#006: What Is the Space for Tools that Aren't Google Analytics or Adobe Analytics

The following is a straight-up machine translation. It has not been human-reviewed or human-corrected. However, we did replace the original transcription, produced in 2017, with an updated one produced using OpenAI’s WhisperX in 2025, which, trust us, is much, much better than the original. Still, we apologize on behalf of the machines for any text that winds up being incorrect, nonsensical, or offensive. We have asked the machine to do better, but it simply responds with, “I’m sorry, Dave. I’m afraid I can’t do that.”

00:00:04.00 [Announcer]: Welcome to the Digital Analytics Power Hour. Three analytics pros and the occasional guest discussing digital analytics issues of the day. Find them on Facebook at facebook.com forward slash analytics hour. And now, the Digital Analytics Power Hour.

00:00:21.91 [Michael Helbling]: Hi there everybody, this is Episode 6. Welcome to the Digital Analytics Power Hour. As always, I’m Michael Helbling, the Analytics Practice Leader at Search Discovery. And I’m joined by my two other hosts, Jim Cain, CEO of Napkyn and Babbage Systems, and Tim Wilson, a partner at Web Analytics Demystified. But today we have a special treat. We have our first ever guest on the Digital Analytics Power Hour, and we decided to swing for the fences. Heat and Shaw is with us tonight. He’s the co-founder of two different digital analytics companies, Crazy Egg and Kissmetrics, and he knows a little bit about the topic we’re going to discuss tonight. Heaton, hello, and welcome.

00:01:12.18 [Hiten Shah]: Thanks for having me, and I didn’t know I was going to be the first guest, so I better make this good.

00:01:16.58 [Michael Helbling]: Yeah, you better. You better be really good. No. We’ll get that out. So guys, let’s jump into tonight’s topic. And it’s really about disruption in the digital analytics space. Right now, in digital analytics today, there’s really two vendors who dominate the space, Google Analytics and Adobe Analytics. And if you go and look at any website in the Fortune 1000 or the Fortune, I don’t know how far down they count, but lots of thousands, these are the tools you’re going to see out there predominantly. There’s a lot of other ones out there. And if you look at the three of us on the show, we typically deal with those two tools. So that’s why we wanted you to come on the show tonight to really help us round out the conversation, understand the place for these other tool sets. How do they disrupt? How do we do things with them? Can people think of them as a replacement for these tools? Those are the kinds of things we’re going to get into. So let’s jump right into it, guys. Of the major tools out there, how do the other tools stack up and where do they fit into the space?

00:02:22.81 [Tim Wilson]: So I feel like there’s actually sort of two classes. There’s the classes of the traditional web analytics tools that are trying to some pretty much all of them kind of broaden their footprint to be into the Adobe into the full marketing cloud or into customer analytics or elsewhere. And then there’s the class of these other tools, which Heaton’s definitely one of the things I was eager to get your thoughts on is like, how do you even describe kiss metrics or crazy egg? How do you frame that relative to these kind of core web analytics tools? Because I struggle to.

00:03:01.50 [Hiten Shah]: Yeah, you literally could call most of us that are in that category. And there’s a lot of tools. I’m guessing there’s probably 100 at this point that are not Adobe or Google Analytics. You can just call us ankle biters to all of those folks for the most part. And the reason is both these companies have established themselves as dominant, dominant being obviously Omniture, which I’ll still keep calling it. But anyways, Adobe Web Analytics, I guess. or digital marketing cloud or whatever the hell they’re calling it now.

00:03:34.66 [Michael Helbling]: You rename it every year.

00:03:36.28 [Hiten Shah]: That’s right, and they’re taking the Salesforce strategy of trying to invent a new category every year or whatever it cares.

00:03:41.11 [Tim Wilson]: The URL is still sc.onmitter.com, so they’ve got cycles on it you’re hanging out.

00:03:46.53 [Hiten Shah]: Good, so I’m super glad that you guys can keep up with it because I can’t even keep up with it. I think they have dominated enterprise for such a long time. And what typically happens, I just keep thinking about innovators’ dilemma, innovators’ solution, and those whole models of disrupting industries as to what’s happening and probably going to keep happening. And so basically, Adobe on the high end, Google Analytics on the every website should have it. And if they don’t, I’m always wondering why. Because it’s free, and it’s very comprehensive. But at the end of the day, these are all both businesses, product lines, whatever you want to call it, that were created many, many, many years ago. The way I would describe it is that there’s basically a bunch of use cases that a lot of us that are smaller tools from a footprint standpoint are able to solve problems for customers. Maybe emerging needs, sometimes it’s like for example in some companies are focused just on mobile. Other companies are focused just on e-commerce. Other companies are focused just on Let’s say dashboards right so everyone’s got their own perspective on how to disrupt and or solve a problem for customers and so the way I would I know you kind of think of it as like there’s legacy companies and then there’s disruptors and I think that’s a reasonable way to think about it in general but the market is completely There’s just new stuff coming up all the time and new use cases and new things that these companies can’t support very well. I mean, it took Google forever, even though they have a whole mobile platform sitting there to understand how to do mobile SDKs for analytics. While many of us already figured that out years before they did, the problem is we don’t have distribution like they do that’s instant. And in Adobe’s case, it’s like there’s a whole support ecosystem around it where if you’re an enterprise company and you’re willing to spend 30 grand on a new change that you need to make, just like something that would take literally five minutes in our system at Kissmetrics or many of the other tools, you can do that. And enterprises want that sort of hand-holding support and sort of process, and I think it’s just a matter of maybe another five or ten more years of just chipping away at these large companies and also some of us really leveraging some of the shifts that are happening such as mobile. And this is only if you look at it as analytics and I know I’m sure we’re going to get into a deeper conversation but that’s I guess how I would think about it.

