Belong

Many of us don’t think of data when we think about cultivating belonging. In this conversation with Kim Larson from Luminoso we dig into how data, text analytics, and surveys can transform our community engagement. Kim and I dig into the insights we’ve gained from surveying our communities and we discuss how to balance AI and the human connection.

Links

Chapters
  • (00:00) - 2024-10-07-Interview with Kim Larson
  • (00:41) - Introduction and Background
  • (01:45) - Educational Journey and Community Involvement
  • (03:09) - Neighborhood Survey Initiative
  • (06:48) - Survey Design and Implementation
  • (11:36) - Analyzing Survey Results
  • (16:12) - Community Connection and Challenges
  • (18:30) - Livability and Change Management
  • (25:26) - Connection and Community Building
  • (29:10) - Transportation and Infrastructure Needs
  • (36:53) - Reflections on Survey Design and Impact
  • (40:00) - Balancing AI and Human Connection
  • (43:46) - Final Thoughts and Advice

Credits
Music by Denys Kyshchuk from Pixabay.

Creators & Guests

Host
Kevin Micalizzi (he/him)
Community Builder, Storyteller, Marketer
Guest
Kim Larson (she/her)
Opinionated Survey Geek

What is Belong?

The power of belonging in business, community, and life.

[00:00:00]

Introduction and Background
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Kevin Micalizzi: I'm super excited to be chatting with you because you and I have worked closely together on a survey for my neighborhood. I know you do a lot for your neighborhood and just so excited to have you on the show. One of the things I think people listening won't know is [00:01:00] that you've got a Bachelor's in Economics and a Master's in Data Science.

Kim Larson: Almost. Just started the data science

Kevin Micalizzi: got it.

Kim Larson: Learning as we go.

Kevin Micalizzi: Got it. So working towards your Master's in Data Science, but still a very different background than you'd expect for someone who works with communities.

Kim Larson: That's so, that is disappointing because you would hope that folks working with communities would have an understanding of like the incentives and the economics and like be data driven. But that's part of why I pursued it. I think I started community first and then wanted to assess how to do it well, which is how I ended up with the econ and data science background.

Educational Journey and Community Involvement
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Kevin Micalizzi: What did that journey look like?

Kim Larson: Initially when I was in high school, I did a lot of volunteering. So that was back during the Invisible Children and Darfur Genocide era. And so I had a [00:02:00] really strong passion around, like, just wanting to make things better.

Better.

Kevin Micalizzi: Right.

Kim Larson: So initially I started off studying nonprofit business. And then the more I learned about the challenges nonprofits face, the more I was like, no, it's just, there's systemic issues that need to be addressed. And let's understand those better. Let's be good at that. So In my econ background, I got a science degree in economics and arts degree in international studies and minors in math and business and part of a developmental economic focus included studying abroad. So I lived in Uganda for a while and studied the effects of pollution on development in Kampala. And then I came back and finished my degree, uh, ended up going into the experience management space. So working with hospitality surveys and employee surveys, which is still using data to make people's lives better. Like if you've ever had a miserable boss. You recognize how important it is

Kevin Micalizzi: Where you [00:03:00] rage type as you respond to the, uh, survey.

Kim Larson: Per my last email. Yeah. Uh, cause those frictions add up to quality of life over time.

Neighborhood Survey Initiative
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Kim Larson: And so kind of building my, my credentials there, I moved into focusing just on text analytics where I'm currently at, at Luminoso, uh, and that kind of snowballed into, uh, showing up at the neighborhood association meeting on election night. And they were like, who's going to run for the board? I'm like, I guess I'm qualified to do that. Um, so I accidentally joined the neighborhood association board. Uh, and the question kind of came up with like, how do we decide what we prioritize as a neighborhood association? And the feedback was a general. Well, people tell us and then we do that and being more of a introverted by default person like I didn't intend to run for the [00:04:00] board. I just kind of fell into it. Um, I recognize that there's probably a large portion of our neighborhood that isn't going to show up that isn't going to speak up, but their experiences are still very important.

At least to me. So that's how we started the Neighborhood Survey. Initially, we didn't expect it to become as popular as it was. Like, we got 800 respondents turning in surveys. Um, the survey was open from November through April ish. Uh, and It turns out when you have that much data with the kind of surveys and stories that we collected, it, it ends up being a bigger deal than we initially anticipated, which I think is probably what got your attention, um, for our neighborhood was, oops, we, we figured out a thing.

