Rethinking Metrics: When KPIs Are Too Basic for Real Growth | ExperiMENTAL Ep. 10

🎯 Is your marketing KPI lying to you?

In this episode of ExperiMENTAL, host Sundar Swaminathan sits down with Russell Tischler, VP of Marketing at Fundrise, to dismantle the myth of “good enough” metrics. From building predictive models that forecast investor behavior to questioning the ROI of lift tests, Russell shares hard-earned lessons from his time at Uber and Fundrise.

If you're a B2C marketer, data scientist, or growth leader wondering how to prioritize the right metrics without wasting time or budget, this episode will completely reframe your thinking.

Get ready for deep insight, no fluff, and some well-earned hot takes.

KEY TAKEAWAYS
• Shallow KPIs are often misleading and can hold back meaningful growth
• Fundrise built a day-90 model to better predict long-term investor value
• The 90-day predictive model offered better accuracy than day-1 projections
• High-capacity investors often start small, making early conversion data deceptive
• Fundrise balances low-dollar, high-volume vs. high-dollar, low-volume acquisition channels
• Direct mail is unexpectedly powerful for trust and high-value targeting
• First-touch attribution is underrated, especially for category-creating businesses
• Startups should optimize for speed of learning, not perfect measurement
• Most lift tests aren’t worth running if the gain is under 10%
• The best growth moves feel obvious, no stats needed to prove it

BEST MOMENTS

00:01:59. “What I do is use too shallow of a metric, and I’ve tried to help move us further into the customer journey.”
00:03:07. “How do we differentiate when we’re acquiring one of the 20% that's super valuable versus someone who churns quickly?”
00:04:43. “You can see where only looking at somebody's conversion behavior can be misguided.”
00:06:05. “The best growth marketers deeply understand the business and analytics, not just KPIs.”
00:09:02. “We started with wanting a 12-month payback period... the cost per dollar fundraising target.”
00:16:18. “We've been able to be pretty accurate by combining the human element with the model approach.”
00:26:42. “Direct mail has been awesome for large investors, really credentializing.”
00:38:06. “Almost any time we've done something really successful, it’s just obvious.”

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🎧 ExperiMENTAL is hosted by Sundar Swaminathan, Head of Data Science at Bounce and former Uber leader. This show is your behind-the-scenes look at how top marketers and data scientists make smarter decisions.

🧠 Expect unfiltered conversations, mental models, and case studies that help you cut waste, build conviction, and grow your B2C business.

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Transcript

0:30

we were really only measuring your initial investment amount. And I would argue the, variability, customer value on rise is like, wider than anywhere else that I've ever worked because you can invest$10 and people invest$100,000 million dollars. another like unique element is there are lots of people who are what we call turned up ours. And you're not just moving the KPI that somebody handed you. But you're actually Moving in business a lot of times, that involves Welcome to experimental, the podcast that cuts through the noise to bring you actionable insights in BDC growth, marketing and data science. I'm your host, Sunder, former head of brand data science at Uber and the mind behind the experimental newsletter. Join me as I talk with industry leaders who have driven growth at companies like Uber, Spotify and Netflix. We'll uncover the experiments, failures, and breakthroughs that lead to real results. Now let's get experimental. Hey, Russell, thanks for joining me today. It's great to have you. Yeah. It's awesome to be here. It's been a while. Yeah, it's been a while. And, you know, just going through some of the things that I know we wanted to talk about today. Like, there's just so much we can learn from you and you've got some really great experience. So, I mean, if you're up for it, I think we should just get into it. So it So one of the things you talked about, and something I'm very passionate about is choosing the right KPI. And what I loved is not like, hey, people are choosing the wrong KPI, but they're not choosing one. That's deep enough. It's almost a shallow metric. I think, like you mentioned, I'd love for you to share just what that means. And just a couple examples. If you have them. Yeah, definitely. I mean, I think a lot of times I guess I'll like. I'll probably wind up catching, like, a lot that that I say that, like, all of this is dependent on the type of business that you're working in, the like job, the marketing has to play, but yeah, I think over, over the course of my career, as I think about, almost almost every company that I've joined, what I do is, is, is used to shallow of my track and I've, like, tried that as much as I can, like when I join these companies to, to, like, help move us a little, a little further into the customer journey. And so, you know, when I think about, you know, Uber, like you've talked about us in the, in the newsletter. But, you know, marketing, like mostly used for trips and cost per first trips. there's so much variability. know, a lot of the companies and like, the lifetime value of, different customers, you know, Uber on the riders, I was like, you know, what are the use case like airport trips whatever, like seven times more, profitable than, than, like the next best use case. So, you know, what's like, how do you account for the value of, like, acquiring a business traveler versus someone who's like, you know, taking away from one mile trip every Friday and Saturday night? You know, the value of those customers is super variable. Same thing on the driver side. like most companies, you know, the principle is applied on the driver's side. So it's like, you know, who how do we differentiate when we're acquiring, you know, like one of the 20% that's super valuable, versus someone who. Sure. Like, they take