00:06:08.94 [Tim Wilson]: I think the the Clayton Christian the innovators dilemma is kind of a pretty fascinating way to to look at it of we’re on a different trajectory and won’t even be talking about the space this way in five years. And is that what’s happening? You’ve got a hundred companies that are all trying to solve more focused problems in a more nimble and creative way. You say mixed panel and I think it’s events. It’s me defining everything they want to track. That’s my crude understanding of mixed panel. Kissmetrics, I sort of see is kind of heads since we’re gonna start from scratch and make sure we’re thinking about hooking into other data and your web stuff. So we’re not gonna be, I don’t know, I don’t know if that’s fair or not. I think of Crazy8 or Clicktail of it’s, I actually need to get heat maps and see what I’m looking at. I look at Pilwick, Pilwick, Pilwick, don’t even know how to pronounce it. And it’s, hey, we’re gonna take the open source route. And those are all, I don’t even know that they’re necessarily converging if they’re saying we’re gonna put a different beach head of what we’re gonna do fantastically and then we’re gonna kind of expand from there. I just struggle to wrap my head around what’s happening there. I feel like Adobe and GA it’s simple. They’re just chasing each other on features and functionality and that’s about what they’re doing.

00:07:36.70 [Jim Cain]: See I think the easiest way to look at it is, you know, Adobe and Google are probably not necessarily going anywhere, but if you think about them as the big flat piece of Lego, they should be platforms on which other things are built, almost like an e-commerce platform, and then you’re in a situation where they do a lot of things well where they don’t do anything awesome. And then you can start thinking about, based on my business and my needs and what we’re good at, how do I start getting best of breed applications and bringing it in? Your integration into Google Analytics is really solid. And it really seems to me that where you’re going with kiss metrics is like that. Google does some things around engagement well, but we do engagement great. And we give you the ability to bring that in. Is that nuts, or is that kind of in the ballpark?

00:08:26.94 [Hiten Shah]: Yeah. It’s not nuts. It’s a good point of view. Both your point of views are somewhat accurate. I think the space is still evolving, but I’m not sure if I’d call it the analytic space that’s evolving. So let me throw a couple other viewpoints into it that are from, I guess, me. Me being somebody who keeps trying to create products in the space and always thinking about what’s the right product for the customer and starts with the product first. So that’s my sort of point of view. So and I’ll try to break down some of these other ones in a second too. But like for me it’s like marketers are still the number one buyer of these things. There’s one caveat which is marketers don’t have that much power. in mobile apps today because marketing is just kind of a shit show right now and tracking is all wacky. There’s some evolution that needs to happen there so right now from what we’ve noticed for mobile analytics most people are actually the people that are buying tend to be mostly engineers and product people especially in the markets we deal with which are everything but enterprise. So everything but Fortune 1000

00:09:34.35 [Michael Helbling]: I always think of that as more of a function of the maturity of that particular platform or technology. Everybody knows they need a mobile app. Let’s get a mobile app out there, guys. But they haven’t actually figured out how that mobile app fits into the overall strategy of their business to say, hey, if I’m not getting these things or these measurements out of that mobile app, I don’t understand how it’s helping or hurting me. The same thing was true 10 years ago on a website where people were putting up websites and They heard somebody at a conference tell them they needed web analytics, so they put web analytics on their site as well, but there was no rhyme or reason or sense for why that website was good for their business or bad for their business and so many terrible looking websites.

00:10:17.25 [Hiten Shah]: I think that would be a reasonable assumption if we were in an independent world like we were with the web, but now we’re in a very highly dependent world where If you have a mobile app, it’s likely you have something on the web as well, even if it’s just a landing page to get people to your mobile app. And most people have a lot more than that. So I guess my viewpoint is just that it goes back to the customer and who are we selling to, at least most of our products. And we’re still selling to marketing, marketing departments, supporting marketing use cases. And on mobile apps, yeah, you’re right. There’s still a lot of people fishing around. Trying to figure out what their strategy is and all that the folks that I deal with tend to already have mobile apps and kind of already have a decent idea of what they want. A lot of the times they’re not even picking one of our tools and they’re building all this stuff in the house. And so the pattern that we saw many years ago. with the reason even kiss metrics exist is that Google Analytics and Omniture and these tools were not enough. They were either not enough because somebody isn’t going to buy them because of their costs or the way that they approach analytics is not in alignment with how the business thinks about it.

