Day 1 | Digging into the Data: the Impact of COVID-19 on Business Areas and Tourism
Day 1 | Digging into the Data: the Impact of COVID-19 on Business Areas and Tourism
Business Improvements Areas (BIA’s) play a central role to any community’s vitality. In this session, BIAs and their partners will have an opportunity to dive in and understand the impacts of the pandemic on their business areas and how visitation rates differ across the country, going back to 2019. BIA’s will be able to leverage this information to support the development of strategies to increase foot traffic and spending in their areas.
Note to readers: This video session was transcribed using auto-transcribing software. Manual editing was undertaken in an effort to improve readability and clarity. Questions or concerns with the transcription can be directed to firstname.lastname@example.org with “transcription” in the subject line.
Mary W. Rowe [00:00:05] So going into this session is now Stephanie McIsaac, who I see is there, hey, Steph. Who’s the senior VP and practice leader for Environics Analytics. She’s going to talk to you about the specific kind of data that Environics is collecting. A lot of their work is with us at CUI around Bring Back Main Streets and what the actual retail composition looks like and so she’s got some really good stuff. So hang on to your hat. All you data geeks, another 30 minutes of it, and then we’re on a break over to you, Stephanie.
Stephanie McIsaac [00:00:31] Thank you so much and hello, everyone. I’m just going to share my screen here and we can jump right into it. So here we go. OK, so it’s a very perfect segue way into this conversation, so I’m going to start with just giving you a little bit of an overview of who Environics Analytics is, and then we’ll dive into some really interesting findings.
Stephanie McIsaac [00:00:55] So to start it off and let me just minimize my screen, there we go. So who are we? Who is Environics Analytics? For those of you who maybe had not worked with us or heard of us. We were founded in 2003. We have clients across every sector. We work very closely with the CUI and I’m very excited to continue to do that, work with other tourism and BIA organizations. We are a team of geographers and mathematicians. We are a team of analysts. We often refer to ourselves as geeks, so please do not feel afraid to ask any very geeky questions. Those often get us the most excited. But at the highest level, what do we do? We provide data that speaks to or helps you speak to understanding the demographics, lifestyle types or behaviours of consumers or people who live within an area of interest. And we’re able to help understand who lives there, what they do, what they shop, how they shop, how they consume media, and we can do this at a postal code level across the country. We do work with clients in almost every sector and regardless of where they are in their analytical roadmap.
Stephanie McIsaac [00:02:03] We have over 30,000 key data points and I know that number is large. But what we do is we really help decision-makers use data to inform those decisions. We primarily focus on helping make decisions around real estate or marketing applications. So, for example, helping with placemaking activities, event marketing, and programming. We also help with retail site selection or doing some business analysis, which is something that we’re starting to do with BIAs so that they can get a sense of which type of tenants they should be marketing to. Everything that we do is privacy compliant. We do offer software as well. I’m not going to get into that today, but what’s really important is to understand that our data is built from the ground up. So we have this information at a very granular level down to the postal code, and we have partnerships that allow our clients to really action this in the media ecosystem, whether it be a traditional media application such as direct mail or in the digital space as well. And obviously, this has been something that’s been very helpful as our clients are recovering from this pandemic.
Stephanie McIsaac [00:03:12] We also have experience directly, hopefully, a lot of you are in the room as well. But we do work with a number of BIA’s, tourism organizations or travel sectors.
Stephanie McIsaac [00:03:24] So today I’m really going to be helping dove into the local visitor or domestic travellers. We know that for BIAs or tourism areas, there are three distinct groups of people that are of interest to them. They’re the local visitors, the people who live or work within the area, those people are likely that that foot traffic, the pedestrian traffic we’re interacting with, with businesses within BIA boundaries. There’s also infrequent domestic travel, which is a population sorry travellers, which is a population that is definitely of more interest nowadays with international travel still being restricted. So those are people who are travelling from further distances, either from within the same province or from other provinces within the country. And then lastly, the international tourism that would include people who are staying here for longer durations and overnight visits. Now we are also going to speak to you, or I’m also going to speak today, using Mobile Movement Data.
Stephanie McIsaac [00:04:21] Our mobile movement data we call MobileScapes is the product that we’ve built that leverages multiple sources of mobile data that is out there so that we could get a sample size that allows us to weigh the sample to the general population. And obviously, that’s a very important factor when we’re talking about not only volume metrics, but what we want to connect this data down to the who. Once we can understand who is visiting, where we can then start to understand why.
