#29 Can you track offline marketing in GA?

The Measure Pod
The Measure Pod
#29 Can you track offline marketing in GA?

This week Dan and Dara discuss the intricacies of measuring offline marketing activities in Google Analytics. What the various methods of doing are, and what to look out for when analysing the performance of the offline channels.

Check out Simo Ahava’s post on the best practice (and recommended) Custom Dimensions you should set up in Universal Analytics asap – https://bit.ly/3sEwNPI.

Here a nice picture of a happy red car 🙂🚗 – https://bit.ly/3hCNJzY.

Check out Dan’s new blog Danalaytics and sign up the the mailing list to get his new posts as soon as they are published – https://bit.ly/3CbhBga.

In other news, Dan gets blogging and Dara goes classical!

Check out on LinkedIn:

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 analytics enthusiasts. I’m Dara, MD at Measurelab, I’m joined as always by Dan, an analytics consultant also at Measurelab. Hey Dan.

[00:00:29] Daniel: Hey Dara how’s it going?

[00:00:30] Dara: Yeah, I’m good thanks. I think we’re going straight into our topic this week aren’t we.

[00:00:33] Daniel: That’s right, yeah.

[00:00:34] Dara: So tell me what is our topic?

[00:00:36] Daniel: This week’s topic is around tracking offline marketing activity in Google Analytics.

[00:00:41] Dara: Oh, and can you even do it?

[00:00:43] Daniel: Well, that is the question, right? Like any good analyst answer to any problem, the answer is it depends. But yeah, there are methods of doing it, whether it gets you what you want. That is the unanswerable question. So I thought we would talk about a couple of the different methods of using the tools at our disposal in Google Analytics to track offline media, but then also discuss maybe some of the pros and cons and maybe some of the more advanced approaches if you have the skills to pay the bills.

[00:01:07] Dara: Sounds exciting.

[00:01:08] Daniel: All right yeah. Well, starting right at the very beginning, I think it’s worth noting that with any method of tracking any marketing, digital or online or offline above or below the fold, however you, however you describe it, there’s always going to be pros and cons. There’s always nuance, there’s always it depends wrapped up in everything. So when we go through these we’ll make sure we touch on the kind of pros and cons, especially if there’s any things that you might be doing now, you might not be aware of that’s going to be the key path.

[00:01:32] Daniel: But the first thing is if you’re doing any kind of marketing, actually, if you’re talking the context of Google Analytics, the first thing is that it only really tracks web activity. Well, it only tracks web activity, right? And the point I’m trying to make there is that everything has to end up on the website for it to be captured in Google Analytics at all. So if you’re pointing people to the website, which is super easy, because that’s the default on digital ads that it’s easy to track, you attach UTMs to the URLs and you get your source, medium, campaign, content, term, just through the standard reports in Google Analytics, we can actually use the same kind of thing in offline media, if you want people to go to the website.

[00:02:06] Daniel: So if you’re looking at as some kind of direct response campaigns and that direct response being visiting the website, that is the sweet spot in measuring offline media that Google Analytics can be very useful for. And I suppose the first point is just using UTMs, but going through generally speaking some kind of like vanity URL. So if we were to run a TV campaign, Dara, what would probably do is go visit measurelab.co.uk/tv now to get your 10% discount or whatever that is. But actually in the back end, we will have a redirect that takes the /tv and turns that to the homepage with utm_medium=tv and we’ll just attach UTMs in that way. So actually it’s the same end result as the digital campaigns, just going through some vanity URL to get to the same result.

[00:02:47] Dara: So are there any problems with using vanity URLs in this way?

[00:02:51] Daniel: Yes, there’s always problems. And actually, it’s no different to the problems you find with using the UTMs for digital marketing channels as well. And that’s the whole thing of a Campaign Timeout window in Google Analytics and Universal Analytics specifically where for, well, the default was six months, but for any subsequent direct visit, it gets reattributed back to that campaign. So if I did click through then that gets applied to some UTMs attributing it to TV, which is great, but if I then bookmark that website or come back directly every day for a month subsequently, then I’m going to get 30 sessions all attributed to TV, even though it was one click if you were from a TV ad, it was one session, one originated session. So, we’re still at the mercy of the product itself, but we can kind of like tie in, we can reuse these UTMs, but it doesn’t change how UTMs are processed or handled within GA (Google Analytics).

