How goHappy 4x'd inbound pipeline by stacking interactive demos + 12 intent signals

Arthur (Head of Community & Customer Marketing): Welcome, everybody, to another Finer Demos Club session. I'm super excited about this one. If you haven't heard, we have the Ted Lasso of growth marketing, Richard Mayer, in the house. He's going to talk about how he stacked so many signals to actually whittle down a bunch of accounts and make his sales team super successful — to the point where they 4x'd their inbound pipeline. We kept this one to thirty minutes, but Richard has graciously volunteered his time, so if we get a bunch of questions in the chat, we can go a little over. So, without further ado, Richard, we'd love for you to get into all of your genius behind stacking these signals.

Richard Mayer (Director of Growth & GTM, GoHappy): Way too kind. Thank you, Arthur. It's really nice to be here, I appreciate it. Nice to meet everybody — please add me on LinkedIn, I'd love to stay in touch if you have any follow-up questions. I'm Richard. I'm the director of growth and go-to-market for GoHappy. I live in Ozark, Missouri — not the Ozarks from the show. There's no Jason Bateman around; my wife would be sure to let me know, that's, like, her free pass. And there's no syndicated crime, none of that here either; it's a really quiet town.

I've been working with GoHappy for two and a half years. I was on the agency side, and I joined the team full-time in October to take over the go-to-market motion. So I have a lot of empathy for agency people, and I'm creating a lot of empathy for in-house people as well, because now I get why you guys were so slow to approve everything — there's a lot that you do.

A little bit about GoHappy: we have a very niche ICP, because we're a tool that helps frontline workers feel more valued and connected so they can reach their full potential and live more fulfilling lives. We've been working in the frontline tech space since 2000. Even though frontline workers themselves are about 80% of the American workforce, the people who manage them are much more difficult to get ahead of. So we have a very traditional B2B problem of a super-niche ICP — super-busy director-plus at multi-location franchises and corporations, people who are pulled in two different directions, managing their office workers and their frontline workforce at the same time. So it's a very challenging go-to-market motion.

The reason I joined is because they'd hit a roadblock, and that roadblock was that we'd been really dependent on LinkedIn. We launched the LinkedIn ad strategy for them in early 2024. Everything was going pretty well, until it wasn't. With the LinkedIn ad platform changes, we saw our CPMs go up 91% over the course of last year, and our audience penetration decreased all the way down to 23%. Combine that with a declining booking rate, which had historically done pretty well on LinkedIn — that decreased over the course of last year by 36%. It suddenly was becoming very cost-prohibitive to just depend on LinkedIn lead gen as our primary source of leads. So we had a pretty big problem at the end of last year.

Arthur: I know you're going to take us through a game plan here, but with all of that, what was one of the first things you started to look at?

Richard: It was a really interesting time, because I'd just come off paternity leave. I'd been working on the account for almost two years, and I took a three-month break — just in the world of kids and diaper changes and midnight feedings. So I was actually able to look at it with pretty fresh eyes and lock in a process with our CMO and our CEO as to how we should approach it.

The first thing we decided — the animation got me here — we knew we needed to reach more people and diversify away from LinkedIn, but we didn't really know where to go. So we broke it up into three steps. The first is that we had to lock in our messaging. We worked with a company called Pitch Maps to redefine our go-to-market message in particular. We'd been saying, "We're an SMS engagement platform for frontline employee workforces," and that's jargon — nobody cares. So we went through and developed new ways to talk that wouldn't feel super-B2B-enterprise and boring, frankly. We did a lot of interviews with our stakeholders and key partners to find out what they loved about our product, and decided to roll that out into a new testing plan — with ad creative, landing pages, and guided product tours with Storylane, because we didn't have any of that when we started in Q4 of last year.

Arthur: So as you're doing all this, talk to me about some of the things you started to test out in terms of messaging and positioning.

Richard: So, like I mentioned, ad creative, landing pages, demos. Here are some of the outputs, just to show the difference versus what you might see in a traditional B2B ad. Maybe you're like, "Well, that's still pretty boring," but this is a step in the right direction for us. We wanted to test different tone levels, different types of design. We're a texting platform — should we show phones? Should we not? Should we call out the alternative right there, like email or app downloads? "Think outside the inbox" is a pretty on-the-nose, direct message that we hadn't tried before. "Texting on the job" — that's what we're going for, this wittier, sassier language, and we saw some really good traction with that.

