Name: Extending Your Company’s Runway
Uploaded: 2025-05-21T18:16:10.730Z
Duration: 40 min 54 s
Description: Extending Your Company’s Runway

Transcript for "Extending Your Company’s Runway": So hi, everyone. As I mentioned earlier, I'm Paul, and I'm part of the product marketing team here at Mixpanel. I work with many growing companies to understand where they get stuck in their journeys and how they can make better decisions. Our main speaker today is Abby. Abby is a product manager here at Mixpanel, And not only was Abby a solo PM at a series a company, she led her start up to massive growth including an acquisition. So at Mixpanel, she talks to hundreds of growing companies like yourselves to help with their product analytics strategy. So she's seen what's worked and what hasn't worked. So without further ado, take it away, Abby. Thanks, Paul. It's quite the intro to follow. Hi, everyone. My name is Abby Braiman. I'm a product lead here on our, start up and SMB business, as Paul mentioned. I used to be a solo PM, so deeply relate to a lot of the challenges facing start ups and SMBs and and, talk to a lot of companies here internally facing a lot of those same challenges. So everything from getting started to what to measure and why, all those sort of those types of things are the things that I, I spent a lot of time on thinking about. And so excited to, chat with you all today. And to get us started, I'll just quickly talk about, maybe a little bit of sad slide, but a true slide here, which is, why most startups die, and why yours doesn't have to. And, really, this is not data from Mixpanel per se. This is just industry wide data on why startups fail. We have three reasons on the slide, but you'll note that the third kind of underpins the first two. So first reason startups fail, they never find product market fit. So getting to real kind of escape velocity on on people loving their product, getting down the funnel, doing all the things that, the company wants them to do and and really loving and coming back to the product, talking more about it, things like that. It's really hard to find. Famously, product market fit is one of those things where you know it when you see it, but there's actually a lot of signals that can help you get there. And we'll talk about some of that today. The other reason the other big reason we see that that a lot of companies fail is from high customer acquisition costs. So if it costs you too much to acquire a customer relative to what they will actually do for you from a business perspective long term, you're kind of backwards from a business perspective to begin with. And those are really kind of the two big reasons we see. You see a third here, which is ignoring data. That's kind of the underpinning of, all of this. Right? So you can use data to infer whether or not you have product market fit. You can use data to measure pack, all of these sorts of things. And so, really, it comes down to, are you able to use the data to understand what's working, what's not, and and so on. And I'll call out here this isn't just, one form of data. This is talking to customers. This is qualitative data. This is watching session replays. This is looking at funnels, all of the things. All data is, all all data formats are valuable, and, having kind of that 360 degree picture is really, really important. And so getting that being really, data driven in that way is, one of the things that helps you find product market fit and help you understand your pack, in order to build a business. And so companies that don't do this often fail, and that is, the reality of of being at start ups and small companies. And so we'll talk today about kind of avoiding some of those traps, how to survive and how to pivot and figure out where to double down. So to start, a lot of the challenges that I hear internally from companies today are around kind of four big buckets. So the first is it's really hard to know what customers want and need. Right? And this goes straight to, customer acquisition and tech, which is, you know, what do my customers want? What do they need? Do the things that they tell me they want. Actually, are those the things they want? How do we actually figure out what to build and what to do there? Second is, you know, there's no shortage of data. I just mentioned a whole bunch of formats. There's talking to users. There's session replays. There's analytical data, all sorts of things. But knowing what data actually matters and separating signal from noise is a real challenge for many for many, companies. Following that, some more tactical questions, the things that we do hear about are things like why why can I get users to sign up, but they don't stick around? Right? I can get the sign up, but I can't get them further into engaging with our product and doing more there. And then, you know, which features if I am getting engagement or if I am doing these things, which features are working and why? Which ones are, you know, helping me actually build the business? Which ones are, fluff and that sort of thing? And so these are common questions we hear from a lot of, a lot of customers. I myself have personally faced them. I I guess for everyone on the call here, do any of these especially resonate? Are there others that that come to mind for you? What's top of mind for you all? I mean, these resonate with me, Abby. We'd love to hear what the chat thinks. And this happens at many levels. Right? This is at company level. This is at feature level. It's hard to know if the feature is serving the thing you want, all these sorts of things. What are the other challenges that that folks hear? Signal from noise. Yeah. Yep. How are they what are they enjoying? How are they interacting with it? Yeah. Bro, he brings up a good point. Not every customer segment's the same. So one customer might wanna need some one thing. Another customer might want another. Totally. So these are the common challenges we we see. I will talk about, yes, how to know when to iterate the product, what what feedback is good. And let's talk about some of