#81 Marketing vs. product analytics
Dan and Dara kick off a new season of The Measure Pod by introducing Bhav Patel as a guest co-host and discussing all things marketing and product analytics. Dara tries to play Dan and Bhav off each other, Bhav promises to bring controversy, and Dan gains Bhav in team-User versus team-Session.
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The full transcript is below, or you can view it in a Google Doc.
[00:00:15] Dara: We’re back after our break. We’re back recording again, releasing new episodes, and we’ve got some changes this time around, which we’ll go into in detail in the episode itself. But one of the changes for the next 10 episodes or so, we’re going to be joined by Bhav, who’s going to be a third guest host. And on today’s episode we chat with Bhav about product analytics, which is his kind of subject of choice.
[00:00:41] Bhav: I want to assure all users who are listening that this isn’t my only topic. I know we’ve covered it in the previous episodes where I’ve also been a guest. I can talk about other things. It seemed like a nice intro to talk about and go a bit more in depth, especially given that GA4 is such a hot topic right now. So I figured it might be a nice ease into sort of like the next 10 episodes, something I’m comfortable with. And then for the next, remaining episodes feel free to put me well outside my comfort zone.
[00:01:05] Daniel: Well, this episode was great, Bhav, and again, thanks for agreeing to come do this next season with us. I love this chat, I think it was a really good way of kind of jumping straight into this idea of, you know, the stuff you bring into the conversation. Me and Dara have always had this marketing analytics perspective, and we’ve dabbled and dipped into the world of product. And I think what you’re doing is kind of bringing, bringing that full circle. So like you’re kind of coming at it from the other aspect. Well, this was such a great conversation, I loved how we jumped into GA4, product analytics tools like Mixpanel and Amplitude. We jumped into product like growth and all of that stuff you’ll hear on the episode, but I’m really excited about the next couple we are doing. We’ve got some guests lined up, we’ve got a couple of people in the product analytics space as well, so the kind of people that me and Dara would never have found to come on the podcast.
[00:01:44] Daniel: But obviously we’re still going to keep talking about my favourite subject, GA4. So there’s our first shot. So if you’re playing the drinking game of The Measure Pod, there you go. We’re probably going to be a bit tipsy towards the end. So, yeah Bhav what have we interrupted you doing today? What, what’s going on? Anything coming up? What’s going on in the world of Bhavik Patel?
[00:01:58] Bhav: What’s going on? What have I been interrupted on? I’ve been spending a fair bit of time building product. I think you’ll talk, you’ll hear about it at the end of the episode around when Dara does the rapid fire questions, which are new from what I understand. And so I’ve been, I’ve been spending a bit of time trying to solve a problem. I’m one of those people that once I’ve had an idea, quote unquote, into my brain, it’s hard to let go of. So I’m really trying to solve this self-serve problem that’s been my day-to-day, or that’s what would’ve been my day-to-day.
[00:02:24] Daniel: Is there a way to, to find out what it is, Bhav? Or are you going to leave us hanging?
[00:02:28] Bhav: I can give you guys, there is a waiting, like a waiting list, so I can give you a link if you want, or we can put it into the episode if anyone wants to learn more and they’re dying to understand how to self-serve themselves a bit more.
[00:02:37] Dara: Let’s call it there. Enjoy the episode.
[00:02:39] Daniel: Enjoy the show.
[00:02:41] Dara: Welcome back to The Measure Pod, it’s good to be back. We’ve taken a slightly longer break than usual and part of the reason why is because we’re going to shake things up a little bit, so we’ve got a slightly different format going forward, and for the next 10 episodes, we’re really happy to be joined by a guest host who’s none other than Bhav, regular friend of the show. And you’ll notice a couple of other changes in terms of the format and the layout, which you’ll find out as this episode goes on. But firstly Bhav, welcome properly to The Measure Pod as a fellow host.
[00:03:12] Bhav: Thanks, Dara. Thanks, Dan. It’s, you know, it’s great to be here. I know I’ve done a couple of episodes with you guys. I should be more relaxed about this, but actually I’m quite nervous as well at the same time, because I really like The Measure Pod and I’m joining you two as a guest host for the next 10 episodes. I hope I can bring some value to the conversation and some insights and some humour as well. There’ll definitely be some controversy, I promise I’ll bring controversy to these episodes.
[00:03:33] Dara: Well, my goal is going to be to try and get the two of you to debate with each other. I’m going to basically have a big stick and I’m going to try and stir the pot as much as I can and try and set you off against each other.
[00:03:42] Daniel: We’re all friends here, we’re all friends. We won’t disagree about anything, I’m sure. Definitely not about our first topic which is product analytics. But I’m going to bolt a bit on the end of there. I’m going to put, versus marketing analytics. So I think between that, we’ve got the red corner and the blue corner covered, Bhav.
[00:03:57] Bhav: Yeah, let’s go for it. I’m geared up and ready to go.
[00:03:59] Dara: Well, just before we start, what’s the boxing? It just shows that little I know about boxing, whatever the, whatever the phrase is, just before the bell rings and you start slugging it out. For the benefit of anyone who’s listening to us for the first time Bhav, could you just do a quick reminder intro as to who you are and a little bit about your background.
[00:04:16] Bhav: Yeah, sure thing actually, that’s probably a good starting point. So I’m Bhav, if you didn’t know, I’ve done a couple of these episodes, but if this is your first one, my background is typically product analytics and experimentation. I’ve worked at companies like Hopin, Gousto, Photo Box, Moo and the likes and various other places in between. I’ve also built, grown, and run a meetup community in London called Crap Talks where Dan has become a volunteer and helps out every time we run one of these. So thank you, Dan. And currently I’m working as a consultant for a consultancy I’ve started called CAUSL. It’s a product measurement consultancy, which helps product teams connect the dots between the product, the customer, and the organisation. So it’s probably a bit about me. You can find out more if you want to just reach out to me on LinkedIn or something.
[00:05:01] Dara: And again, for the benefit of anyone who’s maybe joining us for the first time Dan, can you give a little intro to yourself?
[00:05:06] Daniel: Well, welcome. If it is your first time listening, I’m Dan. I work at a company called Measurelab. We specialise in marketing analytics and things like Google Analytics, Google Tag Manager, and the Google Cloud Platform. I’m an analytics consultant and trainer focusing on Google Analytics 4, or at least it feels like that’s all I’ve been doing for the last couple of years.
