#39 Product analytics and CRAP Talks (with Bhavik Patel)

The Measure Pod
The Measure Pod
#39 Product analytics and CRAP Talks (with Bhavik Patel)

This week Dan and Dara are joined by Bhavik Patel to talk about the differences and similarities between product and marketing analytics, CRAP Talks, and the concept of ‘analytical debt’.

Find Bhav on his platform of choice Twitter at https://bit.ly/3PntANX.

Check out the blog Bhav wrote on “Data Privacy is the Latest Natural Resource in Tech” on the CRAP Medium on https://bit.ly/3sJM41d.

Visit the CRAP Talks website for info on the next event and links to their Slack community (it’s nice, we can vouch for it!) – https://bit.ly/3sMEhjh.

Check out Bhav’s artwork Instagram – https://bit.ly/38w43BF.

In other news, Dan gets crafty, Dara watches Netflix and Bhav writes and paints!

Check out on LinkedIn:

Music from Confidential, check out more of their lofi beats on Spotify at https://spoti.fi/3JnEdg6 and on Instagram at https://bit.ly/3u3skWp.

Please leave a rating and review in the places one leaves ratings and reviews. If you want to join Dan and Dara on the podcast and talk about something in the analytics industry you have an opinion about (or just want to suggest a topic for them to chit-chat about), email podcast@measurelab.co.uk or find them on LinkedIn and drop them a message.


[00:00:00] Dara: Hello, and thanks for joining us in The Measure Pod, a podcast for people in the analytics world. I’m Dara, I’m MD at Measurelab, and I’m joined as always by Dan, an analytics consultant also at Measurelab. Hey Dan, how are you doing?

[00:00:27] Daniel: Yeah, not bad thank you. How are you?

[00:00:29] Dara: I’m also good, I’m excited. We’ve got a guest on this week, which is always good. So we’re joined by somebody who we know from something called the CRAP talks. And that’s not me being insulting, that is the actual name of it. I’m sure I’m not the first one to make that joke, but we’ll get to that we’ll give Bhav a chance to talk to us a little bit about CRAP, but we’re joined by Bhav Patel. So Bhav what we usually do instead of just getting people to do a kind of standard introduction, we usually ask them how they fell into the world of analytics, because most people we speak to they’ve kind of meandered into it, so in as much, or as little detail as you want, give us a little bit of your backstory and how you got to where you are today.

[00:01:06] Bhav: So thanks for having me on the show guys. I’m Bhav, I’m currently the head of product analytics at a start-up called Hopin. And how I fell into analytics, you’re absolutely right I didn’t plan to land in it, I graduated from university having studied maths. Like most graduates I was just after a job that was remotely related to my field. I stumbled initially into digital marketing, so I was doing PPC, SEO, display advertising, agency side. I really enjoyed the analysis side of looking at our client data, but they were so limited in terms of what I could actually get access to just because being a marketing agency, we’d only really get access to the ad networks.

[00:01:41] Bhav: So I made the decision to move in-house and I’ve just never looked back since. So I think for me, it was really around going deeper into the funnels to understand what user behaviour was looking like and slowly slowly, what I realised was I was spending more and more time trying to understand customer journeys, what onsite behaviour look like, and even though I wasn’t a growth marketing role, I found myself doing a lot of the analytics for the company, and that resulted in me being promoted into a head of analytics role at my first company where this happened. And then I kind of like been on a analytics / data / experimentation journey ever since. I don’t know if you guys remember when you were in year 11 in high school, you have your national record of achievement.

[00:02:17] Bhav: So I dug my national record of achievement out, and in it I talked about what I really loved about the subjects that I’d loved, that was art and science and maths and it really talked about how with science, there’s a kind of concrete answer and I loved experimentation. So I never thought I would be a scientist, I want it to be a scientist growing up, but then you kind of hit like 25, 26, 27 years old and you realise that kind of like dream of what you wanted to do as a kid is forever fading. And then one day I woke up and I was like 33 years old and I was looking through this record and I realised that actually I’m doing a lot of experimentation and A/B testing. So in some ways it is kind of related like, you know, maybe this has me retrospectively trying to fit some lifelong childhood dream into like the reality of what I actually do, that’s kind of how I ended up in analytics and I just never looked back, I love the field.

