The Bold Pricing Strategy That Transformed Trainer Road's Market Position

Oh, OK, um, I think there's two that come to mind, and one is, uh, one involves money, so that's always more important. Yeah, that pricing, pricing is, is, uh, is something that's irreversible most of the time and, uh, causes a lot more stress and, um, a lot more people have, have, uh, Um, have a stake in the game for the, for the pricing. So, uh, at Trainer Road, we had, um, We were coming up to a point where all of our competitors were, um, sort of the same price as we were, and we felt that we had a, a kind of a superior product and a superior ecosystem for someone to live in. So what we ended up doing was, um, I guess I ended up doing is doing quite a bit of research on kind of what the value looked like, um, in Trainer Road, and kind of breaking that down into how much that is worth to our athletes or our customers. And um we went through multiple different, or I went through multiple different scenarios where we could break things into different pricing tiers, we could break things into kind of um How, how do we end up, um, how do we end up making sure that the customer is getting value for a price point and make sure that our price point goes up and it's going to work with our funnel and, and work with our conversions and everything. And so what ended up happening is, um, I think the risk was pretty high, um, as, as you know, our trainer road has kind of a, we're, we're approaching our total addressable market. So if we kind of sour, um, the top or bottom 10 or 20% of our, of our customers, it's going to make a big difference, and they might never come back. And there's, there's plenty of other opportunity. Um, and so it was going to be a really high risk, possibly high reward solution that was going to have to build into the long term. Um, and so, in addition to the research and the different pricing models and, and coming up with three different scenarios, I also had to build out kind of future roadmaps for each of those three things that we were going to pick from. Um, and so what that also did is that was a couple moving pieces. So we had to implement a free trial for one or two of them. Um, we had to implement kind of a, a basic version for one or two of them, and kind of how that was going to weigh into the moving finish line of what this conversion was going to look like and how the money was actually going to stack in the bank account. Um, and so, The, the basic solution was we're gonna give legacy pricing to all of our athletes, or all of our current users. Um, it never changes if you leave, um, and that was, uh, kind of a, uh, thank you to all, all of our, all of our customers who had stuck with us, um, but we did raise the price, uh, almost 25% or 33% depending on, yeah, and, uh, there was, it was a big deal. Um, it was a lot of, there was a lot of really noisy feedback, um. That kind of shook the foundation of Trainer Road because generally speaking, we'd, we'd always been such a Uh, well regarded company, and we had a lot of brand equity built into the system. Um, and so what we ended up doing was When you, um, hear all the, the feedback and, and kind of the. The loud, the loud people making a lot of noise about all of these pricing and how it's never gonna work and, and all these things. Um, I think the solution for me, um, and we had a lot of follow-ups right really quickly afterwards as, as we were figuring this out, is that the numbers were actually in our favor. Um, and we were losing a small amount of our athletes, we were losing kind of, I think it ended up being about a 5% drop off total, but initially, it was, it was really, really small. Um, like a 0.5% for the first kind of the fall leading into that. And then there was a drop off as more people came back and the returning customers came back and it end up, ended up being about 5%, but overall, it increased our, our kind of a rolling MRR by 20%. Um, and so, a lot of those people. Um, a lot of those customers weren't, weren't actually going to be happy at any price point. Um, and so I do think that, um, making sure that we're making 80 or 90% of our customers happy and kind of filling the higher realm of pricing, um, but getting, taking your licks, um, and watching, watching a product launch. Really get kind of smashed from a, from an outside perspective, and, but just steering to the data and looking at the numbers and reading that there is lots of feedback, just as many feedback, just as much positive feedback that Trainer Road is totally worth this amount of money versus there's no way that Trainer Road is worth this amount of money. So the feedback is kind of mirrored on both sides, but the data shows that we're at, we made the right call, and it made us. It set us up for success and enabled us to build a lot more, um, over the next year or two with 20% more money, um, coming in, which was kind of a, it was a bold, it was higher, my, my pri, we picked my price structure and it was kind of not the highest, but it was, it was up there and it knew that it was going to, it was a riskier, riskier scenario, um, and that's the one we ended up going with, um.