Kevin Micalizzi: Well, I mean, we had done, um, a, my, uh, [00:05:00] Arbor Lodge Neighborhood Association, uh, board journey went the exact same way yours did. Uh, I was at the meeting on election night and, uh, uh, one of my neighbors nominated me and I was like. Okay. Yeah, I'll do it. Uh, so I do primarily communications for them, but I was finding the same problem.

Like how do you know, you know, I mean the, the, the few folks that are incredibly vocal are usually on some extreme and you know, they don't necessarily represent everyone in the neighborhood, but how do you figure out, you know, what that is? So the first year I, you know, threw together a, uh, uh, Google, Google form.

We got like a hundred and. I think like 110 people to respond, and I was super excited because, you know, I think the themes I saw were similar to what I expected. But then when you and I started working together, there were, there were just a whole series of questions. Um, I know in terms [00:06:00] of my survey, I was going for quantitative because I, you know, I was Any open ended question I asked, I was the one reading through everyone and trying to figure out, okay, how do I categorize this?

Like, and, and, you know, I mean, literally spent hours trying to crunch those numbers and get a better picture to present back to the neighborhood and to the board. Whereas, you know, bringing in a technology like yours was like, oh, okay, let's ask as many open ended questions as we can. I mean, if, if people are willing to share I would much rather capture their stories, and I've heard you use the term storyful a lot.

Is it, is that, is that kind of central to your thinking when it comes to, uh, especially to surveying?

Survey Design and Implementation
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Kim Larson: Yeah, so first I want to validate your approach prior because the first week of grad school, the professors like when you're designing a research study, these are the forms of [00:07:00] bias that you can have. And the recommendation is to avoid open ended surveys, like lean into the quant. And I was like, no, right. Because it's built off of this presumption of the technology available. And, and what I do for work. So a little bit about what I do with Luminoso and why this became an option at all. Uh, Luminoso is a company that spun out of the MIT media lab as a, uh, PhD research thesis on how can computers, can they learn, can they understand language like a human does? And the way humans learn language, when you think about infants and even dogs to some degree, there's this immersive experience for language where they are based on the context of what words are used when. You realize like, Oh, put on your shoes equals we're going for a walk. There's these context clues. And it's usually [00:08:00] they're, they're strung together in a string, right? So the technology, what they, the computers end up doing with Daylight is the text analytics product. It looks for words used synonymously or in conjunction with each other. So for St. John's, it was able to determine the difference between Lombard House, a very beloved bar and Lombard the street. Lombard House is right across from Beer Porch. There's food carts. They're both very recommended. Um, there's some clientele overlap. So one of the questions in the survey that both Arbor Lodge and St. John's asked was: what advice would you give to a new neighbor? Things they should try, things they should do, things they should avoid. And it turns out the restaurants and coffee shops that people gravitate to have demographic clustering. So the folks who go to some dive bars will mention similar locations. Whereas some people go to like Cathedral Coffee on Willamette, they're, [00:09:00] they're going to different coffee shops than the folks who go to 48 North or Daydreamer or all these local businesses that we have. So what our technology allows us to do is: we have to get the storyful data. We need folks to be describing it as they would be explaining it to a peer or a neighbor, someone new. And that gives the AI the context that it needs to surface like, Oh, Fessenden has these connotations. Lombard has these connotations. Where do we need crosswalks? Where do we need, like, do we need police? Turns out that's a very polarizing topic in St. John's. Whereas. And maybe we'll get to this later. Uh, there was a, an event during the survey period where the neighborhood found out on February 28th, after the survey was supposed to be closed, that there was gonna be a BottleDrop that, they purchased the Dollar Tree location and there was like an NDA.

So we didn't know about it. And we're like, [00:10:00] why is, why did you buy it for over asking? Like red flags went up and across the neighborhood. And I checked with one of our like local community organizers and like, what do we do? We, there's this, all this news and people have big feelings about this. And the advice was close the survey, preserve the data as it is. I was like, I don't want to mute people's voices that way. Right? Like they, people need an outlet. We have a channel or a forum for that to be siphoned into. And it turned out to be really good for the survey data. Because it solidified by increasing the volume, the existing narratives. And there was really only one question in the entire 10 essay question survey that really changed. And it didn't change as much as, uh, gain focus. We can probably talk about that in a little bit if we want to go through what was in this survey and

Kevin Micalizzi: I would actually love to. Um, I mean, obviously I'm, I'm pretty [00:11:00] familiar with it, uh, both yours and, and the one we ran for my neighborhood. But

Kim Larson: Yeah.

Kevin Micalizzi: when we're talking about creating a sense of belonging, um, I think a lot of people focus on your behaviors, your approach, even your mental state, you know, are you approaching everything with empathy?