[00:03:39] Dara: Another thing you can do without using a vanity URL, as such is you can create unique terms for people to search for. So in your TV ads or radio ads, or even on billboards, you can have a phrase, bit like a hashtag in a way and then you would bid on those particular terms. So it might be something like ‘happy red car’ or something like that, where that phrase itself, you can then bid against to drive people to whatever page it is you want on your website or through to an app or whatever the case may be.

[00:04:08] Daniel: Yeah just kind of overtake the search results on Bing on Google Ads or whatever, but just find some, hopefully very cheap keyword or phrase that you can bid on and then just take over and then like you said, we’ve seen these kinds of things before on TV ads. Some random string of words that no one’s ever had to search for before. But what they’ll do is although it costs money, it costs additional money than running the offline campaign you’re paying for the digital ads.

[00:04:31] Daniel: It’s a really good way of, no one would search for that and get to your website any other way, they would have to have seen your ads, even if it’s not a direct response. People are aware of that phrase that you’ve created for that campaign. And they are actively searching for that. So it is, it’s like in a different way it’s slightly better in that you can measure, not just our response, but that kind of brand awareness campaign as well. I think it’s a really good approach, but it requires a lot of setup, a lot of preamble and bit more additional investment as well, probably a bunch of more heads to get up off the ground.

[00:05:00] Dara: It might be more memorable, I think the problem sometimes with the vanity URL is someone might just go and actually just Google the brand instead and forget about the fact that they saw a vanity URL. If it’s using some kind of unique combination of words that can also sometimes be tied in with some kind of discounts as well. So it’s likely to be more memorable than just a vanity URL that somebody might just bypass and just end up googling the brand.

[00:05:22] Daniel: Yeah that’s always a risk with this kind of stuff is you’re really nudging people to use a specific URL or a specific QR code or whatever. But if people find a discount code they want, they just go Google search, or go directly or click on their last email they might’ve already got from you and just go purchase. And if you’re advertising a vanity URL, it’s the same way that you might advertise a discount code and do the same kind of thing, because you’re not measuring traffic then. So you can’t really do attribution in the sense of what was the total contributed value of all the traffic via this channel, but you can do purchase attribution. So it’s around how many of our purchases have used this discount code have used this thing, and you might even hyper localise or you might narrow down those discount codes so that different segments or different people or different audiences or different channels have different discount codes. But again, the risk with that is that people then find a discount code, put it onto a discount code website, and then everyone starts using it.

[00:06:11] Daniel: I suppose you could argue the same for UTM based links. You can argue the same for vanity URLs. If I wanted to share the measurelab/tv URL with you via WhatsApp, Dara, then you’re going to click through that same link and not having seen the TV ad. So there’s always an inherent risk with all this stuff.

[00:06:27] Dara: Well, yeah and a risk the other way as well, which is that it gets dropped off. So either it’s getting accidentally shared with the tracking parameters, meaning you’re over attributing or the opposite where it gets shared somehow without the whether it’s a vanity URL or that unique code or whatever, and then you’re under attributing so it’s never going to be a perfect science, that’s the simple fact of it.

[00:06:48] Daniel: No, it’s really interesting thinking that, maybe we’re coming at this thinking that the digital attribution is an exact science, but even then it’s not. So maybe it’s no better or no worse.

[00:06:56] Dara: True and I guess on a similar note about imperfect science. There’s other things you can do, like looking at correlation effects as well. So if you’re running a big TV campaign, you can look to see if that’s had an impact in the analytics data in terms of some of the navigational channels, like organic search and direct traffic. So it can be quite obvious if it’s a big peak. If you do a, if you do a big TV campaign at a prime time slot, then chances are, you’re going to see a big increase in probably all your channels or all major channels, but definitely things like organic search and direct traffic and probably PPC as well.

