0:00 Hey everyone, I'm Joel. I was asked to record a quick loom about the vision work I did back at Heap, where I was previously VP of Design. 0:09 For some context, before we start, Heap was a product analytics tool that differentiated through how it automatically captured and managed data compared to other tools in the space. 0:21 The story here is that I was asked by the CEO to put something together to help align and excite the company. 0:29 And the process was actually pretty simple, if a little intense. 0:33 I think every company that has passionate people working there also has a ton of high potential ideas that are just floating around. 0:42 You know, maybe not super well articulated or prioritized or known to the rest of the company, but they're around. 0:49 And what I did was basically just gather those ideas that resonated with me into a cohesive platform story and then iterated on it pretty heavily until it felt right. 0:59 I then hired a friend of mine from my GitHub days to do some of the illustrations, keep them a little, you know, sketchy to clarify that this wasn't real. 1:09 Shout out to Kim, who did a phenomenal job and then this entire thing that you're about to see was defined, storyboarded, illustrated with, you know, a ton of back and forth on the visuals and the story that we're telling with the interface modules and then presented all in under two weeks. 1:30 So that's to say this work doesn't have to be a huge lift or it doesn't have to take a ton of time to figure it out. 1:38 And this was basically an opportunity to illustrate our company's thesis to our company and how it would play out over the long term. 1:46 So we wanted to remind folks why this thing, this idea that we had was going to win. 1:52 And one of the main results was that following the all hands in which I first presented the vision, this Culture Amp question, which is, you know, one of the key questions for measuring employee engagement. 2:05 So the leaders at this company have communicated a vision that motivates me, went from 60% before that all hands to the next survey being 100%, like a perfect 100%. 2:18 So I think I'm very proud of and also a thing I think we felt on the ground with engagement and excitement to continue building. 2:26 And I ran through all of this with a hypothetical med tech startup called Provide that more or less matched our ICP at the time. 2:34 So at this point, I'm going to jump in as if I'm presenting to the company at an all hands. 2:42 And this is basically what it looked like back then. 2:45 All right. 2:46 So what I'm about to show isn't a roadmap or a design proposal. 2:50 Everything in here is theoretical and fuzzy. 2:54 The goal here is just to introduce the vision of what Heap might become and get us thinking more ambitiously about how we can transform the way that people build products and what we can 3:04 do for our customers. 3:06 So Provide is disrupting the healthcare market through clear pricing, great customer service, and digital experiences. 3:16 Provide's head of product is trying to figure out how to cement their place in the industry. 3:21 The problem is she doesn't have a ton of visibility into what's going on. 3:25 She doesn't know why they aren't getting more signups. 3:27 She doesn't know how to identify the right problems to work on next. 3:31 Or maybe there's too many problems and she doesn't know where to start. 3:35 And in the meantime, the company is in chaos, right? 3:38 There's no clear direction. 3:39 There's no consensus on what they're currently working on. 3:42 No one really knows what their users are doing. 3:44 So people get in these heated conversations over decisions, which waste time and resources. 3:51 People feel lost and frustrated and are looking for clarity. 3:55 And so here we have a head of product, down on her luck, hanging around the office, staring 4:01 poignantly out a window, trying to find the answer to all of these questions. 4:06 And what does she see but a billboard for a magical product that solves all our problems? 4:11 Is this a sign? 4:12 Well, yeah, it's, you know, it's a sign. 4:15 So she goes back to her desk and signs up for a Heap trial. 4:22 And yeah, I was very cringe back then. 4:24 And yes, I still am. 4:27 Anyway, before she knows it, Heap starts building a map of what's happening in their product. 4:32 It surfaces the most important information and areas of the product right off the bat. 4:38 So this is us truly leveraging autocapture, doing something no other product in the market can. 4:45 She thinks, is this real? 4:47 Could it be? 4:48 She's getting ideas. 4:49 She's inspired. 4:50 And over time, that journey fills up and becomes more robust. 4:54 She zooms into an area that Heap is marked as important, in awe of that information at her 5:00 fingertips. 5:01 And now Heap identifies some flows within the app that are more difficult than others. 5:06 And it points this out. 5:08 She wants to know more about this specific flow. 5:11 And she sees that there's some user feedback given in the area, gathered by Heap's built-in 5:16 feedback module, or one of our integration partners. 5:20 Now, one of the users says that setting up an appointment with a provider is a bit confusing. 5:26 And all the comments are grouped by subject and by, you know, place in the path. 5:30 So she can easily find a few more and start seeing a pattern. 5:33 So this area clearly needs work. 5:35 She factors this now into her new roadmap. 5:39 And so this is the first example of how Heap will surface not just the what of what's happening, 5:44 but also why it might be happening. 5:46 So you can take action on that. 5:49 And Heap lets her peers and her track all of their KPIs and allows them to define targets 5:57 or OKRs right inside the app. 5:59 She defines appointment creation rate as something to improve. 6:03 And she thinks, like, finally, some clarity within this company. 