying something, and then I go to work, and now I’m looking at, you know, software vendors website, there’s not a lot of interesting data that translates to that. And that that’s part of what the leads to that lack of interesting data that’s available to b2b marketers. But the other thing, other reason that that that data is not often available is because of the incentives.
In my personal life and my consumer life, there are lots of incentives for me to share information. Part of it is that you know, some object appears on my doorstep when I order it. But the other incentives are, you know, this data is actually I mean, while there are bad actors and whatnot in the marketplace, it’s largely being used for good, right, I’m finding the things I want, and being exposed to things that I didn’t know I want, but actually suit me very, very well. Anybody who spent any time on YouTube, going down deep into holes on topics of interest knows this. But in the in the business world, the incentives are almost there, almost disincentives, quite frankly, to sharing your information. You’re part of it is that, you know, if you do share your information to learn the process, you’re going to get harassed by sales reps in an endless nurture campaign in your email inbox. But there’s not a lot of trade for value, right? You know, getting a white paper, and then taking on the burden of these endless emails doesn’t often seem like a fair trade for value. So prospects, visitors resist that. And that, really, at the core is the challenges. Why anonymous personalization because what anonymous personalization is all about is creating engaging moments without having to know oh, this is Mike. And he’s been to this website five times in the past, and he’s done these certain activities. It’s really in the moment, can you create an engaging experience, based upon not specific data about the person, but general data about the behaviour. And that’s what we like to think about as anonymous personalization, engaging experiences that don’t require personal knowledge of the person, primarily, because in b2b, it’s very hard to get that data. And so why struggle to try and get the data, why not just accept and embrace what you already have, which is nothing and use that anonymous data to create those engaging experiences.
Mike: Interesting. So I mean, just explained to me a little more about what that means. So you’re looking at the behaviour, just on one website, and then personalising based on that. So how does it work?
Steve: Yeah, so we have technologies and some of its kind of traditional predictive analytics, there are some machine learning as well as some natural language processing components to it as well. And we’re looking at primarily behavioural data. So the two places the behavioural data that we find most interesting are first intent data that you can get out of out of a website’s search engine. So while not a lot of people search on b2b websites, those who do give you some interesting information about content and the relationship with content to intent, like what they’re interested in, and why they’re interested in it. And once you understand that, you can then almost reverse it, right? And so for any piece of content, you know, what its intent is. And so that’s the first piece of data that we look at is intent data on the website so that we know when somebody is on a page, you know, we can make a prediction That’s if that’s the fancy word for in machine learning for a guess, you know, we can make a prediction about what the odds are that somebody has a certain intent for a certain piece of content. And as you might imagine, that, you know, varies by content from content to content. But the other behavioural data we look at is just all of the visitor journeys that have gone on on the website, right, people start in one place, they end in another. And what we’re looking for, especially in the longer journeys, the 2345 page journeys, is we’re looking for journeys that, you know, lead to some sort of goal achievement. And by understanding those patterns, we can begin to gather with that intent data to, to make some guesses about when you’re on a page, what, why you might be there, and what piece of content you might want to see next, right based upon the pattern analysis that the machine is doing. And of course, every time you give the machine some information, the machine makes better predictions going forward. And there’s a third piece of data, of course, which is the content itself, we have a natural language processing technology that looks at content, and tries to understand what it’s about what his topic is, what industry it might be about, you can imagine a lot of other things that we can discern.
And so when somebody comes to a website, you know, we’re immediately the models are immediately running, they’re looking at what the person is looking at, looking at how they’re looking at it, right, their scroll depth, how they’re interacting with the page, but and they’re making these predictions of two things, right, based upon the intent based upon the content based upon all the journeys that are similar to this one. What might you be trying to achieve? And what piece of content might you need to see next in order to progress towards that goal?
Mike: And that helps. So I mean, it sounds like there’s lots of elements of it, if I look on your website, you’ve got, you know, effectively four key products identified, can you explain how they work together to produce a solution?