[00:03:01] Dara: I love that, and you’ve actually proved me wrong as well.

[00:03:03] Bhav: Well, I really wanted to be a proper scientist, right? Like by no stretch of the imagination do I consider myself a scientist. But when you start doing A/B testing and you start looking at P-values and normal distributions, you can kind of say you are. I’m sure like, you know, Isaac Newton is turning in his grave listening to his podcast and hearing me talk.

[00:03:19] Dara: So I introduced you by saying that Dan and I saw you at the CRAP talks that you organised. So before we probably dig into our actual topic this week, let’s have a quick chat about CRAP. So can you give us a bit of background to it? What inspired you to set it up? Maybe any plans you have to reinstate it?

[00:03:35] Bhav: So I think it came out of frustration, it was born out of frustration. First and foremost, CRAP is actually an acronym. It stands for Conversion Rate Analytics and Product. I’m sure most people are familiar with silos in companies. You kind of hear about like silos and breaking silos, within the industry when we go to events, we kind of like reaffirm these silos and we have analytics events, we have product events, marketing events etc. etc. So that was kind of like why there was this discipline and if you put a venn diagram together with conversion optimisation, analytics and product as three circles, the intersection is where I was trying to put CRAP. So that’s kind of like the premise behind it, and why I started it was purely just out of frustrations.

[00:04:09] Bhav: But I think the final nail in the coffin was I went to this event I think it was Marketing Week Live or something like that. And it’s a five day event with each day dedicated to a specific track. One of the days was data and analytics, so naturally that was when I went to, and I remember the first event, the speakers on stage, they were massively under qualified to be on that stage, talking to the audience that they were talking to. And all I heard for the 45 minute duration of this fireside chat, were cliches, big data this, big data that, and I got really fed up because I had so much work to do. I’d taken a day out of my week to attend what I thought was going to be a highly relevant event for myself and it just fell flat on its face.

[00:04:45] Bhav: So when I got back to the office, I said, I’m going to start my own one. I created a page on meetup.com, put an event in the calendar for a couple of months later and then prayed for the best. I think it was the first event, I think we had about 12 people turn up, then by the end of the evening were like, we should do this again. So we did it again, the next time 20 people turned up and again, the intimacy of the event was really great. We were able to have meaningful discussions. The people in the room were practitioners that were, you know, pretty much in the trenches doing this day in and day out and highly qualified to be there.

[00:05:13] Bhav: And then that that kind of like continued snowballing and it was through word of mouth for the next event we had kind of like 50, after that there was 100 attendees. I think at peak, we had nearly 190 attendees at the event we run at Expedia, the Expedia offices during summer. It was really great to see this grow organically and everyone had such great things to say about it. With each event that followed, it just kept getting better and better, and I just wanted to do more events, then lockdown hit unfortunately. I’ve tried to do a few virtual events, I just haven’t had the bandwidth and capacity to do it.

[00:05:38] Bhav: I still wanted to contribute to the community, so I started writing. I genuinely believe in the power of the written word and the spoken word. So I figured if I couldn’t run events where people were able to share their knowledge verbally, I wanted to write it down. I joined a writing community and I’ve just been writing about the same topics, CRO, CRAP related topics, but it’s been nice to continue contributing even if it’s not in the same way.

[00:05:59] Dara: We were really big fans, I don’t know if it was at the Expedia one or if maybe it was the one before that, but it was really good. I always love the content, I think we could probably echo what you said about being frustrated about some of the industry events where they’re glorified sales pitches, aren’t they in a lot of cases. Or just an excuse to throw out lots and lots of buzzwords, but we were big fans of CRAP because it was really top-notch speakers and it was a good mixture of content as well, because it span those different disciplines it wasn’t just in one area. So what I found great about it was I would get the most out of the speakers that were less related to the work that we do. So as an analytics practitioner, I got more out of maybe the people who specialise in conversion rate optimisation, or the people who were working in product analytics roles, because you’re getting that transferable knowledge from other domains. That was kind of refreshing because otherwise you go to these events and often it’s a bit of a case of a mutual back patting or just getting to sit there and think, wow yeah, I know all of this already, which can be nice, nice stroke to the ego, but you don’t actually learn anything. You don’t come away with any kind of different thoughts or different approaches to how you’re going about your job.