[00:07:32] Daniel: Yeah, especially on the brand campaigns, for sure. I mean, this is the kind of analysis I’ve done over the last many, many years in this industry, but if you get someone’s TV ad schedule, let’s say it’s national, let’s say it’s not localised just yet, but let’s say it’s got a national TV ad schedule and they’re running it across multiple different programs, multiple different networks. All they’ll do, is they’ll generally give you after the fact, at least, because it’s never confirmed beforehand, but after the fact they’ll give you an exact down to the second time slot that it was shown. And so if you’ve got this to the second data of like the ad was shown then, you can actually go into the data and start looking at that response curve, that uplift. And I like what you said there about the navigational channels, because that’s a really interesting way you wouldn’t look at total traffic in the next five minutes after that and attribute it to TV. What you’d look at is the uplift from the baseline and especially when you look at things like most likely it’s going to be mobile and tablet, traffic, right? People aren’t going to go to their laptop or desktop necessarily as a direct response to a TV ad, they might just go on their phone.

[00:08:27] Dara: Unless they’re like us and they’re working at the time while they’re watching it on their laptop.

[00:08:33] Daniel: Yeah all the crazy people, I never understand this when people are watching TV in the background while doing something on their laptop. I can’t concentrate, I can’t do both. I can’t even listen to music with words in it when I’m working.

[00:08:42] Dara: Yeah, that was definitely a joke for me. There’s no way I could do two things at the same time.

[00:08:47] Daniel: But yeah I mean, you’re taking a baseline, however you do it, and then you look at the uplift from that baseline. There’s generally a time decay if TV it’s pretty quick, within minutes there’s like a big influx and then it dies down. And if you’re doing localised campaigns it’s even easier because if you’re targeting the whole of just London, for example, with a TV campaign, then you just narrow your uplift data to London. You look a response curve just afterwards, and you do a bit of analysis to understand the drop off rates and the time decay. But the statistical approach is actually one of the best ways of doing it, but what we’re not doing is we’re not tracking the offline media, we’re inferring it. There’s a very big distinction because either you know that someone saw an advert, whether it’s online or offline or you don’t, and you can infer. And I think with this inferal stuff, it’s really valuable because it’s like any kind of prospecting, right. If you’re doing any kind of, even if it’s the same stuff we’ve just been talking about like TV campaigns or radio or billboard stuff. It’s the same thing, if you’re doing direct response marketing, that’s one way of tracking it but what if you’re doing like brand campaigns or brand awareness campaigns. Now how the hell are you meant to track those if you’re not pushing someone to do something on your website immediately, because how would you infer that? Actually there are ways of doing that, probably there’s a bunch of people way clever than I that could explain it in way more detail.

[00:09:59] Daniel: Ultimately it’s all around incrementality testing, like any AB test, right? Having a base case that hasn’t seen something and then comparing that against the pool of people that have. So if you’re doing a national campaign TV ad, and let’s say it’s just brand awareness, have a specific region or area that don’t see the ads. So have a kind of base group, the A on the AB test right, and then when you can measure the two of those against each other, you can look at the overall uplift of a campaign over a period of time, and then you can have a relative more certainty of the the value that that campaign has provided.

[00:10:33] Dara: I guess one problem or question there is around that timeframe because that’s the difficulty even with online brand awareness is what is that timeframe. You don’t know necessarily how long it is going to take for that to take effect, even when it does, you often won’t know for certain that it was, you don’t know what exactly what part that plays and we’re at risk probably here of going down an attribution rabbit hole.

[00:10:54] Daniel: All right so let’s pull ourselves out of the rabbit hole before we get too deep, but there’s one way of doing it. So AB test everything, AB test branding campaigns, that’s really the best way of understanding, like a brand awareness or a branding campaign in general is always just to kind of AB test or to do incrementality studies, just to see as you’re not trying to get people to do something there and then there is a longer tail to it too. But I think depending on the brand, depending on the activity, the marketing type, I think you’re all gonna have different windows there. Even if you’re doing brand awareness, if you’re not doing this kind of prospecting, targeting everyone approach, if you’re doing direct targeting, if you know who you’re advertising to, this is the best possible situation.

