Why Retention is the New Growth for Product Leaders with tray.io Head of Product Bella Renney

Everyone come in and then we can get started. Okay, I hope everyone can hear me okay. Let us know in the Q&A if there's any problems, but I just wanted to introduce myself to kick off. So my name is Bella Rennie, I'm out of London, and I'm the Head of Product of Trey.io, and I'm gonna kind of predominantly talk all around this kind of key theme here. So what is it about retention that can provide the new growth for product leaders and to inform product strategy. And to kind of kick off, I'll just go over kind of the agenda. So, there's 3 kind of key buckets that I'm going to talk about today. The first one being how the new kind of growth driver for product strategy can really be all around retention and expansion, upselling your customers. And then secondly, what, what is it that you need in the engine room to make that happen? So looking specifically around the data and the analytics framework that might be useful in order to facilitate this and how you can kind of automate and break down those data silos to make that happen. And then the tools that you'll need in order to do that. So hopefully a really actionable and practical 20 minutes to give folks some ideas around how they can take these and implement them in their own context. So, you know, this is kind of the theme, right? So, you know, in the past, strategies that product people and whole companies would have to grow and to engage with their customers in person, at events, in other spots, is not what's going to work today. And we've got obviously a new environment to be getting used to and to be wrestling with, and everything needs to change to facilitate that— the growth of businesses in a sort of different environment. So, you know, for me, this is the crux of the matter, right? Turning that strategy on its head from net new revenue and acquiring new logos to actually a focus on retention and how that can be the driver for growth. You know, and to start off with, it's important, I think, to frame why that matters. And I think the first reason, or the most important reason, is that it's much, much more efficient. You know, you think about efficiency and the fact that we're going to need, as kind of product leaders and as business leaders, to focus in on the investments that we're making, be very strategic with those investments, and also to do a lot more with less. So, you know, just kind of zeroing in on this graphic here, it's really clear that it's 7 times more expensive to acquire new customers than it is to renew and to expand existing customers. And if you think about what happens when you lose customers, when customers churn, not only do you lose that ARR that they provide, but the average lifetime value of the customer account goes down as the customer life cycle— lifespan, sorry— shrinks. And then you've got to go out and do the really, really expensive hard graft of acquiring new revenue and new customers to replace the ARR that your business has lost. And that's incredibly painful. And it's also really, really difficult. You know, one of the biggest costs that there is to doing business is acquiring new customers. And that CAC ratio, you want that to be as strong as possible. And the cost of acquiring new business is really substantial. So I think that's kind of the key piece, right? To make sure that you can focus in on efficiency. And when budgets are being analyzed to kind of within an inch of their lives, making sure that you're using that money and making sure that you're providing value. So, you know, what does it mean if you do kind of switch to this, you know, so you sort of switch this mindset and switch to this kind of strategy all around focus on retaining customers and growing these accounts? Well, this is what can happen, right? You know, you have the fastest growing companies have a huge amount of revenue coming from expansion. And it's the kind of key thing as to how you can sort of get to the utopia of what some people kind of call negative churn, right? Where not only you're retaining customers, but you're expanding them. And what does that mean? Well, it means that if you've got, you know, 120% or 130% of, of retention that you can essentially grow organically. And I think that it was Twilio that posted in Q1 of 2020 that they had sort of a net retention of 143% based on a strategy of retention and expansion. And what that essentially means is that you can have a whole year— Twilio can have a whole year of not acquiring any new customers whatsoever, but they'll still grow 43% as a business, which is pretty incredible. So, if we kind of go forward with that context in mind, what is it that you can do from a product strategy standpoint to action some of this context? And I think that there's 3 things that I personally did myself and that I would kind of advise folks to do on the call. And the first thing is to look at what are the data points that indicate success for your users, and conversely, identify what are the data points that indicate that a customer is not really engaged with your product, is not getting a huge amount of value out of it, and be sort of laser-focused on what those indicators are and utilize the product data that you have in order to be really clear on those indicators. And then the second thing is about getting that data that maybe, you know, your product team has, that you as a product leader might have, and then democratizing access to it and distributing it to make sure that people can access it. And the key piece here is Making sure that users themselves can get successful on your product and with your platform alone. They don't need to rely on sort of a high-touch approach, but actually they've got access to the resources that they can dig into to empower themselves. And then it's this final piece, right? Being smart about where you invest that time and where you invest in terms of where your engineering resources are going. Are they going towards building your product? Are they going towards building out sort of in-house tools that then facilitate customer health, whereas actually there are other folks in the business, account management or customer success, that actually if they have access to those tools, they can then make sure that those customers are successful themselves. So kind of let's dig into the first piece here. So it is around the automation, essentially, and breaking down that data to automate processes and, and access to it. So first of all, when you're thinking about product analytics and what are the indicators of success in the product to show that a customer is either ready for a potential upsell opportunity or to expand their usage or to make sure that they're not going to churn out and they're not going to renew, That's all about building actionable data dashboards. So an example that I just thought I'd throw in here is something that we did, something that I did with the data team at Trey, specifically all around this strategy. So if you look at the sort of pyramid on the left there, this is what we created. So at the bottom is all about kind of impersonation, I think. Everybody has a sort of version of this themselves, which is how much do customers take action in your product and in your platform themselves versus other folks in maybe support or professional services or in customer success building out things or doing things or troubleshooting on behalf of the customer. And that's kind of our impersonation model. So how frequently do users do something themselves versus the percentage that it's being done by folks internally at Trey. And then on top of that, we built a user score model. And I'll go into that with the graphic that's in the bottom right in a second. And that's all about 3 key pillars. The first pillar being engagement, the second being capability, and the third being value. And