00:11:23.64 [Tim Wilson]: If you’re largely selling to Are you more often displacing an existing technology? Does somebody have, they’re trying to do Google Analytics on their mobile and they’re saying it’s not giving us what we need or is it more you’re getting in at the development point where they’ve got a requirement and say we’ve got to actually capture data on this thing and they’re actually sending out, I guess, what is kind of the entry point for you and then who do you wind up competing with to the extent that you’re comfortable not asking you to necessarily name competitors.

00:11:57.47 [Hiten Shah]: Yeah, that’s fine. I’m always happy to name other companies in the space. So we actually don’t focus on mobile apps because marketers aren’t buying mobile app analytics in the markets we’re in, so in the sort of everything below enterprise. So we tend to sell to web companies or people that want to attach web, mobile, and offline data together about actual customers. So you’re talking e-commerce companies, SaaS companies, and some lead gen companies as well. And so our point of view has always been that people who are right now sort of innovators in their own businesses tend to not just want to see page views and event data, they actually want to see that data tied to individual users of theirs. The reason is they can trust the data more. I mean, just fundamentally, you can trust the data if you can say, okay, I had 10 page views, but three people did it, and these are the three people, and here’s everything about them that I know, essentially, that Kissmetrics knows because I tagged it and I sent it there. You can’t get a person view in Google Analytics, and I dare ask you guys how to do that in Adobe, because I know it’s virtually impossible by the way their data models.

00:13:04.87 [Tim Wilson]: But you’re saying, say I’m a mid-market CRM, SaaS CRM play where I’ve got a highly transactional, operational system where I’ve built a lot of custom functionality into it. You’re saying that’s the sort of thing that would be kind of a sweet spot. When you’re saying SaaS or e-commerce, you’re saying the actual, it’s like a platform where they say we have functionality designed and we want to track that functionality And it’s not as much. We have a website that we’re using as a marketing platform. Is that a fair description?

00:13:43.84 [Hiten Shah]: Let me try a different approach. If you want to audit your data, it has to be tied in key to something common across your multiple systems. Our belief has always been the common identifier is the actual person based on their email address. And what we do is we basically, if someone visited a site for the last six months, Anonymously and there’s a cookie and they’re in the same browser they didn’t clear the cookie of course and all that stuff and then they sign up today and give us the email we actually merged the data together. Which is some of the magic for a solution which we spent a lot of time working on we believe it’s an advantage it’s been working out but. The idea is that you don’t see that as two people in our system. You see it as one person once it happens and now all of a sudden this email address, your attribution to your channel data, all that stuff is completely different and way more accurate and you can do that. Even going forward, if I wanted to know my lifetime value, it’s actually a lot more accurate when you can say what’s the lifetime value of an individual customer and then roll that up into what’s the lifetime value of a group of customers. So it’s more of a, honestly, it’s data model fundamental difference between at least our solution and some of the other ones, but also parts of the other ones. For example, Mixpanel, you’re correct. It’s a real-time event-driven system. The majority of their customers buy it because of that functionality, and they added on people, and they came out and said recently that only 20% of their customer base is using people. And people is what the whole core of our tool Kissmetrics is built because partly because of what Jim said. He was saying that these other tools might be more like that flat Lego base plate. And you can build on top of it. Well, how can you build on top of it if the data model is flawed? And we’ll let you transport the data back and forth between Google Analytics or Omniture and other systems very easily.

00:15:32.56 [Tim Wilson]: That’s funny. Years ago when I worked with Eloqua, now Oracle, so marketing automation. They said they had web analytics and they reported never matched with whatever they were running, Urchin or Google, whatever web analytics tool. And I sort of had this minor epiphany that web analytics is fundamentally a content-centric platform, right? The model’s sort of based on the page, even if you’ve got a visitor ID and you’re tracking this other stuff, web analytics looks at things, kind of starting with the page, and the marketing automation, or at least Eloqua, which did that same thing, where it would drop the cookie and say, you’re anonymous until the point that you’re not anonymous, and then we’re going to assign all of that other stuff back to you. That was more to kind of pass that whole history into the CRM or to pass into a nurturing program. It actually makes a lot of sense. I said I was going to learn something on this tonight.

00:16:30.49 [Michael Helbling]: Well, and I think we’ve seen all the other tools move that direction too, right? So there’s, I mean, you can’t be in this space for very long. I can be in this space for quite a while without realizing that the person is the most important measurement, but most people can’t be in this space for very long before you realize that the visit or the session or the visitor is sort of a bad proxy for understanding the value of what’s happening with your digital experience. But, you know, Google and Adobe and others are building those capabilities, right? So there are services inside of Adobe today that you can jerry rig, you can jerry rig Adobe or Google Analytics right now.

00:17:13.91 [Jim Cain]: to get 80% of the way towards what?

00:17:17.25 [Michael Helbling]: In 2008, we were jury-rigging Adobe to do this, and now it’s part of Adobe.

00:17:21.86 [Tim Wilson]: Well, but I think just not to suck up to our special guest, but I think the point that he made, well, you probably debate with Ben Gange or somebody is whether or not they’re fundamentally re-architecting it. I think it does sound like a, it’ll be a legitimate, just from the outside assessment, to try to pivot your comic level of measurement from content and the page-driven call to a person is a pretty seismic shift that if you actually are built from that, and I don’t think, I’m not saying one is better or right. I think there are gonna be trade-offs. And absolutely Adobe, they are aggressively moving to try to get that universal person indicator tied across things. GA is still fundamentally hiding that, right? That is something that they have and are not exposing.