We took that same approach to our website — multivariate testing in terms of design and language against our controls, which would be our previous home page, and really tried to identify what people cared about. What was nice — the marketer in me loves this — is that we tested directly the word-for-word recommendation from our positioning agency against a hybrid version that I thought would work a little better, in our version one. That's always a nice little moment.

The other big thing: we'd launched guided product tours in November, and in January we started to really refine that product tour. We tried to make it storytelling-focused. We started off with completely ungated demos, then went completely gated, and we've ended up somewhere in the middle, where we found the average drop-off point, and that's where we added our mid-gate form — the "ask or get off the pot" moment. We really wanted to hook the user in those first couple of slides: here's the value we're providing, this is not just a feature tour. We'll show it from the frontline employees' perspective, and from your perspective. And as soon as you're about to learn more about your perspective, we pause: hey, we'd love some sort of exchange for value here. But it starts with being value-focused and experience-focused, not just, "Yes, we translate to 115 languages, here's our AI copywriting tool."

Arthur: That was the main difference, where you were almost too product-focused — here are our features — versus something like Dunder Mifflin. Is that more of the storytelling aspect you leaned into?

Richard: Exactly. We wanted it to feel — these are, it's a real account, a real demo account. I can actually send texts from this account; I send myself texts in demos. But I had almost taken a "checking the box" type of demo, showing all the different capabilities it can do, when most people don't care about every single capability you have. They care most about what problems you help them solve. So instead of leaning on hyper-segmentation of different audiences — you can filter by job title and location and manager and all these things — just, "You can reach exactly who you want to and reach them immediately, because it's a text." Just simplifying that. You don't have to show everything, because then you start to lose people, I think.

Arthur: One of the things we just talked about: locked-in positioning, telling more of a storytelling narrative. What was step two that you went to after this?

Richard: The second thing is we really reworked our ABM approach. I don't know about y'all, but I've been doing ABM for a long time — four or five years, which is ancient in the ABM world. When you're on the agency side, so many times you just look at ABM as, "I have an ICP, and that's who I'm going after, and these are my accounts, my account list." What's problematic is that it's static, and it doesn't take prioritization into account. There's a difference between your total addressable market versus who you should actually sell to. That was a problem we had — a very simple ABM approach that was over-indexed on SMBs.

So we started off by taking our entire ICP — that's 18,000 accounts. 18,000 accounts is huge; unless you're a Salesforce or some other massive company, you're probably not going to be able to effectively market to 18,000 accounts at once. So we prioritized. We scored them based off of that ICP fit — technically they're ICP, but how ICP are they? Do you check all the boxes? So we did things like the number of locations, because there's a sweet spot for us. If you have just a few locations, you're ICP because you're multi-location, but maybe you're not truly ICP in the way that we can serve more locations than that. Or maybe the problem is the exact opposite, where the number of employees you have per location is so low that it's not effective for you to use a tool like us. So we used that to create scoring methodologies, honing in on a weight of the ICP fit, and then also weighting based off of intent — what we're seeing happen in real time in terms of your historic interaction with us, and also what we're seeing in the market using third-party tools like Vector. So we took the 18,000 accounts and whittled it down to around 97 to 100 accounts, which we're considering our sellable addressable market. And from there, target accounts and things of that nature.

So I mentioned the marriage of ICP and technographic as well as intent data. This is a big jam — a walkthrough of our process. It probably looks way more complicated than it is. Essentially, we fed that raw list of ICP accounts into Clay, and then we married in all the intent signals we'd consolidated. We'd been consolidating and tracking these intent signals for a few months — we just weren't doing anything with them. We were like, "Hey, signals, yay," but we weren't doing anything with them. So we were able to marry them in Clay. You can do account lookups and say, on one major table, "Has this account interacted with us in Storylane? Yes or no? If it has, how many times? What's the value? What's that telling me?" You can add filters to that using the Storylane webhook as well — like, not only have they interacted with the demo, they interacted beyond a certain percentage amount. We do all of our demos as embedded, inline demos — am I getting that right, inline? Yeah, not the pop-up ones. So sometimes we pick up engagements that are somebody accidentally clicking on it. Sometimes somebody gets to the fifth or sixth slide — that's actually really good, and that's a different signal for us. So it's all these signals, making sense of them, ingesting them, and matching them to the accounts. When we get to that point, that's the deduplication level, the enrichment level, and we've married that with the ICP and technographic data.

