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Lee:
Welcome to the Event Engine podcast. My name is Lee and we are joined by the one, the only, it’s Caroline McGuckian. How are you today?
Caroline McGuckian:
I’m good, thank you very much. Thank you for having me.
Lee:
Wonderful. Thanks for being here. And I must say, that view out of your window, is it Edwardian or something? It just looks. It looks wonderful.
Caroline McGuckian:
Temple Chambers. So law courts, actually.
Lee:
Nice.
Caroline McGuckian:
Yeah, just right by the river. We’ve only just moved about a month ago, so still extremely exploring it, but so far it’s lovely. Yeah.
Lee:
Still unpacking, I imagine, then.
Caroline McGuckian:
Yeah, hence the blank walls around me.
Lee:
The whiteboard leaning against the wall. It’s all right, I’m still moving in. Years later, I just posted on. Well, I’ve been here for 18 years and I still have a whole pile of junk off to the right here that no one can see just off camera that I’ve not found a place for. So, anyway, folks, Caroline is from Mesh and she is here to talk about. About spatial analytics. But don’t get anywhere because there are some really cool applications that we’re going to discuss things that you may not realise you can do at your event. So, Caroline, it would be lovely to hear from yourself in your own words, just a little potted history of who you are and the company that you are a part of.
Caroline McGuckian:
So, hi, I’m the CEO of Mesh and Mesh is a WI fi analytics business that looks at the movement of people and we are specialists in understanding that movement at live events. So B2B and B2C, we look at everything from kind of experiential individual activations right through to the totality of conferences, fan zones, festivals. And I think that one of the things that makes us little bit different is that we are all from a background where the. The team have worked in the world of live, so they understand what it’s like to be standing the day before or the morning of when doors open, when gates open, and you are under that pressure to line all of everything up and, and get it all perfect. So we keep our product really simple to deploy and we focus on providing metrics that you can use that make sense for live experiences, rather than just measuring things for the sake of it. So, yeah, and we also have been around for about eight years now, so we’ve got quite an extensive history globally across a wide range of events. And why I think that’s. That’s quite interesting is because one of the areas that we also focus on is helping our clients understand what they’re looking at.
Caroline McGuckian:
So you know, a lot of the time whenever we present sort of background metrics and our data, you know, you turn around to a client and you say, well, hey, you had a 27% conversion rate. So the next question is, is that any good? You know, what does that mean? Yeah, you know, so we work a lot with our clients to, to help support them in interpreting the data and applying it to their needs and their briefs and I think so between the technology and the services wrapper that we provide. I don’t like to refer to this as a SaaS business actually, although we do have a platform and obviously we have, you know, we have dashboards and APIs and all of those sort of essential things. When you’re a data business, we, we also have client services and account managers that hold your hand and help you understand how to set up that measurement framework in the first place, deploy it and interpret what it’s telling you and learn from it, because otherwise you’re just doing things for the sake of it.
Lee:
That makes sense and kind of jumping back in that time machine for when the inceptions that were of mesh happened. How did that start? Was that in a restaurant with a napkin or what’s the story there?
Caroline McGuckian:
Obviously, of course. So an old colleague of mine introduced me to a gentleman called Anthony Ganji. Ants is from, he’s from the experiential world actually. My background is very digital, so I was, I was involved in digital agencies for 20 something years, since the 90s and got talking and he had had a brief to try and help his client understand what was happening at the experience that he had built out for them. And we ended up discussing how you can literally measure everything in a digital world, but in the physical world it was still pure guesswork. And my experience of the live landscape at that point was very limited. So I was totally gobsmacked. If the trispy taught that, I could tell you who clicked on what, who looked at what, how many pages they consumed, the time spent, where they went, where they were before, where they went after, you know, in granular detail. But when it came to looking at what was then an increasing amount of investment into sort of experiential and live or the experience economy as it’s now become was, it was like the blind leading the blind. I was, I was genuinely surprised by the lack of accountability and responsibility that people were taking when they were spending clients money.