that first trip by, maybe they're, you know, they're just like, they weren't great at figuring it out. And so they either, like, churn out after their after, like, their 10th sharp or their 20th trap. Or they were driving in, like, less valuable areas within driving at less valuable times. Things like that. And so, and then, you know, coming to fund drives, when I joined, we were really only measuring your, and talking about is, is, a private market investment platform so you can invest in real estate, private kind of venture capital. And so we were really only measuring your initial investment amount. And I would argue the, the very the variability, customer value on rise is like, wider than anywhere else that, that I've ever worked because you can invest$10 and people invest $100,000 million dollars. So it's crazy. And so, another like unique element is there are lots of people who are like what we call turned up ours. And so, can imagine somebody who invest $10 can be somebody who doesn't actually have that much money, or it's like their first time ever investing in anything. And so they're they just want to invest $10 was also a lot of people who, you know, make like six, seven figures in here who will invest like $10 thousand dollars. And for, you know, a month or two, they just want to see what the platform's all about. Returns are like, so what the investor experiences and then they invest like, you know, their next investment is $100,000. And so you can see where, only looking at somebodies, like conversion behavior can be misguided. And so, you know, so fast, just like it's so important, think one of the most valuable traits, like being a marketer can bring to our organization is like, you know, not just somebody saying, like, hey, here's the KPI that you need to move and and you just kind of like, cover your eyes. Okay, I'm going to do that KPI if I do a good job actually API that's an impact business. But you know, I think the like best growth marketers are those like that. Like, yeah, they do a little bit of everything. They're really good marketers but also like, deeply understand the business, you know, have a really close partnership with analytics, understand how to do, some depth of analytics, themselves and make sure that, like, you know, you're not just moving the KPI that somebody handed you. But you're actually moving. Moving in business a lot of times, you know, like that involves bringing to the surface, previous surface, you know, when you said, like, just just a more deep KPI, than that, like, you know, you're not just, like, hoping that somebody handed you the right metric to move. to really, I think important for UPS because I love that there's a lot there. So, you know, you framed it as like a marketing KPI is I feel like this, this framework though, or this thought of going deeper could also apply across product growth, etc. like, like, have you been able to champion that across her functions or where does that sort of like start from where you go, hey, I, I think this KPI is a bit too shallow. For sure. Yeah. I mean, I think always naturally starts, at least for me, in marketing, because I find my, you know, functional, functional area, but really, within our data visualization, I work with our analytics team to create, know, created a model, that predicts where how much money someone will have on the platform at 90 days and also up there in 65 days. And so, you know, I think first step is like you gotta, like, pitched the idea and sell, sell the idea that, like, this is valuable to do. having an analytics partner who can make it happen is incredibly helpful. But you gotta, like, every person that you know, you work with along the way, you got to sell the idea to, so they, they believe in and also and, you know, I think for us having it added to the data visualization tool, just like that puts it in everybody's hands, you know, and then as, like, as I'm working with, marketing team, voice faculty and product team, you know, making folks aware that this exists. You know, I'm kind of continuing to ask questions like, anytime you see someone just reporting, conversion amount or like a single transaction value, I think just continuing to try to say like, hey, you know, have you thought about pursuing, what the sales behavior, like down the road and, and reminder that we have this model built into, built into our tool that, you know, you can just join with any user, and it's available to you immediately. Yeah. So we just even logistically. Right. So I guess let's take sunrise as an example. You've got a KPI that originally may have been funded accounts or just number of funded accounts. And you wanted to move to this more deeper KPI like what would that new KPI actually look like? What is it? How do you define it? Go through that a bit. Yeah. That's awesome. So, I guess take a step back. the way that we think about marketing efficiency is more so around payback period. That's always kind of how how it started. And I'll say honestly, that was I like thinking about it in terms of payback here and a big difference from, well, like, know, there's just like so much money sloshing around inside the company that it's like, nobody really cared about marketing having a 12 month payback period. You cared about how much you could grow because it was like, you know, such a different competitive environment, such a different, you know, fundraising environment or, and so, again, like you said, of going, like, I'll probably has a lot of accounts, a lot of these things and like, it depends what scale companies are and all of that. And so we started with wanting a 12 month payback period. And so our, our like efficiency metric is the cost per dollar fundraising target is just what what our margin. Yes. And so making sure like that's like the whole reason. So we used like when we were focused on just the conversion amount, we were like trying to just generalize and extrapolate that to, to 12 months, Estimate. And so we'd say like, x dollars. Then there's like the target for cost per initial investment dollars. And we just