How Wilmington, N.C., Used Lyft Ride-Share to Navigate a Bomb Cyclone

Inclement weather exposes our transportation options—and where we most need to go. In the case of Wilmington, NC, as winter storm Gianna hit, data showed residents used the Lyft ride-share app to meet some of their most critical emergency needs.

In this episode, Shoresides talks with Sarah Conlisk of Lyft about the data and how snow in the Carolinas brought first-time riders, trips to grocery stores and healthcare destinations and higher driver tips, along with other moments of community connectivity.

Learn about this work and about the Coastal Journalism Hub at http://www.coastaljournalism.org

Transcript

SPEAKER_01 0:17

Yeah, totally. Um, so my name is Sarah Conelisk. Um I do data storytelling for Lyft, uh, the rideshare company. Um basically I have access to the millions of uh anonymized ride level data. Um I aggregate it in different ways to find trends um and tell stories about you know transportation um in North America. Yeah, um so my background's in economics. I was working at the Federal Reserve Board before. Um, but it whatever and I like I love economic research. Um yeah, I love I love that sort of analysis. Um, but I was doing a lot of stuff on like tipping and I was um trying to get data on tipping. Um, but uh what every economist needs is like good data. Um and you know, data's the best when it's like geographically dispersed and like there's a lot of it like over time because then you can do all these like microanalysis. Um and so lift, you know, rideshare has like great data. So I pivoted from more like the academic and like the federal route into um the industry level stuff because I just you know I wanted access to this data to be able to answer all these questions. Uh so yeah, that's how that's how I got here. And it's it's cool, you know. I can I can tell these stories and instead of the more formal academic paper, they come out more like journalism. Um, and there's like a sometimes a tighter relationship to journalists um who can you can talk about them. Yeah, so there's all these tables. Um there's like a ride level table, which has every single ride, there's a driver level table, which is every single driver, there's a rider one, there's like a region one, so there's a bunch of different like sources of information. Um, and I write code uh querying um in like an SQL. And so I kind of like combine these data sources and aggregate them in different ways with code to like ask questions. Um, and then I visualize them with some other like coding software. So um in New England, or also, I mean across the across the US, but there's this Storm Fern, um, and also this storm called Storm Hernando, um, which were were really big this this January. Um, and like uh a lot of Americans were like not prepared for this much snow and precipitation. Um for many like cities, it was like the high the most snow they've seen in in decades. Um and it created like a lot of um, you know, people were like looking, like, how do I get, you know, how do I get around? How do I um without like there could a lot of people's cars were not prepared um for this level of snow. Uh we looked at like Google searches and we found that snow tires were the highest they've been in five years. Um and the search for like driving in snow hit twice twice its usual winter peak. Um, you know, snow has kind of been on the decline in a lot of cities and regions of the US um more recently. So it was like a big, a big um big wham to most people when it when it came so so strong this winter. Um and many weren't like yeah, many weren't prepared uh for driving it, driving it, especially because you know you have to outfit your car with all the like the four-wheel drive or the snow tires, and um a lot of people didn't find it worth it uh if you just know it's like once or twice uh in a given year. So we saw this kind of show up in the rideshare data. Um on January 26th, which is like the first work day after Storm Fern hit, which is you know the day people would have to start going back to work. We saw that the share of new of ride requests by new riders in like the heavily impacted regions in the US was up 30%. So that suggests that people, you know, they were going out to go to their car and they're like, I can't drive this thing, but I need to get to work. So they called a lift for sometimes the first time. Um and that was like particularly true in places that don't normally perceive or don't normally receive heavy snow, um like Little Rock, Little Rock, Arkansas, and Memphis, Tennessee. Um in both those places, the the share of new riders over like the typical level um was three times uh its typical level um on January 25th. And we also found, yeah, um, yeah, and we also found that um the right like the the distribution of where riders went to go was also a bit different. Um there was more activity going to like the the crucial or the the high stakes trips. Um so in like so healthcare destinations uh were 16% above average. Um and especially in like places that were hit by more snow, like Western Massachusetts, which received, I think, um like 21 inches of snow. There were like 31% more trips to healthcare destinations. Um, so that shows you know, people when they they had these like really important um appointments, they also are are more likely to take ride share uh during the snow. Um, it's funny, like a lot of my job ends is also talking to drivers. So you have this like macro level, like looking at the data and finding patterns, and then a much more like on the ground approach as well. Um, and so I was in con in contact with this driver, and we were, you know, we were just chatting and and she was talking about driving during the storm, and she was saying that her Subaru Outback was able to get someone who had it had like had the can't had um like five or six drivers cancel on them before uh because of the storm. So that just like made me think like I wonder which cars are which vehicles are being are being driven more during the storm. You know, those point to these vehicles that are like super um, you know, like well uh they just can handle it. Um so I looked at which rides, which or which yeah, which vehicles uh were like most over-indexed on rides or were