[00:07:02] Bhav: I think that was the most surprising thing for me that I discovered is what I assumed would happen were the people who were from within the discipline, that the speaker was, that would be the talk that resonated most with them, or they got the most value out of. But as you mentioned, I found often the feedback because I collect a lot of data after the events, like through surveys. And the feedback has always very similar around actually the most enjoyable talks for everyone else was when it was from another discipline because it kind of like opened their eyes to what’s happening in other parts of the organisation which they maybe didn’t have access to before. So that was kind of cool to see that happen.

[00:07:33] Dara: So one thing we wanted to dig into with you a little bit, because Dan and I, and at Measurelab, we’re often focused on marketing analytics, not exclusively, by and large it’s marketing analytics and we’re working with marketing teams. So you mentioned that your current role is head of product analytics. So what’s product analytics as distinct from marketing analytics?

[00:07:52] Bhav: Yeah that’s a good question. I think historically the industry, the tech industry has relied on marketing led growth. So this is going out and doing your PPC advertising, your SEO, your digital advertising, doing your TV, your display, your social media, all of those types of advertising and then growing through marketing led activities. And I think what’s happened is over the last like three or four years, there’s been a shift in dynamic towards more product led growth. And you see companies who, not to say they’re not doing any marketing analytics, but actually their primary engine for growth comes via the adoption of the product and getting users to use it either through offering at a very subsidised rate or completely free in the case of products like Spotify and Slack. So what product analytics focuses on, I guess you could say it’s a different branch of the same tree, and it’s really about trying to find opportunities of growth by using your product as the main lever to attract customers, engage them and then retain them.

[00:08:47] Bhav: So I think historically companies have been great at driving traffic to the website and getting people to download their app or their product, whatever it was. But then where it’s really fallen apart is there hasn’t been that same level of focus on the user experience and building a product that is truly sticky. And I think it was only when you started seeing companies like Slack, like Spotify heavily invest in their product first and things like marketing second. I think companies started seeing that as a more sustainable engine for growth. You can attract all the customers in the world, all the traffic in the world, but if you then lose them after your first or second step, or if they’re using a subpar product, you’ve wasted all of this marketing spend.

[00:09:25] Bhav: So really I think, in an ideal situation, when we talk about product analytics, marketing analytics, they really complement each other. But historically it’s only really just been a focus on marketing analytics and it’s now great to see more and more companies hire for this product analyst role. And I’ve seen it, day in and day out, either being reached out directly from recruiters who are looking to hire leaders in the product analytics space or companies who are hiring for their first product analyst. And I’ve written a couple of posts around what I look for when I’m hiring and the skillsets, they’re not dramatically different between a product analyst and a marketing analyst, I think the big changes come from like mindset. So the technical skill sets are really going to be the same, but it’s really about the mindset of how you approach the problem and the understanding of the space you’re in. Whereas marketing, you’re focused on things such as ROI and CPAs and optimising the cost of your marketing spend.

[00:10:13] Bhav: Product analytics is really focused on understanding your business metrics. So looking at your unit economics, understand well, okay, this is how we make money, or our primary goal might be revenue. And then we break it down into sub-components, so we get deeper and deeper and deeper until we start hitting those behavioural metrics, which then ladder up to your revenue metrics. And of course, one arm of that will be marketing spend and traffic acquired to the site, but there’s this big arm, which is really around behavioural analysis and the quality of the product and how sticky it is and how people use it. I would say really that’s the core difference between product analytics and marketing analytics.

[00:10:47] Dara: And you mentioned silos earlier. So, how do you avoid that either in your current role or just generally, how would you advise people to avoid the silo effect between maybe if there is a distinct marketing analytics team and then a product analytics team.