[00:11:29] Daniel: Let’s say you’ve got a CDP or a data warehouse, and you’ve got a bunch of people in there or in your CRM, even, you got a bunch of people in there and you’re like, I’m going to send these people, I’ve got your addresses, I’m going to send them all a brochure, let’s say I’m a holiday company and I’m going to send them a brochure of all the holidays that we are launching this, this season. It’s really easy then to say, okay, I’ve got my data. I know them all individually and their addresses and I’ll send them all a piece of direct mail. Let’s say I posted them all today. Then quite confidently you can put two days after that send let’s say, just on average, you can put a little touch point in their user journey that they received a piece of direct mail, they’ve received that brochure. And then over time you can look at those users’ re-engagement or whether they purchased again with you after that campaign, you always, again, always go back to having an AB test, having an incrementality study at play here.

[00:12:16] Daniel: What you’d be able to do is say, I know you let’s say you’re already an existing customer. I’m going to send you a piece of marketing directly, posted it through your letterbox, and then I’m going to see if you come back. And that’s the best case scenario there because you have a user ID with a touchpoint of an offline marketing send, but then again, the pool of those people are going to be very small comparatively to your prospecting campaigns because these have to be existing known consented customers. So it’s always going to be a smaller pool, but you have a, way more of a certainty around the performance of those campaigns. And maybe that can infer or influence your willingness to spend on people you don’t know, right. It’s not just doing a door drop send of like blanket coating postcodes, for example, with leaflets, or that let’s say, we’ll talk about that in a sec because there’s another way of maybe doing that I’ve done before with a couple of companies. But if you know who the person is, when you’ve sent them something and then, if they ever purchase again, that is the ideal situation to do that analysis to really understand if that was a driving force of them to continue to be a customer of yours.

[00:13:12] Dara: Yeah and you’re talking ideal, I guess the ideal, ideal would be where you’ve also got some kind of loyalty scheme. So you can identify those users in store if assuming you are a business that has physical stores as well. So then you can identify that they’ve been sent a brochure and then you can track them if they purchase in store, or if they actually purchase on the website.

[00:13:32] Daniel: Yeah, this is the kind of world where, you know, everyone’s known by everywhere. We’re literally fingerprinting them as they walk into a shop just to see if they’ve had that store visit right? No I joke but just go back onto the door drop side. I worked with a company that provides, let’s say they provide house insurance and what we did or what they did is they then blanket coated certain postcodes just in case we don’t have any UK listeners here, the post codes are broken into two parts. So the first part gives you a rough region, and then the second part is very localised to your probably neighbourhood or your road. And so they just blanket coated the first part of postcodes. So it was like a BN1-10 for example and then that means a big chunk of the Brighton and surrounding towns have received a leaflet through their letterbox.

[00:14:13] Daniel: But what happens then, let’s say if you’re selling insurance, you need to provide at the point of getting a quote or purchasing insurance, you need to provide your postcode again, right. Because you are buying it for the house, and this is the really important part. So it’s not going to work for everyone but you can just blanket send certain postcodes with some marketing, and then you’re basically collecting all of your policies in the other side, so the conversions. You can’t track traffic based on this by the way, but you can only track conversions, but you can look at those or you can infer that if every single person in this postcode received there leaflet and if 10% more conversions happened in that area. You can start to associate some value to that campaign, and then you might even just do it hyper-localised to begin with before you do like a big national campaign or roll it out into different regions. But it’s a really good way of if your product requires you to collect a postcode at the other side of it, it’s a really good way to do things like regional targeting or blanket targeting rather, and actually measuring in some aspect, not user to user, but like region to region if it’s working.

[00:15:14] Dara: All right, let’s zoom out a level again, Dan. Maybe we should talk about some of the ways of doing this within GA (Google Analytics) and then also potential pitfalls or some of the things to be careful of if you are actually doing this in GA.