6:08 The top-level OKR can automatically be shared with all stakeholders via Heap, from ICs to a board of directors. 6:16 So it becomes the source of truth. 6:19 And so over on the other side of the world, we have a product manager who is in charge of providing scheduling flows. 6:26 And he looks at his own screens and sees those top-level OKRs. 6:30 He can then define his own KPIs or tie a project to one of those top-level OKRs right inside Heap. 6:37 And now he knows something needs to be improved because the numbers don't lie, but he doesn't know exactly what. 6:44 So he's looking for the reason that people aren't scheduling more appointments. 6:50 He doesn't really know what's going on yet. 6:52 He can make a guess, which is maybe what he would have done in the past. 6:55 But now with Heap, he can just define a journey in Heap by selecting a starting and ending point. 7:02 So again, we're leveraging our differentiator, which is auto-capture and all of our ML features, to paint a clear picture with very minimal effort. 7:11 So you select the starting and ending point. 7:13 And then immediately, this PM can now visualize the volume of users moving through this area in a really, like, tacit way. 7:21 He can see where they go. 7:23 He can see when they backtrack. 7:24 He can see where they drop off. 7:26 He can even see other frequent starting points that he didn't expect. 7:31 But at this point, he still doesn't know why people are dropping off in this flow. 7:35 But luckily, Heap can show him what his users are doing in context. 7:39 So he can build a better idea of what's going on. 7:42 So he runs through a session replay of one of the users who dropped off on that provider profile page. 7:48 And he sees them try to search for a specific provider, going back and forth between profiles and the search page unsuccessfully. 7:56 He checks out a few other sessions and sees similar patterns. 8:00 Now, he wants more insights, so he checks out the customer feedback that's mapped to this same flow. 8:06 He reads one comment from a customer that just wants to see the same doctor again. 8:11 And he realized that Provide as an app doesn't really make this easy. 8:17 So I just want to stop and make sure everyone understands why this is so cool. 8:22 Analytics tools, historically, make it really easy to figure out what is happening, but they don't get you much closer to figuring out why something is happening. 8:31 Qualitative tools such as session replay and customer feedback are really powerful tools for this and have never been integrated with these kinds of quantitative journeys in this way. 8:42 So now we know these things. 8:45 And he wonders whether the experience is actually worse for returning users, which is a completely new hypothesis that never occurred to him before. 8:54 So if that's the case, that would suck. 8:56 And then he can just easily create a comparison. 8:59 Now he sees how return users in teal here compared to new users in purple throughout the entire journey. 9:07 And he makes it really easy for him to see that return users are the ones backtracking most of the time, and they represent the majority of drop-off right before scheduling, perhaps counterintuitively. 9:18 And now he's fairly certain that this is a good area to invest, so he creates a hypothesis for what's happening in this area. 9:25 He says return users are frustrated because it's difficult to reschedule the same provider. 9:32 Now Heap automatically creates a dashboard for him. 9:36 From the queries he ran up until this point, Heap understands what he cares about. 9:41 We understand what he cares about and tailor this dashboard to that. 9:45 All of his dashboards automatically include his defined KPIs for visibility and try to determine whether their respective project will affect those KPIs. 9:55 Because Heap knows which numbers he's trying to move, it suggests a few experiments it's seen work in the past across the entire industry, right, along with industry benchmarks on what lift he might expect from those changes. 10:08 So for the first time in his career, he doesn't need to define an arbitrary number that he thinks he might be able to hit. 10:16 He can actually have a good sense of what he might be able to accomplish. 10:21 Now, the PM doesn't work alone. He works with engineers and designers, other PMs, you know, success, sales, support, and more. 10:28 And all of these stakeholders will not only need to know what's happening, but their voices can lend a ton more insights. 10:35 So he tweaks the descriptions, explain what each graph means, and telling the story of this project, right, rather than this being kind of a generic, you know, list of different charts. 10:46 And then he can invite his peers, and they can have conversations directly in Heap, marking the graphs up and adding comments as they go. 10:55 Anyone who looks at this dashboard in the future will see this conversation history, will see what each thing means, and be able to determine their goals and, you know, what the meaning of this thing is. 11:09 Together, they decide to run two experiments, another thing that we're talking about integrating within Heap. 11:15 First, they run an experiment where they add a previously seen provider section to the list page. 11:21 They also run a separate experiment sending emails to users who have seen a provider in the past but can't find them. 11:28 So this experiment is created within Heap, and the action is taken automatically when certain behaviors are identified, and they trigger an integration with Braze, or one of our other integration partners. 11:40 So for both of these experiments, Heap already knows which of their users are included, and so it can automatically show results in that dashboard. 11:48 So back on that dashboard, these experiments are automatically added as filters and labels, and this can help the PM to see when experiments were started and what their effects were. 12:00 So he finds that the UI changes result in more repeat users, less backtracking, and less drop-off. 12:05 So huge success. 