[00:11:01] Bhav: So when I was working at Gousto my previous company, they have one of the best setups when it comes to team structures. So rather than having these siloed teams, actually what we have with these multidisciplinary tribes and squads, and they’re made up of product analysts, they’re made up of growth managers, they’re made up of product managers, engineering managers, designers, researchers. And actually what you have is group of people who have very unique skillsets all working to solve the same problem, as opposed to this homogenous group of people who all have the same skill set working on the same problem and, you know, you don’t get the same, the diversity of thought. So I think that’s probably the best way because I think Gousto nailed it.

[00:11:37] Bhav: Where I’m working right now, we don’t have the same team structures, but I guess my approach is communication, communication, communication. So I think one of the things I learnt a lot at Gousto is like the best things you can do, especially when you work in these remote conditions like most of us are working at the moment. There’s no such thing as oversharing, and I think keeping people informed about what you’re doing is the best way to keep them in the loop. Because I think working in this remote environment, we miss those coffee chats and those water cooler chats, but moving to a remote environment the act of over-communicating just to keep people informed, I think that’s probably the best way to overcome silos.

[00:12:08] Daniel: So, is it fair to say then. So going back to the product analytics, marketing analytics, it’s like the marketing analytics is driving people in or driving the kind of top of the funnel activity, trying to widen that, trying to get people in. You’ve got the kind of CRO kind of middle of the funnel, trying to convert them once they’re on the website or the application and then the product analytics is more about retention and it’s about creating that sticky product, so that there’s less churn. So in a sense, we’re working in the same funnel, we’re just at different ends of that funnel and different roles or different focuses have different areas of specialisms.

[00:12:36] Bhav: Yeah and I don’t see CRO is really a role I see it as more of a skillset. So there’s no reason why a marketing analyst couldn’t do CRO, it’s really around conversion optimisation. You test your ad copy, you might test landing pages, you might test images, you know whatever it is that you’re doing on the marketing side of things. When we’re talking about the acquisition, now for some companies, they might call their acquisition team like a CRO team, but actually generally where I’ve worked, that is a product team, or it’s a marketing team, or it’s a more traditional skillset like product analytics, you know, whatever it might be. And CRO is just really just the skillsets that you apply to it, I think right now we have a group of CRO practitioners, but yeah, ultimately you’re working on the same funnel, product analytics might be further up, so if you think about the acquisition that actually happens on the product.

[00:13:15] Bhav: So when you look at your form analytics that’s still your product. I think ultimately you’re right it’s all one funnel, but I think product analytics and marketing analytics there’s a grey area somewhere very early on in the user experience.

[00:13:27] Dara: So I think you’ve kind of answered what my next question was going to be there, but I was going to ask you about whether you’re doing experimentation within the product analytics team and I think you’ve just said you are.

[00:13:37] Bhav: So we’re not doing experimentation at Hopin right now. But however, when I was working at Gousto, we were doing a lot of experimentation. There’s really two schools of thought around experimentation and this is what we had at Gousto and what we’ve had previously in my previous companies, is you’ve got your first school, which is a centralised experimentation team who will run A/B tests as a central function. They might be made up of product managers, growth managers, designers. Or you’ve got your centralised team. The centralised team are really there to create an environment of experimentation, they’re there to facilitate an experimentation mindset. And I think that one’s scales much better so when I say I do experimentation, I won’t lie and sit there and say, hey I come up with all these great ideas. I always have great ideas, but I’ve been told constantly bad ideas are cheap, execution is everything.

[00:14:17] Bhav: But I much prefer a creative environment where other people can run experiments themselves. So like a centralised team who, who will share things like how we designed the experiment, what are the experiments happening across the site and really share best practices and educate stakeholders and product managers and marketing managers and whoever else to think about how we might prove causality or hypothesis through the use of experimentation as a tool, as opposed to as a team. So yes, I do experimentation, I have run experiments, but I much prefer an environment where me and my team can facilitate experimentation, and Gousto again was the best example I can think of.