Caroline McGuckian:
You know, this is big money. You know, you’re, you’re investing a lot in, in whether it’s a stand, whether it’s a touring activation. Whether it’s a sponsorship doesn’t really matter what it is, but you’re, you’re investing money and you have a right to understand what that’s delivering you and what that’s returning you. So that was the start of it and that was eight years ago. We’ve been through a few different iterations. We, we are now, yeah, eight years in and have our offices in New York, the Gold coast and, and in London. And we’re lucky. We got, you know, one of the best client lists ever. The thing that probably made the business was in, in 2018, we were doing some work, some work for Johnnie Walker in their sponsorship of F1.
Lee:
Yeah.
Caroline McGuckian:
And a few weeks later, after casual name drop, well, after we, after we’d provided the report back, I got this phone call and I was called by Formula One management as it was at the time, TCGM’s, and they said, how do you know more about what’s happening in our fan zone than we do? And it was, to this day remains one of the most surreal professional meetings I have ever had. And it was luck. I would love to say we were, you know, some sort of amazing genius. Like, you know, we, we had a lucky brick and we were then appointed by Formula One in 2018 and that sort of just changed the order of magnitudes of mesh, really, and we snowballed from there.
Lee:
That’s amazing. So for many people listening right now, event organisers, I know, conference, exhibition, etc. We get it. A lot of it is guesswork. We’ll normally put on our first event and we’ll try and keep our eye on what’s going on. Where do people go? Where are the busiest stands? Where do people go? Hang out and have conversations? Are people around the coffee stand that we set up over there next to the restrooms or whatever else. You know, a lot of it is just our own observations, etc. If I was to come to you as therefore, as an event organiser, say, hey, how can you help me? What is it that you would actually do for us and get a set up and what does the tech kind of look like so that someone can actually understand what it is?
Caroline McGuckian:
So in the first instance, when people come to us, they usually have a problem. Now, they might not be able to articulate it very well or they might not tease it out yet, but we try and measure with intent. So we will sit down and work with whoever the client might be to understand on Monday morning, when you look back, what information can you, what information will help you do about a dog. Right. So what is the missing gaps? Because we’re only one part of a measurement strategy. Yeah. There’s a multiple different inputs to a measurement framework for an event. You know, what, what we do and that measurement of people, passive, anonymous and aggregate, it is not the same as first party data collection. Of course you’re going to have your CRM, your collecting of the email address, whatever the constituent parts of your experience and your event and you know, your investment looks like we’re one piece of it. So we encourage our clients to think about their intention before they start measurement. Because too often people measure things and then they try and retrofit. So they look back and they go, you know, you’re looking for patterns in data rather than looking at.
Caroline McGuckian:
This is my expectation. I’ve decided to do this because I want reach, because I want to speak to my existing customers, because I want to talk to a new audience. I’ve decided to sponsor it because I want people that hear my CEO in his keynote speech to come to the stand afterwards so that we can collect their details. There is a lot of thought goes into, there’s a lot of curation goes into all of these events. So we ask people before the event what success of that looks like, what’s the success of that investment look like for you. And then we measure against that rather than just slapping up sensors and hoping that afterwards we go, oh, look, I mean, don’t get me wrong, obviously there’s some of that too.
Lee:
Sure.
Caroline McGuckian:
You know, obviously whenever you come to your post event analysis, you look back and sometimes there’s surprises. Yeah. A lot of times being honest, there isn’t. You know, a lot of the time, 80% of what you’re looking at validates your assumptions, it validates your, your thoughts, your experienced individuals. You know, it’s, it would be highly unusual for people not to be congregating around your coffee area. Right.
Lee:
So unless you have really bad coffee.
Caroline McGuckian:
Yeah, well, all sorts. Right, yeah, yeah. So we try and discourage people from measuring the obvious and to use mesh and apply it for the things that are a little bit more kind of brain teaser y and a little bit more challenging to understand.
Lee:
Yeah.
Caroline McGuckian:
So we look at the relationship. For example, if you are a sponsor from all of your different touch points, not just your stand, maybe like I mentioned, you’re, you’ve contributed some content, your staff are on a panel. Yeah. So what’s the relationship between people that saw that panel and came to your stand afterwards? Did they come beforehand and then go to the panel? What order did they do things in those cohorts? Like you can start to look at the different behaviours of people. So if you were sitting in your panel and does that mean that I spent 30 minutes on the stand versus someone who hadn’t seen our content? He only spent 11. So we try and challenge our clients to think broader than just counts and numbers. And you know, 37 people did this for 11 minutes.