What's really fun is we then took this and created a scoring methodology. Our methodology, to be clear, is a work in progress — we're constantly changing and tweaking. Maybe our pricing-page hit is not as valuable as we think, or maybe it's more valuable. So we'll adjust scores. But everything is weighted, because I don't know about y'all — I hate intent scores that make no sense. Intent scores where this account has 13,000 points. What does that mean to me? I need a scale to maximize our knowledge of what's actually happening in real time. So our intent score is set to decay over time, and it's also set so it multiplies based off of the number of user activities — one person doing a lot of things doesn't mean as much as multiple users in an account doing several things. When we did this original scoring, we weighted half of it based off of ICP fit and half off of intent.

Arthur: I love it. To your point, when I used to be in sales, it was almost like a different language from marketing. You're giving us all this information, but how do you simplify it? I really like what you did, where you gave it an actual numerical value. Was it out of 100?

Richard: So the original scoring was 200 — 100 points for ICP and 100 points for intent. It's a scale of zero to 100 of how effective. That scale could have been fifty-fifty for a total of 100; it really doesn't matter. But for me, I wanted my sales team to associate, "Oh, this score is 140 — sick, that's really good."

So here are some examples of what that looks like in real time. I hid some data, so you can't see — this is FedEx, or whatever. I actually don't know if it's FedEx; it probably is. You'll have your intent score and your ICP score, and they're weighted, because the activities aren't just one thing, so it's not a perfectly rounded number. You'll see where we ended up with some of our accounts in terms of their final score in this column. You might think somebody is a really good ICP fit, but they're not showing tons of intent. So this is a good example — pretty good ICP score here of 63 out of 100, not much intent at all. So what can I do to increase that account's intent and velocity?

Arthur: And how did you start to tier these out? You said it's out of 200, but for reps to understand how to prioritize, you gave them somewhat of a tiering score, right?

Richard: Yeah. I'm skipping a slide, and I'll come back. We ended up thinking of it in terms of concentric circles of an audience. We have our entire ICP — that's great. But then our reps were assigned a number of accounts that hit a certain threshold in terms of their ICP and intent fit, so they're not just marketing to solely cold accounts. And from those, they chose their own priority accounts. So we do tiers as well: their tier A and B are the ones they really want to get this year; C is the ones they'd love to get, but they're not staking their claim on it. And within that, we have a subset of accounts that, as they're engaging in real time, get assigned out. We start picking up a lot of first-party signals — I'll keep using FedEx as an example. Maybe FedEx is in this ICP, but it's not one of our target accounts. Great — now it's a target account, because they're actively engaging with us, and we want to make hay.

Arthur: I love that call-out, because there are so many definitions for ABM, and the traditional one is, "Let's name 500, a thousand accounts." But what I like about your intent scoring is exactly what you said — once they hit a certain level, they actually become a target account. The ones we wanted to go after are actually engaging with us, and now that they're showing so much intent, they become part of our ABM program. I love the way you're thinking about this.

Richard: Yeah. We have some evergreen, like air-cover, brand-awareness plays too, because maybe someone at this ICP level is going to show up at one of our conferences — we'd love to have some general awareness going on. And when we're able to move off LinkedIn to other ad channels like Meta, air cover gets a lot cheaper. So we could devote some of our ad budget to evergreen plays, and accounts might migrate down and up. I think the next phase of ABM is actually reacting in real time to what's actually happening, rather than making an ABM play an annual exercise you do with sales. At the very least, we should be looking at these target accounts quarterly — what's changed, what's in, what's out. And we do weekly sales sprints of what's happening with our sales team, so they're really engaged and they buy into it, which is awesome.

I'll go back one slide to show some examples — that's the wrong way. Here's some of the intent methodology. When do I prioritize what I'd consider higher-intent actions for higher scores? And I do include some softer, directional signals in my score, because they're not meaningless — they do mean something, they just don't mean as much. So I treat a lead-gen form on LinkedIn, even though it might not be someone booking a demo, differently than somebody doing competitive research that you pick up in a tool like Bombora or Vector. They're different things, so they should have different weights.

Arthur: So this is what you're weighting. Did the sales team have input on this, or is this a hypothesis you guys are continuing to look at quarter over quarter?