then that all rolls up into essentially one account health score and a sort of account health dashboard so that you can see, is there a churn risk with that account or is there conversely an expansion opportunity with that account? So focusing in a little bit on the user score and how I basically tried to identify touchpoints across our product portfolio to build into 3 pillars with one overarching metric that indicated sort of various metrics for those pillars that showed sort of the breadth of actions that users were taking, and that then all helps us analyze whether they are kind of healthy as an account. So first of all, it's about engagement. You know, everyone has, I think, a traditional set of metrics around engagement. You know, they're to do with logins that you can see here. So 1-month logins versus 3-month logins. Particular to our use case is all about the engagement that the individual users and users in the whole account actually are showing on our different learning platforms. So the Trey Academy is something that's referenced in green, and then the documentation platform as well. So are they utilizing the resources to help them be successful in our product. And then the hours updating, which is essentially, you know, the hours that the user is spending doing something of value in our product. And then the value score. So how much of our product are they using essentially? Like what's the volume? So the number of services, for example, or in our case, with the workflow automation and integration platform, the number of distinct workflows that they're building out, and then the number of API calls that they're making. So task usage. And then finally, it's about capability, which I think is hard to get right, but is really important to try and tackle, which is how proficient is that user at utilizing your product? You know, what areas of the product are they touching? Are they touching areas that are really difficult to use and showing that they're really capable of, of getting your product to do what, what it is that they want. So we kind of have two pieces here, which is the Connector Difficulty Score, which is particular to our use case, but essentially, like, can the user do something that we consider relatively difficult, and how can we measure the overall sort of percentage of users who are able to do that, and then we can prioritize where to put resources to making that easier and less difficult. And then also the workflow count score. So how many workflows they have, how many times they're utilizing our product to build an integration between different services and to automate a process, and what's the volume of it. So they're building something that's valuable, hopefully, and are they doing it in a kind of complex— are they building something that's complex and difficult to do? And as you can see through the different sort of colors, indicators on this graphic, we've iterated on this a lot. So we had sort of data points that we deprecated that weren't really showing the story that we needed them to, and they weren't necessarily indicators of success. There were data points that we went back to and we reworked the weighting of how important they were to the overall pillar. So those are the gray ones. The green ones were brand new that we built out when we sort of reframed what success in our product looked like sort of 3 to 5 months ago. And we've been iterating continually ever since. So that's kind of an example of how you can get the data that you need as a product person and identify those indicators and build kind of something similar that rolls up into an account health dashboard. And then how do you turn that into kind of action? So we talked before around the different sort of actions that you can take as a result. And this is the big one, right? Connecting all of that data together to then drive scale and efficiency. So when you've got all of that data, you then need the right tech stack to sort of take action. On it. I think the first thing here is making sure that the tools that you utilize, be they product analytics tools like Amplitude or Mixpanel, do you have access to everything that you need? Are you able to utilize the public API, for example? Are you able to add as many people that you need? Are you able to control their roles? And do you have access to role-based permission settings? Can you containerize or compartmentalize important assets or groups of people and access to different data. And then how can you break down those barriers between different tools in your stack to democratize access to this data visibility and to make sure that members of different teams are able to collaborate? You know, no one exists in a silo, and it's great that I've, as a product person, identified these key touch points, but if I don't, then make sure that our customer success team or our account management team have access to that data and can see how healthy is that account, what's their capability like, how engaged are they across the product portfolio. It's almost useless if you kind of keep everything within the product or the product and engineering teams. You've got to get that out to your go-to-market team so that they can then focus on employing the best strategy possible to make sure that each sort of account can be retained, not only retained but expanded. And having access to that data then drives decision-making. So for example, if you can identify as a CS or as an account management team that a particular group of customers or a particular customer that we know is really important and has a huge value, isn't as engaged in the product as maybe other customers are, or maybe their capability score is really low, maybe you do provide that high-touch approach. Or actually, if it is just about engagement, but when they do use your product they're really capable, is there an opportunity then to add them to marketing campaigns to remind them around the self-service resources that they can have access to, to get other ideas around use cases that they can utilize. And it's a different approach, right, depending on what the data is showing not only the product team but the whole business about the customer. And then you can employ the right retention strategy or the right upsell opportunities based on that data. And then finally, I think that it's important never to kind of forget that your customers are looking to your product for the exact same thing, right? They're looking to your product so that they can become more efficient, so that they can get their data in the hands of the right people. And I think that making your product as sticky as possible is a strategy that just empowers the sort of efficiency that your customers get from using your product, right? So if they really rely on it, if it's improving their efficiency, if it's able to break down their data silos that they have, then it's only ever going to be stickier. And if it solves a particular problem for them to make them more productive, it sits so nicely in their tech stack that it's so unlikely it's ever going to be ripped out. So I think with that kind of final point, the, the thing for me and the theme is that breaking down the silos between different teams and making sure that data is integrated between the different tools that you use, but also between the different teams that are all providing that sort of 360 sort of hug around the customer in order to focus on that retention and upsell strategy. Integration is, is the most important piece there. So with that, I've come to an end. Thank you so much. It's been great to kind of share thoughts, and it'd be great to hear from more of you in the future. So thanks very much for having me. Thank you so much for joining us today, Bella. It was such a pleasure, and looking forward to the follow-ups of the questions that you will be sharing as well alongside the, the deck and the recordings.