[00:05:22] Dara: And I’m Dara, I’m also at Measurelab. I’m the CEO and one of the co-founders.
[00:05:26] Daniel: All right, well, this is the first of our series of 10 Bhav, and so I would say welcome back, but I’m just going to say welcome home for the next period of time anyway. I want to start by asking you probably a very basic and dumb question, but I think I’m allowed at least one or two every episode and just start by talking about product analytics. Like me and Dara, if you have been listening before we come at this from a very much a marketing analytics angle. The Google stack is very adapted and very suited for marketing technology, but coming at this from a product analytics perspective is a really interesting position, but with lots of stuff that’s going on with Google Analytics 4 which I’m sure we’ll get into later on. Let’s start at the very beginning and start by defining what makes a product analytics tool a product analytics tool, and why is that not the same as a marketing analytics or other analytics tools?
[00:06:08] Bhav: It might be worth before going into the tool and technology space, talking a bit about the difference between product analytics and marketing analytics. To start off with, there isn’t that much of a difference in the grand scheme of things. We use these terms product analytics, marketing analytics, they’re just terms, you know, a product company will still do marketing, and a marketing company will still have a product. Product analytics is specifically talking about your digital product or service. How do you analyse the digital product and service is going to be very different to how you might analyse your marketing activity, because there’ll be companies which are very product heavy first you know, for example, the likes of Spotify, Facebook, Twitter, all of these are more product heavy companies. They don’t really sell anything, okay, Spotify sells a subscription service, but that’s not, you know, that’s not the core of what they do ultimately, it’s creating great experiences for users by giving them music that’s built around their taste.
[00:07:02] Bhav: And then you have more traditional ecommerce companies and you know, you’ll probably spend more time focusing on marketing than you will on the product because the purchase funnel is going to be quite straightforward. So, you know, your companies like ASOS and even Amazon to some extent, you know, these are probably going to be more of your ecommerce companies. And they have products that users will interact with but at the end of the day, the goal for them is to get users from the start to the end of that funnel as quickly as possible. Whereas in product analytics, you want to keep users on your site as long as you can, engaging with your product. So those are the two kind of differences between product analytics and marketing analytics.
[00:07:38] Bhav: In terms of the technology, I guess the big difference is, and why GA4 has not been the primary tool for product folks is that historically it’s been very much a session based tool. And when you think about products like, let’s say Spotify, just because I like product, it’s not a product which you measure in terms of sessions and journeys and you know, all of those classical ecommerce reference points. It’s a kind of an ecosystem in itself. And in order to measure that, you can’t use a technology like GA, well, Google Analytics anyway, Universal Analytics to do that, at least not in a way that makes sense. You probably can for how much traffic is being driven to the Spotify signup page and how many people go through the signup funnel and things like that. But when you’re actually a user of the platform Google Analytics, Universal Analytics, starts to break down because it relies on the concept of session, whereas product analytics platforms like Amplitude, Heap and Mixpanel, they typically focus on events, what users do, how frequently they do them, the depth to which they do them.
[00:08:38] Bhav: And so you don’t have a clear, straightforward, linear journey. What you have are multiple permutations of how users might interact with your product, and that, I think, creates the core fundamental difference for why product teams have historically gravitated towards product analytics platforms like Amplitude, but as you guys of all people will know, Google has now shifted from Universal Analytics to GA4 to kind of like tap into that event based model for analytics.
[00:09:06] Dara: Just a quick follow up question from me on that, Bhav, would you typically, would the users typically be identified within a product analytics environment. So regardless of the technology you’re using, you’re typically talking about a product where this is a signed up user or a paying customer. So would that be a kind of fairly fundamental difference between maybe marketing analytics and product analytics where, you know, the volume of identified or the percentage of identified users would be vastly different.
[00:09:33] Bhav: You know, that’s a really good point. I think the answer to that is, it’s obviously going to be a lot more nuanced, but yes, in short, you would use product analytics where you probably know more about your users than you do in a more ecommerce space. We’ll have signup funnels, you’ll create user IDs, which you will then tie to anonymous cookie IDs and try to tie all of it all together so that you can build a single customer view of that user to understand, you know, how engaged they are. Are they a customer who’s likely to churn? Are they a customer you’ve retained for a long time? Whereas in the marketing and the ecommerce space, you probably don’t worry about it too much, and especially if you don’t have a luxury product, which customers buy from frequently. I think Amazon, you would probably say, would know everything they’d want to know about their user just because of the value proposition.
[00:10:16] Bhav: It is sticky, their prices are low, they do create a subscription service. You do make multiple purchases from them in a given week or a month. So I would say yes. You’d probably want to know more about your customers in their product space than you would in their classic ecommerce space.
[00:10:31] Daniel: I think that’s a core difference. Maybe I’m saying the same thing, but it’s not just because they’re logged in, but you’re talking about account analytics rather than user analytics, and I know we’re all talking about human beings here, but actually if you’re looking at like a B2B SaaS platform, then actually looking at the account usage is probably an angle which something like Google Analytics or marketing analytics that sort of historically uses is more user activity and it’s acquiring a user or converting a user or a session. Whereas actually what I found over the years is trying to look at account acquisition from like a B2B company that’s got like five people browsing a website or maybe fulfilling different parts of the sales funnel. That’s a nightmare to do in any marketing analytics tool. But actually from a product analytics tool, they’re more designed to be spun and pivoted in those different ways, because that’s a kind of fundamental part of a product, right? It isn’t necessarily about individual human beings. You might have five people logging into one account, or at least you might have something more baked in that way.
[00:11:26] Bhav: Yeah, I agree with some respect. You know, I think from a SaaS perspective, you typically sign up as an organisation and then you have users within that. But actually you also get, you know, you’ll have products where you’ll have your own personal account and you’ll identify as an individual as opposed to an organisation. So for example, Canva is an interesting one. I imagine Canva has organisations which sign up to Canva, but I have a personal Canva account just because I’m not a designer. So for me, having that personal account, you know, I think Canva will probably look at me and think, okay, this an individual and try to create an experience that is bespoke for my needs if they do certainly go into things like personalization. You know, obviously I’ve given you my views but you’ve done nearly a hundred of these podcasts, I think we’re approaching a hundred, I think. What would you say are the big differences, like from your point of view?