Lee:
Yeah. So. And then how are you able to do that then? So how are you able to tell that a lot of people showed up to the CEOs talk in the speech area and then moseyed on over to stand B3 just via their phones.
Caroline McGuckian:
So mobile phones are permanently sending out signals now? To be clear, we are 100% compliant with GDPR.
Lee:
Okay. That was going to be my follow up question, so I’m glad you covered that.
Caroline McGuckian:
No idea who owns the device. There is no, there is no attribution of this device to me, Caroline. There is no way to correlate those two pieces information. So we deal in anonymous aggregates and buckets of people, not individual individually. We know who you are, we know where you live. We also don’t follow anyone home. So we’re very, very contained to the experience that that individual is having. These pings are being sent out permanently, not very consistently, but permanently. And they register on the mesh sensors. So you will come to us, we will work with you, we will understand what it is that you’re trying to measure and we will make recommendations about where to place these sensors so that they can hear the pings. So you will have the opportunity to put your sensor in the stage area, maybe at the bar, maybe you have branded something at the front door. And then possibly on your stand you have a lounge area, a reception desk and a demo unit. We would look at putting sensors on each of those individual areas. And what we’re able to do is look at the relationship between the devices that get registered on those different sensors.
Lee:
Wow. And then use case wise as well then is that something that not only the organiser can do, but they can also get exhibitors involved in, should they choose, so that everyone could kind of share some of that information.
Caroline McGuckian:
We have, we have all sorts of different clients. So we have exhibitors, we have venues, we have promoters, you know, we have rights holders, we have sponsors, we have all. All. The number is the number. Right. So it doesn’t really, from my perspective, the, the, the number is the number. What that means to you depends on who you are and what your day job Is, you know, so if the dwell Time is 25 minutes, what that means to a sponsor is high exposure. Maybe what that means to the. To the promoter is we didn’t have enough staff on. That’s far too long for people to be queuing at the bar. So, you know, I generate the data and then depending on the role and the objective and the intention of your measurement.
Lee:
Yeah.
Caroline McGuckian:
You then take that data and apply it to your business, your objectives, your needs.
Lee:
Well, that is phenomenal. I mean, I got to admit, I initially I thought it must be something to do with phones, but I could just kind of imagine that somehow you’d worked out a way of sensing body movement and identifying the body or something like that through the WI fi signals. Because, you know, when you watch movies and the spy thrillers and they’re like, oh, we’re gonna work out what the inside of that room looks like based on the sound signal of the recording that we heard. And then they. This digital diagram. I was like, oh, I wonder if it’s that cool.
Caroline McGuckian:
Yeah, one. One day we’ll get there. I mean, there’s an increase in use of LiDAR, which can do some of that.
Lee:
Yeah.
Caroline McGuckian:
You know, but that’s a. The other thing as well is just because you can do something doesn’t mean you should.
Lee:
Yes.
Caroline McGuckian:
So, you know, MASH is. It’s ultimately really relatively simple. You know, the actual. That the. The secret sauce or the magic is knowing how to apply it and knowing how to make the most of the information that you gather. What we’re doing isn’t. I don’t want to do a disservice, but it’s not. It’s not technically the most challenging thing in the world, you know, but understanding the appropriate application, understanding how to take that information and use it is. Is probably as meaningful, if not more so than the ability to collect it in the first place.
Lee:
Yeah, I think that could be applied though it couldn’t it in many cases even say, for example, building a website is technically not too hard for many people to do, but to actually build one that will end up converting people into paying customers is a whole different ball game and needs experience of building other sites and understanding what the user activity is, et cetera, what they’re more likely to do, colours that are going to attract them versus others. So it makes. That makes a lot of sense.
Caroline McGuckian:
We talk a lot about data in context. A number is a number until you put that context around it. And that’s what makes it useful and interesting.
Lee:
Absolutely. What kind of spaces does it work for best?