And I think very few people think about it in terms of how can we use data to better understand and therefore do the right things for that community or for others to feel like they belong. So, yeah, I would love to dig into it if you'd like.

Kim Larson: Okay.

Analyzing Survey Results
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Kim Larson: So we're about to get into a pretty long segment as I take us kind of page by page through the survey. The first part of the survey is the introduction and the goal for this section is for folks to identify. their, uh, their opinion being valid. And there's a hypothesis that, um, it's one of my hypotheses.

It may be proven. I still need to dig into it. But when people [00:12:00] feel like they're taking the survey on behalf of their community, they may take it a bit more seriously than if they feel like an individual or a number.

Right? So we have them pick their geographical zone. So I split St. John's into five zones based on significant roadways. Because sometimes if it sucks to cross the street, you make your dog walk loop within the contained easy zone. And that creates these interesting sub geographies within the community. So I split it into five based on what those significant roadways were and move forward from there. We also asked how long they've been in the community. We had it broken out into, less than 12 months. Do you know the neighborhood as it is one to five years? Are most of your memories here, pandemic related and influenced by. not starting with block parties and kind of figuring it out as we go. Folks who've been here five to 15 years. So do you have a solid memory pre pandemic? And then you saw the events [00:13:00] stop. You saw businesses closed and then like, are those your primary memories? And folks who'd been here 15 years or more. One of our surveys talked about how we needed an arcade where the old Blockbuster used to be. I remember Blockbuster. I don't know where the Blockbuster in St. John's was. So we had to do some, like, community archaeology and figure out, like, where was it? Because that level of experience matters, right?

Because some people raised their kids here, some people raised their Like their grandkids here. Like there's some generational families in our neighborhood. And we want to get a sense of where were those located?

How many of those do we have left? How do we make sure that we're getting enough new people? Because if people have only moved in here last month, they're like, I don't have enough experience to tell you about anything here. I'm going to skip it. I don't feel like I've opted in enough. And recognizing that we're like, okay, so maybe we need to approach some of these new high rise apartments. And be like, hey, can your community members, can you [00:14:00] help us kind of solicit their feedback? It is a benefit to the apartment complexes to have, residents who are attached to the neighborhood because they're more likely to renew the lease and it's helpful for the neighborhood to be like, these are our neighbors.

Like when we're out walking the dog. This is who we're going to see. This is who our friends are. If there's an emergency and in St. John's his case, we always talk about the bridges collapsing because the cut is a very big divide between us and the rest of North Portland. Who is going to be our emergency services? Our neighbors are going to be the emergency services. Let's get to know them. So there's page one. We also had a shout out section, which told us like, if you took the survey on behalf of someone. So that's where we found out how effective our flyers were. Our newsletters were, Instagram, QR codes, local newspapers. And then we could redistribute the surveys back out to those entities. So. [00:15:00] We presented it in the neighborhood. We shared the results with the local newspaper. We shared the results as broadly as we can and continuing to do so today. So if you want to see the St. John's neighborhood data, I'd say luminoso.com/sjna-study.

Kevin Micalizzi: I'll, I'll add

Kim Larson: And you can look at the, survey.

Kevin Micalizzi: I'll add it to the podcast episode notes as well.

Kim Larson: Yeah. So you can click on that link and see the survey design. We go through quite a few of these events, and if you want to see the actual feedback yourself, I'm happy to pass that along. Cause it's one of my core survey philosophies is, this data collected should not be archived exclusively something should come from it.

And as a community organizer, I don't know who can do something about it. One of the things that came up in my survey and the Arbor Lodge one, Was like, Trader Joe's. Cause we want, we want like affordable food options in addition to Grocery Outlet and Safeway. Cause it's a different shopping experience.

[00:16:00] Like Trader Joe's is pretty unique. Where else are you going to get the weird cookie butter Trader Joe's stuff? Right? You have to go to Trader Joe's for that. And St. John's kind of wants that too. So, there's page one of the survey.

Community Connection and Challenges
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Kim Larson: Page two, much shorter, that was, what drew you to, in our case, St. John's, in the first place, and what keeps you here?

Or what drew you to Arbor Lodge in the first place, and what keeps you here? From a marketing perspective, this would be our strengths. What did our PR say that got us connected. Right? Like what had us hit the buy link And it was pretty similar between Arbor Lodge and St. John's affordability, walkability, these are the strengths that kind of like drew. And there were some unique things too, like what we wanted to walk to, slightly different. St. John's tap houses and coffee. We just want to drink our calories.

Kevin Micalizzi: You, you also have far more businesses because you're in a larger neighborhood.

Kim Larson: Right. Right. Where is walkability in Arbor Lodge? To the park. We [00:17:00] want to go see the trees. It's like they called it Arbor Lodge for a reason.

Kevin Micalizzi: The trees and one of the only accessible playgrounds in the city,

Harper's Playground.

Kim Larson: Yeah, your park is very popular. So, it would be really one of my, like passion ideas, like I really wish I could get all this neighborhood data for all of Portland and outside of Portland. There's a community up in Saskatchewan, too small to qualify as a town. They are a hamlet.

And I would love to see their feedback on this. Because they're not working, like affordability might be huge, but walkability I don't think would make the list at all because it's super rural, right? Like you need to get in your truck to go to the gas station, or to get food or, you know, there's more of a homesteading vibe. Also the relationship with guns in that neighborhood. St. John's, if you go through the neighborhood data, you will see that we are a [00:18:00] city neighborhood with city challenges as it relates to, to gun issues. Up in Lumsden, it's because you had to shoot the bear because they were harassing the horses. Like that's not going to be the case in st. John's. So yeah, why did you choose the community and what keeps you here?

That's our strengths. After that we had. The let's see. I have it pulled up because I was working with someone on it earlier today. All right.

Livability and Change Management
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Kim Larson: So the next section section was on defining livability. So the neighborhood association charters, and for, I think, a lot of the city, it's to improve livability. What does that mean?

Kevin Micalizzi: Such a common word with such a vague meaning for like local governments, nonprofits. Yeah.

Kim Larson: It's like, well, it improves how well it, like how well you live there and how people want to define their lives is completely personal. [00:19:00] So is livability, the feeling of community, connection, access, commerce, economics plays a huge part of that. And so to have an understanding of how do we improve something that we can't define or measure. That's not good goal metrics, right? You're supposed to make smart goals. You gotta be able to define it. So we have, well, what does livability mean to you? And that could allow us to define like, what are we prioritizing safety in terms of curb cuts, in terms of lighting, or are we improving safety in terms of connection, exchanging phone numbers, if there's an earthquake or the volcanoes explode. What is livability? Right? Like we just talked about gun violence, like that is a thing. That does you know, potentially threaten people's quality of life and the livability of the neighborhood. For some folks it's like, I need access to restaurants and [00:20:00] entertainment and things that make me want to feel alive here.

I need a place to spend my kids and to do things with them and build childhood memories. Arbor Lodge had some really cute, teach my kids how to ride a bike. St. John's, that, that didn't come through in the same way. You guys have much more of like a family core. Which is really wholesome to see all the surveys that we look through.

I'm always like, I'm gonna cry. And, and training my kids or teaching my kids how to ride a bike, different reasons to cry than maybe some of my St. John's stuff. And then there were two questions about change management. So generally in survey design, I have most of the questions I tend to work with for the storyful categories fall into, reflective, projective, and hypothesis or change management. So, people generally have a [00:21:00] degree of comfort that is likely different between how vulnerable do they feel safe being, how confident are they to tell other people what to do, and then change management is allowing us to do some hypothesis testing on like, what changes would improve, make things worse, what are the consequences of, those should be evaluated. So, if you think of reflective, that's often like your CSAT. Or your five star rating after a online purchase. Reflective, you are looking at: how did the experience relate to the expectations. That's your satisfaction. The projection is your NPS stuff, your advice stuff. What would, what would you recommend someone else do? There may be a gender split regarding who feels comfortable being vulnerable and reflecting and who feels confident telling other people what to do, but we offer both because both are very important to capture and then change management tells us. Would adding police make things better or worse? Some [00:22:00] people are like, yeah, we need someone to crack down on this gun violence and car racing and donuts happening at 2 p. m. on a Wednesday. Like that's, it's unsafe. We need, we need to stop this and do a crackdown. And other people are bringing up like, there's other solutions. Like, yes, that's a problem, but police is a solution that may make things worse. What if we tried for more green infrastructure, speed bumps. Let's get more creative and let's find out what is, what do we have consensus on and where do we have polarization on? Where are we drawn to the two ends? So we have a changes for better and a changes for worse question. Changes for worse is really hard for folks, generally, right?

Because they're like, I don't know, it hasn't happened yet. What are you planning? So that one can be a little bit tricky. For St. John's, the BottleDrop really distilled. We had some loose themes about like, well, if there was an increase in unhoused [00:23:00] population, or if more of our business is closed, those would be changes that would make the neighborhood worse. And then when the BottleDrop topic was introduced, they're like, the bottle drop would make things worse because of exactly those reasons. We'd get more car traffic, which would be worse. We would have more, folks who are unemployed hanging out, worried about economic issues, make things worse. And so that kind of distilled everything together for us. Any questions on the stuff we've covered so far? Other contributions to those three

Kevin Micalizzi: No, no. Um, I, I really liked the, uh, the change for better and change for worse questions, because it's not something I think we intuitively think to ask. And by asking it, we got such a wide variety of answers that I don't think would have come out in any other questions. And, you know, you always end with like the open ended, you know, anything else you want to tell us, but like, unless you're guiding their thinking [00:24:00] on it, You're really not going to get to that.

Kim Larson: No, it's, it's tough brainstorming to navigate. And one of, I have found that the more novel or interesting the survey design is, the more people want to reciprocate that experience. And they really did feel heard. I felt surprised and validated that folks were writing six paragraph essays on the change for worse question and six paragraph and like how many thousands of hours did the community invest in this question?

Just because we asked good questions. One of the things that I've learned from my clients here at Luminoso is we tend to perform best in applications where: people are familiar with focus group methodology, and you need to flesh out a full discussion guide. What this survey design allowed us to do is do that focus group qualitative research at [00:25:00] a quantitative scale. And it was a lot, it was a lot to go through, but I, I kind of cheated with using the platform because, you

Kevin Micalizzi: It's not really cheating if you have a technology that is designed for this.

Kim Larson: Yeah, yeah, it's true. And it let us get into some really deep stuff. Like the, the next section there's, that was my smooth transition sentence.

Connection and Community Building
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Kim Larson: The next section was about my hypothesis that connection displaces fear. So the more connected folks feel the less likely they are to, create caricatures of other groups and, take more of a community minded approach to the problem solving compared to, seeking out levels of, like adversive approach solutions. So like, inviting a police force [00:26:00] would be a last resort. There's a problem. We should lock people away. Okay. Right? So I wanted to find out, well, how connected do we feel and how do we start to flesh that out as it compares to changes for better, changes for worse, that kind of thing, right?

Because if you're at wits end, you're like, just make the pain stop. So we have this connection question on, you know, not connected at all to extremely connected. And then the question was, describe the events and locations that have helped you feel most connected to the community and why, what makes them so special and effective? And that had a good distribution of, you know, folks who walk their dogs, they see the same people in the dog park every day or PTA or volunteering or being regulars at a coffee shop or a bar. And it was an interesting distribution on this, like, how connected do you feel? Scaled question to the open end. Interestingly, Arbor Lodge, people who felt less connected felt connected via [00:27:00] the newsletter in Saint John's people who felt less connected, their gateway into the community was block parties because it brought the community to them instead of having to go outreach to the community. People who volunteer, much more connected than people who didn't mention volunteering. The farmer's market is a very popular way of connecting with folks in St. John's. So that was a high volume towards the average. Did you find anything in your connection question that kind of resonated or?

The responses were, I think, along the lines of what I was expecting. I think what fascinated me the most was the differences based on which part of the neighborhood you're in. In all the responses. I think, in part, because we just have 2 commercial quarters, 2 major roads that kind of buffer, or not really buffer because 1 does cut through the neighborhood.

Kevin Micalizzi: But, just looking at [00:28:00] those, the experiences and the challenges are entirely different or perceived differently for them than if you go four blocks closer to the park.

Kim Larson: Mm hmm. We had that with, Fessenden. So folks north of Fessenden, which is a part of the neighborhood that is not covered by some of the grant writing, like small business assistance doesn't extend as far as fessenden. It only goes along Lombard. And so, as a consequence of that, there are few active businesses on Fessenden compared to Lombard, where there are dozens. So in this connection question, the folks north of Fessenden, they described, they had Daydreamer. Like, that is their go to business that were tipped on with the survey. There are more businesses over there, but they weren't surfaced in the survey in the same way. Whereas folks who were south of Lombard, along the bridge, in the Cathedral Park area, variety of more businesses were [00:29:00] mentioned. There are more niches. It was just, and the advice that people gave for advice, new neighbor also had some really stark geographical breakdowns.

Transportation and Infrastructure Needs
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Kim Larson: So we had some questions about downtown, about, how people usually get around and how they would like to get around. That one was. Maybe it's because it wasn't particularly storyful. It didn't seem to have the same kind of grasp. We have the question on if there were decreased car traffic on Lombard, how much time would you spend in the district? And either they would spend less time with less traffic, or they would spend more time with more traffic. That had an interesting kind of correlation with, how they felt about the state of the neighborhood today. If they felt positive about the state of the neighborhood today, they would spend more time with less traffic, probably because they're walking around. I say probably because I haven't looked at it, but it's a hypothesis, right? And then the,, I [00:30:00] was surprised that folks would spend less time downtown if. Like at all, like, what do you mean? If there was fewer cars, you would spend less time there. I looked into those surveys and they had feedback kind of with the assumption of if there are fewer cars, that means there'd be fewer people because there's, it'd be less

Kevin Micalizzi: Oh, okay.

Kim Larson: right?

This, this perception that car traffic, it equals popularity equals safety.

Kevin Micalizzi: Yeah.

Kim Larson: So it was, it was interesting.

Kevin Micalizzi: I mean, that's something you see. It's incredibly common here in Portland. The, no cars, everybody bikes and walks camp versus the, Oh my gosh, we, we still need cars and we need more parking. We need more access. So it wouldn't have surprised me if some of those folks who are like, Oh yeah, if there were, you know, Less cars down there.

They're thinking also it's going to be harder to get to

Kim Larson: Yeah, yeah. So it's interesting to see [00:31:00] how, how folks perceive that. And, I would love to get this information in front of PBOT, for example, so we could look into those folks who said I would spend less time if there was less car traffic, because the less car traffic doesn't mean less parking. It could just mean more bike parking so that there is more space for folks to park their bikes. So maybe there's more parking spaces available because people biked instead of drove. You now have fewer people to compete for spots with. We have the data. We're happy to share it. Uh, just to see because I've noticed I bike to downtown St. John's more than I drive since I can. And there's been times where I'm like, there's nowhere to park my bike. What does, what a Portland problem to have like all the bike parking taken. You have to take it like a few more businesses down. You're like, well, no, I can't keep an eye on my bike. And I like my bike.

I don't want it to get stolen.

Kevin Micalizzi: Yeah. And it's tough because, [00:32:00] where I live, my neighborhood has a light rail that comes right up through it. I can also walk less than a block, hop on a bus and go straight up to downtown St. John's. And I have to admit, I have never taken the bus up there. Like we will. We will drive up there.

Yeah. Fascinating.

Yeah.

Kim Larson: Cause the bus. I, I live between two bus lines. I can go two blocks to catch the bus on Fessenden. I can go two blocks, catch the bus on Lombard. I either, I either bike or drive. And the smooth transit, you guys have a Max line. St. John's. One of the things, the next question on the survey was, what is St. John's missing? Be specific. And that has a prefa, a preface of explain why St. John's needs it, where it is needed and examples of similar things. So that we can compare, right? Like, cause you may say like, we're missing a [00:33:00] pedestrian island or bike safety or bike infrastructure point out what, where you're thinking of.

Cause green paint is different from physical barriers is different from bike only lanes. What do you mean by bike infrastructure? And in the, what is St. John's missing section? People brought up the Frog Ferry, which, and people also brought up the Max, like there's people want. A way to get downtown. One of the reasons I don't take the bus is because I was going to go there for I had a race.

So I did the half marathon on Sunday. Thanks. And recognizing like all of downtown was going to be locked off. No cars. A similar situation for Pride, right?

There's just no way to get downtown. And so I was like, okay, well, public transportation goes right by where I need to be. And taking public transit was going to take an hour, an hour, an hour, 20 minutes, or it's a 15 minute car ride. When I have to be there at 6 30 [00:34:00] AM, I'm not, I'm not getting up at four.

Kevin Micalizzi: Yeah. No, definitely not. Definitely

Kim Larson: So the Frog Ferry was. The Frog Ferry was something that was mentioned and in the what is missing question, I think we've explored that question more than anything else in the survey, because there was such a broad economic impact. It's because it's surfacing problems. So, previously, we talked about changes for better changes for worse. What is missing is a very explicit question that people keep the long laundry lists of we're missing a crosswalk here. We're missing paint here. We're missing a dry cleaner. We're missing ice cream. We're missing Frog Ferry, like whole bunch of topics. And we put the survey hadn't even closed yet. So we opened it in November. We got some early feedback and people said, like, we're missing ice cream. Like [00:35:00] It's 20 degrees outside.

Kevin Micalizzi: Right. Right.