[00:12:13] Daniel: I think a key one is going to be the, the sessionization, the only time I hear the word session used is from a marketing analytics perspective. And I think for me this is the most interesting spin on this whole thing is to try and aggregate events or hits or pages or actions into clusters. Because generally from a marketing perspective, especially from like things like search marketing, you’re paying per click, and so you want to measure a success or failure rate of a click, and so you have to kind of aggregate clicks into something in, in your own sort of web or app data, which doesn’t, it’s not always easy because you know, you can say, I’ve driven 15,000 clicks and I’ve spent, I don’t know, 20 grand on something, was that successful? But you know, it’s always a layer of complexity where to say, well, actually, those users then went on to, and this is the whole conversation around attribution modelling and cohort analysis and things like this, where actually someone just wants 15% worked. You know, that’s the kind of numbers that people want and I think, you know, me and Dara have talked about this a lot, and I can link in the show notes off to some episodes where we discussed the merits of sessions versus users, which has reared its head a couple of times I think over the years, Dara.
[00:13:15] Daniel: The idea of a session is squarely within the marketing analytics space. And what I want to get onto and ask back to you as well, Bhav, is this idea of Google Analytics 4, as you said, has come along and it’s this, in this very unique position where, Universal Analytics might have been the most widely adopted analytics tool out there for whatever reason, because it was free, it’s kind of easy to implement. Most platforms, at least at this point have integrated or got an automatic integration with it. But when they introduced Google Analytics 4 at least in its infancy, when it was app only software in Firebase Analytics. It was purely product analytics, it’s all event based, users and events. They didn’t even have sessions in there. I don’t know if you remember this, Dara, but we had to aggregate and work out sessions using BigQuery. We had to export all the data and then reaggregate up sessions because it wasn’t a fundamental metric within this. And I mean, we can talk to the way Google Analytics 4 is now, and we’ve gone well back into the world of sessionization and all that kind of thing.
[00:14:04] Daniel: But it very much started life out as a product analytics tool, but it’s kind of been forced back into this world of marketing analytics. So yes, a long answer there, Bhav, but I think for me it’s the, the concept of a session or the dependency on the idea of a session is the defining factor that makes, you know, they’re all tracking the same things in very similar ways, but whether you turn it into sessions and measure those as a primary metric or whether you’re looking at user cohort sequences, funnels, that I think that’s the key difference between the two.
[00:14:29] Bhav: I don’t want to belittle the whole concept of the session because I think it is still going to be important. The main difference is that rather than Google defining what that session is, you get to define what that is as an organisation because I think, you know, if we go even one layer deeper to sessions, I think the real thing that’s archaic in this like kind of modern product era that we’re in is page views. And I think page views are the fundamental thing that defines the start and end of a session. Maybe I talk about sessions, but actually maybe what I should really be talking about is actually we need to kill off the concept of page views because, you know, going back to my, actually, you know, I won’t use the Spotify example. Let’s say chess.com. I’m a big fan of chess.com. You wouldn’t ever play chess and, you know, in the point of a session, right? Especially if you use the app. And for them it might be better for them to create the concept of a session as the length of a game.
[00:15:17] Bhav: Now, the length of a game can be anything from a blitz game, which is about you know, three minutes per player. Or even one minute if you really like adrenaline, to games that are played out over 2, 3, 4 days, my rankings for a longer game is naturally better than my rankings for a blitz game because I’m terrible. But in that sense, I’m not, you know, I imagine chess don’t give a rat’s ass about how many page views I’ve had or how many sessions I’ve had. They’re probably keen on the fact that I’ve completed an entire game and they’re probably racking up from their point of view what the concept of a game would be, as, you know, as their session. You know, my point is I don’t want to belittle sessions. I think they do exist, they’re still going to be important. It’s just the definition of a session needs to be more than the start page and the exit page and the 30 minute timer, which Universal Analytics historically put on these type of things.
[00:16:04] Dara: You could argue the same these days for, well, maybe you always could have actually, but for websites, we all have multiple tabs and multiple windows all the time, so what GA will count as a session could actually be what you as the user thinks of as one experience or multiple experiences, there’s not a one-to-one relationship there. You know, you might start browsing before you start work in the morning, and then you go back to it at lunchtime. GA’s going to count that as a second session, whereas in reality, you are thinking, oh, I must go back to that travel website and look for where I’m going on holiday again, and then maybe at the end of the day, this is assuming it all happens in one day, which obviously it won’t typically, but let’s say it is something that happens within the day, then at the end of the day, you might go in and complete your purchase.
[00:16:47] Dara: So GA might count that as three sessions, but in reality, It’s not really three sessions, it’s three parts of the same experience for the user. So I’d love to see Google Analytics get to a point where you as the owner of that Google Analytics account, you can customise your own definition of what a session actually is.
[00:17:08] Daniel: I think you can, to an extent, and I think this is maybe where we go a bit deeper into the GA4 world, I’ve obviously been spending a number of, I think I’ve may have clocked up my 10,000 hours already. But the thing with GA4 is that it has killed off the idea of a, of a page view and even a session. When I’m teaching someone GA4 for the very first time when they’re, when they’re new to it, I tell them, especially if they’re used to Universal Analytics, I tell them one thing at the beginning, which is there is no such thing as page views and sessions anymore. I mean, the number, the column in the reports that exist, like you said, Bhav, like sessionization is still a thing. The dependency on sessions and page views just don’t exist. And it kind of makes sense in the grand scheme of things when you realise this is a tracking tool that’s capable of tracking, you know shop tills or servers but also Android, iOS apps and websites where sessions don’t have to have page views anymore.
[00:17:50] Daniel: There’s nothing special about a pageview anymore in GA4. It’s just an event that happens to have the name “page_view”. And I think this shift of a way of dependency is actually affecting things like the definition of a session. So fundamentally, the definition of session is very similar to Universal Analytics, which has become kind of industry standard just because the nature of GA being everywhere. But now what a session is defined as, let’s say you leave all the defaults on whatever they are, is a string of events from a user with no gap between any one of them of more than 30 minutes. So in a sense, the more a sort of user engagement, the more tracking you implement, the more likely you are to stitch these sessions together and fundamentally change the definition of a session.