Caroline McGuckian:
Well, one of the other areas that we probably stand out a little bit is we are as effective outside as we are inside. So what we find is that clients seem to think that the customer experience starts at a nice sort of line on a CAD map and it doesn’t. Customer experience starts from the point of arrival. It starts from the branding outside. It starts. It can be made up of a lot of different touch points and different experiences. So MASH is easy to deploy. The sensors are small, they’re smaller than your phone, they’re very lightweight, they can run on batteries. What that means is in a very. Is inelegant word. Unelegant. Inelegant. Okay. In a very simple way, we can velcro those things to the back of a poster. We have set them in plant pots before. Now I personally have deployed a sensor up a tree because what it does is the flexibility of that deployment and the simplicity of it means that you can measure where the people are. You have to look at where the people are, not where there’s a plug socket. If you create a framework and you’re looking at pre existing infrastructure, so access points or even cameras, you’re kind of stuck in terms of where you can put these things and then you’re hoping that the people will walk underneath them.
Caroline McGuckian:
Whereas what we do is we have much more flexibility in terms of where those sensors and pickup points can be placed. So we can get quite creative in terms of what we can measure. I mean, at Silverstone we measured as well as the Grand Prix. That’s great.
Lee:
Casual name drops again. I love it.
Caroline McGuckian:
We measured the field. So camping is massive.
Lee:
Yeah.
Caroline McGuckian:
And they needed to understand how many people were using the cut Thrace. So we actually measured a field from the campsite to the track to help them understand people who are not following the paths that they want them to follow. You know, other clients do exist.
Lee:
Star.
Caroline McGuckian:
Star. Star.
Lee:
If I had them on my client list, I would, I would. Casual name drop a few times as well.
Caroline McGuckian:
I mean, yeah, we, we, we have, we have quite a few, but we do a lot of work in. We do a lot of work in pharmaceuticals actually, and big conferences, sport and entertainment and then experiential marketing. So yeah, a lot of brand sponsorships and marketing agencies are users as well.
Lee:
Awesome. Talking about the data then, because you shared that obviously for yourselves. You’re going to review the data in context based on what it is the clients are looking to achieve, etc. From the data. What, what sort of information do you find Clients are most surprised by.
Caroline McGuckian:
Well, a lot of people assume that measurement means validation. You know, the, the more challenging. The more challenging meetings of my week are usually when you have to let people know that it wasn’t very effective. So there’s often some. Not often, but there’s occasionally some sticky moments where you have to tell people that the results were disappointing. And that can be in terms of anything from the reach of it to the conversion rate of passersby, the amount of time that someone spent with the brand, the frequency with which they visited, you know, the percentage of an event that actually touched their stand. So again, that’s another common one would be, oh, but there’s a hundred thousand attendees and you’re expecting all 100,000 of those attendees, which, by the way, are there for three days. So that probably means about 40,000 unique individuals to visit your stand and spend a day. You know, like, come on, lads. You know, when you go, when you got 10,000 visitors, they’re like, oh, no, but that can’t possibly be right. Yeah. So there’s a. There’s a journey that people need to be taken on in terms of their data understanding and whenever they start any measurement framework being realistic about what they can expect to achieve.
Caroline McGuckian:
But that said, if you don’t start to measure it, you can’t improve it. Right. So if you don’t know what your baseline is and you don’t know what your starting point is, you can’t make progress on that. So we work with our clients a lot in terms of things like reach, frequency, dwell time, the performance of different assets and different attributes. High. They are comparative, so that can be comparative across your own body of work. So a good example might be kind of touring experiential work. Yeah, yeah. So we would do quite a lot of that, whereby an event or an activation might be in Westfield one day and then it might move to the bullring the next day and then it’ll be in Edinburgh the day after that. So it’s about looking at the different geographies and the different placements, so to speak, and helping people understand that that one was good for reach, that one was good for engagement, that one shouldn’t be on the schedule next year because you’ve got to balance the portfolio of what you’re trying to achieve with the tour and the event as well. So we work with people a lot in that context.
Lee:
Yeah. Use cases go way beyond then, don’t they? Just an individual space or event. Here we’re talking about things that are going across multiple yeah. Wow.