these. And so the things that help people break through a lot, are, one, getting insights in real time. So you see, we hear a lot from folks about getting insights in, in a speedy way. This matters particularly when you're a small company and you're shipping fast. You need those insights quickly. And if you can pinpoint the thing that you shipped and what it's actually done for your for your different metrics, that's important. So having that really tight connection between shipment and and analytics and having that speed is really, really important so that you can understand what's working and what's not. Tied to that, seeing exactly being able to get precise. So not just fast kind of rapid iteration, being able to get precise around where exactly are users getting stuck, what exactly do they not like, what's not working, and actually optimizing and understanding very specifically the points of, of friction that the customers are having is really, really important. And then finally, the other thing that we see is, frankly, with a small company, data literacy really matters across the company and being able to get these answers quickly. So getting them fast and getting precise on it quickly is going to be really important, and you want everybody at the company to be able to do it. Right? You don't have time, you don't have energy, and you don't have the resources to have somebody just kind of doing this analysis for you, pulling it as as kind of ad hoc reporting. It has to be real time. It has to be something that everyone in the company, can kind of get access to and understand quickly. And so, you know, we see a lot of these challenges around, separating signal from noise, figuring out what's working. And, really, the the solutions to that are, one, can you get real time or very close to to to quick insights here so that you can understand if I change this thing, what does it do and have that really rapid feedback loop? Can you get really precise? Precision is the other piece of this around. Can you get precise on what's working? And then and then finally, can can everybody at the company speak the same language on this and get to get to insights quickly and precisely? So today, we'll spend a bunch of time talking about both navigating survival mode. So when you're just getting off the ground, how do you actually figure out what's working and understand your users with very, very limited resources? And then we'll we'll double click on actually understanding what's working and figuring out where to place big debts, where to double down, where to optimize and spend those limited resources that you have. So from there, we'll start by talking about survival mode. And we'll start with one of the one of the big things that we've heard in the chat here of separating signal from noise. You know, data really matters. Startups fail when they ignore data, but not all data is created equal. And so we have on this slide you see here examples of metrics that I hear over and over from companies that they're tracking, things like time spent on-site, things like cap, consumer acquisition cost, number of likes in social media, number of press mentions, activation rate, email subscribers, and the number of countries that something's downloaded in. I myself have tracked all forms of these metrics, but not all metrics are created equal. And vanity metrics and and the ones that don't matter are easy, to get distracted by. And so what really matters is focusing on the right things. And, really, when you're early on, there's going to be only a few things that matter. Matter. And if you can really focus and hone in on those, it's gonna solve a lot of the distraction and noise for you in terms of understanding what what is actually the thing to focus on and learn more on. So you see here, we've actually bubbled up to here consumer acquisition cost or CAC or activation rate. These are gonna be examples of metrics that are more important than things like press mentions or email subscribers or things. Now some metrics, this is not a this we we we know that there's always a time and place for certain metrics. So this isn't to say, you know, ignore everything else, but this is really to say what it should where should your emphasis and focus be, particularly when you're starting off. And, really, we've talked about acquisition here and activation rate. There's really kind of four metrics that we recommend that companies start on and focus on. And this really represents the funnel of your business as well. So the top metric or the first metric that that, really matters is acquisition. And, really, this is your first signal of, am I on to something? Is it easy to acquire people? And customer acquisition cost comes into play here. This is a really good proxy for, am I solving a problem that's valuable for people? Is this something that they wanna do? And you see and you hear from and I I myself do this, and I remember doing this as a solo PM of literally spinning up landing pages with different calls to action and seeing which ones drove the most demand or people trying to sign up for the product. Right? Because that's how you start to tell. If you can acquire people on something, you might actually be onto a business. And so that really represents the top of the funnel, and the first thing to kind of look out there is, can you generate those sign ups? Can you get people excited? Once you get people in the funnel, it becomes more about engagement and retention. And so when we say engagement here, we mean are people using the product and the features that you've built. Right? So are they actually using your mobile app? Are they actually using your web application? Are they are they playing with the features that that you think matter or that you've built out for them? And that's kind of the second piece there. One, have you acquired them? And then two, are they using your product in a way that you're expecting and, doing the things you want? From there, you can get into retention. And what retention is is do these do people come back and use these features over and