[00:18:26] Daniel: If you are someone like Spotify, for example, and you send the app to the background, obviously while you’re doing other stuff, you’re listening to music then let’s say they’re using GA4, I don’t know why, but every single track that comes and changes over, if you log that as an event, it will keep that session active. And so as long as you’re logging events, but you know, with no gap between them, more than that, 30 minutes is keeping that session alive, and I think this is the biggest change. And also there doesn’t need to be any page views in a session anymore. And so sessions are these clusters of events, and what I find fascinating about this is because whenever I’m teaching people Google Analytics 4 often they’re marketers or analysts, but they’ve come from a Universal Analytics view of the world. But actually this is no different to most other product analytics tools in a sense this way of looking at data has been around for many, many, many years.
[00:19:10] Daniel: But because Google are doing it now, it’s like it’s brand new, right? Because no one’s really been aware of it. Product analytics has been a specialist thing for product analysts or for product owners. Whereas now it’s like, the masses, everyone, the marketers, the business owners. Everyone’s now using Google Analytics because it’s such a change, but I’m like, oh, it’s like, it’s almost like Google is catching up, and yet everyone’s treating it as if they’ve, you know, they’ve invented it. I always find that quite fascinating when we go through this kind of stuff.
[00:19:35] Bhav: Well, it’s going to blow people’s mind when they think about not in the session sense, but in terms of a user sense, because that’s going to be, that was going to be my next thing. If we keep peeling this layer apart, you know, okay, we went inwards to understand page views, but actually if we go outwards and understand the meta onion, the concept now starts to move towards users. Are you guys familiar with the term product-led growth or PLG?
[00:19:55] Dara: I’ve heard of it, but please enlighten me further on what exactly it means.
[00:19:59] Bhav: It’s just a kind of like modern way of thinking about how you grow your user base or your organisation and or your, you know, your revenue. And instead of it being a classical marketing led approach where you pump money into the marketing funnel and drive users to your website and then grow through that stream. You take the users that you have, you engage with them, you get them to interact with your product. You get them to try it for free or using some type of like freemium service where it could be a 30 day free trial. It could be a free tier on the of your pricing plan, whatever it is, you basically get them indoctrinated with the product and institutionalised with the product, and then turn them into a paid customer. Now, how you do that could be through your sales team if you’re going after the big hefty contracts or it could just be, you know, showing them the limitations of the free platform, you know, the free version that they’re on, and encouraging them to start paying for the service.
[00:20:50] Bhav: So, that’s what PLG is in a nutshell, and we can pick it apart a bit more if they, you know, if you still have any questions. But my point is on this was that actually the whole concept of PLG is largely baked around users as opposed to sessions or page views. And most product organisations, and you know, maybe I should have mentioned it before, when we talk about the differences between product analytics and marketing analytics, is that it’s predominantly based around users. And when you start thinking about how a product organisation might be measured from a success point of view, it’s yes, of course there’s going to be revenue. There’s always revenue at the end of the day, right? But the way they would measure it, like one classic north star metric is monthly active users or weekly active users or quarterly active users. And you kill this idea of like, an active user being active in a particular time period or having visited a number of pages, it’s just have they performed a set of actions on your website to make them active?
[00:21:40] Bhav: So I think what’s great about like moving away from session base is that now you start, you really do start looking at the users and their interactions and you start to value the interactions and how they engage with your product a lot more than just did they see a page for you. And I think what’s great about this is that companies can now start getting, they can start becoming much slicker and much more advanced in how they measure engagement because it’s not just going to be a page view, it’s going to be, did they perform this very complex action and moving to an event based model allows you to create very complex actions. So, you know, in chess, in my chess.com example, it’s going to be making a move. It could be making your 10th move, it could be setting your AI difficulty. It could be playing your first game, it could be, you know, a myriad of things that would define and an action that they’ve deemed valuable and it doesn’t have to be like, page depth anymore.
[00:22:29] Bhav: It really can be something as you know, I come from Hopin, my previous company. We recognize that a very critical action was a user, not just creating an event, but actually publishing the event. And that became our kind of like north star, like how do we get users to create the event, but more importantly customise it and then publish it? So that became kind of like a north star that we were driving towards, and that became a monthly active organiser metric, anyway.
[00:22:51] Daniel: There’s so much overlap here with the stuff that I’ve been looking at and we’ve been looking at over the last couple of years with app tracking and specifically to do with, I suppose the way that tracking iOS and Android apps are so different to tracking websites. Even if you say the word marketing analytics, it doesn’t actually have the same kind of definition over the and when you’re saying things like the daily active users, weekly active users, monthly active users. So GA4 actually refers to these as user stickiness. The thing with this is that these worlds have collided, GA4 has collided the app and the web world, right? And they’re focusing in it from a marketing analytics, but they’re so different and a lot of the approach is the acronyms. A lot of the terminologies you’re using from a product analytics perspective is exactly the same as what they’re using over in the app space. And now in a sense those have been thrust upon the web marketers right?
[00:23:36] Daniel: And so what’s happening now is there’s that, it was almost like, not in terms of quantity of people or money spent maybe, but like in terms of the anomaly, that’s web marketing analytics or web marketing, and yet it’s just playing catch up and it’s bringing into the, the forefront when you go over to GA4. That’s why it kind of feels a bit like whiplash when you go into GA4 if you’re used to Universal Analytics because it’s so different. But actually it’s just aligning these stars, aligning the product analytics terminologies, the app analytics terminologies and especially when it comes to things like the SKAdNetwork from doing sort of attribution on iOS devices. So you have to run through an MMP (Mobile Measurement Partner) to be able to do any kind of marketing analytics on iOS devices and soon Android in the next year or this year.
[00:24:16] Daniel: But the idea there is that you have these key events in the lifecycle of a user that then go back into the model to attribute against, and you’re not tracking everything against everything and Apple’s hiding all this information from you. But exactly as you said, Bhav, I’m getting to my point finally which is that the the idea of having these key events that you define that isn’t defined for you, and then you put a weighting on importance on them, which then you can measure back and say, these are our north star metrics. In a sense that’s becoming so much more important, whereas I think what I’ve noticed over many years of doing the kind of web specific marketing analytics job is that often people just rely on out the box defaults or whatever GA puts in front of them and they’ve never truly thought about well, a really good example is performance, you know, the term ‘performance’ or content performance. Like everyone’s got a different definition of that, there’s no such thing as the metric performance, right? So like you’re having to really evaluate and starting to think like what is that north star for this content? What is the key action, whether it’s something like MOO or chess.com or you know, any kind of content publisher?