00:18:13.85 [Michael Helbling]: Well, they’re working toward it too. And I think, you know, where we can give props to Heaton is that, you know, he was doing this quite a while ago while the others are just getting caught up now.

00:18:22.90 [Jim Cain]: Well, but the other point is that you can buy Kiss Metrics as a best of breed tool for what it’s great at and go from zero to hero in a couple of days of implementation work versus writing a check to Adobe Pro Services. I don’t resell Adobe Services, and Michael does. I don’t resell services. Okay, you see, anyways, so if we think again to go back to the flat piece of Lego thing, right? And one of the places I love to use Kissmetrics, by the way, is for software as a service, post login. So I become a customer, I log in, and I have the ability with Kissmetrics at the email address level to not just look at lifetime value, but lifetime feature use, and feed that into product marketers. And it’s a way to evolve the things you can do with digital measurement tools and inform and empower other stakeholders in the business. It’s one of the things I like KISS metrics for. Now, could you do that with another tool eventually? Yes, but could you create a cohesive We’ve got GA across the enterprise and we’re bringing KISS metrics to fulfill the specific need and bring it all together. I think absolutely and a heat and a question I’d have for you is, are there other tools that you’re seeing coming into the marketplace that really fulfill a, the big boy tools do not do this well. If you’re an expert practitioner in this discipline, you’d be nuts if you weren’t using blank.

00:19:46.61 [Tim Wilson]: And by the way, that was just Jim talking because he realized that he is not running KISS metrics on the Analysis Engine client side portal. He’s running Google Analytics and Gravitar or whatever the hell that is. So, Heaton, if you want to go ahead and get Jim entered in your CRM for a little follow-up, I think there’s an opportunity for a KISS metrics implementation. He just is on record as saying that he’d like to buy it. Look at that. It’s on every podcast where we close a sale.

00:20:15.31 [Michael Helbling]: consider me a prospect. Back to the question. Actually that is a good question and I wanted to ask it too which is you know if you thought of that then what are you thinking about now and what’s what’s happening out there that’s new and exciting.

00:20:31.32 [Hiten Shah]: Yeah all right so we agree about the data model correct like there is a better data model forget like who’s doing it who’s not there’s a better data model that can we agree on that because I think the foundation of the future actually is based on that so

00:20:45.13 [Michael Helbling]: I think we all agree that you need to really do digital marketing well. You’ve got to have an understanding of the customer or the person who is the customer and what their behaviors are specifically. So yeah, I think that’s probably fair.

00:21:00.77 [Hiten Shah]: Cool. So a few things before I get into this, because I’m dying to talk about this, but the person is the core object, the core thing that any business cares about. So all data should be tied to a person. That’s just a personal belief I have. If at all possible, whenever possible, it should be merged around. It should be very accurate. It should be auditable. In fact, at Kissmetrics, we will not audit against another analytics tool, we will audit all day long against CRM tools. We will audit all day long against anything you have in your database that’s tied to a user, your user table. And if it’s inaccurate, if it’s bad, we will help you fix it, because it’s our fault. But if you’re trying to benchmark us against Google Analytics or something else, we don’t care. That’s just not the way to think about it. So again, it’s this stressing point of, it is contacts. It is people that matter to you. And that’s been our take since 2009 when we year into the business when we figured that out. But the kind of thing that I’m thinking and the thing that’s on my mind right now is I believe that in a few data points, do you guys know Scott Brinker, I think that’s his name, chiefmartech.com?

00:22:06.84 [Tim Wilson]: I just grabbed his landscape for a presentation.

00:22:10.82 [Hiten Shah]: I put it in every deck of mine that’s talking to marketers because it’s just really important and really keys on the point I want to get at. So there was 900 tools for marketers last year. There’s about 1800 tools this year. So there’s a lot of tools out there and there’s a lot of supposedly innovation or whatever going on. But one of the most interesting things I’ve noticed about all these tools is that the statement I would make is analytics is now just a feature. If you look at the majority of these tools out there, they all have some form of what we would call analytics. They have tables with data and statistical significance and channels and conversions and all that kind of stuff going on. And I can’t even, you could take his landscape and be like, okay, that quadrant, that quadrant, that quadrant, that quadrant, all the tools have this like analytics looking reporting interface. So I think analytics long-term just becomes a future of something else or everything else.

00:23:06.91 [Tim Wilson]: And so- I just think those, I think those, there’s so many things called analytics and they suck so bad. I mean, it goes back to my days with Eloqua where it’s like, hey, we have data We can chart that data because we get a little webkit or something, some sort of plug-in, and now we can give you charts and graphs and timeframes, and then as an analyst I go in and say, I can’t use any of this because I can’t actually look at the data in the way that I want to look at it. So I agree. I think it’s being sold as analytics is just a feature. And all of these tools, they say, oh, we have analytics, and they sell well, they demo well, and they say, look, we can slice it. We can show you a map. with stuff on it, and then as an analyst trying to dig in and say, god damn it, I need a time series breakdown of this and that, and I need to customize my dimensions and metrics, and I’m screwed. I agree they offer a feature they call analytics, whether or not it’s actually analytics in a way that an analyst can meaningfully use it, I think I’d question a little bit.

