 Thank you again for having me everybody. I'm so so pleased to be here to be with everyone Today, I'm going to speak a little bit about data and innovation in the out-of-home space and I hope you enjoy what I've put together For those of you who don't know me. Hello. My name is Amanda Dornberg I am currently the president of comb, which is the Canadian out-of-home marketing and measurement Bureau Please feel free to follow me on the social channels to the left or the content channel sort of to the right of my screen I'm very active in this space actively contributing to various different media outlets Speaking about the importance of out-of-home the importance of innovation and data within out-of-home as well So I would love to connect with you all. Please feel free to reach out For those of you who are unfamiliar with comb comb is as I mentioned the Canadian out-of-home marketing and measurement Bureau, we are the National Association For the out-of-home industry and we provide both marketing as well as measurement services So what that means is we're sort of a hybrid Association that both provides the currency by which the industry transacts upon which would be your circulation essentially a representation of volume of of audience as Well as your impression, so the extrapolation of how many people out of that audience Garnard and impression and we'll talk about how we do that in a little bit And then we also provide marketing services to the industry So we're really an active voice within the within the landscape Not just on the Canadian side of things, but internationally multinational and globally as well Which is I'm grateful to be here to speak to you all today and really what our our focus is from a marketing perspective is to Showcase the value of out-of-home and its importance within the media mix. So we talk about media mix modeling. We talk about How we can incorporate out-of-home as a larger share of the total Advertising spend if you will So again, we're a very active part of the the ecosystem in the out-of-home landscape internationally So that's just a brief little bit about who comb is specifically what I want to talk to you guys today about is New methodologies and new measurements new initiatives that are happening globally But specifically I'm going to highlight some of the initiatives that we're taking on here in the Canadian landscape And we will look to provide these services on a multinational basis if organizations or other countries are interested in Sort of licensing some of the approaches that we have taken We are currently exploring how that could look as well We're fortunate to have a great deal of Interest and exposure on a multinational perspective And I think that is because we're a combination of both marketing and measurement So we have the ability to be able to really highlight In a very effective way what we're doing from a measurement perspective And so for Many years we've been working on a new Outdoor methodology as well as a place-based methodology at place-based being indoor I'm going to focus predominantly today on some of the key innovations relative to outdoor Some of the data sources that we're leveraging some of the techniques that we're we're using and how how we're really innovating and driving change To be more complimentary to other media formats not necessarily competitive to I always like to say that out-of-home is very complimentary to other media formats and we shouldn't be competing for Against the other Formats such as you know native online search social etc. We should be complimentary to that. There's a lot of Case studies and research out there that that really highlights very well The efficacy of out-of-home in combination with other media formats particularly in the digital space So today I'm going to speak a little bit about some of the sophisticated data science techniques that we have leveraged specifically to enhance the measurement offering of out-of-home Particularly in the Canadian landscape, but certainly there are other companies and organizations doing this on a global scale as well So one of the really interesting innovations that we have taken in the Canadian space is We've we've ingested what we're calling a national data set this national data sets Is inclusive of over six point seven million road segments and when I say a road segment It's a portion of road in between various different Exit and entry points if you will or various different intersections So it's not tied to an entry or exit point It's a it's an extrapolation of various different data sections within In between those so we have over six point seven million of these road segments. It's it's a lot Every single road across the country is mapped. So things like on ramps or off ramps of highways any type of side street back street, they're all mapped within our system and These road segments contain very powerful information On an hourly basis. So we ingest directional vehicular and pedestrian volume Within each of these road segments on an hourly basis. So we know on an average Tuesday at 2 p.m. Exactly how many cars or pedestrians are walking through each of these six point seven million road segments and Additionally, we ingest And and we're extrapolating out a modernized reach and frequency methodology so in most markets From a global landscape reach and frequency is an extra extrapolation of your your GRP gross rating point. So You know in traditional out-of-home planning GRPs have been used for decades however, that was typically done at the market level and What we have introduced is the ability to understand your reach and frequency Not just at the market level, but at the face level and then for digital at the spot or ad play level This is available in the Canadian space in the top 45 markets across the country In Canada, we have well over 150 different markets from an advertising perspective But the top 45 tend to be the ones where most of the national advertisers are looking to Just to spend if you will Additionally, we have introduced what we're calling audience profiling and this is an understanding of demographic lifestyle and