[00:14:51] Bhav: When you’ve got a centralised team of experiment professionals, or CROs, what you get is you’ve kind of ring fenced your domain expertise, usually to some low hanging fruit. However, when you expand the ream of experimentation, allow other teams to experiment. What you also get with them is deep domain knowledge. And the best example I can think of is when I was working at Gousto, we were planning how to do experiments in our supply chain. Now I couldn’t tell you one bit about how a supply chain works. However our product manager, he was fantastic, he knew the ins and outs of our supply chain. So all I really needed to was arm him about how we might design an experiment to prove what it was we were trying to prove. So in this case, we were trying to improve throughput, the number of boxes we can get out of the other production line. I can’t do that.

[00:15:33] Bhav: And I think this is one of the ugly truths of CRO and you don’t hear about a lot is because you’ve got people talking about copy and you’ve got people talking about like behavioural mindset, but actually that’s all very surface level information. I would much prefer a product manager or marketing manager who spends day in and day out in their discipline, running an experiment then having a team who will do some high-level surface level understand experimentation based on very limited knowledge of what their area is. And I think that’s really the only way for experimentation to be successful. You might get a few good winning tests, you might get some ideas that prove their value, but ultimately I don’t think it beats deep domain knowledge.

[00:16:12] Bhav: And if you can arm those teams with the knowledge of how to run a proper experiment, then you’re more likely to see your experimentation as a program of work succeed rather than the individual experiments.

[00:16:23] Dara: Yeah, that makes complete sense. I guess you’re going to naturally you’ll hit the end of the road with that low hanging fruit. And if you’re not actually embedding it into the teams themselves, then you’re going to run out of road, aren’t you. So shifting focus slightly, we talk on this podcast a lot about Google Analytics because that’s the main analytics tool that we work with. So you mentioned earlier that there’s a lot of comparable kind of technical skills between somebody who might be in a product analyst role versus a marketing analyst. What about the tool sets? Are you using different tools, different technology to do your work compared to what maybe we might be doing of we’re using GA (Google Analytics) to analyse marketing campaigns.

[00:16:59] Bhav: Yeah, so I think certainly in my experience, Google Analytics is very strong when it comes to understanding your marketing activity and what’s driven traffic to your site. It works quite well for like an e-commerce platform when you have to like prove ROI value at a channel and the spend level. But when you start going deeper into the product it has its own limitations, I think the teams that I’ve traditionally worked with much prefer working with more bespoke event tracking based tools. And I think GA4 is moving towards event tracking for this purpose. And I’ve not really used GA4 myself. I’ve seen it floating in the in the analytics ecosystem all over the place and seems to be a very hot topic right now and I’ve stayed very clear of that topic just because I don’t really have an opinion on it.

[00:17:36] Bhav: However, from a product analytics perspective I guess it doesn’t really matter about the tool, for me it’s really around the strategy that goes behind tracking. So right out of the bat, if you’ve got a poor implementation of your event tracking, it doesn’t matter what tool you use ultimately, you’re not going to be able to gain the insights you need to improve that product. And I think that’s probably true in some cases of marketing as well right? If you haven’t set up your parameters well, you’re not going to really be able to track your traffic. The quality of your marketing analytics depends on the quality of the parameters that you put in, and how well you are able to segment them, look at it at a very granular level. If you only just tagged it as, you know, Facebook or email or something like that it’s not going to be very useful.

[00:18:12] Bhav: And I think in that sense product analytics is very similar. So I think one of the things that you know, just slightly moving away from the topic of the technology, one thing that people companies tend to forget, and it’s a term I’m coining, and I’m calling it analytical debt. You see companies spend tons and tons of time trying to improve their technical debt and actually they forget that your event tracking is part of your wider tech ecosystem. And by not naming your event tracking properly, by not using proper naming conventions, by not passing the correct parameters, you’re racking up this debt, which means that you’re just collecting all this information, which isn’t very useful in the grand scheme of things. And I think in the same way as like marketing analytics, exactly the same, the better the quality of your tracking, the better you can analyse your marketing campaigns and build things like attribution models and all of those types of things.