[00:25:14] Daniel: What I’m saying is GA4 is kind of bringing this into this world of having to consider that but the thing that people are maybe bouncing off a little bit is the fact they’ve never had to do this before. Yet it is the exception, not the rule, like everyone else was already playing this game, but now it’s for the web marketers and the web analysts to kind of play catch up in a sense.
[00:25:31] Bhav: Can I ask you guys a question maybe? I’d love to understand, because I don’t want to remove the human element of all of this and I imagine there’s going to be a whole bunch of marketers out there who are probably feeling overwhelmed with the amount of information they have to take in about moving away from something that’s been 101 to their way of working to now suddenly moving to this event-based world. Based on your customers, conversations you’ve had, people you’ve trained Dan maybe specifically, is there this worry that moving to GA4 and this event-based schema model, are people worried about their jobs? Are they worried that they’re going to have to, they’re going to see their roles being moved over into the product space? Like what are your thoughts on this?
[00:26:06] Daniel: Let’s take a marketer for example. I don’t think I’m seeing that from a marketer’s perspective. I mean, obviously change is hard for anybody and learning a new tool kind of sucks, especially if you didn’t choose it. So I think there’s definitely a lot of that I’m seeing. Fundamentally, if you’re after bounce rates and sessions and page views, that still exists. That’s not changing, and the integrations is the key thing. The integrations with the ad platforms like Google Ads and the Google Marketing Platform still stays. And if anything, you can actually do more interesting and powerful stuff there now. So, from a marketer’s perspective, that’s not changed. I think for me, where I’ve seen the biggest, I suppose, reaction to this, is actually from the analyst’s perspective and say, look, we’ve got this data stack, we’ve got these pipelines set up, this ecosystem of data that’s based on data being in a certain format and that changes, breaks everything. And we have to reinvent the wheel in a sense, and it might not be as dramatic as I’m making it sound, but if you’ve got like a single customer view or a kind of data stack, or let’s say you are, you are synchronising data between all these platforms and your CRM and Google Analytics and your products and you’re service.
[00:27:02] Daniel: Maybe even you’re selling the data that you are tracking as a product to your clients, especially from a product perspective. You might give them a dashboard and things like that, like all of that’s changing. And that’s such a big undertaking, I think give it five years, objectively, you know, people are going to realise GA4 is simpler than Universal Analytics but that is a big old change in restructuring data from the ground up. And I think that’s where I’ve seen the biggest kind of, nervous laughs actually, is coming from having to rebuild infrastructure like that. From a kind of out of the box perspective, it’s actually doing fundamentally the same thing. It’s still tracking the same thing, right? Especially if you’re dual tracking.
[00:27:34] Dara: I wonder if there’s a bit of fear the other way around as well, so this is total, this is where I go into full on speculation mode, but with Mixpanel releasing their marketing analytics product very closely after GA4 kind of, well, it was in advance of obviously Universal Analytics being sunset, but it was kind of like very recent. So it was when GA4 was really, really picking up momentum across the board, so speculating, I wonder if people like Mixpanel are nervous because they’re starting to hear and feel like GA4 can be used more effectively as a product analytics tool.
[00:28:09] Bhav: Based on the limited things I’ve observed in GA4 myself, you know, from personal websites and a couple of things here and there. GA has still got a long way to go in terms of parity of feature usage and ease of use, I think there is still a big difference and people are still coming to terms with that and I think Mixpanels shouldn’t be worried right now, but Google being Google, if they do decide to throw everything and the kitchen sink at this product, they really could turn it into an absolute goliath and completely own the space for this. And I think it’s going to come, you know, come down to how much they invest and how much companies decide at this stage to move from GA to another platform because of the complexity of moving from Universal Analytics to GA4.
[00:28:49] Bhav: If the majority of them do it anyway, then you know, that’s a big problem, right? Like it’s, it’s, but then, you know, you could argue that that’s a part of the share of the market that these other platforms never really had access to anyway. What this does is it starts to crossover users, and I think that’s the grey area. Whereas Universal Analytics has typically owned the marketing team and the ecommerce team and the trading team. The product teams you know, by and large haven’t ever really truly relied on GA4. So, you know, and that would’ve been mixed across all of the other three big players, which are Amplitude, Heap, and Mixpanel.
[00:29:23] Bhav: I think what’s really interesting actually, and I don’t want to give too much time to it because it’s, you know, these other platforms are still small, but there are a whole bunch of smaller platforms that are coming up through the market as event-based, you know, user-based platforms that will compete in that space and they’re offering from a value perspective much better value for money than, you know, some of the big players especially if you’re a very early stage startup. So you don’t necessarily have to think it’s GA4 or one of these other big companies. There are actually a whole bunch of other ones out there. One of my clients is using post hoc and it’s a wonderful little tool. It has an open source model, the pricing is very transparent and I love it. You know, it operates very similarly to some of these other big product analytics tools. I think everyone should be worried, it’s just going to be who takes their eyes off the prize first, will probably be the one that ends the, you know, like last in the race.
[00:30:09] Daniel: For sure. It’s innovate or stagnate, right? That’s going to be the key thing with these products. The thing that I would be, and you’re quite right, you’re probably saying there’s no feature parity and there’s no reason to panic if you’re an Amplitude, Mixpanel, or Heap. Definitely let’s come back to this another time because there’s some really interesting stuff about their product evolution, but I think we can drill into a bit and maybe it’s a reaction to Google or maybe it’s just coincidental or just a change in the market that’s dictating it. But without going kind of off to that tangent too much, we’ll save that for another time. I definitely think that there is risk there for them, for Google. Google has this ability to dictate a lot on the market, people use it because it’s quote unquote free, even though, you know, we know that you are paying for it some way, whether it’s financially or some other way.
[00:30:48] Daniel: I mean me and Dara and I don’t know if you were around doing this at the same time, Bhav, but when Google released Google Tag Manager and then just opened that up for free, it completely obliterated the tag management market overnight. I was working at a company that had a paid for tag management solution and that went out of business overnight as well because people moved away and we had to re-pivot, and that’s why a lot of tag management platforms pivoted to DMPs or to other things pretty quickly to stay relevant, to stay in business or to create some other skew. And I think, you know, I’m not saying it is happening, but that could, that could happen here, right? If Google’s gone all in on product analytics, then you know, that we might see what’s happening in these other tools like that dashboard you said Dara, from one of the product analytics tools kind of coming out, constantly timed. Maybe it’s you know, not a coincidence, but maybe they’re pivoting to stay relevant to kind of, to keep different to Google, stay objectively different and kind of differentiate those lines more prominently than ever.