said like, okay, we think if we can hit that like that generally translates to you know, to y and cost per dollars fundraise. If you, if you like, just generalize what some will be. At their 12 month mark. And so you know, I think, big thing is like, you know, anytime, like, you join your joining a new company, it's just like, especially in the first three, six, 12 months, you're like, figuring out your specific function, but also like, just learning, just like the business how like there's behave. It's like everything. And so, you know, the thing the thing that I learned quickly is like, holy crap, you know, people are investing $10 or they're investing like $100,000, and we're not accounting for any of, there's also like we have certain channels that are good at driving a high volume of lower value custom. I mean, some channels are going to driving, low volume of high value, just, and so figuring out how do we, like, make sure that we're creating the right mix of those channels together? We're also instance like our, our funnel. Within our conversion funnel, we ask you a bunch of questions. That are like, are you an accredited investor? If those are promoter accredited, Jeremy Irons and, you know, above a certain amount of money, and we ask you about, like, if you're satisfied with this investment fundraise, how much would you, you know, how much would you potentially vast, vast bunch of different questions over time. And through that we created this picture, we've created this, this dimension called capacity. was basically allows us to, like, classify, you know, how much money do we think you have, regardless of how much you actually invested? And so one thing that became clear when we were only looking at initial conversion about was we'd have these people who were high capacity based on their responses. And there are lots of high capacity, investors who immediately invest lots of money, but also offer high capacity investors who would invest only a lot of money. Upfront. But then when we were, now and looking like, okay, let's just take a snapshot of, you know, how much money you do, all, you know, what's the average, investment amount that high capacity investors have on the platform? We would say like, oh, actually, like, kind of tends to merge over time. And that's why they invest in initial. And that was like, you know, it's like various light bulb moments that go off as your, know, like I said, you're like doing your job of like being a marketer, but also just like constantly looking into user behavior to understand the business. That's where, like, there's just various light bulb moments that go off over time. I think like conversations with, your manager, and like leadership. Those like, those are great conversations to have as well because you're like hearing how folks who have more experience are thinking about this with like a broader lens, thinking about it. So there's just like various light bulb moments that go off over time. You're like sometimes we're not like, something's not right here. We're like unnecessarily blind to a bunch of these different things. And that's that's why. And, having close partner in analytics is super helpful. Like, you and I work super closely together. And you were. That's awesome. You know, I've had had some close partners, analytics and fundraisers as well. And so, you know, having having someone who's like, understands where you're trying to do, understands the business, is a good data scientist and can like, you know, make the thing happen that you're discussing sitting down and kind of like, I think to to everyone you want to like, Aruba was like, such a dark, dark and, like, investigation culture, which I was like, great. We got to, like, write a doc and, like, start an investigation. That's like, one of the things that, like, gets me going. And so, you know. right. Like write a memo, like what you're seeing, what the problems are, what the opportunity is. We can solve the, you know, what's like the potential benefit and just kind of build momentum around that start to scope out like, talk to the folks in analytics who are like the subject matter experts on how to actually make this happen. and work really closely. And, that's where we're like, started out, we built a model that can predict, at day 90, how much money someone would have. We tried to build a model that would predict a day during 65 how much money someone would have. We found like, okay, day 90. like, error bars were pretty small, so we could, like, really reliably do that. Felt really good about it. And, but when we tried to, extend it to 265 days, error bars got pretty wide, because, like, so variable. And so we were like, okay, let's just, let's like 90 days can be better on the one day, let's say I was right about 90 days. So we moved to 90 days and we were like trying to remember we're not we used to use the 90 day model for six months or a year, maybe, until you're like, just more light bulb moments that continued going off. And ultimately, what what, we wound up doing because with, like, purely just just the model based approach, we, we could never get the error bars something that was acceptable because there was like, know, our business hours probably with every business, you know, that like, thinking beyond just like the reporting that marketing is doing, there's like a cash flow management element to these numbers being right. And so, you know, in our business, the real estate team wants to know, like, how many dollars are they going to need to deploy, next year. And so like when we were growing really quick, the challenge was like, do we find enough, enough good deals? With all of this, all these dollars that, like, the growth org is bringing in, and, you know, you don't want to put real estate in a position where, like, we overestimate or we underestimate. It's like a tricky position, because there's, like, physical work going into, like, sourcing those deals and committing capital and all of that. And so what we wound up doing was creating a manual production process for a 91 to 265, and that has