psychographic components so we also offer this in the top 45 markets across the country and we have introduced this as a way to provide more contextualization to our To our audience to the to the buyers and to the sellers where you can dispel the Notion that perhaps a physical board or physical face, whether it be digital or static Located in a neighborhood that could be perceived as less than desirable Is actually garnering a very different audience than perhaps what is living around the board So traditional audience segmentation was about who's who lives within a certain radius around a Geographical location and what we're looking at and what we've introduced is an understanding of who's actually passing by the board Not who's living around it So we look at a great deal of mobile location data. We ingest The information directionally of Devices that are passing by each of these locations and then we're able to observe that to a home origin which is In our terms very simply defined as a device is persistently static location during sleeping hours over the course of our study period and That allows us to then take the long and lat of that home origin and put it through Like statistics Canada, which gives us the they have all sorts of survey data on on consumers It's the federal agency in the Canadian space that Has all of the the consumer information and the consumer surveys So that's how we're working with the audience profiling Additionally when it comes to pedestrian data in most markets, that was a relatively ad hoc request where you know Media owners might say hey, I've got you know a bunch of locations in In Montreal and it's a very pedestrian centric area. So could you go out and do a study? Now what we've introduced is with these 6.7 million road segments the the linear sidewalks that are running parallel to To the in town roadways. We do have pedestrian data for each of these segments And then we're introducing what we're calling spot modeling for pedestrian data In very pedestrian centric hubs, which would be like a young Dundas square, which is basically the Times Square of of Canada So that's another enhancement that we're looking that we've introduced and then when it comes to vehicular occupancy, which is essentially a representation of the number of the average number of people within a car and Historically that was done at the provincial level and we're now moving down to the market level And we're actually currently working on getting that down to the road segment level So really trying to ensure that we provide granular data when it comes to understanding and extrapolating the the potential audience that could be exposed We did a really cool study Last year and we looked at illumination hours So, you know an out-of-home not every board is is illuminated for 24 hours of the day Some of them are partially lit. Some of them are unlit and thus only can can be visible during Twilight hours or dawn to dusk if you will date daylight So we did a really interesting study last year a data science team looked at the geographical representation and disbursement of where each of the the Out-of-home billboards were were were located and Understood the average Twilight and and sunset hours so sunrise to sunset and what what the average amount of Daylight was based on if you were further north within the in the country or if you were a little more south within the country And that was an interesting project because we have this data on an hourly basis when I say this data I mean our circulations our impression data We were able to really enhance the illumination reporting to understand Exactly the peak outputs of circulation and impression by our if you will And so that was a really interesting project that our data science team Took on last year and then another enhancement that we've introduced And and this was this was a rationale to try to again be more complimentary to other media formats So particularly on the digital side of our reporting So when we're looking at our digital out-of-home reporting, which is obviously an impression reporting versus just a standard circulation Which is a representation of volume on the impression reporting With respect to how we calculate a GRP, which of course is the extrapolation of your reach and frequency Your unique versus your repeat audience if you will we've adopted the It's technically a broadcast term called spill, which is your out-of-market audience And so we will not only report the in-market audience of your specific target demographic However, we'll also be reporting the out-of-market audience which represents one percent or more of this specific target, which is a really interesting way to to Look at your national campaigns in the Canadian landscape We have about 85 percent of our buys are national advertisers And so we we really have to ensure that we're providing as much Value to these national advertisers as well as the local regional but because 85 percent is is coming from national We need to be highly complimentary to other media formats And so the ability to to report out this spill audience Allows us to be more complimentary when we're doing when when the buyers are doing sort of media mix modeling When we look at our digital Data sets since I'm on the topic of digital specifically We needed to really amp up how we were reporting and how we were calculating the impression outputs and so Historically in the marketplace there there was no delineation between static and digital it was just that there was one value that was being reported which was a circulation and Of course with digital we're sharing that share voice with multiple advertisers and Thus we really need to understand exactly how many potential impressions. We're being able to deliver As a medium in order again to be Complementary to other media formats. That's the planners and buyers whether they're 360 or omnichannel buyers are looking to incorporate so Some of the the additions that we've have Relative to a data set so all of the information that I sort of just spoke to previously Is available right across the board for static as well as digital