00:24:06.03 [Hiten Shah]: no argument here on that right but like an analyst again isn’t the core buyer right not every company has an analyst that’s right the average analyst buying power is about like negative twenty whatever they’ll invest personally in the tool we think about this we think about this a lot like if i get a chance i’d love to demo are again i’m gonna sell right now because you brought it up but i’d love to demo our power report for you it’s like a pivot table in the interface and it’s crazy What we discovered though is that a majority of our customers, it demos well. You’re right. It actually demos better than some of the other tools that are claiming analytics because we’re actually an analytics tool. We know how to build that stuff, but we hate selling it because it causes so much support. for our, you know, 70 person company. You know, I kiss metrics on like dealing with that and, you know, Jim doesn’t like it or he doesn’t know how to help us sell it or get people to use it so I have no idea on that one. But like, what I mean by analytics as a feature is like, yeah, on the enterprise end people are demoing analytics and sales force and all that and you run through the issues you’re talking about. But I just mean literally that you’re seeing data and charts and views in tools that are action oriented, right? And it’s like my favorite tool right now that’s really close to the action that’s not something I’ve built is Intercom. Are you guys familiar with Intercom at all? Pretty sure you’re not talking about the button outside of my front door. No, I’m not. It’s intercom.io. And their message on the home page right now says an entirely new way to connect with your customers. And so if you log in to it, they have literally your whole customer database sitting there and you can filter it. And to me that is starting to be like what we’re going to start seeing in the future. They also send me this lovely email every day about who signed up yesterday and how many of them signed up and the fact that I can message them. They even tell me who’s slipping away that I should be re-engaging with. So to me like at the backbone of what they built is a data warehouse to store your data. It is the ability to get that data fast and then be able to analyze it and then let you take action on it. So that’s kind of what I mean by analytics is a feature. We’re going to see, I think, more analytics or what we used to call analytics in a lot of these tools, but they’re not analytics tools. They’re action tools.

00:26:35.52 [Michael Helbling]: So I would probably agree in principle and disagree a little bit with sort of the idea that it’s a feature. What I think is that you have all of these action-oriented tools and kind of, if you look at sort of marketing technology and the Scott Brinker stuff is really a good way to think about it. In what I think is you still need to think comprehensively about data and data usage across the enterprise and has to have an owner and has to have a system of record so that you can actually use it for something meaningful in terms of actually doing analysis and making decisions. So I would say the all these tools and all these different action oriented platforms. Instead of having their own analytics, really should focus on data transportation and portability. So then I can go and easily integrate them into wherever I’m using my system of record. So that’s kind of how I would probably me personally is probably how I would want to approach it.

00:27:34.13 [Jim Cain]: Yeah, but you’re an analyst, dude. Like what I think is interesting. No, that’s not true. You just play one on TV. But the thing that I think is really interesting about what Heaton said, and I’ve never thought about it before, is our last couple of discussions have always been about quality of data, transparency of data, accuracy of data, being able to have an opinion and those kinds of things. If I’m not totally wrong, your point is those things are great, but one of the ways to solve the problem of there aren’t enough analysts is to make the product smart enough to shorten the list of things that you should care about. So instead of having a total that lets you do your own discovery, here’s five things you should give a shit about. Do those.

00:28:13.45 [Michael Helbling]: Don’t take it inside, Jim.

00:28:16.35 [Hiten Shah]: I think it’s a really interesting comment. I would say that there are complex business problems that mostly right now enterprises and really high growth companies with lots of data have that analysts will always be required for. But there are a ton of problems that today analysts are doing repeatedly that they will not have to do in the future. So it’s not even a gripe against analysts. It’s just like I would say 80% of your job, I don’t want you to do anymore because you shouldn’t have to. You should be working on the 20% you know that’s hard and you should probably learn data science if you don’t know it because that’s where your jobs go in my opinion right and so it’s like these two honestly intercom kiss matrix mix panel all these tools were so far we’re still in the dumb tools era. I think our tools might be a little smarter than Adobe, a little smarter than GA, but we’re still all pretty dumb. And what you’re going to see as a next wave, in my opinion, would be all these tools get smarter. They get closer to helping you take action if not doing it for you. your job is mostly going to be as a marketer, hopefully, about obviously analyzing the harder problems in your business, but also spending more time on the creative side of it, and trying to figure out better ways to get clicks, or better ways to get people to do good things for themselves, hopefully, or not, and things like that.

00:29:35.06 [Jim Cain]: Could we say that a hallmark of a best of breed tool is the fact that rather than just data Capture and data analysis. It’s designed to create more actionable like it’s designed just to filter Oh good lord.