helped. certainly more labor intensive to do. And so I essentially I take the 90 day model, which is totally, totally model based. And then I map out, like by top by monthly cohort. You know, what is our, like, current growth rate and what has historical growth rates look like for, for monthly cohorts that are like already fully doing 65 days mature. And then I'm looking at like, okay, for these like newer cohorts, how does their 90 day model growth rate look compared to the past ones? And then based on that, I'm making, I guess, like, I mean, manual sound sounds like kind of terrible. probably like, poisonous to to scientist. To hear that. But the error bars are just, are just smaller because, like, it doesn't have to be built into this, like, one size fits all model. we've been able to be pretty accurate by, by kind of combining the human element. What's the model approach? Yeah. That's really cool, because it's really like you're predicting instead of trying to predict 365 day a day one, you're predicting a day 90. And so you've inherently got more insights. And how much time do you need? How much data do you need to get to the 90 day insight. Is that almost instantaneous or like is that over after a couple of weeks? Like what's what does that look like? Yeah. The 90 day model predicts on day one. And then. And then to Reaper that song, the seven day 30, day 60, and then actually, this is undeniably, And so it takes into account at the user level, you know, like there, there are that's like the one element of introducing the manual piece for 91 to 265 days is I'm not trying to predict anything at the user level. I'm just I'm just applying a general, grant for the 90 day model. Because that's like, you know, actually, mathematical model is predicting banks at the user level. Oh, cool. So the day 90s at the user and the 365 one is at the cohort level. Yeah. Really cool. Really cool. And I think what's really an interesting takeaway here is just how Fundraises business model is so different than the average B2C tech company. Specifically around you guys actually have an opportunity cost if you don't invest at the right time. Right. Like if you sort of like you've got you underestimate how much cash you're going to have. And then all of a sudden you have more and it's just sitting there. Or vice versa. This is like that's pretty rare for most BDC companies. Like how have you thought through that as a marketer? Just understanding our business model is way different than most companies. Yeah. That's where, you know, I think going back to what I was saying before and, like, you highlight, you know, cash drag, bad. Because, you know, you can imagine, a real estate deal that's out there and you can be investing in that will deliver, you know, 10% or 10% annual returns, which is really good. you have cash just sitting there, is, you know, maybe returning just forever, whatever the savings rate, or, you know, whatever the money market. Right. And stock shot. So that's a pretty big opportunity for us if you, if you like, miss this forecast. that's where this model is super important. You know, I think the thing that, yeah, maybe it's not super unique to ask is everyone, like, there's always financial implications of of missing a forecast, but I always try to be like, you know, with our model and our, our prediction, try to be like 5 to 10% to conservative, because there's like, a real problem if the deployment team thinks there's going to be more money than there actually will be. another thing that I've been thinking through is, like your user base and, like, your average order volume, if you will, is so different in your number of transactions. So different your frequency. Like how like going from Uber which was low of high frequency to sunrise, which feels like it would likely be the opposite. Walk us through like how you're you know, just you as a marketer, how you've evolved, how you've changed, and also how you think about marketing at Fundrise. would say the biggest difference is, I mean, numero is just like volume and volume. Volume. And certainly funnel wise is volume, volume, volume. Like, we're not small. We're not like, you know, we're not, Goldman Sachs wealth management. I don't know how many clients they have, but but like, we have 400,000 active investors on platform. And we've got around $3.5 billion on the platform. And so it's not like a, it's not B2B, you know, from a scale standpoint where we're just like, okay, how do we find how do we find like ten people this month or, you know, this week who well, who want to invest $1 million? And so the biggest thing is just like, you know, I think, like everything with marketing's, it's like a little bit, a little bit science is finding the right mix, because you can imagine, like, hey, we want to raise,$100 million this year. You know, you can get there with smaller number of high dollar investors. You get there with a, large number of small investors. And so I think that's like, I think that's been the biggest difference is like figuring out how do you put that puzzle together of how you're going it. Get there. Because we definitely found, like, if I try to focus too much on really high quality customers, that can just, like stop our growth, because you think, like, hey, like I should just, like, I should only focus on this audience and hope that I get enough, you know, $100,000 investors. But it's like it's a really risky approach because it's like, all or nothing. you're not convincing those folks. And so another stop signs like almost impossible that are goals only focusing on smaller investors. And so you've got to find what that right mix is of to deploy dollars, what channels, what partners to work with all of that. Because inevitably every year, you know, we had we had our goals or, you know, our output is like, you know, some combination of, of, like, a decent percentage of large investors and a decent percentage of small investors. And like, the economic environment plays a role in, certainly like, managing share especially over the last five years since I've been a