inventory, but with digital we really needed to Enhance and add in a few more extra sprinkles of secret sauce I guess and so We have we ingest within those 6.7 million road segments We also particularly for digital ingest what we call intersection flow data and this is a representation and an understanding of what percentage of traffic turns left versus go straight versus turns right at an intersection and This is necessary for us to be able to understand The exact sort of volume of audience that's going by and then we also need to understand the speed of that Audience so again within that intersection flow data and within those road segments that hourly road segment data that I mentioned We have access to the average speed of The vehicles that are passing through these road segments and then we apply an average speed factor for Pedestrians we did some proprietary studies that look at various different geographical regions to understand how fast a person walks basically And so the intersection flow information as well as the speed Gets combined with what we call a distance visibility zone. So in some in some regions What we call DVZ could be Equated to an opportunity to see so an OTS However, we we parse that down a little bit further So we take our distance visibility zone, which is the maximum distance area That's an out-of-home asset could be visible from and that varies depending on the size of the board the placement the flagging the offset of where it is located in in In comparison to the type of roadway that it's on And we've applied distance factors. So for example, you know a large format board That's on the side of a highway is 457 meters or 1500 feet if you refer feet versus meters and That distance visibility area really helps us to assign the data So we look within that specific DVZ and our data science team applies each of the road segments that have the volume and have the speed data We look at the intersection flow information to understand. Okay within this distance visibility zone. We have you know 20% of cars moving left and and 30% going straight and then the other remaining percentage Veers off to the right and they can no longer see the board. Let's say We look at that on a face-by-face basis and and in in our market That's about 70,000 locations across the country to really Understand and extrapolate true analytics for each particular face This information helps us to understand a dwell time and in order for us to get to an impression that dwell time is really critical Additionally with the dwell time information. So we look at an understanding of how how many ad plays Are being played within a specific period of time. So in the Canadian market, we do have media owners that Are in a loop based environment, so perhaps they have a one-minute loop and they've got six ten seconds thoughts But we also have media owners that are loopless Completely loopless and we have a great deal of programmatic digital art of home here We were one of the markets that was a very early adopter for programmatic digital art of home. We started back in 2016 I remember doing programmatic integration So we were definitely one of the early adopters relative to programmatic digital And so we have to understand the average ad plays On a typical days we need to make a few assumptions within the math to really extrapolate an output of an impression So we look at whether the media owner is a loop based environment or whether they're loopless and we can understand the average Spot exposure. So for example, if you have a dwell time, that's 25 seconds You could potentially see on average 3.6 Ad plays because we don't know exactly when you enter into the first spot. So you might see three Or you could exit at the end of a spot and then enter in at the the beginning of a spot and maybe potentially see four So we've done an extensive amount of research on What this looks like to be able to understand based on various different spot lengths various different speeds various different geographical Locations of out of home assets what that ad exposure would be and then of course the dwell time comes from the The distance and speed information What's really interesting is I know this is a lot of like technical data, but everything in our platform is built api first and so This is one of the the great advancements I would say with technology and data As I said everything that we have is on an hourly basis. So there's about 4,000 different hourly data points that we've got living and breathing in our back and architecture That can be queried at any time via api So we can connect directly with our media owner systems. We can connect directly with our buy side systems All through api and they can get as granular as they want They could query, you know, just an average day information. They could query an average spot Information or they could query specifically that information on an hourly basis They could parse that up between I want to understand hourly data just from a vehicular perspective Or hourly data just from a pedestrian perspective It's really quite advanced What has been developed and and you know from an out-of-home perspective How we're able to to provide very similar analytics To other media formats such as, you know, digital native search online social, etc None of this would be possible without some of our key partners and I do like to highlight Who these partners are? So terror litics is a multinational Company they Provide to us the road segment data. So that's 6.7 million Figure that I've mentioned a few times They're our partner that we work with to To build that Helmerex is a canadian-based company. So they're they're one of our stk mobile location data providers They have a very robust understanding of of consumer movements. They own a number of very prominent Mobile location apps Such as the weather network, etc, which actively require location services to be enabled So they have they have a very strong presence here in the canadian space DOCMA is a multinational organization, although it is founded in canada They are a multinational organization that does reach and frequency