over? And what that tells you is are you actually solving their problem? Are you solving a real problem for them? So then you have really this this first three pieces of the funnel, which is, do you know that the problem is real? Are people interested in trying to solve it? Are they then figuring out how to solve it with your, application or your product? And then does it actually solve it effectively? Do they come back? Do they do the thing again? Do they recommend it to other people? All sorts of things. So if you solve those three, then you really have the ability to build a business, which is how do you monetize them and build and and kind of start building that real business model where you can solve problems for people. They're willing to pay for it. The value exchange is there and more. And so these are really kind of the four metrics that we recommend, every every start up or every small company starts with and really just doubling down and focusing on these really in this order, frankly. And we'll talk a little bit about what this looks like. We we can talk through different examples in q and a as well if folks wanna talk through specific company examples. But you can imagine if you have a sense of these, you can start to really think through the following. You can think through, with acquisition, what are the right channels? Where should I be advertising? Where should I be putting, my time and effort? What's the right message to say to people? How do I get them excited about the problem I'm solving? With engagement, you can start to say, like, hey. Is my application or my product set up in a way that allows people to get access to the feature that my product promised to solve. Right? So we promise something in acquisition. We find the channels to acquire users. And then within the application or the product, we say, hey. Can users find, you know, the features that they need to use to actually solve that problem? And then in retention, it's does it actually solve the problem? And you can start to address real real things like, hey. Is my product not working the way it's intended? Are there usability issues? Are there other things I need to solve? And then, ultimately, once you've addressed a lot of those, you can start talking about pricing and packaging and and getting to value, there. And so, with that, we'll talk a little bit about how fast this is to start with Mixpanel, which is, again, if you need to just start with this top line of getting some of this setup to start to get to some of these insights, we make it very easy for you to do out of the box. And I'm actually really proud of the work that we've done here because it comes from talking with hundreds of startups like you. So the first thing is is we have auto capture, and you can set that up in seconds. And you can start to get events like sign ups, people clicking on things, all sorts of stuff. So you can start to get that funnel that we just talked about of acquisition to engagement to retention. You can get all of that really quickly and and literally under two minutes with a single code snippet. And then we don't want folks to have to stand up dashboards all by themselves when they start out and get really custom. And so we have out of the box templates to measure these recommended, metrics. And in fact, there's a company KPI dashboard that literally ties to those four metrics that we just talked about that in Mixpanel, you can you can sign up and have, all that data flowing in and populate that report in under five minutes. And then finally, when you do wanna see how users are actually engaging, what they're doing, you can watch users in action with session replay. And you can see what all of that looks like, and and, and start to double down. And so with that, I for folks here who have used, Mixpanel or something similar, Let's talk about a little bit of what some of your first moments were when you used Mixpanel or when you used a similar thing to get to an insight. And I'll share a a famous example of one that I, that I, that is an example of a great moment that I love as a product manager, which is this is not a digital product example, but a great one to show kind of some of the insights that are possible when you talk to people and you get user information and get some of this data, which is famously, when, when the Huggies team was deciding whether or not to build a new diaper line, they went out and interviewed a whole bunch of moms. And they started asking moms about, like, hey. You know, what do you like about, you know, current current kind of products for for diapers, things like that? And, as they started interviewing moms, they heard one phrase over and over. They heard, you know, moms asking about, like, is are other are other people's kids still in diapers? Are other people's kids at this age still in diapers? And they caught something to that of there was a really interesting emotion behind what people were saying around comparing where their kid was in the life, you know, in the in the life cycle of growing up. And was it embarrassing or was it not for them still to be in diapers? And so with that, they ended up coming up with the category of pull ups, which is a diaper for those who are not familiar that you end up not having to use a changing table for. It can work and make kids seem a lot more, self sufficient, all these sorts of things. And it's a really good example of finding an moment where pull ups are now a huge category in this space. And what it allowed people to do by discovering this moment by talking to users was discover a really, really powerful value proposition, which is, hey. People really needed to solve this problem, and, and that became a whole category. And so that's a nondigital example, but I'm curious for people in the chat if they have other examples of moments they found in their own products. And I see a question in the chat about what is auto capture. Auto capture is a single snippet of code that actually ties to Mixpanel that will capture all of your a a lot of standard front end events for you. So all you'll