Steve: The are independent, or they can be used independently, they all share a common platform. You know, we’re, we sell two products, search box and guide box, they’re kind of our two primary products, mostly, because that’s how our customers think about web interaction, it’s kind of interesting, you know, we we separate searching and behaviour from navigating behaviour. And there’s even variations of navigating behaviour, right, we have navigation behaviour, where people are responding to, to campaigns versus navigation behaviour, maybe they’re coming in through organic search, or they’re just typing a URL coming direct. So there’s lots of different types of behaviours. But when you think about how our customers think about the world, often they think about the website in those two areas, right? We have searchers, and we have navigators. And so that’s why search box and guide box were delivered, but they all share this common platform. And that is, you know, looking at the behaviours of people on the website, and using data to automatically drive improvement. So let’s talk for a moment about searching behaviour. In searching behaviour, you know, one of the key challenges is a and you would think one of the key inputs in the search engines, even though it’s not, would be, hey, when somebody has a successful behaviour on a search, we should, you know, take that data and do something with it. And that doesn’t often happen, right? A lot of how search engines work are based upon how good the content is. But it very rarely looks at the behaviours after the content. So that’s what’s unique about search box. And honestly, that’s where a lot of our intent data comes from, is we’re looking deeply at not only what did somebody search for, and what did somebody click on, but we’re looking at the behaviours after the click to really discern, was this a successful interaction or an unsuccessful interaction? And that not only gives us data about searcher success, which you can then feed back to the search engine to give it some, you know, information about which links are the better answers versus which links are the worst answers. But more importantly, that then becomes a data set, were we really understand on a specific company’s website? You know, how good is search? And, and are those searchers based upon again, coming back to intent what they intended to achieve achieving that thing?
Mike: Interesting. So you’re, you’re looking at what people search for, and then you’re trying to use that to almost assess the value of different content in different situations? Is that how it’s working?
Steve: Yeah, I mean, that’s a good way of thinking about it. You know, the search engines are always trying to programmatically evaluate content and discern, you know, what it’s about. And that, of course, once this once the search engine knows what it’s about, you know, through a variety of techniques that are, you know, very mathematically driven, so I won’t go into them too much. But most search engines work that right, right? They look at content, that’s called indexing, right? They gather all the content, and then they evaluate that content to try to figure out what it’s about. And we take that whole thing the next step further, which is to say, Okay, great, the search engines done that evaluation. It’s figured out what this content is about. But now let’s add the user feedback into it. Right, let’s add customer experience back into it. And it’s not just the customer experience while they’re on the search engine results page, but it’s really the experience after they leave the search engine results page after they make that click and start their journey. You know, was that journey actually successful or not?
Mike: Interesting. And in terms of working this out? I mean, I think you said the AI guesses. I’m sure it’s a lot more complicated than that. I mean, can you explain what AI gives you that you couldn’t get from something that’s more of a programmatic formula type approach?
Steve: Yeah. So, you know, thinking about AI, is one of the ways I like to think about it. And I think it helps marketers think about it is kind of the traditional ways of doing, as you said, programmatic sort of solutions to this problem is very similar to a b testing, right? So you come up with an A and a B ad, and you run them and you see which one performs better. And then you start, you know, the machine would automatically say, you know, what B’s doing a lot better, let’s promote B. And so that’s kind of a traditional way of thinking about those, you have you posit two hypotheses, and you test them, what machine learning allows you to do is to not have to come up with the hypothesis, right? You don’t have to come up with the A and the B, you actually come up with a goal, right? So you define, I want more leads. And what the machine is going to do is it’s going to come up with the A and the B and the C and the D. And it’s just going to constantly try to optimise on that goal versus optimising the two choices you have given it. And so it the same way, when you think about all this journey analytics that goes on, we’re compiling all of this information about people and their interactions with a website on a continuous basis.
Now, some of those interactions are very small, right, somebody responds to a campaign and leaves the site a one page visit a bounce. Sometimes they’re very short, you know, you look at a lot of these companies. And they are their goal is to get two pages per visit on average, right? So they’re very short interactions. But when you can look at the longer interactions, you just have so many of them, that it’s hard to, for a human to kind of discern the pattern and choose, you know, which of these two, two pathways are better, right, and the human defines the pathways. So instead, we just tell the machine, you know, we want more downloads, we want more contact forms, we want more whatever. And now the machine knows that those sorts of events are the goals. And it’s going to look for the patterns that that lead to the goals. And over time, as somebody comes to the website, it will recognise when somebody is on one of those patterns. And it could be as simple as G everybody who starts on this page, who happens to land on this page has an 80% likelihood that they’re going that they’re shooting for the contact form, let me nudge this person forward, to try to get him to the contact form, right. So it’s that’s the kind of predictions that the machines working on. But the the real difference between programmatic ways and machine learning ways is in machine learning, you define the goal. And once you’ve defined the goal, the machine can figure out the optimal ways towards achieving the goal versus having to draw, you know, for a human to actually have to figure out, well, here’s the five ways to the goal, we’re going to test let’s just figure out which of my five ideas is best.