Kim Larson: ice cream? And Wonderwood, Mike Bennett's little installation on Lombard that is increasingly beloved, because he's making such a big splash. He added a soft serve machine in December, because I was still trying to get people to promote the survey taking, and we had some initial feedback, like it's going to be good. And Mike's like already on it. Soft serve machine introduced. And he added this cute little, like there's the Wonderwood sign out front. And he did a little chain thing to ice cream hanging from it. Just like we have ice cream. Good, good job,

Kevin Micalizzi: I love it.

Kim Larson: So it, it had such an immediate impact. Mosaic down the street, it's another tap house. For a limited time they had beer inspired ice cream. So chocolate in honor of a stout, like a fruity flavor in honor of the hazy.

It's not beer derived ice cream, but inspired ice cream.

Kevin Micalizzi: [00:36:00] Right,

Kim Larson: They had a little bit of a seasonal thing there. We have a lot of big companies in Portland that can afford this market research, the small local businesses that we want to support in our neighborhoods, they often need to be equipped with data to build confidence to know that they're meeting a need in order to do it.

Right? Like, because they are listening to customer feedback. They're doing the same thing that our local neighborhood associations are doing. Like, Okay. Oh, yeah. If you tell us, we'll go do it. It's like, well, let's, can we equip them with feasibility studies that help everyone, right. When we go back to share that, cause I, like, I personally don't want to take a survey for the 200 businesses in St. John's, but if I can take one survey and it can fuel the economy for the next two to five years, let's do that.

Reflections on Survey Design and Impact
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Kevin Micalizzi: Well, what would you have done differently with the survey or, you know, thinking ahead, if you do this [00:37:00] again in a year or two, like what, what would you change?

Kim Larson: Yeah. So the first thing we actually have a webinar coming up on this, one of the things I had missed, cause I didn't think the survey would be as successful as it was, was demographic information. So when we go to Prosper Portland, we're like, okay, we need, bike parking and these, these things and their priority is based on DEI initiatives.

So diversity, equity, inclusion initiatives. They're like, well, is this serving the BIPOC community? Is this serving underserved communities? Or is this further amplifying the privilege because they took the survey. They had a mobile phone. They had the extra time. And I didn't, I didn't, I didn't feel equipped. To ask the demographic information like race, ethnicity, gender, income, because there's some loaded economics and incentives behind it, right? So I wish I had added that and I've, I've done more research since the survey to figure out how I could do [00:38:00] that better. So next time I would add those demographic questions to the end. Non exclusive options with, gender because Portland has a comfort with a more wider variety of genders than, say, Lumsden, right?

Yeah, so I would include those at the end because the, the core of what we looked at was solid, right? Like, when we asked about how they feel about St. John's, today. There was that emotion grid that we included in St. John's. We didn't include for Arbor Lodge. I would include the emotion grid in future iterations because it added, such diversity to like show, like, no, we're not just getting the angry folks and the excited folks. We got folks who felt complacent or sad or had general medium feelings. That was really good. we just needed to figure out

Kevin Micalizzi: we did that question

Kim Larson: we, you had the scales, but the image, uh, the hundred point,

Kevin Micalizzi: Oh, right. Right. Yep.

Kim Larson: So for the audience, because we kind of just [00:39:00] like glossed over that, if you look up the emotion grid, it equips them with emotions like enraged, panic, stress, jittery, livid, furious, frustrated. That's in the angry quadrant. And they can start to map like how high of an energy feeling do I have, how mood, and then they can figure out how to navigate from there. Like, do I need to decrease my emotions? Increase the pleasantness by what spectrum. Okay, let's do a dance party, get the energy out and we'll feel better. And what that does is that helps equip respondents with the vocabulary for their experience. Some folks, they say, how are you doing? And they say, good, bad. That's not specific enough for the research we want to do. So we have them kind of identify what their feelings are in the survey. And that showed us how diverse of a experience our community is offering. But yeah, what would I do differently? I would include that image. I'd include demographic questions.

That's my two things.

Kevin Micalizzi: [00:40:00] Got it.

Balancing AI and Human Connection
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Kevin Micalizzi: So one thing I wanted to make sure we we carve out time to talk about is when we're talking about AI. I think there is, you know, a lot of fear, uncertainty and doubt it. That's a given.

Kim Larson: And valid.

Kevin Micalizzi: But, but I also feel like especially experiences we've had with the, like, just people in general with the, the tools that are available to us is that it doesn't understand context. You know, it misses social cues. Like it doesn't look at a question like we would, like humans would, you know, gen AI is really looking for, you know, patterns and probability. And I think my big question for you, like as somebody working in the space and using the technology to help improve your neighborhood and your community: how do you keep the human [00:41:00] factor in all of this.

Kim Larson: Yeah. So first I would say they are not exclusive. They are, they're supplementary to each other, right? A lot of the shortcomings with AI, are rooted in human feelings of insecurity or safety. So one of the things that we would say we don't want to put through either our text analytics engine or in general, it's really tough to detect sarcasm is a context dependent thing, right? A lot of humans are also not good at sarcasm. Like, we get an autism diagnosis when we're not good at sarcasm because there's context outside of what is said. Sarcasm happens when people don't feel safe. And so building things that build trust, having those human connections helps preserve the quality of the information we're given. So keep having the human conversations [00:42:00] and then utilize the technology to empower that at scale, right? Because people do what works. So if they, if they open up and they are not rewarded for it, they'll retreat. It's work to open up, right? They'll scale back. So what, that's one of the things that we're trying to do with the survey is you were vulnerable enough to tell us about your police trauma a day after Christmas in front of Thai Cottage. How do we respect that and bring it back to you as like: how do we, how do we help foster that healing? When people are rewarded for being vulnerable and being thoughtful and like, you know, I spent all this time taking the survey and saying I need ice cream and then I got ice cream. Okay. They have, they have been validated for that integrity. So we're not automating any of the outputs, right? We're just automating the processing that allows us to ask those questions at [00:43:00] scale. Ideally the technology. Would foster more connection because we can add this line of you're not alone, right? Like, you're frustrated with not having a place to hang out with your kids on weekends. You're not alone. Let's go find a solution. You are frustrated with the car track. You're not alone. You want Frog Ferry. You're not alone. Cause we shouldn't be covering our ears to the reality of people's experiences just because we don't think we have the time or bandwidth to ask. So I think that is, um, it's a, it's a big yes, and.

Kevin Micalizzi: I love it. I love it. So I, we're, we're kind of coming up towards time.

Final Thoughts and Advice
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Kevin Micalizzi: Uh, we've talked a lot about the surveys that were done for those listening who have a passion for building community, better understanding their communities. What [00:44:00] advice would you give for how to get started doing this and, and how to get started really quantifying the needs of your community?

Kim Larson: Yeah, so I think the first step is always have an objective. And evaluate the resources you have available because there may not be a perfect alignment. Like I want to improve communities across the U. S. I don't have relationships across the U. S., right.

I got them within my little radius of St. John's. So understand your objectives and like who your stakeholders are.

Right. I want my neighbors to benefit. I want my local businesses to benefit. Okay. So that's going to limit some of the questions we may or may not ask. Then I'd say start fostering that community because we could not have done the survey without the support from our local businesses, hanging our QR codes on their tables. Without the support of like the local newspapers, putting those QR codes in to reach a demographic that we may not have reached [00:45:00] otherwise. And then say, work on asking thoughtful questions and test it on someone who doesn't have the time, right? Because they will tell you the shortest way to answer the question. If they can answer with a yes, no, when you wanted a story. You probably need to work on how you ask the question. And yeah, we'll figure things out from there.

Kevin Micalizzi: I love that. Test it on someone who doesn't have the time

Kim Larson: Or interns.

Or the CEO. There's so many folks who just don't have the time. Because there's some questions that, like, how will you remember St. John's in five to ten years? That's not a yes

no question.

Kevin Micalizzi: Right. And, and some people don't think long term, so you really have to pause and, and spend some time on it.

Kim Larson: Yeah, yeah, it's

Kevin Micalizzi: Yeah. Oh, agreed. Agreed. I love the fact that we have a better understanding of, the perspectives across our communities. So for any [00:46:00] Portland neighborhoods listening who want to, uh, want to do this as well, it would be awesome to be able to actually analyze that data across the entire city.

Kim Larson: Yeah, compare Lombard to 82nd. I want to get the data data from about 82nd. Yeah, I think it'd be interesting because we have as much diversity in Portland as we do across the US.

Kevin Micalizzi: Agreed. All right. Anything I didn't think of asking you that you were hoping it would.

Kim Larson: No, I, I came in here as a blank slate. I just, if people want to see more of the data, obviously, and we also have a webinar coming up, so that'll be released on the Luminoso YouTube page. If folks want to catch up on how I might actually redesign the

Kevin Micalizzi: Totally. And, and the, webinar may actually will likely actually happen before this episode goes live. So we can include a link to the video in the, uh, show notes.

Kim Larson: [00:47:00] perfect.

Kevin Micalizzi: Kim, thank you so much.

Kim Larson: Thanks for having

Kevin Micalizzi: I love doing this.