Stephanie McIsaac [00:04:52] So a little bit of the geekiness is going to come out here, but it is important that you understand a little bit more about what this data or how this data was created before I jump into the findings. So as I mentioned, MobileScapes is our permission-based mobile movement data product. It’s based on apps or SDKs. Where we’re capturing that geographic location of the device in order for us to infer where that device is likely to reside or to work. Once we can get that information we’re then able to weight it up to the general population 15+ within those areas to get that very robust sample that we can use in all of our studies. Once we get that, where the postal code of where that device is likely to work or reside, we’re then able to attach it to all of those other data products that I had mentioned that allow us to really understand the demographics, the expenditures or any other behaviours that we’re looking at analyzing. This information also allows us, which is something that has become very, very important through the pandemic recovery to monitor changes over time. So this data, we can get down to any timeframe of interest dating back to 2018 so we can look at month over month, year over year, day over day. This has been something that we really worked with a lot of BIAs to use so that they can understand, the impact of programs that they’ve created or completed within their BIA boundary and what those populations attending that event looks like compared to the other visitors that they’re observing.
Stephanie McIsaac [00:06:21] So let’s get into it. How is COVID-19 actually impacted by BIAs and surrounding areas and how does this differ regionally?
Stephanie McIsaac [00:06:28] Now I do need to stop for a moment and talk about that international visitor. So we know the international visitorship is down. Not surprising. In 2019, we can see that there were a total of 7.5 million trips made to Canada from international visitors, and this dropped significantly down to only 650,000 in 2021. So because of this reason for the study and really focusing only on domestic travellers, this will allow us to get into some of the detail.
Stephanie McIsaac [00:06:59] So what does this mean for BIAs on what you’re looking at? Here is a view from our footfall product, which uses that MobileScapes data, and it allows us to get a sense of who has walked through a BIA within Canada. So we have geofence, which is a fancy word for saying drawing a boundary around any BIA, every BIA Canada. And this here is aggregating accounts up at a Canadian level or national level. We can see that the trend from January 1st, 2019 to December 31st, 2020 is that the BIA traffic is down. At a high level, we see that it has improved in 2021, but I’m going to show you that that story is not consistent regionally or down at an individual BIA level. So overall, we can see the obvious decline in March 2020 when the pandemic came into play. And you can see that there were increases in decreases over time while restrictions were changing. In 2019, BIAs across Canada saw a total of five billion visits or 94 million in an average week. This dropped by 42 percent in 2020, down to 2.8 billion from five. In 2021 overall, BIAs did see an increase of 14 percent. So up to 3.2 from 2.8 the year prior. But there’s still an overall decrease of thirty-five percent compared to 2019.
Stephanie McIsaac [00:08:27] When we look at this from a provincial view, we see that the trend is similar in Alberta and Ontario. However, we do start to see some differences here.
Mary W. Rowe [00:08:35] Steph, can you just slow down a little bit, please? Everybody is mesmerized. They just need you to speak a little slower.
Stephanie McIsaac [00:08:41] Yes. Thank you for that reminder.
Mary W. Rowe [00:08:43] OK.
Stephanie McIsaac [00:08:45] So yes, we do see that the trend in Alberta and in Ontario is similar to national, but we start to see some differences here. And I am going to peel it back from here as well and go into a few individual BIAs. What’s interesting to us is that there is a similar trend. But the decreases are happening at different times. So not a surprise, I’m sure, to anybody on this call, the summer months see the largest traffic. Alberta does see a few other spikes, those stars that you’re seeing, and I’m not sure if you can see my mouse, but the stars here we’ve put at the second week of July, which is at the stampede. So Alberta BIAs do benefit from that intra- or interprovincial tourism.
Stephanie McIsaac [00:09:37] When we look at the actual numbers. We see that neither Alberta nor Ontario has returned to 2019, but both show an improvement in 2021 compared to 2020. So in 2020, Ontario BIAs experienced a forty-five percent decline from 2019. And in 2021, they are still seeing thirty-six percent fewer visits than in 2019. However, in 2021, they did see a lift from 1.4 billion to 1.6 billion. It’s a similar story in Alberta, where 2021 looks promising compared to 2020. But still a significant fewer, still significantly fewer visits compared to 2019.
Stephanie McIsaac [00:10:32] Now, using our MobileScapes because it is built at that granular level and we have those geofences created, we’re able to start looking at this in different aggregations. So what you’re looking at here are four specific BIA associations. One in Montreal, one in Hamilton, one in Ottawa and the Toronto Association of BIAs. And the story starts to get interesting. So of these four that we analyzed, we know that Toronto does a significant amount of volume compared to the others. In 2019, the Toronto Association of BIAs observed 1.7 million visits compared to Montreal, which observed 625,000 visits. That’s the next largest of these four. The volume shouldn’t skew the findings because it is interesting to see how each of them are starting to rebound. Hamilton Association of BIAs is showing signs of quickly revamping. Their visits dropped by forty-one percent in 2020. But last year, they only saw thirty-two percent fewer than 2019. The opposite side of this, however, is Ottawa, they’re not yet rebounding. The Ottawa Coalition of Business Improvement Areas, BIA, sorry observed forty-five percent fewer visits in both 2020 and 2019. They did not rebound last year compared to some of the others. The Toronto BIA Association saw forty-seven percent fewer visits in 2020, but only 40 percent visits, 40 percent fewer visits in 2021, so they are showing signs of improvement. We wanted to dive a little bit deeper to see if that story is the same at an individual BIA level.
Stephanie McIsaac [00:12:21] We selected four BIAs to focus on today, but we could do this any BIA or boundary across the country. Well, each of these four urban center BIAs experienced larger declines in 2020 than the national and provincial averages. We see that they haven’t all been impacted the same. The downtown Vancouver BIA and downtown Halifax BIA saw an increase in visitation in 2021 compared to 2020. However, the other two did not. Downtown Vancouver BIA saw fifty-nine million visits, which is $3 million more sorry, three million, not dollars, three million more in 2020, but that’s still thirty-one million fewer than they did in 2019. So they’re showing signs of improvement, but there’s still not a 2019 number, which I don’t think any of us are surprised. What is also interesting to us here is both the Toronto Financial District and the Ottawa Bank Street BIA in 2021 rates, we’re not only less than what they were in 2019 but also fewer than 2020. Of these four the Toronto Financial District has been impacted the most. Sixty-one percent less visits in 2020 compared to 2019 and 62 percent fewer in 2021. We wanted to dive into this to see if we could better understand why they’re still seeing a decline and what might be driving this.
Stephanie McIsaac [00:13:56] What you’re looking at now is a map of Toronto. The colours indicate how likely populations from those neighbourhoods are to be leaving their home. We know that BIA visitation is a result of the population’s ability to use the member businesses, whether it be for work or for pleasure. Our Out and About project, which is also created from that mobile movement data allow us to understand trip purposes. Why are people leaving their homes and how has this shifted over time? The darker, darker purple areas on this map are areas with higher rates of people leaving their homes from December 2019.
Stephanie McIsaac [00:14:38] This here is the same data for December of 2020, you were able to see a very dramatic difference when compared to the prior. And it allows you to understand which neighbourhoods are experiencing less what we say out and about, so people are leaving their houses at a lower rate than they were before.
Stephanie McIsaac [00:15:04] When we compared last December 2020 to the December of 2021, we do see that things are starting to improve. But we know the people are still working from home. So we wanted to get a sense of why people are now more likely to leave their homes than they were in December of 2020 but are not yet at the rate they were leaving in 2019.
Stephanie McIsaac [00:15:28] We can now bring in the who. So on this slide, what you’re looking at is our PRIZM Segmentation system, the PRIZM segments with the highest rates of leaving their home in December of 2021. For those of you who might not have used PRIZM before, PRIZM is the leading segmentation system that allows our clients to understand customers, population and markets. It classifies every postal code in Canada into one of 67 lifestyle types. Which are differentiated by socioeconomic status indicators, demographics and behaviours. The PRIZM icons on this slide already tell us a lot of information. The numbers speak to the socioeconomic status, with one being the most affluent Canadians. The colour of the icon speaks to the urbanity type, red being urban and yellow being suburban. For purposes of today’s presentation, we’ve created three simple groups: the wealthy mature family and empty nesters, downscale young urban singles and couples and midscale diverse large families. These three groups are showing differences in why they’re leaving their home for one another and from the Toronto average. The wealthy, mature family segment is more likely to be leaving their home for purposes of using green spaces or parks within the city, whereas the downscale youngster, young singles and couples are leaving for commercial or shopping purposes. We also know that a lot of them are likely working where they’re going.
Stephanie McIsaac [00:17:03] We can do the same analysis focusing on Ottawa, and we see a similar story. What you’re looking at here is pre-pandemic. What rates for people leaving their homes?
Stephanie McIsaac [00:17:14] The smaller scale, less dramatic change than what we observe in Toronto, but we do see a decline. 19 percent fewer people were leaving their home in Ottawa in December 2020, compared to twenty-five percent in Toronto.
Stephanie McIsaac [00:17:31] Similar story here as well, but the trip purpose is where it gets important. We saw a similar thing when we were looking at the Ottawa market, with upscale mature groups likely visiting their home now at higher rates for purposes of visiting a park or a green space. This is consistent with what we saw in Toronto.
Stephanie McIsaac [00:17:50] Another lens we can layer is the workplace population. So what you’re looking at here is a map in December 2019, where neighbourhoods were experiencing the highest rate of people at work. It’s the opposite of what we were just looking at, where people were leaving their homes. We’re now showing you where people are going to work. Many BIAs, including the Toronto BIA association, which experienced the greatest decline in traffic from what we looked at today, rely heavily on workplace populations. This allows you to evaluate not only the workplace presence within your BIA boundary but also the surrounding who might be using your services on a daily basis.
Stephanie McIsaac [00:18:35] When we compare December 2019 to Ottawa 2020. We do see differences in where people are going to work. 40 percent fewer people were seen working in Toronto in October 2020 than in December 2019. That’s a significant impact on what BIA’s might be expecting from a visitation perspective.
Stephanie McIsaac [00:18:58] We can then compare that to October of 2021. So although we have we’re observing that people, we’re back to leaving their homes at similar rates to 2019. We know that they’re not leaving their homes for purposes of going to work at this time. It’s going to be interesting to monitor this on an ongoing basis.
Stephanie McIsaac [00:19:18] So I know I went very quickly. I was very excited to show you some of the findings and wanted to make sure that we were able to make it through all of them. But what did we learn? So to start, we see that not all BIAs across Canada have experienced the same pattern of rebound. We know that all experienced a drop from 2019. Some are continuing to decrease in 2020, whereas others started to rebound. We also know that not all lifestyle types are leaving their homes at the same rate. Those who might have visited your BIA in the past for purposes of work may no longer be having to return to work. What does that mean? The people who are likely to be using your BIAs now may be similar people, but the reasons for their trips have likely changed. We also see that the workplace-bound travel has not yet returned to the 2019 value, which means the frequency of visits has likely decreased as well. So I know we’re going to have time for questions.
Stephanie McIsaac [00:20:22] And I do welcome them. I’m going to stop sharing my screen before I drop Tanishah Nathoo is also within the chat. She’s our BIA expert, so if there is any question that I’m unable to cover today, I will definitely be in touch and connect after.
Mary W. Rowe [00:20:40] Thanks, Stephanie. That’s great. It’s been great to have you here and great for us to have a chance to see it. Some of the questions that you’re getting, I mean, there’s a lot of data there and people want to put more into it. I should just say that Environics has been working with CUI on the rollout of my Main Street, which is this, which Mayor Sohi mentioned as well, which is a pilot in southern Ontario funded by the government of Canada to support Main Street recovery. Two sides of it, the Economic Developer Council of Ontario, doing, creating ambassadors for main streets and then us doing some community activation. And then this data that we’ve been collecting with you. So we’re learning a ton, right? And I think you’re asking, you’re getting asked a bunch of questions in the chat here about, for instance, if you were to, how far back does your data go? That’s one question people are asking, does it? How far actually back have you been tracking?
Stephanie McIsaac [00:21:27] We have the mobile movement data back to 2018.
Mary W. Rowe [00:21:30] OK. OK. And are there limitations from your point of view in terms of, are there things that it can’t tell us that we want? So for instance, could it be even scaled back to go even to smaller communities? Is it available? I don’t know to. You can see somebody asked a question here in the chat. Could it be available for a very small community? What do you think?
Stephanie McIsaac [00:21:51] Yes. Yes. I love the question of what can it not do? I am the same type of person when I ask questions. So it is available at a postal code level, which means that we’re able to draw a boundary around any area and pull the data at that postcode level.
Mary W. Rowe [00:22:08] Mm-Hmm.
Stephanie McIsaac [00:22:09] What it cannot do is it cannot speak to dwell time, so we aren’t able to let you know the average duration of a visit. And that’s just due to the data availability and the importance of being privacy compliant. But we are able to talk to how frequently people are visiting so we can determine. And we were starting to go down that path, who is visiting more frequently than in the past, who was visiting for three days in a year versus 10 days in a year?
Mary W. Rowe [00:22:39] Mm-Hmm.
Stephanie McIsaac [00:22:40] We are able to do that at a very granular level.
Mary W. Rowe [00:22:43] Mm hmm. And another question is, is the data only for Canadian cities, Stephanie? Or do we have it too? Can we compare it to American cities or other cities around the world?
Stephanie McIsaac [00:22:52] We can absolutely compare it to the States, the American cities. We do have similar data for the U.S.. We can also speak to where international visitors are coming from into Canada. And so I touched only briefly on overnight visitors or overnight trips, but we can also tell you the countries where those trips are originating from.
Mary W. Rowe [00:23:16] Mm hmm. I guess one of the challenges we’ve got is how do we know what factors have contributed to a change? Right? So for instance, as Mark’s asking in the question here, you know, is it bike lanes? Is it curbside patios? Is it fewer cars? You know what I mean? The thing that’s puzzling about this is that we’ve had great reductions in transit, so we know that people are having, as she was mentioned in the earlier session that in the case of some of the Canadian downtowns, you can walk there. So if you weren’t taking transit, you could still walk in. So is there any way to be able to for you folks in as you’re doing it to say, I mean, you saw other people in the chat saying, Oh, that was the Christmas holiday that with summer holidays, any other kinds of ways that you can spot certain contributors?
Stephanie McIsaac [00:24:01] Yes. So that’s why we place such emphasis on the who. Once you understand who is visiting, who is not visiting, who is visiting more frequently than others, we’re able to get a sense of their behaviours, of their opinions, of the softer attributes that we could then get a sense of, of what might be driving that change in behaviour.
Mary W. Rowe [00:24:22] And suppose they’re maybe, they’re walking less of a distance. So I might be leaving my home, but I’m actually not going as far, right? So in the before time, I might have elected to get in my car and go into a whole different shopping district. But in the now time, I don’t get in my car, I actually get out and I walk. So are there are ways for us to track that to see the trip length, the shorter?
Stephanie McIsaac [00:24:44] Yes, of course. Of course. Yes, we’re able to track the distance between who is coming. And if you can think back in my presentation when I was showing the dots going to the financial district, we’re doing exactly that, remembering the distance of where a person originated from versus where they were going to observe.
Mary W. Rowe [00:25:02] Mm hmm. Mm hmm. I’m noticing that one of our listeners who’s coming in from overseas is saying that in Rio de Janeiro, they’re actually looking at energy consumption. And I know there are other clues that we can derive to tell whether people are home more. So for instance, interested to see whether our utility bills are higher. I’m assuming they are, right? They must be because we’re home more. But I don’t know whether or not that’s been offset by the fact that we’re not using the same utilities in the office we used to go to. Anyway, I’m wondering if you have an opportunity to talk to us. I mean, you did warn us data geeks and I did warn them, and you’ve lived up to that billing just saying, but are there other kinds of overlays? Sorry, I just hit my mic. There may be other kinds of overlays that people might be interested in seeing, you know, energy. What are the impacts in terms of what we heard anecdotally, there was an air quality improvement, for instance, when we weren’t going so many places, right? Have you looked at that about what are, do you have questions that you’d love to be asking and getting answers to?
Stephanie McIsaac [00:26:00] Yeah. So we don’t have data on those metrics. But the who in those more subjective pieces are where we find it very interesting when we’re able to layer in when other organizations have those factors and we can get a sense of pairing that data. When do, we have data that tell us a lifestyle type propensity to be interested in moving to an electric vehicle?
Mary W. Rowe [00:26:25] Right.
Stephanie McIsaac [00:26:25] If we pair that with what we know about some of their shopping behaviours or their consumption behaviours, you’re able to get a sense of prioritizing what’s important to the people who you’re you’re seeing more frequently.
Mary W. Rowe [00:26:37] Mm hmm. Again, because we’d like to be able to determine. So it could be I mean, I saw the categories you had, but there are all sorts of other ways to bisect it. So is it not just by age? Could it also be by gender? Is it also by race? Do you have it by race? Do you have it by different kinds of because we know that people’s comfort levels of being actually outside of their own space vary considerably, and that’s part of what we’ll be talking about over the next couple of days is public safety, community safety and who feels safe going out at the moment? So I’m wondering if can you get it at that level again? I hear, I think what I hear you saying is you’re receptive to other data sets. So if there are other folks here that have access to data sets and ideas for you and I appreciate that your colleague Tanishah is on here, maybe they can start to think about mashups, isn’t it called mashups? I think it’s called mashups when you combine different sets, right?
Stephanie McIsaac [00:27:26] Yes. Yes. We do also have in our demographic data, we do have all of those demographic indicators down to that same postal code level. So if there was a certain group of the population that you were looking at and identifying and then better understanding that subsets behaviour, that’s something that we do often and we can absolutely help with. Because we have everything down to that postal code level were then able to infer that the people within that postal code and attach to it all the other behaviours that we understand.
Mary W. Rowe [00:27:59] Mm hmm. And again, at the BIA level, I mean, Lorne Cutler’s point in the chat that, you know, not all BIAs are the same, you know. And so and that’s true because they, you know, we’ve got ones that are their area is predominantly commercial office. And then we’ve got others that are more suburban and they’re more distributed and they don’t have offices. So it’s all quite different. But I think this is part of the tool for us to be able to identify and then be able to extract as best we can what our actual understanding is. What do you think is the next step for you in terms of continuing to do this work? Do you want to do more? Would you like to collect more local data and have more opportunities to be able to learn from the local experience and then continue to? And I think part of what we’re going to try to make the case of, and I see someone has suggested here it might be. Marc has suggested here that this is part of our case to the federal government, saying that they need to invest specifically in downtowns and main streets in a particular kind of way because the data is showing us how people are behaving in these local communities.
Stephanie McIsaac [00:28:57] I think that’s exactly our next step is we’re really trying to help use data to make decisions, looking at volume metrics or focusing on the big cities, as we’ve often done in the past. We’re seeing that there are so many differences down to that nuanced level that we want to make sure that decisions are being made based on the data so that the results can be as impactful as possible.
Mary W. Rowe [00:29:22] Yeah. So people need to hear this. We need all hands on deck thinking about this because to make public policy work at that granular level, it’s really tough. If you’re saying postal code, census tract postal code, that’s a very specific area. So what’s going to work in Yale town is different than what will work. Yeah. So I appreciate that and I appreciate you taking time, Stephanie, to give us a sense of this. As everybody knows, we’re going to post all this online. You’ll be able to learn tons more about this, and it’s only the beginning. This is an ongoing data collection that we’re doing, and we appreciate Stephanie coming on and all your folks at Environics Analytics. Thanks for joining us. Good news, guys. Fifteen-minute break. Listen to that playlist! Come on back. We’re going to talk about housing and bringing people back and what is it going to take housing? It’s going to take housing, transit, a bunch of other things. Housing is the first really good session, Frances Bula from the Globe hosting and then a number of different perspectives from across the country in different ways of looking at this about how does housing bring back downtown? See you in 15 minutes. Listen to some music in the meantime.
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From Canadian Urban Institute: You can find transcripts and recordings of today’s and all our webinars at https://canurb.org/citytalk
Canadian Urban Institute: COMING UP: Digging Into the Date: The Impact of COVID-19 on Business and Tourism (1:15pm – 1:45pm ET) with Stephanie McIsaac, Senior Vice President and Practice Leader from Environics Analytics
02:10:10 Canadian Urban Institute: Stephanie McIsaac is the Senior Vice President and Practice Leader of the Retail, Real Estate, Travel and Gaming sector at Environics Analytics. She brings more than 10 years of experience in research, analytics and geodemography to help clients strategy in the use of data to solve their business challenges. Stephanie specializes in customer segmentation, retail network and asset evaluation, to evaluate untapped potential for growth in real estate and e-commerce. Previously, she was a founding member of Environics Analytics’ Project Management Office in the Analytics Program and a Director of Insights. Prior to joining EA, Stephanie held positions at the Southlake Regional Health Centre Foundation, Canada’s Wonderland and Women of Influence.
02:10:24 paul mackinnon: Thanks Ryan. We need a few developers to convert successfully, and once they do, others will give it a go. We have 2 med size conversions in DT Halifax right now and we hope to see some more.
02:11:28 Wesley Reibeling: Mary Rowe – Just want to thank you for doing such a phenomenal job of moderating today.
02:11:55 Rylan Graham: Yes – it’s started to pick up in Calgary over recent years (30% office vacancy does that…). Here’s a project currently underway from office to affordable housing: https://www.cbc.ca/news/canada/calgary/calgary-sierra-place-conversion-construction-1.6067789
02:14:00 Mary W Rowe, she/her, Canada’s Urban Institute/IUC: Thanks @wesley – stay with us for the two days!
02:15:08 Dinesh Burad: In continuation to Rylan Grahams comment, In Edmonton the city in converting two hotes into affordable housing : https://www.cbc.ca/news/canada/edmonton/edmonton-sands-hotel-housing-homeless-1.6279386
02:17:58 paul mackinnon: ALL BIAs? Wow – great data.
02:18:12 Mark van Elsberg: What generated the relative drop even before the pandemic? (global restrictions which started earlier?
02:19:11 Cathy Quinton: drop before pandemic: increase in online shopping?
02:20:00 Jeff Hrynkiw: I’m so happy to see some data from the west!
02:20:10 Mark van Elsberg: it would have been useful to see 2018 to see previous patterns
02:20:25 paul mackinnon: Do you have data for local ped traffic?
02:22:28 Samuel Lau: The data is available for over 200K+ geofences across Canada!
02:22:40 Shiv Ruparell: This is excellent data
02:22:55 Samuel Lau: @Paul, so yes it has the ability to capture ped traffic, depending on location
02:23:17 Samuel Lau: @Mark, the data is available from Jan 1 2019
02:23:40 Samuel Lau: so there is an ability to compare pre vs post pandemic for example
02:24:31 Mark van Elsberg: It would also be interesting to see how the govt responses have impacted these results..and the hospital loads
02:24:34 Alison Theodore: 2019 an important benchmark as it was the best year for Canadian tourism on record
02:25:59 Samuel Lau: that’s a great point Mark! the data is updated weekly, so we can observe the changes closely
02:27:02 Mark van Elsberg: These maps showing mobility also highlight what areas are walkable ..or what areas have essential workers who have to go to work
02:27:54 Lorne Cutler: A key difference between the Ottawa and Toronto map is that most of the Ottawa map is rural.
02:30:32 Tanishah Nathoo: Hi Everyone! Please reach out if needed!
02:30:41 Graham Singh: Great job!
02:30:51 Cherie Klassen: This is great data! Is it available?
02:30:55 Mark van Elsberg: It would be interesting to highlight main streets (managed mostly by BIA’s) and the likelihood of people leaving their homes to go to these main streets, which likely draw more people than the parks with even minor reductions of lockdown. And on street cafes!
02:30:56 Michelle Groulx: Great presentation!
02:30:57 Washington Fajardo: Great data!
02:30:58 Leslie Fink: Would love to see that deck again 🙂
02:31:09 Michelle Groulx: Will the deck be available?
02:31:26 Angela Macdonald: Excellent information- would love to see it again
02:31:30 steve gillespie: could the data be scaled for smaller markets
02:31:49 Sue Uteck: I would love a funding program that could help bids access this data. It is out of reach for most of us.
02:32:05 Amelia Bauer-Kong: Is that 3 or 6 digit postal code?
02:32:18 Tanishah Nathoo: 6 digit
02:32:20 Leslie Fink: Do you only have Canadian Data? Would love to see Toronto data vs. other major Cities
02:32:38 Lauren Goethel: Will the deck be available?
02:32:54 Judith Cox: Can you send us data if we send our postal code?
02:32:57 Leslie Fink: Great – thank you!
02:32:58 Mark van Elsberg: Can the data measure the impact of new bike lanes, curbside patios, and reductions of space for cars?
02:33:19 Canadian Urban Institute: The presentation will be posted, along with the recording after the summit.