Mike: Interesting. So, I mean, how does a user use seller segment? It sounds like, you know, there might be this incredibly complicated set up before suddenly the magic happens it? Is it tough, or is it straightforward?
Steve: It’s relatively straightforward. I’ll say that. And, you know, we’re working every day to kind of make it more straightforward. You know, certainly, when, when I was in my role at IBM, you know, one of the deep pain points that we had was time to value. You know, we were a large enterprise, when we bought large enterprise software was often complex to implement. It was often and part of that was by design, by the way, right? Because it’s, it’s far easier to retain a software, you know, retain an account if you’re a software vendor, if it’s hard to unplug you. So I think some of that complexity was by design, but but you know, required integrations with systems that, you know, we had, whether it was integrating to the CRM system or fulfilment systems. And so is the time to value was was, you know, one of the biggest struggles that you’d be a year into a contract and you’re just getting the most basic function sort of deployed.
And I think that’s where, you know, where I started in my role there, you know, getting involved in a lot of what I would refer to as best in class vendors, right, these smaller vendors who were far more agile, their price points were a lot more appealing. Yeah. And, you know, often they didn’t require the complexity that that these larger kind of more traditional vendors required. And so that was really our goal, when we were thinking about what type of company do we want to be, you know, we started off with this idea that we don’t want to be a company that makes it really hard to manage the data. And that was part of our, you know, focus on anonymous data versus personal data. But the other thing was, you know, we want to make it easy to get started. And so I mean, search box is the easiest product to get started with, because, you know, it gathers all the data via JavaScript, you put a couple of lines of code on the page. And it just begins to, to gather data about what’s going on in search and what’s going on after search. And that was our first product, by the way. And so that design decision where we said, we’re not going to integrate with the technology that our customer uses, whether it’s their web analytics, or their search engine, we’re going to use JavaScript to capture the data ourselves, that now kind of pervades everything we do, right? What can we do with the JavaScript to make it easier for our customers to adopt, and honestly make it easier for us to get them to value, right that you know, to speed the time to value. So JavaScript is a way that we gather a lot of data, much like any analytics programme does. And we also the second way we gather data is we searched the website like a search engine would so we can index all the content and apply our NLP against those indexes that we created all the content, but we try to make it as easy as possible. And again, having been in large enterprise marketing tech, I get the pain point and the time to value problem. And so that’s part of our goal.
Mike: But it sounds like you can load that JavaScript things start happening immediately. And then you obviously need to presumably give some idea of what a conversion is, whether it’s a form fill or something, is it is that right?
Steve: Yes and no. So the general processes that JavaScript gets installed, and for some companies, and by the way, some people think when I give these examples, oh, he’s talking about the small company had an easy time and a big company had a hard time, it actually doesn’t matter on company size, it’s often just, you know, the where the Paranoid dial is set out, some some companies said at 11, break it and some companies set it up for but you know, getting that JavaScript deployed, you know, is usually a couple of weeks just because these large companies have processes that they want to go through to, you know, test them and put it on board. And then we usually need some baseline set of data to get both search box and guide box to work. Because all of these learning technologies, you know, just they work they need to learn, right, they need some data set to learn. And while the holy grail is some general model that will work across all businesses in all industries, the reality is it has to learn on the behaviours of each of our clients. So that usually takes about 30 days. And again, it depends on the size of the client and the volume of data. But most of our, our clients are dealing with 10s of 1000s of pages of content and hundreds of 1000s of visits a month. And so we pretty pretty quickly gather enough data, enough head of steam, if you will, enough learning that the models are working within 30 days or so and and that’s when the comp plan can begin to really get value from them. Where where the client has some work to do, of course, is getting through all of their processes to deploy, deploy the code, and that they have to make some choices, some of our technology appears on the glass, right that we deliver some sort of user experience. And so they have to decide, you know, share with us their design, standards and whatnot. So we make sure that it looks like something that comes from that company. But you know, again, our goal is always to kind of lower the barrier to getting started, lower the barriers, time to value.
Mike: And it sounds like you’re also giving a little bit of consultancy in terms of helping the customer is that right? I mean, it sounds like you’re not a classic SAS vendor that you sign up online, and you’re on your own.
Steve: Yeah, I mean, you know, we had intended to be that SAS vendor, you know, that was already dead. And by the way, experiences, again, in my career, you know, these large enterprises, they are, they can be high touch. So, you know, they, you know, when I think about all of our client relationships, you know, I know most of my clients, but, you know, we’re, you know, I try to make sure that I’m speaking to them fairly frequently. But they’re, I mean, the nature of their businesses is they’re large and complex. And so, because we have a point of view on, on not only our area of expertise, which is in digital engagement, personalization, sort of technologies, but on how those technologies integrate with the entire marketing processes, you know, you bet our customer success, people definitely, you know, chat with our clients about broader issues. And in some cases, we do some consulting, where they ask us to go deeper than honestly a software vendor might normally but where we have some expertise, we definitely do that.
I mean, I never want to turn away a client who, who we can help extract value, but our core really is, you know, how do we make help the software drive value? Because at the end of the day, you know, my frustration, as an executive was always that, you know, I’d get the PowerPoint and you know, it’d be 102 pages of insight. But how do I then execute that? Right? It’s really hard to do so. And what we’re we want to focus on is how do we use data to automatically drive improvement, whether that’s data that’s automatically improving the search experience, or whether it’s data automatically helping navigators. But there is far too much content, there are far too many visitors. And there’s far too few resources, whether it’s money, or people within these origin enterprises to do anything manually. And so, you know, it’s funny, we have a dashboard for all our products that shows the value, etc, etc. And our clients rarely use them. And so we knew that like, that was an early feedback point. You know, we knew that sharing data was not the most important thing, right? using that data, in a way to automatically make things better, was a lot better than sharing a dashboard, which gives some overworked marketer more work to do.
Mike: I mean, trade, I mean, obviously, as a company, you’re really focused on value. And I guess one of the ways of measuring value is, is in terms of number of leads and cost per lead? Is that the primary way people measure or are there other ways that people look at value from the product?
Steve: Yeah, I think that the folks that, you know, that’s those are certainly Top of Mind measures for all of our clients, you know, they are under pressure to deliver mq ELLs, right. That is the that is the ultimate the ultimate point of the exercise. You know, of course, when we’re one piece of an integrated stack, in a very complex business, it’s hard to do attribution, right, that is the Achilles heel of everything that marketers do, and quite frankly, the marketing technology companies do. So, you know, what we’re looking at is well, what are the metrics that lead up to an M qL, that we can contribute to in some meaningful way and measure from an attribution perspective very specifically? So certainly, we’re looking at, you know, a lot of those leading metrics, right. So are we getting more engagement and engagement is a fairly complex algorithm, but it basically means are more people staying on the site? are they seeing more content? Are they progressing more towards their goals? Right, so those are, that’s our viewpoint is we want to increase the level of engagement with content on the website, where we can measure those goals. And we tend to refer to them as events because I think goal has a very specific meaning, right? A goal is something that a marketer has defined as the point of a campaign, say, or product manager is defined as the on this page, when somebody gets to it, they’re going to take this specific action.
One of the things we do when we evaluate the content automatically on our website, is we look for places where people can do stuff, right. So it could be if you had, say, a commerce element, two of our clients have a relatively small portion of commerce on their website, but they have carts and they have checkouts and those sorts of things. So we look for those sorts of events. But the other things that are more common are events, like, you know, download the white paper, or fill out the contact form, or those sorts of things. And so what we’re looking for is signals that indicate that one of those events have taken place. And that of course, you know, once we see a signal that an event has taken place, we’re then going to try to drive more people who fit that pattern towards that event. But that’s really our goal. So as opposed to leads, I think the most thing you the thing you could most likely attribute our technology towards driving is probably contacts, right that people are actually taking some of those events or and sharing their information. So that now there, they can fall into quite frankly, a personalised experience. Right. So now they can fall into a technology which will nurture them with an email campaign or will, you know, prompt a sales rep to make a call?