[00:15:27] Daniel: Yeah, for sure. First of all, we need to define, are we in Universal Analytics or GA4 because I think that does make a difference nowadays. And let’s also just assume we’re both using the free versions of each product, right? But in the free version of Universal Analytics, the first thing I’d recommend to do, and this is the first thing I do with anyone I’m working with, regardless, there’s a set of custom dimensions that are just go to best practice, make sure you implement them, but there’s a couple of custom dimensions, including the client ID, session ID, and hit timestamp. And these three things, well the hit timestamp is the most vital part for this kind of analysis. I make sure we get that done before any campaign like this needs to be analysed. The reason I say that is because the vanilla version of Universal Analytics only gives you down to an hourly level data.

[00:16:10] Daniel: So if I’m doing any analysis in the interface, I can go down to the hour and it’s fine. And I have done, or I attempted to do some TV analysis and uplift analysis for certain clients. But now you’re having to work to hours, and the thing is, I don’t think anyone can remember a TV ad they saw an hour after they saw it. So you’re now attributing everything within that hour to a TV ad and that’s just not good enough. It’s not detailed enough, I kind of shutter at the thought of that analysis looking back now because I knew it wasn’t good enough, but they needed something so yeah, I’m in two minds about that. So yeah get the timestamp data out, so at the very least you can get to the minute data, and then if you’re looking at to the minute schedules like TV ad schedules, then at least you’ve got the opportunity to do some analysis there.

[00:16:53] Daniel: On the other side in GA4 it’s already there. You don’t have access to the minute by minute data in the interface, but the connector to BigQuery as part of the free version of GA4 so just use the connector to BigQuery and do that analysis there. At least then you have the second-to-second data, I know there’s some nuance around the timestamps, being the batch timestamp for all of them, they hit timestamp and all that funky stuff that’s happening in a GA4 but nevertheless, it’s still way better than hourly data that you’ll get in Universal Analytics. So how we do it is make sure you have the data first of all, make sure you’re tracking before the campaign goes live. This isn’t just a nice to have, it just means this might be impossible to do.

[00:17:30] Daniel: Then when it comes to things like Universal Analytics, it’s all about creating segments or creating custom reports. And I filter for that specific day, break it down by hour by minute, and then actually look and see if there’s a response curve. Just have a look in the data and see if there’s a response curve, I’m not doing anything hyper clever or statistical here. I’m just looking to see if there was a response. Let’s say it’s regional filtering for certain cities, filtering for certain regions and just to kind of see if there’s trends, if there’s something to pursue further. If there is, then you can take that to the next step and pull it out into spreadsheets or BigQuery or whatever you want to do, maybe automate it and apply across their entire schedule. But the first thing to do is just to see if there is a response worthy of investing the time to do further analysis.

[00:18:11] Dara: I’ve got a contentious question for you, so people have had different views on how direct gets treated in GA (Google Analytics) over the years in terms of the last non-direct attribution model. And the thinking was always that well, give favour to the digital first channels. If you’re going to be pushing in offline channel data, using any of these techniques that we’ve been talking about, what’s your view on whether that should or shouldn’t override the digital channels.

[00:18:41] Daniel: Yeah, that’s a really good point. I don’t want to say it depends again. So I won’t, I haven’t said that, I will not say that. If I had to come down on one side of the fence, I would say don’t. And the reason I say that is because most of the examples we’ve given thus far, and most of the ways of tracking or inferring offline marketing within your digital data set is actually at the expense of a digital channel. So we’re looking at even just the last example we said about TV response curves, direct response, it’s going to be through what we called navigational channels. It’s going to be through SEO, paid search or brand SEO, brand paid search, direct. But the thing is, all of those are still really important to know. I don’t want to lose that data and overwrite them to be TV. TV is interesting for the purpose of a piece of analysis I’m doing now, but it’s not something I need there permanently. Actually, if anything, I need to know that that was SEO this landing page, and then starting to look at, if I needed to go into the SEO side of the world, then that is more relevant for me as an analyst.

