A Product Market Fit Show | Startup Podcast for Founders
00:01:02 · Mike Murchison, Pablo Srugo
[00:01:02] S1: Great to be here, Pablo. [00:01:03] S0: You know, today you're, you're the CEO of a billion dollar company, one of Canada's hottest startups. But of course, it didn't start out this way. And, you know, I think a lot of people will be surprised to hear that ADA , kind of like Twitter or Slack, is actually the result of a massive pivot. You know, about two years before ADA launched, I believe you'd started a company called Volley . So maybe let's start there. You know, can you tell us a bit about Volley ? What was it, what was the thesis there?
00:01:28 · Mike Murchison
[00:01:28] S1: So, ADA's story really begins seven years ago with Vol , which is a completely different product going after a completely different opportunity. Volley was a social search engine. Our goal was to make it easy for people to help each other solve problems, specifically problems related to , uh, entrepreneurial opportunities. People were, were pursuing , uh, by, by helping them connect with relevant experts in their network or through their social network that had the skills to, to help. We built this. David and I built this product on iOS and on the web that was growing really quickly , uh, at one point, quickly out of the gate, and we felt like we had sort of lightning in a bottle. Uh , it was very exciting. We encountered this customer service problem pretty early on. Uh, the problem was how do we scale our customer service operations in line with our user growth? Now, this was a particularly challenging problem for us because everything that we'd ever built , David and I go way back building a bunch of different software together, and everything we'd ever built that had been remotely valuable had come from a really tight feedback loop between our users and our product and engineering teams. You know, we knew our customer's names, we had a relationship with them . And I personally believe that, you know, great software, you know , bestows ownership on its customers, you feel as a customer, like the software, the product is yours, sort of in the same way that, you know, you might have a , a feeling of ownership over your favorite restaurant or your, your , your favorite cafe. We use the word, you know, that that's my restaurant, my cafe, my gym. And I , I've long been very interested in that level of ownership , uh, when it comes to, you know , software and that that intimacy was really eroding as volley got bigger. You know, we went from treating our customers as people whose names we knew and whose lives we felt like we were somewhat a part of, to treating them as numbers, to then treating them as numbers that we were trying to keep at bay.
00:03:26 · Pablo Srugo, Mike Murchison
[00:03:26] S0: And to be clear, these are, which, which types of customers? Like, are we talking business customers that, that you need to service or these consumers, like these [00:03:33] S1: Are all , it's all B two css , is it B2C app. So these are all consumers all not paying us. I should be clear too. So customers might be a generous term, users , um, and users at some point that we were hoping to figure out a way of monetizing. [00:03:47] S0: I see . But there was still a big customer success element to it, customer support element. There
00:03:51 · Mike Murchison
[00:03:51] S1: Was, you know, we wanted to make sure everyone was successful. And , um, you know, and , and especially in the early days of our, our app's growth, you know, we were really, we really, really cared about the quality of the community and the quality of the, you know, the, the engagement that our initial user base was, was experiencing. And so, you know, it was, it was pretty sad to see us sort of pursue the conventional customer service playbook, which is essentially figure out how to talk to your customers less, the bigger you get. And that's what we, we were pursuing. I mean, that was the, that was the playbook that, you know, we like almost every other business in the world was running. And I, I'd say that that playbook was, when we saw that, you know , I became pretty curious about why it was that, you know, we were, we were investing in talk , figuring out ways of talking to our customers less because it struck me that the , you know, the bigger we got, the more valuable customer data would become to us. In other words, this whole paradigm felt backwards. And so I, you know, I became very curious about that. So picked up the phone and, and called , uh, as many VPs of customer experience as I could, I could find. And , uh, David and I interviewed a bunch of people and we asked them like, why is it that you're speaking to your customers less and not more as you're growing? And virtually everyone agreed with, you know, the, the premise that it was sort of backwards to be pursuing the strategy that they were, but they also echoed, they also echoed each other in saying that, you know, customer service is a cost center. You know, this is, this is how we're, this is how we are structured. This is how we are , we've designed things. This is my job, and while I know more about the customer than anyone else in the company, we, you know, can't afford to increase our level of interactions. That was really the understanding of that problem that became the, the sort of laid the ground where it ended up becoming a pivot.
00:05:42 · Pablo Srugo
[00:05:42] S0: This is where the insight kind of really starts, right? I mean, I think to an extent the reason is , is obvious why you wanna minimize, you know, the amount of customer interaction. It's just like, it's more profitable. And you could argue the other time thing too, which is the less, in a sense, customers reaching out to you too much might mean that your , your product's not working well, you should just make the product more user friendly, et cetera, et cetera. What did you, you obviously disagreed with that, at least to a certain extent. Like what, what were , what were your , what was your thinking? What was your reason for, for disagreeing with that in the first place? And not just, I think like everybody else, just , you
00:06:13 · Mike Murchison
[00:06:13] S1: Know, it was a few fold , a few reasons. Like, one was just this deep belief that, you know, software is a service. We know this as like, you know, people who work in the SaaS industry. The , the , the word service is a really important word. It , it's, you know, we don't tolerate an experience where in the physical world where we , we don't like to tolerate experiences where we pay for something and, and we don't get what we paid for, you know , the, the , the service bar in the, in the software world. You know, I think we just had a sort of visceral reaction how low that was. Um, so maybe that was the , the first thing. The second thing was that I think that the, the world, the , the paradigm of talking to your customers less, you know, it was really , really born of an era where people really weren't making as many data informed decisions. And it might've been because a lot of this information wasn't digitized to begin with. Very , if you're running a , a legacy contact center and you're doing millions of phone calls a day, and those are analog phone calls, very difficult to mine that data extract insights and, you know, inform your decision making . And that's really where, you know, customer service was born. It's through the, the telephone. However, you know, in the digital era where we can actually start to make use of this information, you know, you can do more with this, it becomes much more action, much more useful. And so I, I felt as though the technology was actually quite a bit ahead of the strategy, and that seemed like an opportunity for us in building volley felt like we, we really should be, we knew our success had come from really rapid feedback loops between our users and our product teams. You know, the , the question was, why , how do we, if that works at a small scale, it should work at least as well at a big scale, maybe even better if we had more data. So how do we figure out how to solve that problem? That was the, that was the question.