Mike: Brilliant, nice. That’s really clear. And you said earlier, you’re talking about, you know, typically having hundreds of 1000s of visits for a typical customer? I mean, can you talk to me about you know, who benefits the most from using solely segment?
Steve: Yeah, so these are generally companies that are kind of later to the digital game, I think that there are a fair amount of companies very mature companies digitally mature, by the way, you know, it’s funny how interesting, you know, a company size almost is not a predictor of digital maturity. But it’s somewhat related, but not highly related. But, you know, we’re talking to a lot of companies who are a little bit later to the digital game, right, that they’re, they, you know, didn’t get involved early, but they’re looking to advance quickly. And, you know, I think one of the frustrations that these companies often face is that you know, they go to some of these law Large integrated vendors. And, you know, they’re faced with, you know, six figure seven figure licence fees. And, you know, equally six, figure seven figure integration, installation fees. And of course, you know, months and months to value. And so, so these so these companies that are coming a little bit later to the game, they see that they’re a little intimidated, and now they want to think, well, how can I get started without having to take that huge bite.
So those are companies that are very good for us as well, we deal with some large manufacturing companies, some large chemical companies, medical device manufacturers have been very popular now in COVID. But as these companies who are a little bit late to the game and want to accelerate are very good. And generally, the folks we’re talking to are, you know, the people who are really at the, at the tip of the spear, you know, all CEOs with their, you know, favourite, you know, people like be right, I want to go talk to the CMO and I want to have a great relationship. But, you know, at the end of the day, the CMOS don’t feel the pain as acutely as, say, a senior manager or director of marketing, right, they are, they live where the pain is. And so, you know, we have a lot of conversations with those folks who are wrestling with, you know, yield on their marketing campaigns with, with, you know, just, you know, engagement on the website, you know, they’ve got a 80% bounce rate, and, you know, every page has a 90% exit rate, you know, so they’re, they’re really dealing with, you know, trying to create engagement connection with their clients. But we’re fairly industry agnostic, but it’s really, you know, helping to talk to the folks who really, you know, are at the tip of the spear with regards to the pain and the challenges that the business is facing.
Mike: That’s interesting. So you’re almost coming into people who are, you know, lagging behind and give them giving them a bit of a speed boost to catch up?
Steve: Yes.
Mike: And I’m interested in you talked about bounce rate, you know, people having 80% bounce rate, which I know, in on some sites is the case. So say the segment can really make a difference on that first page in terms of serving the right content, can it?
Steve: Yeah, you bet. You know, I think, and I don’t think marketers Think about it this, but certainly lay people think about it like this, or people maybe who aren’t marketers, but you know, fans, folks, and all those other people who exist in a corporation, you know, they always think about, somebody comes to our website, and they’re coming to the homepage, and they’re navigating around. And that’s not the way it works at all right? A very small portion, everybody, most people come in sideways, what I like to think of is sideways, or they come in the back door, they come in the side door through the garage, because they’re most often, you know, go into Google and doing a search. And, you know, they’re landing on some random page on the website. And, you know, for a marketer, you know, we spend a lot of our time and attention on the high value stuff, right. So we spend a lot of time on campaigns, and campaign landing experiences, and, you know, increasing yields there, we spend a lot of time on our top products, we spend a lot of time on this homepage, because the CEO thinks it’s important. And so we spend a lot of time on those experiences. And they account for a very, very small fraction of the total visits to the website.