Richard: Continuing to tweak. We do retros for every closed-won as well, to understand what that journey looked like. Clay keeps a really great log of all that — you have your activity logs for everything. So running through closed-lost analysis in Clay and Claude takes minutes now, compared to a multi-week exercise you'd do annually even two years ago.

Arthur: So fantastic. You took us through the first two steps. Run us through step number three.

Richard: Step number three is expansion. We were launching a bunch of new tools at once — Vector, Storylane, all this stuff — and I wanted to make sure that's actually doing what it's supposed to be doing. I want to make sure my tools aren't just making stuff up. How many of you see all these scandals about, "This AI platform is not actually AI, it's a bunch of dudes in a room somewhere"? Actually, Whole Foods did that — you know that, right? Whole Foods had an AI system that was checking people's carts, and it was actually just a bunch of people watching security cameras doing it in real time. I just want to make sure nobody's doing that for me. So we validate with multiple data sources. I still had Clay's de-anonymization, and I'm comparing that to Vector's and Storylane's. If I'm using a Vector audience, I'm using the LinkedIn company report to see what's going on. I want to make sure, before I start dumping a ton of money into something, that it's actually doing what it's supposed to. And it was.

So then we're like, alright, cool — how do we capitalize on this even more? We started taking those first-party signals and routing them into Clay in real time. And I know you already know, you're like, "Oh, you already said that." Well, this is slightly different, because we're taking the real-time activity in Clay and sending it to HubSpot, and that HubSpot activity is then triggered and sent — via Vector most of the time — to ad platforms, via account lists and things of that nature. So we're taking that real-time intent and creating this flywheel: as accounts show intent — at the company, or an individual at a company showing a level of intent — we're trying to reach more people at that company. Because, ideally, if one person at that company is having a problem and is interested and engaged with you, there are probably multiple people within the company experiencing that same thing; they just haven't articulated or figured it out yet. So it helps expand awareness in accounts that are actively starting to show early signals of interest. And as you deliver ads to people, they tend to show more intent — we're getting more people from these accounts to our website, so they're doing more activities and giving me more intent signals. So it creates a flywheel of activity, which is really fun.

Arthur: A quick time check — I know we have up until thirty minutes, but please go on, in terms of how you started using Storylane a little more as an intent signal.

Richard: Cool. And please, anybody drop questions in real time. I know Steven dropped one — "third dimension of momentum and velocity" — that sounds like an awesome dimension I should add in. So, recency: like I mentioned, there is a decay factor, so it verifies the activity happened within a recent time period, and those time periods vary by, you know, pricing-page hit, I might give it ten days, but a case study I might give seven. And we're messing with that all the time. And thank you, Veronica — I've been thinking about that movie since I saw it last week; I'm going again on Saturday. One of my favorite books, and they did it justice, which is great.

So what this looks like now: we use a lot of webhooks from all of our different data sources to create refined tables, and within these refined tables, we're doing that account scoring in real time. We might have a webhook from Vector refining my audience list down to ICP visits on particular pages, and that's sending into tables that are enriching, helping me reach additional users and resending that information back into things like HubSpot. The way these tables work, if you're not familiar with Clay, is you match LinkedIn URL activity across tables and do lookups. And if that record is not found, great, send it in — or whatever. Depending on the activity and how you're matching things over, you can essentially assign points or verify that activity in real time.

So what we're doing a lot is Storylane activity. Depending on whether somebody's just checking out the first couple of pages of a demo, I treat that differently than someone who gets to the end and clicks the CTA. Maybe it doesn't convert, but they click the CTA. Or they completed 80-plus percent of it. So we'll look up the number of times that's happened within the time period, look at the date it happened, and if that's within my time period, add scores and create additional scoring based off of that. This feeds into that intent flywheel and routing in terms of different activities and plays. Somebody checking us out with a guided product tour — we want to make sure we're doing some outreach, and what that outreach looks like is probably different than someone checking out a pricing page or a case study. So we're really trying to ingest all that material, regardless of whether it's from Storylane, Vector, or one of the other intent signals we're using, like job changes, and leverage that for all our plays in a singular, centralized data provider like Clay.

Arthur: I know we were relying too much on LinkedIn as the single channel. The audience is very curious to hear — what were some of the results you guys got coming out of this?