Caroline McGuckian:
So you can benchmark yourself against your own body of work, but then also, as I mentioned, eight years of data. So we provide our own benchmarks. So for clients that are in specific verticals or if they want to understand, you know, three day exhibitions in Europe where we can go, here’s the average conversion rate or if you’re in pharmaceuticals, we can go all of our pharma clients last year saw an average dwell Time of 17 minutes and yours is 15 minutes and so on and so forth. So that’s what I mean about the context. So it’s not just about the data itself. I mean that is obviously your data is interesting to you.
Lee:
Sure.
Caroline McGuckian:
But invariably once people digest that, the next questions that they have are, are, well, is that good? How do I compare to other people what happened last year, what should I do next year? You know, and it’s about how to apply it, how to use it.
Lee:
That’s insane. I mean just the fact that you obviously, you know, obviously you have that information, you’re able to do that. I hadn’t even clocked like this entire conversation that bang was actually me dropping my coffee in sure. In pure amazement at the idea that I’d be able to say, hey, I’ve got this type of event, etc. I’m looking at kicking off one in Europe. How do two or three day events compare for XYZ? And you’ll be able to say, well, based on our eight years of data, we actually think that two day events in Dusseldorf work best if you’re doing a European conference. I mean, maybe I’ve oversimplified that, but.
Caroline McGuckian:
Yeah, I mean we’ve never.
Lee:
Yeah, but in theory. Yeah, I even snorted then. I’m not impressed.
Caroline McGuckian:
Yeah, no, it’s really assuming, listen, we need to have enough. If we don’t have enough depth in the vertical, we don’t, we don’t provide a benchmark back. But assuming it’s a vertical or, or it fits our criteria of having enough, enough depth to be genuinely anonymous, then yes, we can share that, that’s cool.
Lee:
Let’s jump on the anonymous thing as well, you know, because again, for some people, they might feel a little bit weirded out that they are being tracked, etc. So just to kind of confirm and clarify my kind of reverse brief to you, I rock up with my phone. You don’t know it’s Lee Jackson. All you give me is a gibberish number that you’re going to track all around. So I could be anything, anyone.
Caroline McGuckian:
Yeah, so your, your phone has A multitude of different identifiers. One of them is commonly known as the Mac id, which I’m sure everybody’s heard of. That said, nobody knows their own Mac id. I mean, I do this for a lip and I do not know the Mac ID of this fact. It’s not a piece of information that I need or I would take. However, it is apparently personally identifiable tbc. That said, we, we take that Mac address and we effectively, in a slightly more well considered, more sophisticated way that I’m about to paraphrase it, we turn that into a mesh number. So 1234 becomes ABCD.
Lee:
Yep.
Caroline McGuckian:
We discard 1234, we keep ABCD and you have a mesh number. Knotting Mac AD.
Lee:
Brilliant. That’s fantastic. And then that’s it. You’ll never know who it was, but you are able to know that ABC had this sort of activity. They came in at 9 o’clock, they went straight to the coffee, etc. They went to a talk, they went to the person stand after that talk, you know, etc. Etc. So there’s a bit of a data flow. I mean, my brain is also imploding at the idea of, of potentially 100 or 200 people at a conference and how kind of impossible that might be to look at all that data, at least for my brain, over the course of say, a two day event. So I assume your software has magic involved to let me understand it better. Just tell us about that magic.
Caroline McGuckian:
I mean, it’s just big data, it’s a lot of processing power, it’s a lot of Python script out, a little bit of AI magic in there as well, to ingest it all.
Lee:
So it basically is magic. That’s good, right?
Caroline McGuckian:
Yeah, I mean, we try, we try not to be too clever because we don’t want a black box. So, you know, if you’re a client and you ask us a question about how it works, we want to be able to explain it to you in layman’s terms and not go, I don’t know, there’s a black box over here that spits it out. Yeah, because I don’t think that that’s very, I don’t think that’s very reassuring.
Lee:
No, not really.