And so, you know, part of the reason that, you know, we focused on this anonymous idea was also because there’s so much of the content that’s anonymous. When you think about, again, somebody’s coming to the website on any random page. And then you draw a histogram that says, you know, lists all the web pages and how many visits they got this month, you know, there are probably 150 pages that got 90% of the traffic. And then there are 15,000 pages, they got two or three visits each. But each one of those visits was important to the person who found it. Now granted, a lot of people get to places that Google sends them that aren’t very valuable. But again, whoever came into that page, they only got one or two page views a month, they had a purpose. And of course, nobody creates a bespoke experience on a page that gets one or two page views a month. And so, you know, part of our thought was, if we can provide the ability to somehow figure out somebody’s on a page, where can we send them next? That helps you avoid that bounce helps you if that’s their second page, avoid the exit, it gets you that continued engagement, right, get to another swing at the plate to use a you know, American baseball term, right? Yeah. So, you know, your swings at the plate are the kind of the things that you want, right? You don’t want to strike out, you don’t want to get out, right, you want to, you know, have a lot of opportunities as a, as a baseball manager to, you know, get people on the field. And so in the same way, as a marketing manager, you want the opportunity to somehow connect with this person. And so if they’re coming to the site, and they’re, you know, 80% of them are, you know, bouncing out, then you know, anything you can do to reduce that rate is critical. We had one client, who we’ve done a couple cases studies on this and really study that deeply. And one client in their first six months of having guide box on the page, they reduced their bounce rate by 12 points. And so, you know, it was a pretty significant opportunity for them to turn those one page visits into at least two page visits. And, you know, again, you know, we’re all those successful, absolutely not, but would you like to double your opportunity to engage with somebody? You know, absolutely. Everybody wants that every day?
Mike: Oh, that’s an amazing stat. And I think, you know, it’s interesting, it sounds like you’re almost learning about the visitor from the page they land on, because you’re effectively inferring how they got there in terms of search is that, crudely speaking, how the AI is doing it?
Steve: It is, but and it’s also inferring, you know, why they’re there. And again, it’s, you know, we’ve never really studied to say, you know, how often Is it right? You know, we don’t do surveys of people to see if we got in their minds. But you know, but you can look at the data, right? And if you’re giving somebody a very smart recommendation about, Oh, you like this content, you know, maybe you’d like to see this next. And that’s one of the models that we use is it’s kind of it’s a content recommendation sort of thing, much like say Amazon does product recommendation, what we’re trying to do is offer people really smart alternatives. I mean, when you look at any, any large enterprise, and pretty much any company’s website, it’s organised, like their organisation chart is organised, not how their customers think about their problems. And so you know, not only do they have many ways off the page, one of our clients we counted, they have 70 ways off their pages, because they show this huge menu. And there’s this, you know, right side navigation bar, and there’s a left side navigation is hugely confusing user experience. And again, you wouldn’t do that for your best products. But there’s a lot of other things on your website that you just don’t have the time and energy to invest in. And so, with guide box, saying, Here’s three options to progress your journey some way, would you like to choose one of these three things that seems really smart? You know, it’s a way of creating that engagement that, you know, allows somebody to not be honestly intimidated by all the choice that’s before them, and much of that choice being irrelevant to them?
Mike: Well, so the scope, I mean, you know, effectively seller segments, sat there, it’s it’s customising 10s, of 1000s of pages for hundreds of 1000s of visitors, I’ve got to ask this question, because I’m sure people listening are wondering, it’s terrifyingly expensive, right?
Steve: Actually, it’s not if you that is, I mean, that’s one of the things that while I’d like to choose to charge people a lot of money and make make a lot of money. You know, it’s actually it’s pretty modest with regards to marketing technology spend, you know, you’re spending, you’re not spending millions of dollars. And most folks aren’t even spending hundreds of 1000s of dollars right there. You know, it’s relatively modest, and it scales honestly, to the size of the enterprise. So, you know, we have companies, and as small as sounds weird, but as small as $300 million, so in revenue, so so we can make the solution scales in a way that makes sense for, you know, most of the large enterprise companies that we deal with, you know, the the thing that we’re also working on is a way to scale this down, because the models are driven by data. And so, so you need a fair amount of data, but we’re looking at is some alternative algorithms that try to do the same predictions that we do a large enterprise and smaller Sharpe enterprises, but in fact, we have a beta of it running on our website, and I don’t know how many pages of content we have, but not not 10s of 1000s, that’s for sure. And, and so we’re looking at ways to scale this down in a way that still creates that meaningful engagement. Because, you know, at the end of the day, you know, the marketer wants you on the site, they want you progressing towards some goal, they want swings at the plate. And so if we can do that, for companies, the scale of john deere, while at the same time doing it for companies, the scale of solo segment, we think there’s that’s a tremendous opportunity, we’re not quite ready for primetime on that scaled down model. Because there’s still some things that we have to figure out how to scale on the back end, because as you would imagine, what we did on our website was a little bespoke, but, you know, we’re definitely, we’re definitely looking at those models. Because, you know, there we, you know, think there’s a great economic opportunity for us, and there’s no reason it’s just the big guys should get all the value from a, you know, better engagement.