[00:31:38] Bhav: I’ll tell you what is interesting though, from what you just said, Dan. I think it’s, they are crossing over into new area, but it’s not, it’s not like they’re abandoning their user base. Of course, they’re making it harder for them to do things that they’ve always been able to self-serve, but they’re now able to tap into the product space, which in my opinion, Google has always been a bit weak at. They have the market share on connecting your marketing, your PPC spend and things like that to what’s happening to the website. Now they’ll also be able to continue and own what a user’s doing on your website. That’s an, that’s the area they’ve typically been weak at. I think my big concern for anyone who is thinking about moving, or who has moved from, you know, Universal Analytics to GA4 is really going to be, does this move limit your ability to self-serve?
[00:32:22] Bhav: And I say this coming from a point where product teams that I’ve worked with have used Amplitude, Heap, you know, all of these, all of these product analytics first tools, and they have struggled to self-serve themselves. Obviously the really savvy teams will figure it out quite quickly and the really savvy product manager will figure out quite quickly. But there is still a steep learning curve, not in the user interface. Of course, the user interface is going to be a big factor in how easily something like this is adopted, but also the ability to understand the data that’s being fed through. So in product analytics we’ll typically have a data dictionary, which tells you what every single event is. You know, what the name of that event is, what it does, what are the parameters that are being passed? How is that data being enriched? And this is, it’s quite complex. And actually even in the product analytics space, a lot of the teams that I’ve worked with, product teams I’ve worked with, have relied on my team, the analysts, to do the analysis for them.
[00:33:12] Bhav: What’s been great about Universal Analytics, and this is something I’m really keen to understand, is by moving to GA4, are they moving into this product analytics space, but are they abandoning the ability for marketing teams, ecommerce teams, trading teams, whoever to self-serve? Like they’ve typically been able to self-serve and for me that’s a big grey area. I don’t even know who’s going to own that space.
[00:33:34] Daniel: Well for sure they are losing the ability to self-serve because the platform’s fundamentally different. And I think there’s going to be an onboarding period where that perception of being able to self-serve is going to take a dip. And I think it will kind of recover maybe to the same extent, maybe beyond maybe, not as much, we don’t know. I suppose we’re going to kind of come back to this with hindsight later on. But definitely people are quick to hate it, people are quick to kind of not be able to self-serve. And I think this is going to be an interesting thing and in a sense, and that it could be Stockholm Syndrome for sure. It a hundred percent could be Stockholm Syndrome. But I definitely can relate to Google’s position here because they, in a sense, it felt like, or at least from my understanding of things, it’s almost like they had no choice.
[00:34:11] Daniel: The changes in the industry around things like privacy compliance with things like cookie banners, ePrivacy, GDPR, and everything else that’s happening across the world, browser technology is just clamping down on third party, first party cookies. So everything is a reaction to just keep a status quo, right? They’re having to fight tooth and nail to keep things the same, right. Let alone kind of improve upon what they’ve got. And so fundamentally, they’ve had to rebuild a platform that’s based on like modeled data. There’s machine learning absolutely every corner you can imagine the idea of getting a hundred percent accurate, real data from GA is long gone, right? Like it’s long gone. So at the moment they’re reacting to this thing. And, and I think fundamentally the data’s now modelled. It’s basically guesswork for a lot of the cases and it’s kind of doing a lot to kind of mask that. And I think this idea of self-serve, and they’re definitely not doing themselves any favours, like limiting the data you can pull through the API and things like Looker Studio is definitely a big old slap in our face of like, cool, let’s self-serve. Oh no, we can’t.
[00:35:03] Daniel: But I think there’s going to be some interesting stuff there over time. I do think the self-serve nature, I think is moving and the industry’s changing to a point of like, okay, syncing the data into a warehouse like BigQuery, that’s self-serve now. So tick, they’ve done it, moved on, and you know what Google’s like, they’ve kind of quote, unquote, done it. They don’t listen to the industry. They have product managers themselves that seem to have no input and then they just kind of keep building what they’re building. I’m wondering if it’s a reaction to an industry, maybe a preemptive reaction to the future of an industry and then Google’s just ran into this blind not really considering too much and I don’t want to do a disservice to the product managers there, but like often classic Googleism is that they’re going to do things in their own time, we don’t have much of an impact on those.
[00:35:42] Dara: Like Google are in a bit of an awkward position in a way where they’re victims of their own popularity. So everybody’s got this preconceived idea about what quote unquote Google Analytics should do. And a lot of the buzz when GA4 first came out was, oh, it’s not the same as Universal. And it was never really supposed to be, but that was what all the focus was. Oh, it doesn’t have this feature and it doesn’t do this, and it doesn’t do that. And that’s hopefully going to start coming to an end soon. So next month, Universal stops collecting data. Maybe at some point in four or five years, we might not be talking about Universal Analytics anymore, hopefully, fingers crossed. But I wonder if Google are stuck in a bit of a tough situation where most people using Google Analytics won’t yet be focusing on making the most out of GA4 because they’re going to be too preoccupied with trying to make it match what they’ve done before in Universal.
[00:36:35] Dara: So, question to Dan and then open the question to you, Bhav, just to respond to that any way you want. But Dan, given you’re doing all this training at the moment for companies around GA4, are you seeing anybody who’s really making the full use of what GA4 can offer, or is it mostly people saying, help us to mirror what we had as best as possible in Universal until we can kind of, you know, tick that box and then we’ll start to look at what else GA4 can do in including things like looking at, you know, better product analytics.
[00:37:05] Daniel: Do you know what, I’ll be very brief for this answer, but actually no, I haven’t seen people trying to fight to get the same thing they had in Universal. I think there’s fundamental things like structure of data, like the lack of views in GA4 has been, you know, let’s redesign how we collect data and how we report on data has been changed. But I think it’s more, more because right now it’s been a secondary system that the tech specialists or the analytics person or the people that are kind of interested are paying attention to it. And it’s a good opportunity to reset everything and start again. I think once all eyes are on it, I think that there’s going to be a huge demand to bring things back to the way they used to have things. So maybe in the next couple of months we’ll see that.