[00:19:37] Daniel: So I would always say if you’re looking to do this kind of stuff, and this applies to using UTMs by vanity URLs to. Rather than using things like UTMs, actually add just a random other query parameter of like tv=true or offlinemedia=tv or something like that in the query string. So we can still ultimately get the source of the traffic. So in that case, it will be direct or in the case of, doing that random, what do you say ‘happy red car’? Or some other random search term that you are paying for. We still need to know it’s PPC. We still need to know it as that keyword and we still need to know that ad group and campaign and the structure that’s behind it and the spend of course, behind it. Then adding a flag, adding another random query parameter that you can pull into a custom dimension or just leave it, the URL, whatever you want to do with them, have a way of identifying that as offline is the key part there. Like I say, I don’t want to lose data at the expense of understanding the offline’s influence. What I want to do is have it alongside and to have it alongside, you have to choose what the most important one is. You have to choose what goes into the campaign, the default campaign structure, what goes into this source, medium, campaign, content, term.

[00:20:40] Daniel: My view is again, you force me to come down on one side of the fence. My view is to keep it digital, keep it all business as usual, and then have the ability to pivot that into an offline world. And all of this goes out the window, if you’re putting it into BigQuery doing your own analysis in your own data warehouse, your own single customer view, then you can do what the hell you want out there. But this is about if you’re talking about overwriting the data in GA, keep it digital.

[00:21:02] Dara: Yeah, actually, I agree with you. I think it’s because there, it’s not just about keeping it digital, it’s actually sticking to the real, the channel that does drive the user to the site or to the app, which, in the case of the vanity URL could be, it could be direct, but someone could still search for it and certainly with the happy red car, and I think we’re all probably going to go and search happy red car after this and see why see what actually shows up. But in that case, you are going to be bidding on that term. So you want to know that the user interacted with a TV ad or saw a billboard or whatever. That’s not ultimately what drove them to the website, it is the paid search click. So you want both don’t you, it’s not one or the other. It’s both that you want really isn’t it, but I’m with you. I think it’s track the digital channel through the analytics in the standard way, whether it’s with UTMs or whatever, but then additionally, have a parameter that’s telling you that this particular user did that search, having seen a TV ad or a billboard or listened to a radio ad.

[00:21:58] Daniel: That’s it in the interface you’re quite limited. You’re really limited, using segments is great and customer reports for sure but you wouldn’t be able to take that to let’s say you’re running daily TV ads, you’re not gonna be able to do that one by one.

[00:22:08] Daniel: More importantly, Dara, to change the subject slightly is that there is no one currently bidding on ‘happy red car’. So I’m going to try and get the Measurelab PPC account to start bidding for happy red car. I don’t know how long it would take us to get on there, but if anyone is listening, then don’t search for happy red card because it might drive the price up. Let’s get some ads on there first, and then let’s see if we can capitalise this for the next TV campaign Dara we run, we’ll do happy red car.

[00:22:30] Dara: You’ve given me real easy summary this week. It depends.

[00:22:34] Daniel: It does, it’s not wrong though.

[00:22:36] Dara: It’s not wrong. We kind of hate saying it, but it is often the, it is often the best answer. There are ways you can do this, none of them are perfect. Like with anything, this has been a bit of a theme on The Measure Pod. It’s more about understanding the limitations, so if you’re going to track offline marketing through GA (Google Analytics) or any other analytics tool, just be aware of what some of the drawbacks are, but there are ways to do it to varying degrees of effectiveness.

[00:22:59] Dara: Okay moving swiftly on, all this talk of TV leads quite nicely into our usual wind down, because it often is Netflix related. Are you going to prove me wrong this week?

[00:23:09] Daniel: I am, probably for the first time I am going to prove you wrong, it’s not TV. So it’s a bit of a cop out actually, because we’re talking about what we’re doing to take our brain away from analytics. But what I’ve done is I’ve actually set up my own analytics blog, which is completely contradictory to winding down, but let me justify it slightly. This is a new year’s resolution I’ve had that’s only just come to fruition back in February. The idea behind it is that I can publish just random rants and raves and nuances that I come across focusing around GA4. I don’t know if you know Dara, but I like talking about GA4 and I mentioned it a fair few times, so I thought I’d have a forum to, to rant about it a little bit as well as the wider GMP (Google Marketing Platform) of course. Shameless plug time, it’s danalytics.co.uk I know it’s a very clever website name, combines my name and analytics, but it was too good an opportunity to pass. So danalytics.co.uk and yeah, I’ve only done a couple of posts so far, but I thought it’s a fun that all I can say is it is a personal project and I’m really enjoying it.