12:07 He adds an outcome tile to the dashboard and saves it as a case study to send to his stakeholders. 12:13 This dashboard will continue tracking the behavior in this journey, and if it changes significantly in an unexpected way, it's monitoring it, so it can alert someone. 12:23 But this idea of, like, we don't just have a million dashboards, you know, they're not, they're safe for posterity, and they are explained. 12:31 We are telling stories through data. 12:34 So meanwhile, let's go back to that head of product. 12:37 She's been tracking the progress of the entire customer journey. 12:40 So it started off with a lot of friction and drop-off is slowly getting better. 12:45 There's still a long way to go, but at least now she knows what's happening and where to invest. 12:50 So she notices a key area of friction has now improved. 12:54 So she can toggle the projects layer and see what's being worked on in various areas of the journey along with their KPIs. 13:02 This project that we were just talking about seems to be doing well. 13:06 So she clicks into it. 13:07 She quickly picks up what the PM was trying to do and how it went. 13:11 What a simple solution to a serious problem, she thinks. 13:16 And she's very proud of her team. 13:19 She comments on the dashboard. 13:21 Great job. 13:21 100. 13:22 Lets out a satisfied sigh. 13:25 Satisfied sigh. 13:27 And so at this point, like, Heap has empowered her team to truly understand the end-to-end customer journey. 13:35 To build alignment on top company goals, to improve communication and create clarity in that data, to answer vague questions in an intuitive way, understand not just the what, but also the why, to easily collaborate across the company with different colleagues from different functions, 13:52 to quickly test improvements via those built-in experiments, to automate actions via integrations, have a larger impact on the business as a result of this, and through all of this, flow. 14:08 So, you know, these tools are powerful, but they enable you to be creative and play around with the data and really enjoy the journey towards finding those answers. 14:18 So, after a couple of months with Heap, Provide is getting rave reviews, customer growth is at an all-time high, and with a shared source of truth, it's suddenly so quiet within the office. 14:30 So, all is well in her world, she heads home for the night, excited for tomorrow. 14:36 And that's it. 14:36 That's the vision that I presented that first time. 14:40 Short and sweet, gets at every workflow we wanted to solve, gets at most of our personas that we wanted to think about. 14:48 And also just outlines, in general, the kind of things we want to build, if not exactly tactically what we want to do. 14:56 And so, about a year later, I presented an update that our fiscal year kickoff to show how far we'd come and generate energy right before, you know, we dove into our priorities for the year. 15:07 So, we did things like this. 15:09 Hey, we did a huge rebrand between that time and this time, and talking about our logo mark and what that means for the company strategically. 15:19 And then things like this slide, which didn't even exist in the original, as we surpassed our expectations dealing with all the, you know, technical eccentricities of mobile, we suddenly were able to do something even we didn't consider. 15:32 And juxtaposing this with an already ambitious vision was super motivating for people. 15:39 We highlighted how new features like our explore events and effort analysis fit into that big picture we were talking about, how some of the product bets materialized almost to a T, much, much faster than we'd expect, than we initially expected. 15:55 For instance, session replay was a multi-year bet, but within a year, from a point where we didn't have that at all, and it was just an idea floating around, we were already shipping this exact workflow, following a strategic acquisition that we made, because we had this vision in mind. 16:13 So, this was also an opportunity to frame our current in-flight initiatives within that larger vision. 16:20 So, Heap wasn't just a product that had now added a session replay feature, we had a new kind of session replay feature, a new kind of workflow that had never been seen before. 16:31 It was also an opportunity to generate hype for other things on the roadmap that we hadn't started working on through the same lens. 16:38 I also highlighted how some of our long-awaited platform work was going to contribute to this future. 16:44 So, this exercise was really good at generating that kind of energy within the company and getting everyone super pumped to work on new stuff. 16:54 Finally, reiterated how much we'd accomplished in a much shorter time frame than we imagined, and contextualized us for where we were in this larger vision. 17:05 So, again, this was followed by the rest of the leadership team outlining our priorities and diving into new initiatives, and people work in the mindset to be super excited about these new things coming up, and to be very creative about them and feel a lot of agency. 17:23 So, that said, I found this exercise and the artifact really powerful, both in recruiting new people, by showing them, hey, this is where we're going. 17:34 So, recruiting top people that you couldn't otherwise, as well as kind of directing the entire company in the same direction. 17:43 So, I've been a part of high-performing product orgs, like a bunch of them. 17:47 But before this, I'd never seen a company defining and sticking to a North Star vision the way we did at Heap. 17:54 It required so much discipline, so much alignment, and I think a lot of that had to do with having this kind of shared story to ground it. 18:03 So, yeah, overall, recommended. 18:05 Hope this video helped somewhat and you got something out of it. 18:08 And catch you at some point. 18:13 Thank you.