00:29:52.62 [Tim Wilson]: You should be selling for some large enterprise Company along with unicorns. There we go. What do we make it? We made it 30 minutes in before before I think it’s a valid point Well, but I guess I was I was actually I think I was coming I was gonna ask this I was gonna ask a similar so he didn’t if you look five years down the road and and your roadmap and vision for KISS metrics, is it taking that core data model built around the user and making that so flip and fantastic and you’ve captured that much more and better data in more places But there’s another tool, and whether it’s intercom or it’s pick your, I’m going to blank on every possible name. There’s somebody else saying, hey, that’s amazing data capture. And it’s captured and modeled in a way that I can take it and hook it into all this other stuff and get us to the promise of big data. Or is your would you say five years ten years down the road you actually want to be that so we got a better data model and therefore we are going to be able to shorten that cycle and remove some of the analyst workload and drive to action. Or is that a totally false distinction and bullshit question?

00:31:06.83 [Hiten Shah]: I just go back to some examples. When we started Kissmetrics, one of the things that really helped us key in on this idea that it’s about the person is we studied the fastest growing companies that were not enterprise companies, because I don’t think they grow fast, but that’s a different story, except maybe Apple and Amazon, but whatever. But we studied Facebook, we studied these companies at the time, they weren’t as large as they are today, and what we realized is they don’t use Omniture and Google Analytics for the most important decisions they’re making. They’re using their own data warehouse and their own data, and we try to understand why, and what we discovered is they want to tie the data to users, to people, and I know I might be starting to sound like a broken record, I’m getting to the point. And so in the same vein, what I see today is there’s early indicators that are obvious today of a similar trend, just kind of an expansion of that. So what I think about it is not even like, are we going to get better at it around that data model thing? We’re actually fantastic at it. And I think that we’re probably best in class, but I’m completely biased there. And we don’t need to go spend another five years working on that. I think that would be a mistake, because it’s already not even good enough. It’s great. and it’s accurate and it’s auditable and all that, just not enough people know about it. But what’s next is kind of, I could pull up the article, but late last year, Uber, they put out a blog post and said, right when you open the app, they can predict, I think, what’s 74% certainty or something like that, I’m gonna butcher how they said it, what your destination’s gonna be.

00:32:36.36 [Tim Wilson]: Do you know what are they using for their, is it a homegrown data collection? I think your Facebook, Amazon, eBay, our last episode we talked about big data and talked about how those were companies that have big data. I think you’re right, they’re tying it to a huge, like what’s Uber using?

00:32:54.54 [Hiten Shah]: It’s all in-house and they said that they used a Bayesian model to do it. 100% sure it’s all in-house. I’m sure they’re not using outsourced stuff outside of Amazon Redshift and things like that. to do it, and their data, I mean they have a whole blog post on how, basically the statement they said is, we found that 74% of the time our model could correctly predict the exact destination address. So to me, we’re… Ha! They have Crazy Egg on their site. Ha! Yeah, great. I’ll take it. My point of view is we’re starting to see that these companies are on the cutting edge, that the fastest growing companies, they have a ton of data. This is the kind of stuff we’re doing. My goal would be to build product to support these use cases so that more companies can do this. Because the thesis I would have is more companies are going to have the amount of data that basically would enable them to get value from analysis like this.

00:33:48.87 [Michael Helbling]: I think in the quote-unquote enterprise world, we call it personalization, right? But it’s basically the pursuit of the same thing, which is the ability to interact in a much more meaningful way and a personalized way with an individual customer at any given point of contact.

00:34:03.83 [Tim Wilson]: This may be the lobby bargain close to last call talking, but it seems like there’s a little bit of a minor epiphany that this goes to kind of the shifting. It’s not the internet economy. Gen X, Gen Y is getting more comfortable with their personal data. They’re more comfortable being identified as individual people, which means old school. And I’m thinking I’ve got large CPG clients where they don’t get a ton of traffic. And as people come in to look for coupons and product information, and there’s very little reason for them to come back or to be to have kind of a rich ongoing personal experience. But you look at the new economy, I can’t really say new economy, you look at the Uber, you look at Amazon, you look at things where you’re saying I’m buying this kind of hybrid product and service and I do need to be subscribed or I need to have this ongoing transactional relationship and that is kind of a fundamental shift from a website because I’m bouncing across devices. And because of that, it sounds like some of the more like heat in your research was some of the most explosive growth type companies have said the data is so important that we need to build our own solution and pay top dollar for these data scientists and really, really invest in that. But the second wave is going to be, that’s just kind of the new norm that’s expected and there need to be more off the shelf tools that support that kind of mode of tracking and thinking and analysis.

00:35:47.93 [Jim Cain]: That’s correct. See, I heard something similar, Tim, but what I actually am wondering, you know, so you were saying that there are shifts happening. You talked about the best in breed companies and now I’m wondering if If you could make a prediction, in five years are a lot of companies not using a Google or an Omniture or one of those tools, but they’re actually buying best of breed, feature level, best in class tools, and then plugging them directly into the data mart. You said yourself earlier, I could give a shit about Google or Coremetrics for data normalization. I want to look at the in-house data mart. So do you think people are going to, like they’re not going to replace Omniture with Kiss Metrics. They’re just going to get rid of Omniture and plug Kiss Metrics directly into the corporate BI system.