[00:24:06] Daniel: Other than like a stupid MySpace page where you can change some of the HTML and the CSS on there, I’ve never had my own project, my own thing, that I could play with, and I’m really enjoying everything. I feel like a business owner, right? Like I’ve always talked for clients or product side or agency side or what not, but now I’m the client and now I’m setting up Google Analytics and finding another view to the whole thing. It’s actually really fascinating.

[00:24:28] Dara: Not sure what to say to that. You’re winding down by doing more analytics, I mean, why not? If it makes you happy?

[00:24:34] Daniel: Yeah so far, so far, if it ever becomes a bore or a frustration or an annoyance, then I’ll drop it. I’m not that tied to it, but for now I’m finding it very fun. So, how about you Dara? What have you been doing? And tell me you’ve been winding down from analytics, unlike me.

[00:24:49] Dara: I have and unbelievably, yet again, I’ve done something very cultured. So it was a friend’s birthday, we went to the orchestra and so very grownup, very sophisticated. It was a Tchaikovsky symphony and it was the Royal Philharmonic Orchestra and it was amazing. To be honest, I’m easily pleased because I’m not a musician. So I can’t assess these things from a musical point of view. All I know is, does it sound good? And it definitely did, but it was, it was amazing. And then obviously after that we went for a few drinks as well, so it was a good fun night out but quite a sophisticated way to celebrate a birthday.

[00:25:23] Daniel: Yeah, very nice. I can’t believe they let you in.

[00:25:25] Dara: I know me too, from next week, I promise I’ll be back to kind of normal things that I do and not going to the ballet or the orchestra.

[00:25:32] Daniel: Netflix and running.

[00:25:33] Dara: Yeah, exactly.

[00:25:34] Daniel: Oh, wicked. Well I’m nodding, terrible for an audio format show, but I’m nodding along as if I know exactly what you just said, but I do like classical music, but I have no idea. I’m not that into classical music.

[00:25:43] Dara: Yeah I barely understand what I said, so don’t worry about it. Before I wind things up, I think I’m going to try something a little new. We’re going to talk about how people can find out more about us. Dan, if people want to find out more about you, where can they find you apart from danalytics.

[00:25:58] Daniel: Well, that is avenue number one now right. I think LinkedIn, LinkedIn’s the obvious choice, right? Especially from a professional standpoint, I’m not a social media user. I’m on Twitter, but I haven’t done a tweet in forever and I don’t have any other social platforms. The best thing is via LinkedIn or even email. If you want to get in touch with me directly it’s daniel@measurelab.co.uk. Happy to talk about the show, the analytics, or even just TV attribution, how you track offline media, anything like that. I’m more than happy to share anything I’ve done in the past so, feel free to reach out.

[00:26:26] Dara: Same for me really. I’m also not a big social media user, LinkedIn is the best place to find me if you want to reach out and talk about The Measure Pod, LinkedIn is the go-to. We’re simple people aren’t we Dan?

[00:26:37] Daniel: Simple yeah, simply is good. We can focus all of our energy on one rather than being distracted by multiple. That’s why I think so you’re gonna have a great conversation with us on LinkedIn. If you go to Twitter, I probably won’t see it for about a month.

[00:26:47] Dara: Or Tik-Tok, don’t even know what it is.

[00:26:49] Daniel: What’s that?

[00:26:50] Dara: Okay that’s us for this week, as always you find out more about us or even find our previous episodes in our archive over at measurelab.co.uk/podcast, or drop an email to podcast@measurelab.co.uk or as we just mentioned, look us up on LinkedIn, either of us, both of us and reach out if you want to suggest a topic or a better still, if you want to come on The Measure Pod and discuss that topic with us. That’s it from us for this week, join us next time for more analytics chit-chat. I’ve been Dara joined as always by Dan, so it’s a bye from me.

[00:27:24] Daniel: And bye from me.

[00:27:25] 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.

Subscribe to our newsletter: