The Art, Science, and Magic of Insights
In this episode of the Consumer Insights Podcast, we speak with Laura Eddy, VP of Research and Insights at Realtor.com.
Working with consumer insights is both an art and a science, no matter what vertical you’re in.
But the most skilled insights professionals take it a step further; they make it look like magic.
In this episode of The Consumer Insights Podcast, Thor is joined by Laura Eddy, VP of Research and Insights at Realtor.com.
They cover:
- How insights can help make major (and minor) life decisions easier
- The unifying power of insights teams
- Lessons in insights from Walmart, Amazon, Zillow, and Realtor.com
- How small tweaks can have a major impact on customer satisfaction and your bottom line
- The differences and similarities of insights work across verticals
- Why insights teams need to have a seat at the table when decisions are being made (and what you can do to get there)
- How insights teams can facilitate cross-functional collaboration
- Why curiosity, storytelling, and ambition are key skills to hire for when building and scaling insights teams
- Why finding a “project champion” can help elevate your team in the org
- How looking to other industries can help you find new solutions to old problems
If you’re interested in exploring the art, science, and magic of insights, tune in to this episode of The Consumer Insights Podcast.
You can access all episodes of the Consumer Insights Podcast on Apple, Spotify, Google, or use the RSS feed with your favorite player. Below, you'll find a lightly edited transcript of this episode.
Thor Olof Philogène: Hello everyone and welcome to the Consumer Insights Podcast. Today, I'm excited to have an incredible insights leader joining me for what I know will be a fantastic conversation.
I'm thrilled to introduce today's guest, Laura Eddy, VP of Research and Insights at Realtor.com. Prior to her role at Realtor.com, Laura was Head of Insights at Bed Bath & Beyond, and she's also held several senior research roles at Zillow, Amazon, and Walmart. Thank you so much for joining me, Laura.
Laura Eddy: Hi. How are you? I'm very excited to be here.
Thor: So Laura, firstly, could you take a couple minutes to tell us about yourself, your company, and how you got to where you are today? I am quite curious to know how you've made the transition from microbial engineering to consumer insights.
Laura: Absolutely. As you alluded to, I did start my career in microbial engineering. One of my masters is in that area and I spent a number of years in industrial biotechnology.
I worked for Cargill, who had very interesting ambitions of “We want to be in biotechnology, but we're not really sure what to do with it.” So as a scientist, could you work with these marketers to say, “How do you sell whatever it is that you create?” And in that experience, it became apparent very quickly that people and consumers are much more interesting than bacteria and yeast.
I switched over to marketing research working for companies like General Mills, Land O Lakes, traditional kind of CPGs. And taking that really hard science background and analytics moving into retail, you've got companies like Walmart, Amazon with these massive data sets and sometimes traditional market researchers, who at least at the time, weren't necessarily quite as analytical.
So bringing that skill set to those companies really opened my eyes and the eyes of those companies to really the power of data and attitudinal consumer research together to say, “How can we really make lives better for our consumers, customers, users?”
Real estate is such an integral part of the human experience. It's one of those things that you as a person deal with that really hits on literally every level of Maslow's hierarchy of needs from like basic shelter all the way through self-actualization.
And after being in retail for a little while, I moved over to a more traditional tech company, Zillow and got into an area that I've really become passionate about.
Real estate is such an integral part of the human experience. It's one of those things that you as a person deal with that really hits on literally every level of Maslow's hierarchy of needs from like basic shelter all the way through self-actualization.
Yet, the experience of getting real estate, whether you're renting, buying, selling, is borderline traumatic for a lot of people. And so if there are things that we can do through research that help make that easier or better, or at least less traumatic, that is a very worthwhile, exciting place to be.
I've recently come back into the space after a stint at Bed Bath & Beyond, and very excited to really embrace Realtor.com’s vision of how to make this easier, better for consumers, especially as we're moving into a really challenging economic environment, where a lot of people are unsure of what to do around housing.
So it's an exciting time to be in the industry and to be at Realtor.com, which to be quite honest, is a little bit of a second place player. A lot of people know Zillow, you've got Zillow being used in SNL skits, and yet, there are certain things that they've done that maybe have dinged consumer trust a little bit.
And so how can we at Realtor maybe ameliorate that distrust and really become a partner in the process for moving people from a current home to their next home.
Laura's definition of an insight
Thor: And Laura, when you brought the unique skill set you have to the world of research, you must have also brought a unique perspective.
So from that perspective, as an insights leader, how do you define an insight and also how has that definition changed over the course of your career, and if it has changed, what made it change?
Laura: That is a super interesting question. I firmly believe that you can get insight from anywhere in the organization. And part of the magic of an insight or research team is really saying, “How do I take learnings from all these different spaces, whether it is operations in retail, a consumer satisfaction survey, call center data, whatever it happens to be?”
How do I bring all of these sources together and really connect the dots to tell a simple, holistic story that is going to help stakeholders in whatever part of the business they happen to be in, make decisions that are data driven and in the best interest of consumers?
I firmly believe that you can get insight from anywhere in the organization. And part of the magic of an insight or research team is really saying, “How do I take learnings from all these different spaces, whether it is operations in retail, a consumer satisfaction survey, call center data, whatever it happens to be?”
And I'll give you an example of one of my favorite insights from my newbie days back at Walmart that really shaped my perception of what an insight was and how it could be formulated.
Back in 2008, I started at Walmart and actually was brought in because I had this very analytical background, to start their tracking program between store satisfaction, brand perception work, and pricing trackers.
We went through doing the satisfaction work. You went through the traditional steps of let's run a baseline survey, let's figure out what the drivers are, and what the attributes are.
In retail there were three main things that really drove satisfaction. You used to hear the executives talk about these in analyst calls or investor calls all the time.
It was fast. “How quickly can I get through the store and through checkout?” It was friendly. “Did someone help me when I needed help in the store? What was the cashier like?” And it was clean. “Was the store presentable? Were the bathrooms clean? Did the product look like somebody cared about it?”
And surprisingly, things like price value almost fell out of the equation. As far as satisfaction goes, people had already given credit to Walmart as having high value when they came in the store. So you couldn't really impress them, or it was really hard to impress them with the price walking in.
Keeping in mind that in 2007-2008, Walmart had some of the worst reputation in the retail industry, to be honest, in American business history. I mean, they were not a terribly respected company at the time going into an economic recession.
The thought was that going into a recession, Walmart scores should go super high. It's a value you play, right?
And we were looking at CSAP scores, wondering why some of these things weren't going up very quickly and realized through some correlation analyzes that people who rated their cashiers as friendly, thought that their wait in line was one third, compared to the time of people who thought their cashiers were not friendly.
And we went into the store and kind of watched how cashiers who were rated friendly, interacted with consumers, and knowing that ability to get in and out of the store through the checkout line is a huge driver of satisfaction, which in turn is actually a huge driver of whether you choose to spend your next visit with Walmart.
We watched these cashiers and it came down to three easy things. First off the cashier acknowledged the customer when they came up to their place in line, said “Hello” and made eye contact. The second thing was that these cashiers smiled. Just smiled. They didn't look like they were under duress to be there. And the last thing was they said, “Thank you.” Or some acknowledgement of, “We appreciate you being here.”
And we took these couple of pieces of learning from operations from the survey and we lit this very simple program together and we piloted actually in New England, which I'm not sure if you are familiar with, but it's maybe not known as the friendliest, warmest part of the US, they actually have the lowest friendly scores in the country.
That was such a learning experience for me, that you could take this learning from a survey and go in store and talk to operations, and you could make these tweaks that really didn't cost very much for the organization and yet make a fundamentally better shopping experience for customers, which in turn actually materially drove same-store sales impact that bottom line.
And we decided to pilot this program there. We put together little laminated cards. You know, “Say hello”, “Smile”, “Say thank you”. I mean, very simple things. Gave it to all cashiers. We put people who are more outgoing in cashier roles, people who are maybe more introverted in stocking roles.
And we watched those scores jump in the course of literally a six week to three month period. Which actually then correlated to a higher same-store sales. We rolled this program out US wide and ended up actually seeing Walmart same-store sales jump. Again, there was an economic recession going on, there were economic tailwinds, all helping all of this.
It was by pulling these pieces from disparate areas together and knitting them in one place where you could see that impact on the bottom line. And I think that is so key for insights to professionals to be able to do.
That was such a learning experience for me, that you could take this learning from a survey and go in store and talk to operations, and you could make these tweaks that really didn't cost very much for the organization and yet make a fundamentally better shopping experience for customers, which in turn actually materially drove same-store sales impact that bottom line.
It was by pulling these pieces from disparate areas together and knitting them in one place where you could see that impact on the bottom line. And I think that is so key for insights to professionals to be able to do.
How insights work differs across verticals
Thor: I absolutely love that story, Laura and when I look at your career, I think you've really had an amazing journey. One thing that's really interesting about your career and the journey you've been on, is that you've worked both with a variety of companies and the full spectrum of consumer involvement and the purchase decisions.
In other words, my guess is that as an example, the average shopping list for Walmart or Bed Bath & Beyond is quite different from the one you'd have at Realtor.com. So do you shift your approach to research and insights depending on the level of consumer involvement in a purchase? Or are there some aspects that stay the same regardless?
Laura: The data input may be slightly different by company. Walmart, Amazon, Bed Bath, they're retailers, they have massive transactional datasets, all about how people might shop different categories or how they shop one side of the store versus another, or even online versus in-store behaviors.
And of course Realtor, Zillow, some of these other places have much longer product life cycles. Most people don't just decide to buy a house in one week. Some might, but most don't. So there are differences in just scale of what you're looking at, but still, even housing has huge, huge data sets. The government has mounds and mounds of data.
The thing that changes almost more than anything isn't necessarily just the type of data or the amount of data; it's actually the timeline on which these companies work.
The thing that changes almost more than anything isn't necessarily just the type of data or the amount of data; it's actually the timeline on which these companies work.
So I started my career in traditional CPG and you think about it, General Mills at Land O'Lakes, it might take six months, a year plus to launch a new project, you've got months to do in-depth consumer research. If you get a product launch wrong, millions and millions and millions, in sum cost.
In digital, it's a much faster timeline, Amazon, Zillow, it's fast to fail. Put your MVP, your minimal viable product. Some companies say an MLP, a minimum lovable or likable product. Put it out and iterate fast, fail fast, iterate, move on.
And in retail, it's very similar in terms of speed. You move from one week to the next, what's gonna be on an end cap, what your circular is gonna be, things like that. And it can be a little bit challenging to adapt to those different modes of timing.
You have to get very comfortable with making a decision with maybe 80 or 90% of the data in tech or even retail, whereas in CPG, at least at the time, and it's been a number of years since I was in CPG, you really needed that more complete picture, because the upfront costs, those sunk costs were so much greater.
I think it's a little bit of how you balance the art of doing that with the science of it. That's another thing I think that changes between companies. Sometimes more established, big companies are maybe a little bit more aware of the art part of this.
So I would say that is something that you have to adapt to between industries, but how human behavior works and how you analyze behavioral data in conjunction with attitudinal data, those are really pretty fundamental to what we as research professionals do.
I think it's a little bit of how you balance the art of doing that with the science of it. That's another thing I think that changes between companies. Sometimes more established, big companies are maybe a little bit more aware of the art part of this.
There's an interpretation, you're sometimes fighting legacy organizations where people make “I feel, or I think”, kind of decisions versus, especially test two degree retail where it's all about “Show me the spreadsheet, show me the this.”
If you don't have that quantitative sample with stats dig at a 90 time percent confidence level, I don't believe it, sort of thing. And so that approach of how you need to interact with your stakeholders, that audience can change a little bit.
Like I said, that fundamental, bringing the art and science together of behavioral, attitudinal data to really tell that story of the consumer and how they interact with either your product, your brand, your services is pretty consistent.
You tweak maybe the approach a little bit, but at the end of the day, people are people and they want to feel as though their needs are being met and that the brand, product, service, that they are purchasing, whatever it is, box of cereal to a real estate agent, has their best interest in heart.
You tweak maybe the approach a little bit, but at the end of the day, people are people and they want to feel as though their needs are being met and that the brand, product, service, that they are purchasing, whatever it is, box of cereal to a real estate agent has their best interest in heart.
The agent is going to be advocating for them to live their best life, whether it's saving money or the highest quality breakfast cereal or getting me the best price because I can look at 37 different potential vendors for something on Amazon to this real estate agent's gonna go in and fight for the best absolute closing price that I can get.
That's consistent and it's all about how you find the best way to communicate that to your stakeholders in a way that is going to help them make those data driven decisions, that are at the end of the day gonna make life better for their consumers, users, et cetera. Tweak of approach, but I think at the end of the day, we're trying to get those same ideas across, solve those same problems.
Thor: I think that makes a ton of sense. Laura, do you have any stories that you could share about times in your career where you could potentially highlight that difference in the timeline of which the companies work? Tell us what happens in a much more fast paced, digital type environment.
Laura: At General Mills a new product launch might take months to years. We would go through and look at syndicated data sales. We would go through scenario planning exercises to say, “Okay, if we do this in the marketplace, how is Kelloggs gonna respond to this? How is Post going to respond to this?”
They would collect feedback from potential vendors to say, “Where are we gonna put this on shelves? How are we gonna price it?”, exhaustive studies to do some of these things. You wanted to be very sure walking in.
Whereas at Amazon, I remember a particular study that we did around Alexa. I was part of the team that did foundational insights when Alexa was launched and presented to the public.
In the first iteration, Echo was actually presented, if you might recall, as a very hardware-centric product. This is the best speaker, it has the most number of directions that it responds to because it's circular and it fits best with decor because it's very sleek.
Keep in mind, Amazon was actually third to market. Siri was already out with Apple. Google had been launched already. And so Amazon was going to compete with very hardware levels.
That happened literally in the course of weeks, and so that pivot was very fast. We had to take that data, interpret it, quantify it, add this art of unstructured kind of tech based data in a matter of weeks and it wasn't complete.
They put this out and when we started doing text analytics, you realized that consumers were actually treating Alexa as part of the family. In fact within the first couple of weeks of Alexa being launched, one of the top questions that was being asked was an iteration of “Alexa, will you marry me?” “Will you be my boyfriend / girlfriend?”
And we realized that the personal assistant had to be personable. And within a matter of weeks, you literally saw the advertising switch. This is a product developed by engineers, by a tech company to go into people's homes, and they had to pivot really almost on a dime to become this very consumer facing, personable, personality driven product.
And so you started hearing Alexa start to joke with consumers and actually this was driven by a community project that we did. We asked consumers, “What would you like Alexa to do next?”
And part of it was Alexa for pets, there was an April Fool's Day commercial where you had this whole pet talking to Alexa and a cat ordering this deluxe sushi tray and a dog breaking a lamp from playing and ordering a replacement lamp before mom could get home.
That happened literally in the course of weeks, and so that pivot was very fast. We had to take that data, interpret it, quantify it, add this art of unstructured kind of tech based data in a matter of weeks and it wasn't complete.
Amazon was taking a little bit of a leap of faith in going against what all of these engineers said, “This is a tech hardware product and we are gonna have the best technical that is on the market” to a completely different role, and so it was very exciting to be part of that.
How insights professionals can elevate insights in their organization
Thor: I can imagine. What a story, thank you so much for sharing that, Laura. And in your current role, you write that one of your goals is to, I quote, “expand the research and insights functionality to enable more data driven decisions, making within the organization.”
With that in mind, what advice would you give to insights professionals who are looking to elevate the role of insights in their organizations?
Laura: So the biggest thing that I found through my career, and I think this is especially true in tech environments, is really acting as a unifier for the organization as a research function, insights in particular.
We get a perspective that very few functions in the organization have. We see across product, we see across marketing, we see across strategy, we see across operations. It is an exciting place to be because we can again, draw the line through all of those dots of what's going on in all of these different places.
At the end of the day, we all wanna do what's best for our consumer, but what an engineer thinks is best for the consumer may not be a hundred percent off the cuff what a marketer thinks is the best message for consumers.
We get a perspective that very few functions in the organization have. We see across product, we see across marketing, we see across strategy, we see across operations. It is an exciting place to be because we can again, draw the line through all of those dots of what's going on in all of these different places.
And it certainly might not be what somebody in operations who's putting packages in boxes, or having that conversation with a consumer, trying to connect them lifetime to a real estate agent. And so by being able to tell that holistic story that at the end of the day, this is what our consumer is trying to accomplish, and here is why it is so important for that consumer at Realtor.com in particular.
You are figuring out where your family is going to live for the next chunk of time, and let's face it, where you live, how accepted you feel in that neighborhood, “Are you able to afford the mortgage?” “Are my kids happy in school?” “Do they have a place to play?”
That is a hugely emotional decision and you add to that this complication of, for most people, a real estate transaction is literally the highest financial output that they've done to that point in their lives. It's interesting, we've done some studies that show that when a decision that is a super high outlay of resources happens, the human brain has evolved to actually trigger pain receptors.
Back in caveman days, if you overextended yourself, you might be left out in the cold for winter and eaten by a tiger, that tiger might be coming after you, because you overextended yourself, got foreclosed on your cave and you're out in the cold.
And so subconsciously that is a huge thing. And when you are able to help every facet of the business understand and really think with that empathy, a look of what our consumer is going through.
We're all working together to make this easier. At least let's not have 50% of people crying, when they are trying to go through a real estate transaction or 70% of people during the pandemic having buyers remorse, because they bought a home at a time, they're not entirely sure of.
I think a lot of companies would tell you, “Oh yes, we're aligned, we're all pulling in the same direction”, and yet sometimes when the rubber hits the road, you're sitting in these companies. It's kinda like “You may not be quite as streamlined to think.”
And so it's, it's a matter of giving, that research department that mandates that ability to come in and say, “Let's all get on the same page. This is what we are working for.” It doesn't matter what industry it is, there's always a higher purpose.
That's very motivating to employees and I think, especially at Realtor.com, we call it RTC for shorthand. “How do we tell that user story? How do we bring together these market level insights?” How we bring together that transactional data and how people are leveraging online real estate sources to align product and marketing and operations and strategy to all work towards the same goal.
And I think a lot of companies would tell you, “Oh yes, we're aligned, we're all pulling in the same direction”, and yet sometimes when the rubber hits the road, you're sitting in these companies. It's kinda like “You may not be quite as streamlined to think.”
And so it's, it's a matter of giving, that research department that mandates that ability to come in and say, “Let's all get on the same page. This is what we are working for.” It doesn't matter what industry it is, there's always a higher purpose.
That advocacy that I referred to earlier of people want to feel like whoever they work with, brand products, is on their side, it's making our life better in some way, shape, or form. And when we all realize that in a company, the more effective we're gonna be as brands, as products, as services. I think that is a very unique role that research and insights should have the mandate to play and bring the company together with.
How insights professionals can challenge the status quo
Thor: I absolutely love that answer, Laura. And I think you're really putting the finger on an important role that we as insights leaders can claim and should claim in organizations in order to get a seat at the table and actually influence the direction of the companies we work with.
Kind of staying on that topic and maybe highlighting a limited set of opportunities you think are core for insights professionals to make sure that they really spend time on. You've highlighted the fact that we should think about ourselves as a team that can really unify the organization, but what else can we do to support true business impact and to challenge the status quo?
Laura: So one of the big things that I really challenge my teams with is having that seat at the table when decisions are being made, business questions are being asked early in the process.
Sometimes it is easy to fall into the habit of organizations to say “I need a study run on ”, or a product manager to say, “I need you to run a survey with these questions.”
Research should be involved much earlier, and I think one of the ways that unifying function happens is to make sure and really advocate for that voice of the consumer, customer, user. Like almost sitting on the shoulder of every stakeholder, and having that voice in their head as they are considering whatever decision they're trying to make about their product, their message.
Getting that seat at the table early, being involved in formulating what is the business question that's being asked, not just running a survey. “How is the information that we're going to provide you be used in a decision and what impact is it going to drive?”
Research should be involved much earlier, and I think one of the ways that unifying function happens is to make sure and really advocate for that voice of the consumer, customer, user. Like almost sitting on the shoulder of every stakeholder, and having that voice in their head as they are considering whatever decision they're trying to make about their product, their message.