do is you'll put it on your website or your web application or your product, and it will automatically send you, all of the page views, the button clicks, all of these sorts of things. So you can get data into Mixpanel in in literally under two seconds. And it's really powerful for getting started very quickly. Yeah. I see Rachel saying we use Mixpanel to track some errors. We're able to see if a link doesn't work or other things are being saved. Yes. Exactly. And so other funnels that we see a lot of are users who are are customers who use it for their sign up. They look at that sign up button. They have one or two features that they really want customers to use. So they track that feature and the feature usage there, and they're looking at that as kind of their activation metric and saying, hey. What does activation look like as it relates to the number of sign ups? Is it a good activation rate? Do people come back and use that feature over and over, and that becomes retention? And then, you know, if that feature is really valuable, then you can monetize it. And so that's a pretty common common, moment sort of structure that we see as people find along that journey different different elements, that matter. Totally. We're seeing behavioral changes. We started using Mixpanel. It was incredibly helpful to get actual metrics on usage, things like that. Yeah. There you go, Rohit. I'm seeing that retention rate was much better among creators and listeners. Totally. That has massive implications for product direction for sure. And I'll share here, you know, as folks are sharing some of their stories, Perp Social is a customer of ours. They're Brazilian social startup. It's basically if you've ever thought about, like, Tinder but for finding friends, you swipe right or left on on trying to find friends. And the way that you kind of, you know, match with someone as a friend is you use a currency internal to the app called a gem, and you use gems to spend on trying to match with new friends. And when Perf Social came to us, they were they were wondering, like, why their their kind of model wasn't working of, you know, getting people to wanna, you know, buy more gems and do more and do more swiping. And what they found is it's actually really hard for customers to find this gem interface and and get gems in order to do more swiping. And so their funnel was, you know, people sign up and download the app, come in, start swiping and using, using gems to, kind of, you know, match with friends. They wanted people to come back and do that over and over and then eventually, you know, purchase more gems and and get further down the funnel. But they were really missing people coming back and then purchasing and using those gems. And so they discovered user friction actually in their onboarding screen flow, and, they were able to actually optimize that and make it more prominent where where gems were and help people discover this. And it led to an over 40% usage growth, of kind of that gem feature, which, again, if that's your kind of activation and retention features that goes all the way down into, that goes all the way down into into that monetization model for them. Right? So if you fix something further up in the funnel, it will cascade down, and that's what they saw. So they actually saw an over 40% increase in premium to paid conversions. I see Nicholas saying we you use behavioral changes and you create cohorts to communicate with them. Yep. %. So segmenting and looking for the right users and following them on their activation and retention and engagement journey is important there. Ultimately, so you can figure out which cohorts monetize better, which which are sticking with you longer, all that sort of thing. And that's actually a great segue into doubling down. And so with doubling down, the easiest way to think about where do I spend most time. Right? Again, if we're trying to separate signal from noise and figure out where we should go next, the easiest way to do this is follow the money. So follow which user segments, which which sort of cohorts, which sorts of people are doing the things you wanna do. So here we have an example of, of of a full user journey where someone sees, you know, an advertisement for the product, comes to the website, complete sign up, and then and then purchases. And what you see here is that, like, if you look at this, this might tell you what the funnel looks like, and you may wanna double click more and understand of those people who are purchasing, what's different about them, how do they get there versus people who don't purchase. What are the differences between the types of cohorts? Who who matters the most here, and who should we double down and focus on? And from there, you can actually go and look at something like a flow, and you can see which segments if we were to double click on that, you know, that that flow of people who purchased and see what did they do before. For people who purchased, what were things they did in advance of that? Who were how did they engage with the product? What did they do? And you can back into who are my segments that are doing like, that are actually really getting value out of the product? Because, ultimately, people are paying for your product. They actually they might they must like it for some reason. They must wanna use more of it. And so understanding what they look like, who they are, what features they're using, what matters to them, you can work backwards from there and understand, hey. For these people, what is it that's moving the needle for them, and how do we double down on them? And from there, you can actually get to understanding, like, hey. These are the most important cohorts and segments for me. Here are the actions that matter to actually drive people towards purchasing, all these sorts of things. And you can work backwards upstream and really refine your messaging. And you can figure out who is that customer segment that matters, that's purchasing. You can optimize conversion flows for them. You can identify points of drop off that don't allow people to get there and find the best results. So when in doubt, follow the money. Find your most avid at like, avid power users, understand why they are doing the things they are doing, why they're purchasing, and work backwards from there and figure out how can you turn more people into those power users, how can you optimize for them, and and and really double down there. And to give one more example of this, I will, I will share, an example from a startup customer of ours called Mobius. Mobius is a b to b marketplace for hardware man manufacturers. And so what they do is actually if you are somebody who needs to buy hardware, you go to the site, and they will match you with a manufacturer who can print and who can, make that that hardware for you and send it to you. They're a startup. They had a pretty heavy burn rate. They were trying to figure out what they needed to do to grow, and they decided to follow the money. So they looked at the customers who were purchasing, figured out, for customers who weren't able to purchase, where they were falling off in the flow, what the difference was between customers who were able to purchase and ones that weren't, and actually worked backwards. And they said, hey. Of my purchase flow, where are the things where I'm going wrong? Is it showing certain products that are incorrect? Is it, you know, putting things in the wrong order or confusing them? What are the things that matter there? And when they did that and they worked backwards from that that following the money, they actually were able to reduce drop off by a significant amount. It had been 72% of the purchase flow before. They got it down to 12%, and they discovered new desires, again, from those power users of things that were really gonna move the needle and get people further down the funnel around, getting people to, contact the manufacturer directly, being able to do more repeat purchasing, all these sorts of things. And in doing both of these things, they were actually able to extend their runway by three months with Mixpanel. And so if you think about this, this is a great example of, hey. We started with who who is this working for? What are the differences between them and the people that are this is not working for? And how do we work backwards and actually design, and how do you design actually optimal product and and the right flows in order to get people down the journey? And so with that, I see a couple of things in the chat here. I see Miguel saying that no matter how much effort you put in, if you don't measure usability retention, you'll be in an endless loop of needing new features without knowing people what people want. %. That is very much you have to be able to separate the signal from noise, figure out who's actually retaining, who's doing the things you wanna do, and double down on things that will help people get further that way. And that really, really matters. And then, Calum, you asked, did you just show that you can drill down or these completely separate visuals? We can't show proprietary customer data in this, so we didn't show Mobius' data specifically. But you can imagine that they essentially had, you know, a starting of purchase flow all the way to the end of the purchase flow because their product is marketplace. And they were looking at, like, for people who end the purchase flow and complete the purchase versus people who start, they saw a crazy drop off. They saw 72% drop off, and they said, okay. We need to lower that. What's going on? And so through a combination of talking to users, looking at the data on the flows, and figuring out where those drop off points were, putting different kind of instrumentation on every screen and saying, okay. Piece one of the purchase flow is where you enter the order size. Piece two is you enter the amount you want and so on. They were able to understand, hey. Where are people dropping off? What's confusing? What are the features we need here? Right? One of the examples that you that you we heard from them is that actually one of the things they found out from users who were dropping off is they wanted to contact the manufacturer, to confirm things during the purchase process. And, initially, they didn't have a way to do that. And so they added that. And by doing a lot of this to optimize that, they were actually able to really reduce that drop off, and start making money in their purchase flow and then actually extended their runway again by by three months. And so being able to really pinpoint and double down was really, really important for them. Great. Well, thank you, Abby. This mainly covers our content today, but we see a lot of questions in the chat and in the q and a. So please make sure you're sticking around for some q and a here at the end. Before we go, again, I wanna share that this webinar is recorded, so you'll be able to access it after. And I wanna share some more resources to you today. First of all, we have some relevant content for you. So some of this will go deeper into what we chatted today. One is our guide to product analytics. So it covers a lot of what we're talking about today and what you should measure and how to do it. We also have a blog post available about what metrics start ups should be tracking. So we'll make sure to share that with you all. If you haven't given Mixpanel a try yet, all you need to do is go to mixpanel.com and just click the get started free button. We'll send you the link to sign up. And as a reminder, if you are a startup, we do have a startups program here at Mixpanel. So startups do get one year free on all of our, enterprise grade features. And so even if you don't qualify for the startup program, our growth plan starts with a million free events, free session replay, and, again, auto capture to get started quickly. We also encourage you to join our Mixpanel Slack community. You can ask a lot of your questions and learn from your fellow product analytics community. So now we can get into some of the questions you have in q and a. So one that I'm seeing, pop up a few times is do we have, do we have