Richard: By expanding from just LinkedIn to other ad channels, we saw double the amount of impressions in February than we did in all of Q4 — with about 40% of the ad budget that we had in all of Q4, we had double the impressions. We actually hit a million impressions for the first time ever in a month, which is cool; we hadn't even cracked 500,000 in a quarter. We saw a decrease in CPMs by leveraging some of these things, getting additional views. And what's really cool is we also saw web activity tick up with this — so it's the CPMs in terms of the views of your ads, but also the additional views you get on your website pages, your content. Tons more activity on our web pages, on our tours. And we did see our pipeline — we generated 3.5 times the amount of pipeline in February than we would in an average month, and from paid specifically, it's 5.2 times. And this is a little outdated now — we just had another record-breaking month. If we were to compare to our average, we're at like five times this month, with two or three business days left. So fingers crossed our sales team continues to knock it out of the park.

Arthur: Amazing. Thank you all for sticking around. Like we mentioned, Richard still has some time, but round us out with some of your final thoughts.

Richard: I really appreciate it. Again, please stay in touch if you have any questions. I really appreciate the Storylane team — they've been great partners, and Arthur has been really fun to work with, as well as Ranga, who's not publicly on the stage right now but is instrumental in helping get all this together. So thank you, and Renee for doing a Q&A at the beginning.

My final thoughts: one, don't overthink it. ABM seems super scary, and I don't know why we overcomplicate it. It's not actually that complicated. You're trying to define who you want to reach, and a big part of that is actually being able to reach them. So if you can't afford to reach them because LinkedIn is getting prohibitively expensive, think about other creative ways to get in front of them. Two, validate and scale. Storylane, I can tell you, the data's good — that's fantastic. But with any other new partners, you want to make sure you're validating and getting the right data in. With AI, with automation, if you have the wrong inputs, it's just going to steal — bad data, you're going to get bad results. So validating before you really press the throttle all the way down is really important. And the last bit: first-party intent data is the GOAT. Nothing beats your own data. The great thing is that Storylane, Vector, website view and optimization, HubSpot contact activity records, email opens — that's all your own first-party data. You have it. What are you doing with it? Where are you sending it? What are you utilizing it for? Most people treat it as just a standard box of, "Oh, you're on my website, I'm going to throw you a retargeting ad." Well, how many people visit your website every day who actually have no interest in being retargeted — even people from your own company? So think about leveraging your first-party data in smarter, more effective ways, and it truly can be the GOAT.

Arthur: Amazing. Thank you for sharing all of that. There's a ton of interest in how you made this happen. I'll start reading some of the questions. Steven, appreciate you being very active in the chat. He asked: what has been your most effective value exchange within Storylane — unlocking chapters, verticalized, or role-based versions?

Richard: Really good question, Steven. For us, it's actually interconnecting all of the demos via chapters, but having each demo be its own starting point on the different solution pages. So we don't just have the same demo, with all the chapters of all our features, on every single web page that has a solutions focus. Instead, if we're on a rewards landing page — this sounds really simple, and I'm sorry it's probably an underwhelming answer — we'll lead with rewards, and then show you the other features. It sounds dumb, but it is more work to do that; it takes time to set up the chapters that way. But it's worth the investment, worth the grind. That's been a really big unlock for us. I'd also say moving to a mid-gate has proven pretty helpful. We found our average drop-off point was about four and a half slides in, so we said, okay, slide four, that's our point — we need some sort of value exchange here, and that's been tremendously helpful.

Arthur: On that note, correct me if I'm wrong, but I think you're starting to experiment with the next iteration of this — based on where they're landing and what they're most interested in, you're almost taking them down a different buyer's content path?

Richard: Yeah, we're moving now to personalization as well. We're really testing the HTML demos in terms of adding personalization tokens and trying to understand the impact of that. I think that'll be a big unlock for our sales team, because all that feeds in from HubSpot — tokens — and we're doing all our sends from HubSpot. We have the Dunder Mifflin account, which I've gotten emails and messages about — "I love Dunder Mifflin, that's great" — but is that actually the best way to lead, or should we show what it actually looks like for you, your own company? Those seem like really fun things to keep testing. Really early for us, but I'm hopeful it'll prove fruitful.

Arthur: I love it. So, Fabio here had a question, and I'm wondering if you can speak to it — you came from agency life, now you're in-house, and maybe he's going down our path. He asked: how did you build enough trust to internally integrate tools like Clay and Storylane directly into HubSpot? Were there any concerns about data quality, or letting external tools write into HubSpot?