And then, the last part, and I think it's very easy to skip over this in a lot of cases, is the socialization around the organization. We are expected to move very fast and sometimes it can be, “Oh, this group asks this question. Here's your answer. I'm moving on to the next question or the next business question, whatever it happens to be.”
But in a lot of cases it's “How do we use the learning over here and apply it over here?” I think that helps really build cross-functional teams, and it acts as that unifier we're all working the same body of information and people have a richer understanding of what it is they need to do and why we're doing it. Giving the organization a purpose.
Scaling insights teams
Thor: You're highlighting many very important points that we can bring with us. And I also know that you of course have an extensive career, but when you were at Zillow, your team went from 4 researchers to 16 in the span of just a few years.
Could you tell us a bit more about building and leading that team, what skills did you look for and how did you think about building the team culture?
Laura: I'm gonna share all my secrets here. The secret sauce if I ever look for another job. So there are a couple of things that I think are very important.
I'll start with the skill set and then I wanna talk a little bit about how I've had success building teams. And even in my current role, I've been at Realtor.com for two months, and I've already gone from five people to eight and I've got four open positions.
What I can't teach is curiosity. I can't teach a willingness to share and collaborate with stakeholders, how we can bring as many pertinent people into the discussion and talk about these stories with folks.
The key thing that I look for is really intellectual curiosity, looking for what is the right question to ask. Most people come into, whether it's real estate, whether it's tech, maybe not knowing a lot about real estate, or they've not worked in tech before, it's something where you have to learn the industry. We can teach that stuff.
What I can't teach is curiosity. I can't teach a willingness to share and collaborate with stakeholders, how we can bring as many pertinent people into the discussion and talk about these stories with folks.
I look for the ability to tell stories, the ability to communicate learnings. Because you can have the absolute best constructed, tightest, statistically significant learning data point. But if you can't communicate why it's important, how it's going to improve the product, the brand, how it's going to ultimately affect the consumer or user, if it just sits on its shelf, you just wasted your time and money.
Then the last thing I really look for is a level of ambition, what I mean by that is this kind of “go-getterness", this idea of “If I see a problem, I am going to go solve it. I'm going to help with this. If I take that next step, I can get a much better learning for my organization.”
I look for the ability to tell stories, the ability to communicate learnings. Because you can have the absolute best constructed, tightest, statistically significant learning data point. But if you can't communicate why it's important, how it's going to improve the product, the brand, how it's going to ultimately affect the consumer or user, if it just sits on its shelf, you just wasted your time and money.
My hiring philosophy comes down to three things. And I learned these from Robert Atencio, who is the former Head of Insights at Pfizer, he led insights at Walmart. He's been around the block, but he always told us “You hire for smart”, which is that curiosity, and “You hire for nice”, which is all about storytelling and communication.
And then Sarah Mayer at Zillow helped us add potential rockstars that are taking that next step, going beyond what was just asked into “How do I make this the best it can possibly be within the constraints of the project I'm working on.”
So that's my hiring philosophy. As far as growing a team, the thing that I have found most effective is really this idea, especially when it's a new insights function or a research function that's having to maybe come from a little bit of a deficit.
Let's face it, sometimes research can be like, “We have research and we checked that box,” you know, how you really get that relevancy and that seat at the table, and I learned this from my Walmart stakeholders and also, Rebecca Messina, who actually used to run a lot of research marketing at Coca-Cola.
She was a CMO at Uber actually during their IPO process and her little nugget that I have just latched onto is this idea of “Find a project champion, a stakeholder who is placed within the organization where they can really have an impact”. They can make a material change on a business product, brand, in a way that is going to move the needle and make them look like a rock star.
How can you take learning from someplace over here, be in another industry, and apply it to your situation? There are very few new problems in the world; they just are applied in different ways.
Give them something to latch onto that makes them make a difference in the business and who will talk up the reasons why they were able to make that decision. At Zillow, one of the things that we did, and I actually advocate for this in all areas of research is: how can you take learning from someplace over here, be in another industry, and apply it to your situation? There are very few new problems in the world; they just are applied in different ways.