[00:18:55] Bhav: So, yeah I’m quite agnostic at the end of the day. My mindset has generally been, I don’t care what tool someone gives me it’s really around how we use it, how we set up, how do we minimise that analytical debt and ensure that a year from now, we’re not spending time cleaning up events and cleaning up tags and you know, all that boring stuff no one wants to do. So it really should be an ongoing exercise.

[00:19:15] Daniel: You’re preaching to the choir really and I think that this is something that we’re seeing as well. And I think, although you’re saying that you kind of avoid the GA4 conversation, like we’ve not been able to obviously, and that’s very much been our day to day for the last couple of years. But actually we’re finding that it actually affords us an opportunity to clear a lot of analytical debt, as you’ve said. So it’s actually like a lot of the legacy historical nuance, the implementation, the tracking, that kind of stuff that is just in the way and maybe over-complicating things in Universal (Universal Analytics) and the data points they’re capturing there. We’re getting a fresh start because it’s not transferable, you can’t just take your Universal Analytics and convert it to GA4. You actually have to start from scratch, it’s implementing a brand new product and it’s making everyone take a step back and go, what do we need? What’s our objective? What’s our purpose?

[00:19:59] Daniel: I can’t talk to it as maybe as well as you can, but from a GA4 perspective, I’m seeing a lot of conversation around the product analytics space, because of that event schema you suggested and how it is kind of opening a couple of doors or making it more relevant for different functions and especially things like the connection to BigQuery so you get all access to all the raw data as part and parcel of this. So you can kind of do whatever you want with that data. I’m not here to promote GA4 in any way, but it’s definitely something that I’ve noticed, it’s that clearing of the analytical debt but also conversation around the event schema and how that can be useful from a product analytics perspective is, has been something that’s been coming up quite a lot actually.

[00:20:31] Bhav: It’s really interesting, actually. I never thought about it like that and you’re absolutely right. I guess it’s somewhat like switching to a different platform, but all be it it’s the same vendor. It’s a different platform, so joining Hopin one of the opportunities we had was to build our event tracking from scratch. So it’s kind of been nice to build this from scratch and identify kind of like the nomenclature of how we might name events and things like that. Now, one of the challenges we’re facing is as the teams are scaled and as the things become a bit more self-sufficient in learning how to track their own events. Governance becomes a critical topic, and again, it doesn’t get talked about enough in the space. You’re going to go through all of this pain of migrating over all of your tracking over into GA4, which is a great opportunity to like, you know, get rid of all the crap.

[00:21:08] Bhav: What you’re going to find is a year from now all of those kinds of like events that have been added straight into the live environment, a production environment, they’re going to start to like rear their ugly head and what you’re going to do is you’re going to rebuild your analytical debt. So if anyone is listening and you know, I hope they take me very seriously when I say this, please consider the governance as part of the clean-up process, because I can’t stress enough how on a regular basis going through and we’re finding events we’re like, hang on, these have not been approved by the team. How do they get there? And it’s just engineers, like adding test events and they’re making their way into our live environment and it’s an absolute pain. So yeah, governance, governance, governance. If there’s one thing you take away today about event tracking, it’s the governance piece.

[00:21:49] Dara: You’re not going to get any disagreements here. I think it’s a classic case of people repeating their mistakes isn’t it? And we’ve talked on this show a few times about using this migration to GA4 as that chance to do a spring clean-up. That’s only as useful as long as you stick to that governance and it’s very easy for people to just fall into the same habits. So you’re right, it’s like review it, drop the debt, but make sure it stays gone and stick to your governance and make sure that if you’re implementing events that they’re actually going to be used and everybody’s clear on what they’re for and any nuances with the data or anything else.