00:36:33.91 [Hiten Shah]: Yeah, I don’t know. It’s definitely hard to predict the future. I think I just look for things that are obvious and things that are already happening. So Uber is not running on Omniture today from what I can tell. They’re using a lot of in-house stuff. The question is, is the next Uber going to be using Omniture or something else? What’s more likely? It’s likely they’re going to be using something else, if anything. And so, yeah, I think those companies are going to get disrupted very fast. I don’t know, I have a little bit of a fetish for origin stories and so I think the origin of our industry starts with logs and log files and that’s where a lot of these companies started out, grew up, understood what they should be doing and built significant businesses. In today’s world, there’s probably going to be a company that doesn’t exist today that’s likely to power the next Uber on doing this kind of stuff. It’s just the way it works. Even our whole business is… probably going to change as mobile evolves and as marketers get used to or learn, you know, as we figure out as marketers how to deal with mobile. So I think, I don’t know, I mean, I just can’t see a future where like Google Analytics and Adobe, Adobe Web Analytics, Omniture, whatever. are actually the primary tool that companies utilize. And I think this whole idea of best in breed, I mean, if you think about it, SAS is still pretty new. I think a lot of people don’t understand things that I’m going to say that are controversial, but probably whatever is. People need to be able to sign up and try a tool. Like, that’s really important and it’s going to, going forward, be even more important. So if you can’t do that with your tool and you don’t build a right, the proper user interface to let people do that at scale and easily, then I think you’re dead. You’re done. And like, unless these companies start paying attention to some of those things, reinvent themselves around that, yeah, they will be gone. Like, it’s just inevitable. But that’s just classic. It’s like where I started with this, right? It’s innovators dilemma, dilemma, super classic. It’s also like we’re probably in some new category creation mode very soon as well. I really do feel that analytics is just a feature. I don’t believe people are going to be buying analytics in the long run.

00:38:46.85 [Jim Cain]: So to paraphrase, Adobe Analytics is the fax machine of measurement.

00:38:52.44 [Hiten Shah]: Yeah, basically. I’m happy for you to quote me on that. But you can help with it. I’m quoting you on that.

00:38:57.89 [Tim Wilson]: That was Jim Cain of Napkyn Systems. That’s right. Just to be clear, everyone clear on that.

00:39:05.08 [Michael Helbling]: All right. Well, listen, guys, we are, as always, covered a lot of topics. None of them, given the justice they deserve. But I really like where this conversation went. And actually, I feel like we went somewhere different than where we started to. And I’m really glad we did, because I think we exposed some really key things. I want to go around and get everybody just to give a little recap of what they thought was most interesting to them out of what we discussed today before we wrap up.

00:39:34.05 [Tim Wilson]: You’re going to point to someone, maybe, Al. Mine’s not that easy, because I think Heaton’s whole point on the underlying The core model being user-centric versus, I guess, content-centric, that’s me putting words in his mouth, but the ability to have that kind of nimbleness sort of makes me, and I’m not just saying for kiss metrics, I think we kind of hit on not that everything is necessarily user-centric versus content-centric, but that there’s space for tools that say the way people are using digital is Shifting and what is going to make them what it’s going to make companies successful is shifting and evolving and They’re legitimately a very strong claim can be made that you need something it’s something that is Nimble and inherently younger and started at a later point to kind of disrupt that to Actually, you know pull that off. I’m not I’m not prepared to say Adobe’s going away and And that they’re not going to make that pivot. They’ve got a lot of dollars behind it as does Google. And they’re going to be listening to this. It sounds like none of this is super secret. It’s kind of philosophical differences trying to predict the future, which we just said was difficult. But I think that’s a good way to look at it, that there are lots of ways to tackle what’s being captured and how it’s being crunched and when you’ve got two behemoths that are largely going at each other, they’re going to converge around one approach and there’s definitely room for other approaches.

00:41:14.53 [Jim Cain]: I guess my couple of cents are that I’m going to sit down in front of a whiteboard tomorrow after this session. I never really thought about building a measurement ecosystem where you have a set of best in class tools without a web analytics tool and what that looks like. I think it’s really neat and I’m going to wrap my head around it. Again, you know, we said it a couple of times, we can’t predict the future, but the ability to take several tools that are great at something specific and bring them together directly at the BI layer is really interesting. So I definitely, you know, I’m thinking about that one today. I think the second thing that I learned is that Heaton agrees with me a lot more than Tim, which I think is important. Well, but that goes for most of the population of the North America. And you know, I think the last thing is that we never really talked about the practitioner level. And you know, one of the things I’m always surprised about is given how many fantastic tools there are in measurement that more senior level practitioners either don’t have the chance or the opportunity or the budget or the inclination to really spend some time heating you said it earlier a lot of tools like this metrics you could try it before you buy it and people don’t even have the bandwidth right and I would love the conversation about I’m a practitioner I have a specific need how do I find a tool what are the best practices for trying that tool what are the recommendations to bring it into my ecosystem I would love to have talked through that maybe we could do some other time

00:42:50.34 [Tim Wilson]: Also my lightning lightning round question for heat and who actually are your end users? Are they analysts or are they marketers or they something else or is it all over the place? Online marketers 80% so it’s marketers a lot of so big based on who you’re targeting They don’t even have analytics teams or their analytics teams They they need to be self-service because the analytics teams aren’t so top 10% have analytics teams. Okay, that’s awesome. That’s interesting Damn it. There was something else. We’re gonna have to have it back. Okay, I

00:43:17.60 [Michael Helbling]: Tim, Heaton was going to give his recap, but you like jumped in never mind. No, I just had to. No.