Mike: Well, definitely let us know when you’ve got a product because I’m sure we’d love to have it on our website as well. That’d be great.
Steve: Sounds good.
Mike: I mean, it does sound amazing, you know, for the cost of, you know, probably two or three really good marketers, you can get this huge amount of personalization, that just would be impractical. If you were trying to do it manually. I mean, you know, I can certainly see the potential in terms of return on investment there. That’s great.
Steve: Yeah, you bet. I think that’s a great way to think about it. I mean, how many people would Do you have to add to get, you know, engagement on the long tail of people who are coming to your website?
Mike: Yeah, absolutely. Um, so you’ve given us a little hint about the future in terms of where you might go? Is there anything else that you feel we should cover? Any anything you’d like to talk about in terms of salary segments? Or something about the technology I’ve missed?
Steve: Yeah, no, I think I think part of it is, you know, one of the things I think we didn’t talk about was a little bit more about, like, why is this the moment to be thinking about anonymous engagement. And, you know, anybody who’s an advertising is now trying to figure out what to do now with the death of cookies is kind of the thing that’s out there. But with the larger trend is is, you know, people are tired of their data getting stolen and misused. regulators have responded that, by that with GDPR, and the California acts and a lot of others that exist around the world. And, and now the software industry, most notably, the browser industry is acting to, you know, limit the amount of data that browsers will transmit to companies. And so this is, you know, most immediately, folks are freaked out, marketers are freaked out by the fact that ads, the ad business is going to change dramatically. You know, we all we heard Twitter and Facebook already talking about how their ad revenues are going to go down. Well, when ad revenues go down, that means advertisers have less opportunity to engage, right, because that’s why they’re going down. And so, you know, there are certainly some headwinds and significant headwinds, and I think they’re only going to increase over the coming years, with how we’re using personal information, and especially when you’re a b2b marketer, you know, it’s already harder to use personal information. And so, you know, to the extent that companies can they really should be starting to think about, you know, how do they create engaging visitor experiences using data other than personal data, because they’re already starting at a deficit, right, they, you know, very small percentage of the visitors that come to these websites are engageable, that we can know something about them. And if it’s only going to get more difficult, you know, kind of doubling down on a traditional personalization strategy just seems like folly, because, you know, the regulators aren’t going to change the direction, Apple, Google and Firefox aren’t going to change their direction. And so I think that the smart marketers are not only addressing kind of the current pain they’re seeing, but they’re actually starting to think more strategically about how are they going to operate effectively? How are they going to achieve their business objectives? deliver those mq ELLs deliver, you know, more contacts, in a world where personal information is going to be increasingly rare?
Mike: Wow, that’s certainly a trend we’re seeing. And I know, iOS, for example, a lot of people are freaking out over the privacy there. For for the advertising industry. So I think it’s a great point. You know, it really is a time when people need to be thinking about what’s next. And, and he gives this opportunity for really effective personalization. Without any kind of privacy issues. That’s, that’s cool.
Steve: Yeah, indeed.
Mike: So assuming we’ve got somebody listening who’s you know, responsible for a website that’s, you know, got several 100,000 visitors, or more a month? I mean, is there any way they can get in contact with you? You’re the CEO of the company. I mean, yeah, I suppose there’s a way they can get you.
Steve: Yeah, they could definitely get me and my emails probably on the website somewhere, but yeah, I mean, honestly, I could actually just email me directly, Steve@solosegment.com or they could go to the website solosegment.com. Hit me on LinkedIn or Twitter. I’m available in all the normal ways. But yeah, I’d be happy to have conversations and, you know, direct them to the right people in our organisation who can be to the conversation.
Mike: Well, thank you so much for being on the podcast, Steve. Um, there’s so much more, we could ask you and find out. All I ask is if you could come back when you do have a product that works with smaller websites, I’d love to talk to you again.
Steve: You bet, Mike. Thanks very much.
Mike: Thanks so much for listening to marketing b2b tech. We hope you enjoyed the episode. And if you did, please make sure you subscribe on iTunes, or on your favourite podcast application. If you’d like to know more, please visit our website at Napier b2b dot com or contact me directly on LinkedIn.