um, so. The beg for forgiveness part is that, um. Initially, uh, That first, that first day or two of feedback, um, Nate, Nate had to, Nate really wanted to pull the plug, our CEO wanted to pull the plug, um, and, and backtrack, and I guess technically, um, it would be companies for forgiveness, uh, which might change this question just slightly. Um. But technically, that would be me, right? It was my product. It was, it was my feature, it was my launch. I would have had to blow it up and say, that was my, that was mine. Um, and I, it was definitely really close to, um, Taking that. Um, we kind of thought about it for a week and, uh, it was up to me to make the call. Um, Nate, Nate was for it, and I said, well, why don't we, I'll, I'll pull it in, in a week if the, if the numbers aren't there and we're not seeing, seeing the feedback from both sides. Um, and it's one of those where we can't, we can't make an instantaneous decision, um, based on, on a couple, on some small, small amounts of feedback. And so it was gonna be me, um, saying I got it wrong, um, that, that project was, I, I did it incorrectly, and, um, It's all my fault. Um, and so what we ended up doing is just making a dashboard, um, checking the numbers versus the, the previous year, and, um, checking the actual falloff and the actual negative support tickets. Um, and so the feed-in of the support tickets, um, actually ended up not being, um, it was like, A couple of sport tickets a day out of our couple 100. So it, it, the numbers that we were seeing on um various internet channels were not the actual numbers we were seeing from, um, overall. So, uh, it ended up being Um, I didn't actually have to ask for forgiveness, uh, which Doesn't, doesn't really work in this scenario, but it was going to be a, it was going to have to be the way it was going to go, if it, if it went poorly.

No, I would have changed it just slightly, honestly, um. We, it would have been, it was very close to what we wanted, um. But the few things I was close to what you wanted, yeah, the, the end result was close to what we wanted, and, and the kind of the, the given, um. Uh, the given solution that we went with is close, but, um, I would have personally, uh, I would have personally fast tracked. Um, uh, launch feature like free trial to do at the same time, and I knew it would have muddied the data, or some other sort of incentivized thing for, for any of our customers to, um, A good example would be, um, our, when we, when Plan Builder became free, um, and so you could build out a plan for your goal, um, if we could take that at the same time as our price increased because technically all we did was Increase price and say we're going to use it to build new things. Um, and, and from an optics perspective, um, that just doesn't fly. Um, and we said we had done things, you know, there was new desktop apps, and I think the mobile apps were coming, but, uh, from a, from an optics point of view, we did absolutely nothing and there was no, um, Time crunch to win the time, uh, other than we would lose more money by not making the price increase earlier. Um, I would have cherry picked it and reprioritized some of the feature we were building so that there was not a concurrent launch that was tied to it, but a slightly Slightly earlier value add and then a price increase, not at the same time, hopefully not even in the same window, but just to get the wheel turning and, and to make people feel like we're increasing value for them constantly, um, rather than it's tied to a specific feature and that's why this feature costs more money.

So how did you go ahead.

Um It was really hard. Um, yeah, that was, that's the. Um, That was the most difficult part of the whole thing, I would say, looking back on it now. Um, and kind of the best way I could do it, or the only way that I could, I could get, um, my point across is by pulling in things that I wasn't saying. You know, I could, I could say with my finger in the wind and my gut, and this is the way I'm thinking and, and the way the overall ecosystem works, I think this is correct. Um, but if we, as soon as we started pulling in The first thing I did is we had um the negative tickets come in, and then we looked at um kind of their usage metrics. So we were seeing what the people who were complaining about the price increase, um, were doing. Um, and then some of the positive, um, feedback, we also pulled in their usage metrics, and so we were seeing that, um, the kind of determined value that the that the customer had is directly correlated to how much they use the product. And the people who were more, um. Who used, who were complaining more often about the price actually use the product overall less. So in turn, they were actually getting less value out of the product, no matter the price point. And the people who were really happy, they would have paid twice as much because they were getting so much value out of that. So that was the first thing we did because um I wanted to validate. The, the feedback we were getting, and I want to validate against positive feedback as well. So there were some, we had a couple of different channels, we had, um, the forum, um, support tickets, you know, YouTube comments, the whole shebang. Um, and so we, we pulled all those in, and then it's really easy to marry those two. Um, to a member ID and pull in what kind of, uh, what their usage metrics were like, you know, rides per week or, or something like that. So that was the first step. And as soon as we, as soon as we were showing, as soon as I was able to show Nate that a lot of people that were complaining weren't actually using the product and kind of not the people that were, they're not gonna see the value, um, that Trainer gives. No matter the price point, um, and this isn't all of them, but that's just the majority of them, and that's how we ended up pulling, um. More data just to see. So as soon as it wasn't, uh, it was just a knee-jerk reaction from some people, I said, well, then, the next step is let's make sure it's actually making us money, because if it's not making us money, then of course, it's, it's wrong. Um, but you can't, you can't take that within just a couple of. Days, like, let's, let's compare the week from the previous year's week and the year before that and actually see what kind of, um, and the even the previous price raises, um, and so you could compare the kind of uptick um from that, uh, overall.

OK.