session replay and auto capture on mobile? Session replay is in the works. We do have a beta for iOS right now. We are an alpha for Android. If anyone's interested in participating in these, please reach out. We can get you as part of these. We're really excited for that. Auto capture, not currently available on mobile, but we are looking to support that soon. So please keep an eye out for that as well. We have another one here. What's the difference between engagement and retention? Can you give some metrics as examples? Abby, do you wanna share a little bit more there? Yes. So I, I will use an example from my prior startup life with the at the company I was at prior to Mixpanel. And so what we did was we built, a coaching app for people who wanted to build practices to use in, in coaching kids in various sports, so think soccer, basketball, things like that. Engagement is do they use do people use the feature that you want? Are they doing the things you want in the product? And retention is do they come back and do it again, which is really a great metric to know, are is your product really solving their problem in a way that they come back and do it again? And so an example using the the app I just talked about is for us, engagement was is our people coming in and are they building practices? Right? Can a coach come in, build a practice for the first time, and, you know, use that? And then for us, retention is is do they come back and do that a second time? Do they do it a third time? Is it really solving their problem? And so the relationship between engagement and and retention in many ways is are people coming in and doing the thing you want? Are they engaged in doing it? And then does it solve a problem or do something for them such that they come back and do it again? Another example of this would be with Duolingo, which is a big company. Right? They would have when you come in and you engage in doing a Duolingo lesson to learn a language for the first time, that would be engagement. Retention is coming back and doing it the next day and doing another lesson and following on. And that's an example of the difference there of not just do people use the feature you want them to use the first time and activate and do it, but then do they also follow-up and do it again? Cool. Thank you. I'm seeing another one here. Does Mixpanel have certified specialists whom we could hire to help up get started? I am gonna share a chat link here. We do have some, a page here where you can hire partners that can help you get started with Mixpanel. We also offer professional services here, and so these are available to you as you get started. Any other questions? Give it another second here. Looks like how to create retention without harassing users. Do you have an insight there, Abby? Sorry. The question was how do we How do we create retention without harassing users? Yeah. It's a great question. Because, you know, you have a lot of channels where you try and, you know, you send emails, you send push notifications, you put in app pop ups, all these things to try and drive that. The reality is it's a little bit about, kind of, iterating and testing to figure out what the right balance is. And so in many cases, you you will you will mess up is the is the easy way of saying that. You will either send too many, you know, notifications to try and get people to engage or too few or you might prioritize the wrong feature. I would say a couple of things really matter there to get the balance right. The question is is can you can you react quickly and adjust on the fly is really kind of the the piece there. And so do you have instrumentation? Have you set up to know, like, how many emails is this person getting? How many notifications is this person getting? What are the things happening there? And what is it what are the impact of those on actually driving retention relative to driving drop off? Right? And you can actually start to measure that and look at the difference and tweak that over time. And an easy way to follow this in real life, like, you can do this both from an analytical perspective of, you know, actually, like, looking at how many messages get sent, cohorting people, and saying, what happens for people who get a lot more spam spam versus people who don't, and what's the, you know, the implication for drop off rate versus retention. You can also do this qualitatively. You can look at what happens when users feel like they're getting a lot of this via session replay, other pieces there. And then, you know, you should be talking to users and doing some, you know, some actual user research by by talking to them directly as well. And so the key there is you will get the balance wrong. I can a % guarantee you have done it myself. You will get it wrong. It's about can you iterate quickly and understand very quickly what is the right balance there. And it is that trade off basically between how much are you angering a customer so much that they don't come back to you versus how much are you driving retention. And, again, it comes down to following the money again. Right? What's the right balance that gets you to the right number of people doing the thing, that that you want? Cool. I see another question in the chat here. I feel like Mixpanel has a steep learning curve. How can I learn? Are there any videos? I will share this in the chat. We do have a YouTube channel with a lot of different videos on learning to use Mixpanel, so, you can go ahead and get started there. There's a lot of really good content we've created. We have pretty robust documentation that you can use, so, you could share the link there for our Mixpanel docs. And then this is not as directly related to Mixpanel, but there is a certification that's offered, with product analytics that uses Mixpanel for a lot of it. So if you wanna get more familiar with product analytics, we I'm sharing this link to the product school here that you can take that certification. Alright. You're saying you know, go ahead. I see another question around how long should we invest in a customer before