founder, I said, I would guess that, a tech one outside of like 2008, you know, probably like one of the more, volatile economic area, to join somewhere. And that's, like, affected everybody's, everybody's business. But isn't that what is it, different times? it's been like, you know, you got to, like, really have your finger in the air, to, like, figure out which way the wind is blowing. Because that's like, on January 1st, I can say, like, here's the approach that we're going to take, but, you know, something happens with interest rates, or like, stimulus checks happen or whatever has happened. You know, in the last, in the last five years. And like, you got to just be able to read, read the trends and adjust, on the fly, though the other thing, from a marketing standpoint, it's also true from a product standpoint is because large investors know, such an outsized impact. Fundraising. Well, thing that's hard when you're running, like list tasks, whether it's marketing work tasks or whether it's product tasks is, you can have your treatment control split out. And You can't just take the top one numbers when you run those tasks, you have to like look under the hood and see like, okay, here's how much money was fundraising the task? How much money was fundraising? The control? Like, okay, how did that how does that come in? So from, like what was the breakdown? Because one, you know, say like there's an incremental million dollars from the stars and you looking in the test group, it's like, actually, we had to like$400,000 investors. No, there were like, no large investors in the control. And then you've got to, like, continue to dig in like, okay. This is like actually caused by the test variable. Or is this just happenstance. And that's where it's top for I get, you know, lots of tests, you know, like look at the results and then look at the user level behavior and then we'll like have a meeting and not like not just talk about the results but talk about like our hypotheses and why we think, that like was causal or wasn't causal, etc.. And so it's stuff like stuff. Okay. You need a wire. This can be like, you know, it's fun because it's like like I said, like investigations got me going. So the more more investigations, the merrier. It's definitely fun, but, you know, it's also it's also like, because, you know, Uber have their own like, version of, of, like nuance in, in different tasks then and it's just like just something, you know, you deal with and like, especially at something, you know, as you're at companies for longer and you understand what the 360 degree view of like how the user behavior, operates, it's, it's just interesting conversations. Figure out how. We could just talk about testing for so long, and I think because you've got some really good things on, like, how to how startup should think about testing that we'll get into in a bit, but, can you share a little bit more about the channel, maybe even marketing strategy, given that you have to run, you know, a low investor, value in a high investor value strategy at the same time, like, how are you doing that? Yeah. For sure. Different channels do different things. And so, you know, like a good example like paid social guess as tons of investors. for the most part, they're investing, like, you know, an average average investment of, less than $2,000. are they the classic paid social channels or any surprise channels in there? know, mostly, mostly matter. We've tested we've tested on Twitter, and we've tested on, like, LinkedIn and Reddit. you know, back in, like the GameStop is right about it was it was hot for a little bit. and we stopped advertising since I'm kind of interested in going back, especially now that they have their deal with Google. And like the traffic is it's going up so much and they're, you know, they're like almost pinned to the first page of Google results for, for like everything. I want to go back there. We haven't gone back yet. But yeah, when I say paid social talking about, and so that's like a classic example of a high volume channel, lower dollar investors. But then like, we, I don't know, maybe six months or a year into, into when I joined sunrise, we, we started building out our direct mail channel. Direct mail is then awesome for large investors also, because it's so addressable, it's really nice for like, I mentioned the capacity network that we have, it's really nice. We can segment out our leads. And, you know, like it's direct mail. Like, impression basis is super expensive. And so it's tough for, like, low and medium capacity leads back in our necks who just are just challenging to, to send them a physical postcard. Once you know, like, a retargeting impression, Facebook or, like, display signs for that audience. It can be it can be pretty efficient. But anyways, direct mail. Yeah. From a retargeting standpoint, a really nice way to get, to reengage with our high capacity leads would gladly pay, you know, whatever $0.50 per postcard to, to get in front of that. from, prospecting standpoint, we're able to build out a lookalike model, based off some of our larger investors. And, you know, it's interesting. There's, like, when think about the type of investor that we're acquiring, we're going after different channels. there's the audience side of it. And then there's also just like unnatural channel element that we found, because like the same lookalike audience that we use for direct mail, we use that same lookalike audience. Now, and the average investment on that other side, you know, $2,000, an average investment on direct mail is is like $10,000. Yeah. So there's channel market set to. Exactly. And it makes sense. You think about, like, direct mail or super franchising. I hear all the time, like, I almost never hear from people like, hey, I see your Facebook ads all the time. Or Instagram ads. Yeah, all the time from, like, my friends are texting me pictures of our postcards. Yeah. And we hear from, like, some of our real estate partners, we hear from some of our venture partners that they're seeing our postcards, and they're