Richard: So I work really closely with our director of revenue operations, Katie Kilias — KK. She's actually going to be on the job market pretty soon; she wants to explore some other things. So if anybody's looking for a really good rev-ops person, please let me know — she's fantastic, my partner in crime. She and I are constantly Slacking and talking about different ways we can feed data in, because her whole job is to make sure our HubSpot instance is clean. Especially with us — we have a lot of franchise data, so if we're matching off of company URL, most franchisees don't have good websites, so they'll use wendys.com instead of their actual franchise group name. Suddenly you have 14 different Wendy's in your HubSpot. So we're very, very careful — probably too careful — with the way we test and validate, with ten rows at once, before we send anything back into HubSpot. We try to think through, from a systems standpoint, everything that might possibly go wrong before we do it. It is extra work, but you do need to work with a really good systems thinker. It's challenged me to become a better systems thinker, because I usually think of things from A to B — I'm just going to get it done — and I really need to think, okay, I know it's A to B, but maybe I'll take the scenic path, thinking through all the alternatives and outcomes before I hit play.

Arthur: To add to that from a more psychological perspective, Fabio — there's a sales tactic called the rule of two, where you don't necessarily ask for permission, but you give them two options. Always lead with your biggest ask first, because if they say no, then psychologically they feel like they can't say no twice to you, so maybe you get something on your second ask. And what Richard just said is really interesting — highlight the risks, because senior leadership is always thinking, "If we do this, what are the risks?" So let them know you're thinking about it, but also highlight what this will allow you to do. In Richard's case: hey, I think this is going to decrease CPMs, increase our pipeline. Show those, but also highlight how you're thinking, "This is what could go wrong, but I think it's worth the risk, because if we get this right, we can lead to these outcomes."

Richard: That's so wise, Arthur. For me, when I was putting all this together — the Storylane proposal, the Vector proposal, these were new tools for us — I created pros and cons of everything, gave a recommendation, and my recommendation was rooted in: here are the business savings by implementing these tools, and here's how we're going to know if it's successful three months from now. I also, frankly — and you're all here — negotiated three-month outs with every partner. Hey, I'm going to give you ninety days; we're going to figure this out together. And if we're not getting it right after ninety days, let's assess. That was really helpful. The other thing is, sometimes it's a compromise — sometimes you have to take on a little more work to get what you ultimately want. For Storylane, we didn't just hook up the HubSpot integration; I had to take extra steps to do the webhooks, send it into Clay, and then into HubSpot. Our compromise was, I said, "Hey, let's send company and contact records right now," and my rev-ops person was like, "Absolutely not, we're not doing that." So I said, "Let's just send contact directly, and then I'll figure out a way to do it in Clay with the company level." And she's like, "Okay, I'm much less worried about duplicate contact activities — HubSpot is pretty good at that." So we compromised, we figured it out. I went in with this big ask and ended up where I really wanted to be, but I did have to take extra steps to get there.

Arthur: There you go — rule of two in action. That's fantastic. Mike, if you're still on — what kind of impact did you see from gating the Storylanes, and any best practices? Renee, if you're still on the call, maybe after Richard answers, you can share more about how our customers have had success. But, Richard, I know your leadership was like, "Are we showing too much? Should we gate early?" and you landed in the middle.

Richard: Yeah. So we just showed everything at once, but it wasn't tremendously successful. We had a couple of direct conversions, so we knew Storylane was ROI-positive, but the conversion rate wasn't what we wanted it to be immediately. And this is forty-five days ago, guys — my demos were pretty crappy. So we moved to a front gate just to see what would happen, and we saw a huge influx of leads immediately. Great, so many more leads. And then after a couple of weeks, none of those leads were turning into meetings. So we're like, okay, there's got to be a middle ground. We weren't satisfied with the conversion rate, and we weren't satisfied with total engagement time on the demos decreasing so much, because we want a lead — but. So let's do the math, let's figure it out. I exported all of our demo activity into a CSV, uploaded it to Claude, and said, "Where are my average drop-off points by demo? What does my engagement time look like? Help me understand why users are leaving." We were able to identify which demos were performing better, then create hypotheses as to what about those demos was performing better. We found that when we show the frontline workers' perspective early on, they tend to stay longer — an extra two slides. Fantastic. I would love to get users to stay an extra two slides. So it really informed our methodology for how to use a mid-gate and what content should live before that gate.