Caroline McGuckian:
Honest. So we are all quite articulate in terms of explaining to clients our technology and it isn’t, it isn’t. I don’t, like I said, I don’t want to do us a disservice, but it’s not, it’s not rocket science. We. One of our USPs is the fact that we’ve just been doing this for a long time, so we know what to do and we know what not to do. And there’s a, there’s a lot to be said for understanding what data matters and how to apply things and what to measure and why to measure it and disregarding the rest because you can get yourself down sort of a lot of rabbit holes.
Lee:
That’s the rabbit hole I was worried about. You know, if I was going to log onto your online system, I feel like I would go down a rabbit hole. So. And you don’t know what you don’t know. So if I can then lean on you guys and say, all right, I don’t know what I’m looking at. There’s a lot of information here. I could go down multiple rabbit holes. Again, you guys have already kind of pre qualified with me, haven’t you? What it is I want to achieve, I want to understand, etc. So presumably data can be represented or I can talk with you folks and you can help me out as well.
Caroline McGuckian:
Yes. And everybody does it slightly differently and it depends where they are in their journey with Mesh. I mean, some of our clients are seven, eight years old. I say that we’ve had them for seven or eight years. Some of our clients we onboarded last week and some of our clients have sophisticated in house analytics and data teams who are ingesting our information and incorporating it into their business intelligence platforms. Some people just want a PDF with the numbers in it. Yeah, you know, everybody’s slightly.
Lee:
I’m that person. I’m the PDF person. Give me the really high level stuff because my brain won’t cope.
Caroline McGuckian:
Everybody’s at a different point in and has a different level of need and a different level of experience and a different level of value to measurement, you know, so each, each client is different.
Lee:
Awesome. You did mention during the magic talk about AI. Will, Will, do you have any predictions for the future of spatial analytics and AI or is it just all meh so.
Caroline McGuckian:
Okay. I mean, I don’t like predictions. Right. Because if I was any good at that, I wouldn’t be here.
Lee:
Okay, that’s true, that’s true.
Caroline McGuckian:
Somewhere with a pina colada.
Lee:
Yeah.
Caroline McGuckian:
I do think that AI has a role to play in, in all technology and in all businesses moving forward. We are, as I’m sure everyone else is starting to apply it in terms of our workflows and our processes. We are using it in a controlled and in a discreet way at the moment. We are also pouring quite a lot of money into R D to see if we should dial that up and what the implications are. So I feel like. I feel like there’s going to be a lot of words. There’s going to be a lot of people using a lot of words, you know, and I don’t think there’s going to be any clarity on it for a long time. So I worked out quite a while back that I can’t control what anybody else says or does. So all we can do at Mesh is control our own destiny. And our approach is going to be to use everything at our disposal to ensure we have the best product for our clients in a sensible way.
Lee:
That’s it. Best answer you could possibly have given. I’m so glad you said all of that because again, you are so right that people can say anything and people will use the word AI when it’s an algorithm and things like that. You know, it is currently a buzzword, so if you can use the word AI in your conversation, it’s going to make you sound great for whatever reason. Oh, our product’s great because we use AI. No, actually it’s just an algorithm and it’s actually the same algorithm we’ve used for X amount of years. But let’s throw the word AI in now because it sounds good, which is a bit pessimistic, I know, but it’s kind of how I feel about that, I find.
Caroline McGuckian:
I think. I think it’ll settle down. Yeah, you know, I. I do think it’ll settle down, but I think at the moment, you know, it’s the new Black, so that was a great series.
Lee:
Netflix, if you don’t know what we’re talking about. Orange is the New Black. Fantastic.
Caroline McGuckian:
Yes.
Lee:
All right, well, that’s it. We’ve learned absolutely tonnes what is the best way for people to connect with you. And then we shall say Goodbye, Carolina.
Caroline McGuckian:
Mesh.com. not hard to find.
Lee:
Nice. We’ll also throw your LinkedIn, I guess, and other socials into the show notes as well. Feel free to connect with Caroline because she’s clearly a legend and so is Mesh for their product that they’ve created. So if you’re not using Mesh and you want to know what’s going on at your event, conference, whatever you’ve got going on, party, etcetera, Then do connect with Caroline. Caroline, thank you so much for your time. Have a great day and let’s have you on again soon. Cheerio.
Caroline McGuckian:
Okay, bye.