[00:22:19] Daniel: This is the thing, isn’t it? We say it’s a great opportunity to have a clean slate and start again, but starting again with the same mindset, it’s all about when we say it’s a good opportunity for a clean slate, or to start again, we’re saying in terms of process, more than anything, actually it doesn’t matter about the events and stuff you’re tracking, exactly what you said Bhav, it’s that governance. When we do this, as everyone is having to do this right now, let’s write it down. Let’s start with that, let’s just write it down on a, I say piece of paper, digital paper nowadays, but stick it on a piece of digital paper somewhere, but it down, but a date against it and start with that. What is good governance is how long is a piece of string kind of conversation. But if you’re not doing anything, start with something. And actually, you can migrate every single event into GA4 if that’s useful, but just write it down and justify it somehow.

[00:23:01] Bhav: I think it’s also you know, as much as it is around like redefining your processes and doing from scratch, it’s an opportunity to re-educate people about the importance of event tracking, because what I’ve found is and I created this meme a while ago, you guys have seen the movie, The Matrix, right? You know, that scene where one of the agents, fires a gun and Neo and he kind of like starts dodging the bullets. I kind of see those bullets as the owners of event tracking. And it’s kind of like, everyone’s trying to dodge it, data engineering are dodging it, product are dodging it, software engineering are dodging it, analytics are dodging it. And you realise that there isn’t any natural owner of your event tracking. And I think this is one of the main reasons why it ends up being this Frankenstein’s monster of this thing that ends up being a pain in the arse for everyone.

[00:23:41] Dara: So what does your kind of general tech stack look like? Cause we’ve talked a lot about kind of mindset and team structure and governance, but what’s your kind of typical setup?

[00:23:49] Bhav: So I think for me what’s been fairly consistent even if the tools are slightly different, there is one event pipeline. In our case, we use Segment, which captures all the onsite data. You know, your frontend events, your backend events, which gets pushed into our data warehouse, we then enrich that. It’s really cool actually, I’ve not seen it elsewhere, but the enrichment service basically adds on all of the information you probably would have joined later on in the analysis stage, right at the early stages. And then we get, then that gets pushed into Amplitude, which is all our product analytics tool. It also gets pushed into Red Shift and that’s And the BI tool that sits on top of that is Looker where we make a lot of information available.

[00:24:24] Bhav: I have tried and tried and tried again to embed the self-serve mindset into companies that I just, I don’t know why it just, I don’t know about you guys and I’d love to hear from your opinion, like how successful you’ve been. Like, I’d love to hear from you guys, like how do you solve this?

[00:24:37] Daniel: This is exactly what we experienced too. I think it’s really interesting. This whole concept of data democracy and it’s like, how much freedom do you give someone to access? Because you know, on paper it’s like you have access to everything. You can self-serve, you can build everything you want. But actually with all of that comes a relative risk because people grow, grab things that they don’t realise they’re grabbing and it’s, and it’s wrong, but actually that’s not the biggest issue. The biggest issue is just getting them to use it in the first place.

[00:25:02] Daniel: I assume it’s different for every business or it is from my experience, it’s just, it’s almost like creating the kind of democracy of the data that kind of self-serve nature is great, but actually it’s almost for our benefit, not theirs.

[00:25:12] Bhav: So I guess I’m like, why do we keep talking about democratization of data? There’s clearly like a ceiling, which is significantly lower than we all care to believe or accept, and maybe self-serve reporting is the best we’re ever going to get.

[00:25:24] Bhav: I believe that without the work that we do, the quality of decision-making will continue to deteriorate, which will then ultimately have an impact on business performance, which will then ultimately lead to this crash.

[00:25:36] Daniel: Where does something like privacy and cookie policies and things like that, the literal ability to be able to collect the data, whether it’s analytics has been turned off or whether the technology is making it worse and worse and worse, is that the same kind of effect? Do you feel that’s going to eventually kind of become a downfall?

[00:25:49] Bhav: I recently shared a blog post about my thoughts on data privacy, right. I think Silicon Valley in these tech industries has made billions and billions by exploiting our data. And now they’re on track to spend, sorry, make billions and billions by convincing us, we need to protect it, right. So I don’t think the average person really generally cares about data protection in that sense, because I mean also like worst case scenario, like what are they going to, they’re going to target me with slightly better ads.

[00:26:12] Dara: All right, we’re going to change gears now, this is the bit in the show where we put each other on the spot to pretend we have interesting lives outside of work. So I’m going to ask you what you’ve been doing recently to kind of wind down outside of work.