Arthur: I love sharing not only their perspective, but what their users are going to see — because that's kind of what you're selling to, right? This is the end goal of the experience you're going to have. But, Renee, if you could come on and share anything else in terms of Mike's question of what our customers have found most effective.

Renee (Storylane CSM): Yeah, for sure. I also dropped an article to speak a little more to what you just said. We actually have our A/B testing too. So now, layered on top with putting all this data into Claude and having it extract those insights, you can have two different hypotheses and test both of them. That's a pretty new feature, A/B testing — it's available shortly now. I always say, on the home page you have nine seconds to get someone's attention, so keep that short, snappy, engaging, fun, ungated. And then on the deeper product-level pages, I've seen those go a little more than ten, twelve steps, but those are gated, and those are usually higher-intent leads and prospects, because they're taking the extra clicks to get to those deeper pages. So they're way more likely to fill out a form and self-assess whether they're ICP, and hopefully it leads to a faster sales cycle.

Arthur: I love that. It makes a ton of sense — if they're on your product page, that's somewhere in your weighted intent signals, Richard, of going deeper there. I've also heard, Mike — if you're doing chapters — some of our clients offer the first chapter ungated, but if they try to click into chapter two or three, they put up a gate there. So it's leading with the main thing they're interested in, getting them to that moment quickly, and showing there are more chapters to learn — but if they click into those, you can start to gate them.

Renee: For sure. And I'd just say, because this comes up a lot: if you have a product tour with multiple chapters, and you gate it at the second and beyond, they will not see the lead form again once they've filled it out. So, just putting that out there — on the demo creation, you'll have it at every chapter after chapter one, but once they fill it out, they're not going to be asked again. Just wanted to clear that up.

Arthur: Awesome. I think that's everything. As we wait for any last-minute questions — Richard, this has been awesome. Renee, thank you so much for sticking around and sharing those links and best practices. We got a last one from Steven — I'm loving the engagement here. He asks: I understand Storylane has its own engagement-score metric. Is there data and an algorithm supporting this? Renee, can you speak to that more?

Renee: Yeah, so we have our intent signals, pretty newly released. It's for every session, as well as at the demo aggregate level — so you'll see it in the audience sessions, and then in the insights we'll group it by demo for those different signals. We have three different signals, and they're based on a number of factors: one is the lead score, how long they spent, whether they filled out the lead form, whether they've clicked a CTA, how engaged they are. So there are a few things we use to understand how we'd give the intent. We can definitely get some more answers there, but it's a little bit of our special secret sauce, and it's new — I'll link the product updates from when we released it. But, yeah, a multitude of those three or four main properties.

Arthur: Amazing. And maybe this is a clarification question from Edgar, in terms of gating the form — what about whether the form is seen as Storylanes exist throughout the site?

Renee: Yeah, another good question. So you have a setting inside Storylane where you can turn off the lead form being shown again to returning visitors. If you have it on your site, you can extend that to however long you'd like, if you don't want them to see the lead form again — or they can fill it out every single time, on every session, every demo. So once they fill it out once, they wouldn't have to fill it out for another thirty, sixty, ninety days. I've heard both answers on why it's a pro and a con. That's going to be under your workspace settings.

Arthur: Amazing. Renee, thank you so much for staying on. As you can see, Edgar and Steven, our CSMs are very knowledgeable and very technical around the product. So if you continue to have these questions — and this goes for everybody still with us — use your CSMs. They're great resources; I'm constantly learning from them.

Other than that, I know we went way over time, so thank you all for sticking around. Richard, thank you for sharing all of your intent signals and intent flywheels. I thought this was a great session, and keep an eye out for the next one. Actually, it's not a Finer Demos Club — we're not inviting a customer to the stage. If you want to go deeper on this, we're doing an AMA with our CEO, focused on the sales use case in particular. We'll go across the go-to-market funnel, but that's the one we hear about most from our customers in terms of where they want to expand Storylane's usage. So keep an eye out for that — it'll be next week, April 2. You'll probably hear from us even today about that webinar. Thank you so much, Ranga, for putting the link in the chat. Otherwise, that's all we've got. Thank you all for sticking around, and looking forward to seeing you at the next Finer Demos Club webinar. Thanks, guys.

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