most utilized during the during storm fern. Um and you find kind of like the typical things you would what you would you would expect. Um a lot of drivers with trucks and SUVs uh were out on the out on the roads during the storm. The Ram 1500 was the most utilized vehicle. It was like over 1.5 um times or 50% more utilized than average. Same with the Ford Expedition, the Chevrolet Tahoe, the Lincoln Navigator. So you get these like big trucks and SUVs on the streets. Um, which is you know, it's kind of cool. It points to like the value of rideshare and having this diverse fleet of vehicles that the you know the everyday person needs to transport around their city has access to. And you know, a lot of those cars might be more expensive, but they take up a lot of room, their gas mileage is bad, and you don't need them on a normal day-to-day basis, but in times of emergency, um, you do. Uh, and it's it's a cool point. Yeah, totally. So in Wilmington, it looked like the biggest storm was on or the biggest, you know, winter activity storm was Storm Gianni. So that was like on January 31st to like February 2nd, about. Um, does that track with your experience? Yeah, in January. Yeah, totally. So I I looked around that time with these same sort of statistics. Um, and so on February 1st, uh, it looked like new riders in in Wilmington uh increased by 40% and then and and 34% on February 2nd. So you do see that like big increase um those two days uh kind of following like the big impact of the storm. Um that like that trend was even more drastic in other areas of the state. Uh I think it was almost like an 80% um in some other areas of the state, um which was pretty cool. And then like a similar, we saw something uh with healthcare destinations. So in North Carolina, the whole state, the destinations or trips to healthcare destinations were 17% above average um during the period of January 31st through February 2nd. Um, again, indicating that riders were only leaving their homes for the most high-stakes trips. Um, and then another popular destination that I saw was grocery stores. So in Bloomington, North Carolina, rides to the grocery store were up 35% on January, like on that January 31st to February 2nd time period. And then 23% statewide in in all of North Carolina, uh, which is like another one, you know, food is food is essential. Um, and of course, people need to go need to go out to get to get that as well. Not so much. Um, that is like something we don't really collect demographic data. Um, we have a couple products that can like filter it out. Um, so like sometimes we can look at like older riders, but I I didn't look into that here. Um, if you want, I can I can follow up and see if that seems to like overindex, but um, I don't have numbers for that right now. Yeah, I wanted to do that uh same analysis, but my my um access to that database, you know, like that expires every year and then you have to like redo it. So we were we were in that expiration period. Um, but I did I did find a cool stat about tips. Um I found that like tips for drivers were nearly 30% higher during the winter storm in in North Carolina overall, um, which is a cool one. And that was particularly true in Charlotte and Greensboro, actually. Tips were 70, almost 70% higher during the storm. Um, so that like that does point to uh you know the riders' gratitude. Um but yeah, I'm also I'm curious why do mo why do a lot of people not have um cars in Wilmington? Hmm, let's see, not particularly on the storm there. Let me see. The the trips were a little longer, that was interesting. Um, you know, maybe people, I don't know, like there's uh I don't know if there was maybe people had to reroute, you know, even if you have the same destinations, sometimes like certain roads are too icy to go on. Um, so roads might be routes might be longer. Um, or people, you know, they called a they called a ride chair for or something that they like they maybe took a short trip because they were comfortable driving that, but anything longer than that they wanted to do ride chair for. Um yeah, but no, there's a yeah, you go. Um it was definitely it was the highest for grocery. Um, that was like the yeah, notably there. Um, and also one of the highest for going to work, actually. A lot of it looked like a lot of North Glenn of the the share going to work actually somewhat under indexed during the storm from almost all states there or almost all cities there. Um I'm guessing people, you know, just called us a snow day and didn't go in. But Wilmington was the one of the closest to like normal levels. Uh it was at 95% normal level of um share of rides to work. Um and yeah, I'm also let me quickly see the the biggest day. Um yeah, well, yeah, you put you pull it and then you create a couple charts that you think like have like the main stats in there, and then if you need something else, you need to pull it again. Um, but yeah, you know, your little system. Um let's see. The biggest day was on on because it is sort of like when do people come back, you know, is interesting. They start, you know, going start crazy. Um yeah, it looks like February January, February 2nd, people start to come back. Um yeah, a little bit. Um, yeah. Or cut start to yeah, head on back.

SPEAKER_00 17:33

How big is Woman? Yeah.

SPEAKER_02 19:04

Cool.

SPEAKER_00 19:13

Yeah. Yeah.

SPEAKER_01 19:20

No, we don't get free ride share, alas. Um, but I do in in New York we get we get uh free city bike, um, which is the bike share program. So um I do I do a lot of city bike, and honestly, city bike it's faster often than taking a car when you're in New York because the the roads are so trafficy. So I do I vouch for that, you know, and then you're you get some outside time, you get some exercise. Um so yeah, that's the I touch that. Yeah. So just like a couple of like charts and maybe some notes is helpful. Yeah. And I wonder maybe we can get you in touch with a Lyft driver from Wilmington. Um, I don't know if you know any, but that's always at a fun angle. Yeah. Yeah, we have this fun this favorite feature where drive riders can favorite their lift driver. And so a fun one is always to do like the most favorited lift driver in a time, you know, it's always good.

SPEAKER_00 21:58

Yeah, yeah. Yeah.