I had been reading some papers around the medical industry where if a consumer or patient felt as though their doctor was empathetic, understood their situation, was sympathetic to, “I'm scared. I'm not in control of this situation. I don't face this situation often, so I don't know how to deal with it. I don't have the expertise to handle this.”
When a patient felt as though their doctor was empathetic, the prognosis and outcome of the diagnosis was statistically significantly better and faster, more of a positive outcome, and if you asked that patient what their satisfaction with the outcome was, they were significantly more satisfied.
I think that ability to be that storyteller, get that project champion, get stakeholders who said “This study, this learning made a difference in how I was able to drive my business.” I got more people from operations actually giving head count to my team than I ever got from the requisition process of, “Hey, I need researchers to do X, Y, Z”.
We looked at that study and went, those emotional reasonings sound very similar to what people go through when they're buying a home. “I don't do this very often. I'm not in control. I can't handle this by myself, although I don't really know that I trust anybody else. Oh my God, what do I do?“
And so what we did is we looked at how to help real estate agents be more empathetic. And when we were able to get that tied in, this actually became part of the best of Zillow program.
We implemented a satisfaction program for agents. When those agents implemented those programs, on the phone with their client, spending a certain amount of time answering questions, we watched satisfaction scores go up, we watched close rate, transaction rates go up, all sorts of things.
And so that was a huge learning, but I think that ability to be that storyteller, get that project champion, get stakeholders who said “This study, this learning made a difference in how I was able to drive my business.” I got more people from operations actually giving head count to my team than I ever got from the requisition process of, “Hey, I need researchers to do X, Y, Z”.
Who in the world of insights Laura would love to have lunch with
Thor: That is great advice. And Laura, I think this is the part that really hurts, because we've gotten to the end of our conversation. There's one last question that I just love to ask, which is: who in the world of insights would you love to have lunch with?
Laura: Can I have it be a group rather than a person? I actually kind of wanna know what is going on with the Fed. Like literally I would really like to hear their reason, for how they're making some of the decisions.
Is that a group that is taking into account not just the numbers that they're seeing in terms of economic output, but how these folks incorporate, or do they incorporate the emotional state, the needs, wants, barriers, like the lives of everyday people and how they are making decisions.
And that's a little bit of a cop out given that I work in real estate and so many of the decisions that the Fed is making really directly affect my industry. But that's an area where it feels like there is opportunity to expand from just that analytical world to really how are the stories, how are the people that are being affected by these decisions being incorporated into these decisions?
The other person that I admit I would, if I had to give a single answer, is actually John Dick at Civic Science. John is absolutely fascinating. He is hilarious. He has more consumer stories, and the most interesting correlations from just the omnibus that Civic Science runs. I remember I had him come do a talk at Bed Bath & Beyond.
He was like, “Do you know what the number one indicator of whether people tuck in their sheets at night”, which is apparently a very polarizing question, “Do you tuck in your bedsheets on your bed? And what is the number one indicator that you will do that?”
And I remember, he went around the room, “Is it just how you were brought up? Is it age?” It's actually height. Taller people tuck in their bed sheets so they don't kick them out. I was like, that's actually kind of fascinating. I'm not sure what you would do with that piece of information, but it always stuck in my head like, “Huh, the power of correlation in studies.”
It's just absolutely fascinating. John has a ton of those stories.
Summary
Thor: I really appreciate that and those are conversations I would like to eavesdrop on. This has been such a wonderful and insightful conversation, Laura. It's been truly fantastic to hear your unique perspective on leading insights teams and to learn about how you've successfully integrated insights throughout your career.
I'm very happy that you discovered that people and consumers are much more interesting than bacteria and yeast. If I play back some of the things I've learned today, it's just the fact that you've come to the belief that you can get insights from anywhere in the organization.
It's really about bringing all your sources together and connecting the dots. Create a simple, holistic story that enables the business to take data driven decisions. Also, make sure to position the insights team as a unifier in the organization and make sure research is involved much, much earlier.
Advocate for the voice of the consumer sitting on the shoulders of all key stakeholders as they consider whatever decision they want to take for the product or message. I know that I've learned a ton from talking to you today and I'm sure our audience has as well. Laura, thank you so much for joining me and thanks everyone for listening in.
Laura: Thank you.
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