before knowing that they're not a good fit for the product. That is the million dollar question for many startups, which is the the the product market fit question. I would say it depends on you know, this is kind of something that you have to adjust and look at over time. But it really comes down to those four metrics we talked about of acquisition, engagement, retention, and monetization. And so, where you're breaking in the flow kind of helps inform, you know, how long you should invest or not. So is is your problem an acquisition problem? Are you not able to acquire them effectively? And you the ones you do acquire might be, you know, really into it, but are you not acquiring enough effectively? It might be that that segment isn't actually a good fit, and there might be some people within it who are, but the rest are not. And so it's probably where it's doubling down there if you see that there. It's saying what's different about the ones who are, you know, double clicking and and doing more versus the ones who aren't, and maybe you need to refine your profile for who you're targeting more. That can be a piece of it. The other piece can be if it's in, you know, engagement and, retention. It's, you know, are you actually solving the problem that they have? Right? Are you able to, you know, build features that solve the problem that they have if you're able to acquire them? Is it working? Is it not? And, you know, there are some times where it's like, hey. Are we going to be able to solve this problem effectively in a way that's exciting for people and valuable for them that they come back? And that ultimately leads to monetization. Right? So are they willing to purchase, and is the value exchange enough for them to pay? And so what I would say is it really depends on where in the metrics you're seeing, some of the some of the pieces, and that kind of affects how you think about this question. Right? Like, if you're actually having an acquisition problem, you probably like, if if if that's a thing where you can't acquire enough people and and you've tried that for a while, which you can do in a lot of low cost testing ways, you can run landing page experiments, things like that, then that might be time to to adjust and say, like, hey. Is this a problem for this segment? Is this who we should be focused on? If it's happening further down the funnel, if it's happening in in sort of that engagement and retention land, it's, hey. Are we actually solving the problem that these customers have? And then, you know, candidly, can we solve the problem? Right? Some problems are more challenging to solve than others for customers, and are we able to do it? And have we figured out the right way of doing it? And then finally, it's is the problem valuable enough, and are we solving in a way that that, you know, they wanna pay us for it? And then, ultimately, if you're building a startup or you're building a company, they need to the value exchange needs to be there. And so even if you've done those other pieces right, sometimes it's not something that that they're deriving the value from. And so it's it's it's thinking about, hey. Is there more we need? Is there something else we need to do here to actually drive that value exchange and make the the product valuable for them? But, you know, if if you're if you're spending a lot of iterations on this and and pinpointing and seeing problems really at all stages of this, like, there are some there are some questions, I think, in terms of, like, are you investing in the right thing? Should you be doubling down on it? Should you be looking somewhere else? And it's really looking at that from a from a, you know, a perspective of like, hey. Relative to the things we're learning and all that sort of thing, is this the right place to continue doubling down? Definitely. I'm seeing another comment here. Don't forget that you can talk to people. Mixpanel dashboards aren't everything. We agree with that. Mixpanel shouldn't be the only way you're looking at your data, and you should talk to customers. It's a mix of quantitative and qualitative data. %. Cool. Well, I oh, looks like we have another one here. Different users. Oh, I different users use different features. Did you try and cover all of them or focus on a small number of features to invest and develop? And this is, without being specific, like, legal advice or things like that, if you try and be everything to everyone and do everything for everyone, that's a that's a surefire way to fail. And so focusing on solving a problem well first for a small segment that you can expand on is going to be really important. And so, again, I would say follow the money. Figure out the segments that are your, you know, your most powerful, the ones that are purchasing, and and figure out how you build for them and the the closest versions of them, and you can expand from there. But, really, you know, we talked about upfront the things that startups do that that that kind of cause failure. You know? There's not a lot of startups that fail from a lack of vision. There are a lot of startups that fail from a lack of clarity and focus, right, in using that data and figuring out where to double down and find product market fit. So if you have early signs with one segment, focus there. Right? And and that is the segment to to really kind of double down on and figure out how you how you serve. And getting that right, will pay a lot of dividends for you, and it will help you think about the right expansions to make if you add more. But particularly when you're small and your resource constrained, trying to build a ton of different things for different people, is a surefire where you spread yourself too thin and not really solve the problem for anybody. Definitely. You're welcome. Great. Well, I'm not seeing many more questions come in. Thank you all for your time. We're so happy you joined us today. We hope you found this valuable. We will be following up with more resources in the recording, but thank you all for joining, and have a great rest of your day. Thanks, everyone.