modeling with us So we've we've partnered together to really build out one of the most advanced reach and frequency methodologies Within not just within canada, but but from what we're seeing on a global scale Manifold and vivid data are two partners of ours that We work with on the demographic lifestyle Psychographic and sort of behavioral components. So, you know, if if we're creating audience segmentations and audience targeting that Speaks to a specific demographic, whether it's male versus female or a specific behavioral component. So drinks coffee or Is an act lives an active lifestyle Those are the two companies that we work with that really provide some information on that And then we layer this all together internally with our data science team To really enhance and and elevate out-of-home measurements So we're trying to ensure that Again, everything that that is being put out from a data science perspective or from a measurement perspective is really complimentary it it's enticing but it also It can be competitive in the sense that, you know That the data that we're providing Is on par or better than some of the other data sources for other media formats And that's something that's been really important to us as we've worked through this evolution of out-of-home measurements None of this, excuse me, none of this would be possible without our product if you will so we embarked about two years ago on um, a new product development Process where we We we couldn't find anything in market That was a pre-existing tool that really catered to our needs and that really sort of stood out And could handle both what we called production as well as planning So we decided to build it ourselves and we built a tool called roadmap Which will launch in canada in september We're still sort of tweaking some of the features and functionalities But it's very robust. It's it's got a really sleek Uxc y component to it and what you're seeing sort of on the screen here Is is a visual of the production side of things when I speak about production and planning on the production side of things We really catered this to Inventory management, so it's really like media owner centric if you will everything a media owner would need to do from New builds so if if a media owner is looking to get an estimate on a potential new location You can log into roadmap. They can put in the coordinates and Roadmap will shoot back to them exactly what the Circulation or the volume is the impressions based on some assumptions of a loop structure or loop less structure All of that is built in systematically. So Literally log into a web-based interface. They can they can get these these estimates They can then turn that inventory from Just a simple estimate where you know, I was just querying potentially what this could look like To an active location that they can actually then start to garner additional information such as the reach and frequency And the audience segmentation side of things So this this tool manages all 70 000 locations Right in one centralized web-based hub. It's it's all permission. So each media owner only sees their assets But my comb team And my data science team sees everything There's triggers built within it that if a new location is being added You know my my team on the data science side of things get a get an email notification or a trigger within their inbox in roadmap And that identifies that they have something that they need to look at And then all of this flows right through into a really sleek um Planning side of things and the planning side is certainly geared more towards the the buyers Where the buyers can Leverage an interactive map that's got you know a left sidebar for filtering It's got a drawer that comes up that has a tabular form with your your data visualization component in a mapping side of things A right hand read bar. That's churning real time insight. So as you're filtering within the map itself The right hand read is updating your Based on on what is being displayed within the map and it's updating the audience segmentation It's updating the impression output again everything based on what's in the screen in the filter mapping environment And the buyers can then take that tool and or take the plan that they've created Let's say within roadmap and then reach out directly to the media owners to try and execute that plan So we really tried to ensure that we were Able to to not just house all of this data that that we have, you know, it's it's very robust Our back and architecture is built on a platform called snowflake, which is a database management And we can talk through if anybody has questions about the the tech stack or Is curious about roadmap itself Feel free to reach out because we're happy to do demos of the product on more private Stages, if you will not as public as this one But we'd be happy to to share insights We really wanted to ensure that we had a tool that was powerful enough to handle this data And again, because we couldn't find anything in the marketplace We we had to build it ourselves. And I have to say that I'm very pleased with what we have developed thus far All in all in summary, we have been very very busy working through Enhancing out-of-home measurements and it's something that we're very passionate about we speak openly on on global stages about how we're how we're doing certain things and we take ideas from other markets We take insights from other markets and try to really learn The best practices we learn various different unique approaches to whether it be outdoor or place-based And we're really trying to to Bring out-of-home and measurement and out-of-home to the forefront of the advertising industry overall So Anybody has any questions? I would love to hear from you and just Thank you so much for your time. This is sort of shameless self promotion because we are doing an out-of-home awards It's the first in canada On may 25th and there is an international award the submissions are closed But we did receive an overwhelming amount of international submissions and then submissions overall So very grateful for this and Thank you very much