like, this is cool. You know, there's like, cream it's a lot, Jar or similar sounds. Credibility rules. Everything around. And, you know, as a, as a financial success, as an investment business credibility is like the thing that you're, claiming and striving for, it's a non-negotiable. And so, you know, if you think about a channel like hearing about an investment social media, it's like, you know, we fundraise. Fortunately, we have, like, a really good brand. Been around since 2012. We have, like, a good track record, all of that. And so once you start doing research, who's got, like a five star rating with NerdWallet, etc. once you start doing research, you like build that yourself. But the nature of social media, like people typically see an ad, you know, it's direct response. We've seen that and they convert right away. And so, yeah, there's general market fit, direct mail, you know, the hypothesis is, it's just like a really credential izing channel. It's like, oh, like they're sending me a physical postcard that's like something that something that, like, legit companies do, like, I get physical mail from SoFi and American Express and, like, Swiss, yeah, and I don't I don't get okay mail from from, like, you know, like crypto stamps or something. And so, you know, that's like the hypothesis for, for why, there's like the difference in channel markets that, and then like, podcasts, you know, since we're talking about a podcast, I got a shout out podcast, like, that's that's another awesome channel for us. That gets us, like, gets us, you know, really, really high quality investors. I think we're going to have to have you as a follow up because, we're having another conversation because, you know, direct email on podcasts and, just like it's so many marketing channels that a lot of marketers don't like, speak about. Yeah. Yeah. because some really, really cool stuff. I'd love to dig into. A bit of like, it's like I'm making a call of a lightning round, but kind of quick. You've got, like, a lot of good nuggets on on startups in particular. And what, they're not doing great. First thing. Trying too hard to get measurement right. And it seems counterintuitive. And as a data scientist, I agree. And as a data driven marketer, you agree. So there's something here. So what do you mean by, you know, companies are trying too hard to get measurement right. Yeah. I think there's two, two ways I look at it. One is the marketing and the data science community. The fact that, like, there's. So president I'm like, you know, a Twitter addict in some fact there's so present on Twitter and like newsletters and everything's awesome. Just learn to be really smart people like you who write about their experiences. But naturally there's like, selection of survivorship bias where most of the people you hear from are from like large DTC brands or, or like really heavily venture backed companies, that are like doing tons of revenue. And my fear is always and like, I feel this way because over the course of my career, like each company I've worked has been successively smaller, than the previous. And so if you, if you like, just keep adding to things like if you just keep trying to like, work like in my first job, I work for five DirectTV, and then I worked up, like, Major League Baseball and Uber. It's like you try to like bringing these these, like, fortune 500. Ask, like the the approach to marketing and measurement there. And fundraising is like still big. Like I'm talking to like I think the majority of marketers probably worked at like smaller companies. And so you're hearing from people who have like massive, troves of cash, like really like almost unlimited resources and put towards things. And if you were like, oh, if like, you know, if Uber is doing that and I, I should tell you that. And the reality is like, no, you probably shouldn't, especially because, you know, they like if you're running a series, a startup, the thing that matters is not like measuring your marketing 10% better or like making your marketing 10% more efficient. I think a lot of people get hung up on measurement as like the thing as like a marketer. It's like, oh, you're actually a marketer. And you figure out how to measure the things that you're doing. If you spend all your time spent no time figuring out how to measure, it's like you need to grow. It doesn't matter if you get 10% better, you need to get 100% better. So like, raise your next round to, like, grow large enough to have an exert whatever, whatever the whatever, like the short term, the long term goals, especially in startup. It's like almost always you need to grow fast, and like find new things that work. You need to focus, on that, like doing marketing. And so like, you know, tons of talk about, and less testing and all that was, was great. I love it. Like, I'm a data guy. That, like, we worked on a lot of that together. I love that stuff. But, like, there's just not I don't think there's a ton of value when, like, the thing you need to do is figure out how to grow. And when you're at a smaller company, we certainly are obvious because you're not that big. There's not a lot of like, organic growth coming in. You do something that works. You're building an out, you know, and then the other side of this is resource thing, like, we're we've moved into this era where resourcing is extremely finite and teams are getting smaller. And so you just have to be ruthless about what you prioritize. So, you know, you're spending ten, 20% of your time, like, trying to perfect measurement a lot of your time. It's not focused on actually finding like a new lever for growth. Yeah. I also think there's an irony to people thinking Uber, you know, has, like, perfect measurement. I think Yeah. like, I, I've had multiple conversations and I was like we, we looked at blended pay plus organic on the rider side for up until 2018 and even We should. that. So, know, there's there's always this idea that bigger companies are more sophisticated, which is also not true. Yeah. I'm like, there's only people who sell you off track solutions. then