02:33:46 Judith Cox: Staycations!!
02:34:10 Washington Fajardo: We’ve been using energy consumption data for Rio de Janeiro’s downtown as a way of visualizing temporary and continuous vacancies.
02:34:25 Dana Duncanson: Are you able to track how much of the residential population within a BIA are people working from home? This would reflect the working population during COVID times.
02:35:13 Mark van Elsberg: If we can see how much impact investing in our Main streets can make our cities more resilient , desirable and economically competitive? These areas are more socially equitable, easily updated for safety and accessibility
02:36:14 Catherine McKenney: Does the origin-destination data provide insight into how people are travelling to BIAs? Walking? Transit? Cycling? Vehicles?
02:36:24 Mark van Elsberg: Living close to main streets and in the core requires less living space, is more efficient and more equitable. This Data can build a case to BUILD BACK FAR BETTER
02:37:03 Lorne Cutler: Hard to compare BIAs between cities without understanding nature of the BIA. Toronto financial difference has lot of hotels and quality shopping. Tourists to Ottawa are much more likely to shop in the Byward Market and Rideau Centre than Bank Street. Thus while a jump in tourism in Toronto might benefit the financial district, Bank Street in Ottawa is far less likely to benefit. Halifax may have done well because it never went into the same level of lockdown and became a tourist destination.
02:38:04 Stephanie Beausoleil: That’s great @StephanieMcIsaac
02:38:25 Mark van Elsberg: Careful.. Toronto is losing more hotels to redevelopment without any consideration on how this will impact our tourism and international business
02:38:29 Canadian Urban Institute: After this session, we will be taking a short break. We will return at 2:00 p.m. ET with Bringing People Back: Housing (2:00pm – 2:45pm ET) with Frances Bula, Urban Affairs, the Globe and Mail; Bob Dugan, Chief Economist, CMHC
Michael Brooks, CEO, RealPAC; Tim Richter, CEO, Canadian Alliance to End Homelessness, Calgary; and Steven Paynter, Regional Design Resilience Leader, Principal, Gensler, Toronto
02:39:21 Tanishah Nathoo: Feel free to reach out if there are any additional questions about your local area.
Tanishah.Nathoo@EnvironicsAnalytics.com or Stephanie.McIsaac@EnvironicsAnalytics.com
02:39:45 Washington Fajardo: Fantastic!
02:40:09 Mary Chevreau: Thanks everyone!
02:40:24 Kay Matthews: See you all after the OBIAA weekly Best Practice Call with BIAs across Ontario.
02:42:35 Canadian Urban Institute: This Summit would have not been possible without the incredible support of our partners and sponsors. Please visit www.canurb.org/citysummit for the full list of sponsors.
02:46:49 Canadian Urban Institute: We will return at 2:00 p.m. ET with Bringing People Back: Housing (2:00pm – 2:45pm ET) with Bob Dugan, Chief Economist, CMHC,
Frances Bula, Urban Affairs, the Globe and Mail, Vancouver, Michael Brooks, CEO, RealPAC
Tim Richter, CEO, Canadian Alliance to End Homelessness, Calgary, Steve Teekens, Executive Director, Na-Me-Res (Native Men’s Residence) and Steven Paynter, Regional Design Resilience Leader, Principal, Gensler, Toronto
02:49:35 Ushnish Sengupta: Can I be a contrarian to the “must” invest in downtown orthodoxy? With limited budgets, should cities not distribute more equitable its investments, (Neighbourhood Improvement Areas like Toronto). Otherwise its a story of over serviced areas getting more investment funding.
02:53:35 Graham Singh: CUI playlist = epic
02:54:20 Erin Benjamin: The Canadian Live Music Association (CLMA) approves of this AWESOME playlist! More music, less COVID!
02:54:59 David Pensato: @Ushnish: That’s a very good question and a little bit context dependent, but in general, public investments into downtowns and main streets have much higher returns on investment for every level of government. They produce greater GDP per dollar spend and greater property taxes (the latter by far). How each of those levels of government then reinvests in community priorities is where the equity side of things kicks in.
02:55:00 Wesley Reibeling: I have to agree with the above comments. This Canadiana Urbanist Playlist needs up on Spotify.
02:55:18 Clint Wensley: No kidding. The music is rocking
02:55:32 Andrew Peck: Seriously, amazing, thank you for that!