[00:37:41] Daniel: But right now people are enjoying kind of like a sandpit of getting to do what they want and not have to worry about the legacy stuff that’s not been brought over or to bring it over. So yeah, look, that will change it I’m sure in the future, but right now it’s been quite a nice tranquil experience using GA4 because I don’t think as many eyes are on it.
[00:37:57] Bhav: So on the accuracy thing, I think this is an opportunity for Google to claw back accuracy. Now, there’ll always be a limitation when you are using client-side tracking to get to a hundred percent accuracy because of cookie laws and you know, people blocking and apple being jerks and all that type of stuff, right? So there’s always going to be that. But by moving to GA4 and using event tracking, you can now send server-side events. At least, I assume that, correct me if I’m wrong, I’m not GA expert, right? You know what makes Amplitude, Heap, all of these platforms really great for product analytics and product tracking is that you don’t have to rely on client-side events. You can send server-side events with the action being taken. What does that do? That automatically boosts your accuracy level to one that is much closer to a hundred percent. You know, it may never reach a hundred percent, but you’re going to be significantly closer to that.
[00:38:45] Bhav: So on that sense, I don’t think this is a you know, it’s people, I don’t think people have like truly realised that you’re trying to get to some parity for what GA, you know, Universal Analytics was actually, they should be looking as an opportunity to be better. So that’s the first thing. In terms of like, preemptiveness, of course this is, you know, preemptive reaction to the market. I think the fundamental shift in user product base has changed from 10 years ago where we had fairly simplistic models and platforms and ecommerce and you didn’t really need a complex solution for those things. So actually with products and platforms becoming more, you know, geared towards retention and use, you know, and events and engagement, all those type of things, you know, this is just Google, like trying to claw back some of that market share, which they probably lost.
[00:39:28] Bhav: But my point is the server-side tracking is a big one, right? Like there’s going to be a huge opportunity there. Yes, of course there’s out of the box stuff that Google will do automatically, you know, people trying to get back to what they were and using this time to play around with it. But actually the ones who are really smart are going to see the opportunity in taking full advantage of GA4 and Dara you mentioned. Is anyone really fully utilising it? I don’t know the answer to that one. But the savvy people, they really should be looking at this as an opportunity to say hey, look, you know what there’s all of these things which we previously relied on client-side events we can like boost everything we’re doing with server-side events. On top of that, we can reinforce these events with enrichment. So, you know, a good example of how we used to use that at Hopin was the event would be sent-server side, the action would happen, and then before it’s processed and sent along to Amplitude, we would actually throw in a whole bunch of events into the event as properties, then Amplitude would’ve access to not just what they did, but who they were, what was the size of the company that they’re taking part of? When was the last time they logged in, you know, all of these enriched events, which you, you know, if you try to send them all server-side or you try to capture them all client-side, you’re doing a lot of heavy data processing on the front end for it to be really useful.
[00:40:35] Bhav: So actually yes, play around with that of course. But don’t aim for replicating what you’ve done in Universal Analytics, look at this as an opportunity to be better. Have you all seen that movie with Ryan Gosling and Steve Carell, forgot the name of it, but he slaps Ryan Gosling in the face and when he says he wants to shop at the Gap and he says, be better than the Gap, you know, this is a chance to be better than the Gap.
[00:40:53] Dara: Yeah, I like that. We’ve talked about that so much before where, you know, this is a chance to also clean the slate a little bit and let go of some of that, like historical baggage that people have been carrying around in UA and you know, it doesn’t just apply to Google.
[00:41:05] Daniel: When I run these training sessions and I actually help people define what users are and what sessions are, they’re like, oh, that’s not useful. Yeah, in a lot of cases they realise that actually a lot of this stuff is not actually as useful as they thought because they didn’t actually know what it was.
[00:41:18] Daniel: And I think there’s an element there of like, it’s a good opportunity to educate ourselves on a new product and be kind of hypercritical of like things like the different, for me, I always, the way I always talk about things is like, not every metric is a KPI. Like, there’s a difference between KPI and metrics and, you know, I was told once around a KPI is something that you could be promoted or fired over right? Not every metric, like page views is a KPI, right? If we start defining what KPIs are and just focus on those, that could be a thing there. But anyway, I know we’re running long and I know that we’ve got lots of stuff, I’m really excited about this season, Bhav, I’m really excited about you being here and bringing this kind of, this different aspect of analytics into this and kind of helping to round me and Dara’s very narrow marketing analytics minds out to a different aspect here. So yeah, thank you for coming on and staying with us for the next couple of episodes and we’ve got a couple of more chats between the three of us over different topics. More to do on this more detail and more broad stuff. So yeah, more of that to come.
Rapid fire questions
[00:42:13] Dara: Something else new is we’re going to do some rapid fire questions at the end of each episode. So you two get to be the first two in the hot seat. But before we do that, Crazy Stupid Love was the film in case any of our listeners are thinking, I really need to know what that film was, that was the one. Okay, so rapid fire questions. So this time’s going to be to both of you. So Bhav, if you could answer from a kind of product analytics perspective. And Dan, you stick to your favourite topic, which is marketing analytics. And I’ll let you fight it out over who goes first. So first question, what is the biggest challenge today that will be gone in five years?
[00:42:48] Bhav: I think one of the biggest challenges right now, I’m going to go back to self-serve. I think there is a huge reliance on analysts, and I’m not saying five years they’ll be gone, but I’d like to think in five years from now, the ability to self-serve and answer a lot of your own questions will be accessible and available to every person from the CEO right down to someone working in customer service. You know, if they want data and they want to know some insights, I’d like to think in five years from now that should be something we’ve solved. If we haven’t, I’ll be massively disappointed in society.
[00:43:19] Dara: Sounds like AI to me.
[00:43:20] Bhav: Maybe, I mean I didn’t want to label AI or machine learning or whatever the hot buzz word is, but yeah, you’re probably right.
[00:43:26] Daniel: Yeah, so I think from a marketing analytics perspective, it’s just going to have to be the idea of wanting or needing or feeling like you need a hundred percent accurate, real, trackable data. Which was, you know, how it used to be you know, 5, 10 years ago in the wild, wild west of, you know, the web where we could track everyone with third party cookies and all that stuff. So in five years that will be gone, consent will be probably less freely given. There’ll be other systems at play that we don’t even know of yet, and people will have moved on from this notion of having a hundred percent data.