[00:26:26] Bhav: Good question, so I have two boys. So the concept of wind down it’s so far in the past that I don’t remember, but if I do get some time, it’ll be one of the few things. I like to write, so at the start of 2021, I started writing, I joined a writing community. I’ve made a very conscious effort to improve my writing style. I think I’ve clocked in over nearly a thousand hours of writing over the last year and a half. So I’ll spend some time doing that or alternatively if I can’t be bothered to write and I don’t want to watch Netflix I like to paint and draw in my spare time. I’m in the process of learning a Japanese art style which uses this one coloured ink, and you create different shades and create like these really moody images and pictures, so that’s been kind of fun to go on that journey. That’s how I kind of wind down, how about you guys?

[00:27:07] Dara: Yeah, brilliant. Dan, follow that if you can.

[00:27:10] Daniel: I’m not going to attempt because yeah, it’s terrible. But my wind down was the great British Sewing Bee. And it’s basically for anyone that doesn’t know that it’s basically the Great British Bake Off, but for sewing. And it’s a bunch of people that get together and sew in a room once a week and it’s so lovely. I like sewing, I’ve always been around textiles my whole life growing up, both my parents were in the trade, so there’s always been a bit of a soft spot for me. And it’s just one of those lovely non-competition, competition programs that we have. But yeah Great British Sewing Bee. How about you Dara?

[00:27:38] Dara: Yeah it’s where they all want each other to win isn’t it? I’ve seen it before, it’s competition with no actual competitive mean streaks at all. They’re all wishing each other well and best friends. Mine’s very, very boring. It’s Netflix related, we’ve just finished off the final series of Ozark and I can’t really say anything about it in case anybody is watching it and it hasn’t seen the end yet. So all I’ll say is we finished it and that is it. End of update.

[00:28:05] Bhav: Oh I was going to say I heard Ryan Reynolds messaged the main actor, I’ve forgotten his name.

[00:28:09] Dara: Jason Bateman.

[00:28:10] Bhav: He literally just said you’re so fucking talented.

[00:28:12] Bhav: That’s an amazing text to get, right? Ryan Reynolds randomly text you. Yeah.

[00:28:16] Dara: Well, I really want to talk about the ending but I won’t just in case I give any spoilers away.

[00:28:20] Dara: Okay, final question for you Bhav, an easy one and then you’re pretty much off the hook, but where can people find out more about you or even get in touch if you want them to?

[00:28:29] Bhav: So it depends on how much you want to hear from me. LinkedIn is always a great place for me just generally sharing things I find interesting or I’ve written, but Twitter is where I really rant so my Twitter handle is @DodoNerd, don’t ask why, but that’s just my handle. So yeah, LinkedIn or Twitter are usually my go-to places for communications.

[00:28:49] Dara: Great, and Dan, what about you?

[00:28:50] Daniel: Not Twitter for me. I have a Twitter account but I’m not very talkative on there, but LinkedIn for me and my website dananalytics.co.uk.

[00:28:57] Dara: Okay and for me, it’s LinkedIn. Okay that’s it from us for this week as always, you can find our previous episodes of The Measure Pod in our archive over at measurelab.co.uk/podcast. If you want to suggest a topic for us to discuss or better still come on The Measure Pod and discuss it with us. You can email podcast@measurelab.co.uk, or you can reach out to myself or Dan or both of us on LinkedIn and we can arrange that. Our theme music is from Confidential, we’ve got links to their Spotify and their Instagram in our show notes. I’ve been Dara joined by Dan and also this time by Bhav. So it’s a bye from me.

[00:29:34] Daniel: Bye from me.

[00:29:35] Bhav: And bye from me.

[00:29:36] Dara: See you next time.

Written by

Daniel is the innovation and training lead at Measurelab - he is an analytics trainer, co-host of The Measure Pod analytics podcast, and overall fanatic. He loves getting stuck into all things GA4, and most recently with exploring app analytics via Firebase by building his own Android apps.

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