00:43:24.65 [Jim Cain]: Well, apparently we have a lightning round now. I didn’t get the memo.

00:43:30.46 [Tim Wilson]: Episode 6. We think it was the first guess, but it was really where the introduction of the lightning round. I’ll stop now.

00:43:36.91 [Hiten Shah]: All right, I guess it’s my turn. You know, it’s always nice hearing other people’s perspective that are very experienced with the industry from a different point of view than I am. I mean I’m always thinking about I look at a product and I don’t really care why it’s awesome. I think much more about why it sucks just because I tend to build products and like building software and I think it’s something I just can’t get enough of and I keep building more new software. I think there’s a mental model that exists in people, all of you, even myself, you know, Outside of building this product and these products is that there’s just a mental model and the mental model is from based on your experience and based on sort of the cohort you sort of you know and the tools you sort of used as you were sort of practicing your craft. And I think I learned a lot about that mental model. Even the word content that you used was enlightening to me, because the words that you use are probably more accurate to how someone who uses Adobe and has a lot of experience with Google Analytics would use. Because I would say it’s page view, but you’re right. The data models that those systems evolved into had a lot to do with content. And everything was about content focus. I mean, if you think about mobile, that’s not going to work. That’s probably why Google Analytics sucks at mobile. To be honest on the mobile front, I think everybody sucks at mobile analytics today. And you can quote me on that. You can do whatever. I pretty much know what needs to be built in my head. I’m not going to talk about it. And we haven’t built it at Kissmetrics either. And I think it just requires a different target customer. And that’s the issue with mobile right now for us, at least. And we have a blog. We get a lot of marketers because of our blog. We probably get more signups for trials than Omniture gets in a year, would be my guess. But that’s just a whole different game.

00:45:28.58 [Tim Wilson]: So anyway, yeah. Is there a page to sign up for a trial of Omniture?

00:45:32.78 [Michael Helbling]: Yeah, I did it while we were on the air here.

00:45:35.58 [Jim Cain]: It cost $77,000.

00:45:40.53 [Michael Helbling]: You guys are doing all my work for me. First, we have to establish your base CPMMs.

00:45:47.98 [Hiten Shah]: I think it’s a request to demo, and now they’re going to show me the benefits of Adobe Marketing Cloud. I just went to their site, so I think that’s what it is. Anyway, so I think the mental model people have is always enlightening for me. It’s a lot different than what I think about every day. Even the fact that you guys really haven’t heard about Intercom makes my day. So super glad to introduce you to a new product that you probably should be thinking about and using. Anyways, that’s what I got.

00:46:13.54 [Michael Helbling]: That’s great. I think for me this episode more than anything else has confirmed and exposed this dichotomy that I’ve sort of started to see but haven’t been able to nail down between what I would say sort of You know, you kind of call it the fast growth companies that you studied versus maybe traditional enterprise. and how they use analytics. It was certainly run into this multiple times, but I really loved how that sort of crystallized tonight and that those companies that are growing like that, they’re not using the traditional tools, they’re kind of approaching it a different way. And you definitely see that in the startup space, like a lot of times, you know, a startup will have Google Analytics or something on their site, but it is not how they need to work to measure the business to be successful as a startup into and to go and do what they need to do. So anyway, that was kind of my key takeaway. The other thing is this concept of marketing cloud and how I think sort of we’re headed toward a convergence. The enterprise side is trying to take the old school digital analytics tools and build a marketing cloud to basically do what these point solutions have created over here on the side. And at some point, we’ll kind of hit in the middle somewhere, and I think there’s a big interesting fight to be fought across many different layers of the industry around what’s the best or a better way to do that, whether it’s sort of like, okay, go pick the five best tools that do this and do that to be successful, or go buy one vendor’s big package of solutions, and that’s the best way. It’ll be interesting to see how that unfolds. Anyways, that was my two takeaways. Well, thanks everyone for listening. I think it’s been super amazing, eating to have you as a guest on the show. Thank you so much for your time. To do that, I think our listeners will get a ton of value out of this conversation and your perspective. I think there’s a lot that people can kind of take away from that. Obviously, you know, for the digital analytics power hour, we want to talk to you and hear your comments. So please let us know on Facebook, facebook.com slash analytics hour. And also go ahead, if you subscribe to this podcast via iTunes, you know, feel free to rate the podcast and things like that. Again, for Tim and Jim, And thanks once again to Heat and Shaw for being our guests. This is the Digital Analytics Power Hour. Signing off.

00:48:41.63 [Announcer]: Thanks for listening and don’t forget to join the conversation on Facebook or Twitter. We welcome your comments and questions. Facebook.com forward slash analytics hour or at analytics hour on Twitter.

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