like. Like some of them are probably really, really good. I saw now, like, shooting on the off the rack solutions, but a lot of times, like, you don't understand it because you're not working. You're not like, you're a marketer, you're not a data scientist. You're not like working with someone like you on the inside. Like understands how this model is being built. It's like, okay, I got an author solution. Now I need to spend like however much time over the next six months, a year, actually, like getting under the hood and making sure that I can validate that this thing is pointing me in the right direction. Otherwise, like it's a net negative. If you can, if you can validate you spent the money, you spent the time, to try to integrate this thing. You kind of touched on it a bit, but something I think when we were just exchanging emails that you and that, that was really cool to chat about was like lift testing is a necessary. It should be pretty obvious. I love that statement. Tell me a little bit more about or you're saying there. Yeah, I think I mean, along the same lines, there's, Yeah, sure, sure. Like a larger company and you have lots of organic growth, then. Sure. Like spending an extra 10% of money, like ones that actually 10% of money might not actually be super obvious. And also an extra, like, even 5% of money, 5% of your budget could be like a massive amount. And so there's definitely different, different strokes for different folks. So it's definitely not a blanket statement, but, you know, for us, like you know, some like eight figures, it figures on marketing, and even still, like, it's just super obvious when we do things that it's working and like, just, like, not good enough to, to spend your time, things that are only going to like if I need a less test to see that something was 5% better. great. I made something 5% better. But also, it doesn't matter. Most of the time, my tools are aggressive enough that doing something 5% better, I would have, like, the opportunity cost was large enough that even though it gave us more dollars, more investors like it was. It was like either neutral or not negative because I wasted my time on And so that's why I like I don't know, yeah. It depends where your resourcing is, but it's just like, a lot of times it's obvious when, when you're like, try a new lover and you're at a, you know, we we started running with a new podcast, as part of the deal. This is something that, when we got someone to source the awesome job, finding this opportunity, to start running a new podcast, we were able to include an interview our CEO and founder on the podcast. stock Alois podcast. You're familiar with, and so so. Yeah, like, like you said earlier, podcast. Really kind of hard to measure. We use most, you know, we use vanity URLs and I. How did you hear a survey for it? obviously, like, you can actually, like, podcast can actually run a less tests, but it's a good example of, like, we couldn't run a list to us. And so in the past, you know, with other podcasts, it's possible that like, you know, you spend 100 K on a podcast and like, maybe you see, like if you squint at the data, maybe you see something, it's like, I'm probably is not going to keep spending 100 to this podcast if I need to squint at the data. Because it's like 100 K that I can't spend on a new bat, it can have like an even greater impact. this podcast, like, we started running and the first week, not just our podcast, like, line in, in the channel chart went like this, but like our direct line, you know, like, organic, you know, unattributed growth also started, shooting up and, you know, just like, super obvious, like almost any time that we've done something really successful, it's just like, obvious. I like anyone on our team to look at the chart and know that we did something that worked. this is fantastic. Because we have so many stories like this. Both like when numbers go up, but also you do something, the numbers go down, and it's like it's pretty obvious. And no company unless you're, like, 20 years old, is at the stage where you really like you have to squint only to see results. Like we're we're always at companies that can move and break stuff quickly. And there's so much like low hanging fruit in a way, over time. So like, I love like I just another story of just, hey, just use intuition and take the risk and call it a day. Like, was it causal or not by the pure definition. But like, we're pretty, you know, pretty damn sure about that. Well. is cool. It's like it's it's just a good like thing that I just, I want, like, more marketers to share because it's really how most decisions are made. Yeah. I mean, I think, like, a perfect example you and I worked on together was like, I think you talked about it in your newsletter. Was, ten the penetration announcement in while I talked about shutting off writer's spam. I was like, we shut off this band and nothing happened, you know, like, it was. It was like, almost as simple as that. a way, this is a good segue into another great take. That first touch attribution is underrated, and I can't wait to see the comments on this because, like, I love where I think you're going to go with it, but I feel like people are just going to come out of there, come out of the woodworks for Yeah. me a little bit more about about why you think First Touch is underrated. Yeah. Again. I'll, I'll. I couch this and, it depends the type of business, I think, like, rise is somewhat unique because, you know, I like when I think about startups and companies in general, there's, like, you know, there's, like, people who are building a better mousetrap. So it's like, you know, are you making, like, cooler t shirts than what already exists is already a massive market for t shirts? People are constantly looking for new shirts. And certainly people are always looking for new investments. But like, for us, discovery is the hardest. It's the hardest problem. We're like really building a new market that wasn't before, before us or wasn't really a solution for retail investors to invest in the