[00:43:51] Dara: So life would be very boring without challenges. So assuming you’ve solved those two, what will be the biggest challenge in five years?
[00:43:58] Daniel: Well, I’m going to jump straight in but I think that the biggest challenge is going to be integrating and playing with these different technology stacks. We’ve seen already Apple kind of being the first to the game, like reducing the availability of trackable stuff in their ecosystem and you have to play to their rules. Google are going to do the same, there’s no reason why Firefox won’t do the same. Why Brave won’t do the same, why Microsoft won’t do the same. And I think these walled gardens are going to get higher and higher, and just being able to measure anything is going to have to be a real pain and you’re going to have to do it uniquely for each ecosystem. So that’s going to be an interesting change in five years I bet.
[00:44:30] Bhav: I guess it’s linked to what I said in the first rapid fire question for me. It’s going to be with access to so much information, what is going to be the right information to access if you can, you know, measure everything and anything and have access to it and especially if you’ve, you know, not relying on analysts. I think the big challenge is going to be how do you train people who don’t have the critical, analytical thinking needed to interrogate data to suddenly start thinking critically about how to interrogate this data. So for me, the biggest challenge is really going to be how do we measure what matters and how do we learn to let go of the things that don’t?
[00:45:05] Dara: Okay, what’s one myth that you would like to bust?
[00:45:09] Bhav: I’m going to tell you this one first, Dan, because I’m like deeply passionate about it and we kind of touched on product-led growth earlier, but I want to kill this myth that product-led growth is a silver bullet, it’s not. Product-led growth is another tactic or strategy, whatever you want to call it, in a pool of things that you should be doing as a company. I’ve seen companies starting to abandon marketing led growth and sales led growth in favour of product-led growth. And I want to remind people that actually, even if you do offer a freemium service or a free service, getting someone to go from a free service to paying your six figure yearly subscription is not easy, right? And you still are going to rely on classical connections from sales teams and marketing teams to play their role. So my big myth I want to bust is PLG is a silver bullet. It’s absolutely not, don’t listen to people who say it is.
[00:46:00] Daniel: And for me it’s that users are not people. And again, one of those key takeaways I do in the training or when I’m working with clients. I ban the phrase people and say, how many people came to the website or how many people saw our ad last week? And just that you can’t tell there’s no, you can’t represent humans in data, at least, you know, with the technology in the marketing analytics tools we’re looking at. So users are not people, users are often cookies or some different variation of those in GA4 now. But yeah, there’s no such thing as people in data.
[00:46:28] Dara: Okay. If you could wave a magic wand and make everyone know one thing, what would it be? And this sounds like a very dangerous power to give to either of you two, but let’s just say in a hypothetical world, you had such a magic wand.
[00:46:40] Daniel: Do we have to keep it to our product and marketing?
[00:46:43] Dara: I think for the sake of our listeners, yeah.
[00:46:46] Bhav: If I could make wave a magic wand and make everyone know one thing, what would it be? I think it would be that you need to be able to connect everything you do to revenue. I think sometimes it’s easy to go down rabbit holes and focus on the things that matter most to us, or these engagements or metrics that we hold dearly. But actually, as Dan said, the KPIs are the thing that’s going to get you promoted or fired. So if I could wave a magic wand, it would be to make everyone know what the key KPIs are within their organisation.
[00:47:15] Daniel: For me, I think going back to my favourite subject of Google Analytics, if I can make everyone know one thing, and it’s something they already know but don’t think about, it’s just the fact that it’s owned by Google. So we often abbreviate it to GA or GA4, but you know, we forget that Google’s a marketing company and the reason they can give this away for free is because they’re the biggest marketing company in the world. And you know, their goal here is to make money from advertising. So they’re going to have an inherent bias in everything they do. They’re going to have an aim, they’re going to have a reason for doing something that’s going to be like you just said Bhav, of tying it to revenue and how does Google tie something to revenue? Okay, it’s through advertising. So yeah, I just wanted to kind of make everyone realise that they are working with the biggest marketing company in the world and it’s not truly free.
[00:47:55] Dara: Easy one to finish, what’s your favourite thing to do to wind down?
[00:47:59] Bhav: Recently it’s been building product. I’ve been spending a fair bit of my time building a solution to the self-serve problem that I mentioned. It’s only a very basic solution, but I’ve enjoyed doing that and I’ve been doing it any chance I can get to wind down. It’s just problem solving helps me wind down, strange as that sounds.
[00:48:18] Dara: I thought you were going to say chess.com.
[00:48:19] Bhav: That actually raises my blood pressure, because I play chess, I play blitz and I’m not very good at blitz. It forms really bad habits, so it’s probably ruining my long game as well but we’ll save that for another episode.
[00:48:30] Daniel: Mine at the moment has to be going outside and skating and believe it or not it’s skateboarding again, which any listener of the podcast knows I do often, but that’s my true escapism from everything. I leave my phone at home, no headphones. I’m just outside, you know, the whole time. So it’s lovely, it’s pure disconnection and focusing my brain on something else, and it’s the, it’s the only time my brain goes quiet for a bit, you know? So just quiet down the voices around the analytics world. So yeah, skateboarding for me.
[00:48:57] Dara: Okay, thank you both for being the guinea pigs and sitting in the hot seat for the rapid fire questions and for the chat, I really enjoyed it. I feel like I’ve learned a lot. Didn’t quite get the two of you to debate as much as I would’ve liked, but I’ve got another nine episodes or so to go to get the two of you to disagree a bit more seriously about something.
[00:49:14] Daniel: Plenty of time.
[00:49:16] Bhav: I think the topics were quite different. I think Dan and I both specialise in different areas that we’re not going to, if anything we kind of go hand in hand, this is our happy space. We need to uncover what that space is, where we go to war.
[00:49:26] Daniel: Well, Bhav I was actually going to say this is really interesting, so one of the first kind of debate subjects we did way back in, I think the early episodes of this podcast was users versus sessions, and Dara was fixated on sessions and I’m fixated on users. So I’m glad you’ve joined team user. So I think actually it’s going to be me and you versus Dara, and I think that’s the thing that we can start going for the next couple of episodes.
[00:49:46] Dara: And on that note, see you next time.