private markets. And so we're like building a new market and the hardest thing is to tell, tell new people about your product in an interesting way that makes them aware and gets them interested. I don't really care, like, you know, search, fundraise, six months after you heard about us, podcasts that like, does we know I would attribute like virtually zero value to that. And so for us and, you know, I think for, I think for lots of businesses like the scales are like almost always going to be way to, towards, towards last thoughts for like, whether it's like data reason, you know, there's like data is the cleanest most of the marketing platforms. It's advantageous to them to focus on last time, especially like Google and Facebook. Multi-touch is I haven't seen a good solution for multi-touch. Maybe I'm blind to it. But yeah, multi-touch is is like a pipe dream. Like always was. At least before, you know, before five to cookie deprecation and all of that at least was like closer to being solved. Was on that like a path. But yeah, like most most companies even, you know, years, you know, a few years ago weren't using we're using multitasking. So you're basically like choosing between lost touch some kind of some kind of spread or first thoughts. I think you talked about this in one of my newsletters or on LinkedIn posts where it's like reliability, like consistency and reliability, and the attribution model is like the foundation. So you need to have something because you're it's like always part art, always part science. Maybe the most important thing is that, do you understand? Like the kinks are there, But there's of the song was talking about, like, running a business. Like, once you're out of business for a while, you're running it. It's, It's like I'm running, like owning an old car, looking at car really, like, understands, you know, it's like, got like. It's like, if something's not running right, you want to go like elbow. It's like, oh, I seem to like knock. But I'm not. I'm just I'm, I'm it's like, oh, I got to like knock that like motor back into back into place. You just like, know all of, things like different libraries and different things that can affect like how the data looks cool. And so, you know, there's like, it's kind of nothing wrong with any attribution model, so long as you understand, like, it's natural biases. But I just think it's like it's so much harder to tell somebody about your product that's like the hardest thing that you can do then to get them, like to tell them about and get them to, like, actually engage and like click on your ad or whatever it is, than it is to, you know, the first step, I guess, like easiest way to say it's the first step is a lot harder than the last step. that's the thing that I care about. I'm certainly aware, like, I'm very aware of the different, touches that happen. But I just like my preference, my biases towards first thoughts because it just it just tells you, what is driving people's attention. I think, like. Especially when you're building a new market. Like, that's a really, really, like, just great insight from you on just that nuance. I know we're at time, but if you've got time for one more question, just what are you excited about? Marketing wise, your fundraising, what's on the what's on the horizon for 2025? I think the biggest thing I'm excited to work on is a lot of our attention a little bit earlier with, with, like, how addressable the retargeting is through through direct mail. retargeting has gotten a lot harder over the last couple of years with, like, cookie deprecation, all that. You know, even with, even with, like, Matt, trying to do retargeting when you're prospecting, you're like, also do you do some retargeting? You know, you don't necessarily want to be and, know, with, with like retargeting match rates are hard. And also it's like a little tough to be as exact. So I'm pretty excited for us about, you know, working on, spinning up a lot more addressable retargeting, even if it's like smaller, primarily focused on, like smaller, super valuable audiences, how we can create more touchpoints with them. Yeah. I think the thing that's interesting with those audiences is, which is like, you know, it's a little opposite of like typical DTC and it's, it's like opposite of, you know, having like a really data backed culture, but like the tendency to say, like, okay, we did this thing, we did it for like two weeks or months, like, okay, how's it go? And some, some of these, you know, the conversion journey for, for particularly folks who are, high value is longer. So, you know, you kind of have to commit to a longer, a longer test period. So that, you know, you can make sure that you understand whether what you're doing is, like actually impacting things. So that's like I think that's, that's the biggest thing maybe that, you know, we probably haven't done as good of a job in the past as we kind. Is like, rather than focusing on just like, know, I always say, I always say to my team, like, we don't need to get in front of 100 million people. Let's get in front of, like, 50,000 people and really grab their attention. And that's like, I think that's kind of like flows up into that, into that strategy, of just like lesson lessons more really focus on like depth of integration wherever we can. That's where like podcasts are really good right now is really good. and then from a retargeting standpoint, like, how can we like really, you know, like sending these people handwritten letters. So, you know, how can we helping, like really build, that integration with these people. actually just going to ask you if sunrise is going to do a Super Bowl ad next year, Yeah. well I mean, again, I'd love to have you back on. There's so many cool things we talked about. But Russell, this is great. Just one catching up and part two. Thanks for sharing all of all of your wisdom. It was really awesome and a lot of fun. course, it's fun for me to, Great to see my. I take care. care. Bye. Thanks for tuning in to experimental. 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