Scaling from $200K to $100M ARR, Balancing PLG and Sales-Assisted Motions, AI in Product Analytics, The Power of Human Creativity in Tech, and Leveraging Self-Service Strategies with Michael Hoy
We recently spoke with Michael Hoy, AVP of Commercial Sales at Pendo.io. Michael was one of Pendo's first sales hires, joining when they were at just $200k ARR and helping grow them over 1000x to the industry leaders they are.
In our discussion, Michael shared insights into how Pendo balances product-led growth with human sales support. As he explained, Pendo aims to enable self-service while providing one-to-one assistance when needed. They focus on identifying customers seeking more automation, while enabling personal support at key moments.
Michael understands the hard tradeoffs startups face here with his 17 years in startups and experience founding three himself.
Watch the clip to learn more on how Pendo approaches this balance and sales strategy overall.
Michael Hoy
LinkedInTranscript
Sham Mahajan: Hi everyone, welcome to the GTM Spotlight podcast. I'm Sham, your host. I have Michael Hoy today from Pendo who's joining us to speak about his experience at Pendo. He joined Pendo as one of the first sales hires and helped grow the company from the early days of 200k ARR to over $100M in growth. He's currently the VP of Commercial Sales at Pendo. He has 17 years of startup experience and has been a founder of three startups. So Michael, thank you so much for being here today. As the VP of Sales at Pendo, what are your main responsibilities and objectives?
Michael Hoy: Thanks for having me as well. Super grateful to be here and always good to spend time with friends. So anytime you and I get a chance to connect, it's valuable and it's awesome. My role as VP here at Pendo has certainly evolved over the last few years, but primarily right now, my job is growing our new business for employee accounts under 1,500. We focus on selling to customers who are not just in that startup stage but that scale-up stage and are not yet enterprise. I think very relevant here is the idea of how we are optimizing our sales process and our sales motion to include product-led motions and strategies along with sales-assisted ones, as the majority of the customers we sell into are expecting that innovation, love that innovation, and oftentimes are asking for that from us.
Sham Mahajan: From the early days, how has Pendo always found a balance between PLG and sales?
Michael Hoy: It's a great question, and I'll give some context as to what Pendo does. Pendo is a product cloud. We provide a solution that helps product teams and product builders the opportunity to improve efficiency internally with what product they build, to cross-sell and upsell, create more revenue within their bottom line, and mitigate churn with customers that may be at risk. We do all this through a combination of product analytics, usage data, in-application guidance, AI, and product road mapping.
Oftentimes, the customers that we are selling into are looking to Pendo and looking to our product to become product-led themselves. They're hoping to build these motions internally, they're hoping to understand what their users are doing so that they can automate onboarding and improve conversion rates. They're hoping to automate parts of the churn and renewal process and understand who's ready and who may be at risk.
So at Pendo, our strategy has always been to try to lead from the front. Let's dogfood our own product and let's continue to try out these strategies for ourselves. That, in turn, becomes something we can sell back to our customers or at least consult them on through the process.
To answer your question, from a very early part of the business, from a very early age, we were trying to use our product on the sales floor. When people get into our trials, we measure what they do and we try to understand what converts. We're very transparent with that. If you're evaluating Pendo, oftentimes we'll show you what we know about your usage and we'll say, "Hey, based on what we've discovered and what you've told us, we think you should use these parts of the application."
We use our own product to put guidance inside of our free product and our trial that is targeted and based on parts of the application that people aren't using that we believe they'll get value in. We'll try to take them into those parts of the application. While we're watching on the back end, we know when to airdrop into the sales cycle to assist. We know oftentimes if a person isn't hand-raising, when roundabouts it might be a good time for us to drop in and say, "Hey, I'm noticing some usage patterns that are very interesting. Would it help to get further training? Would it help to get further support in this one area?"
These things have really helped us improve conversion rates over the last eight years, but that stuff doesn't happen overnight. There's a lot of testing, a lot of experimentation. But at the core of it, we've always just tried to dogfood our own product, meet our customers where they are, sales-assist them when needed, and product-lead them every other time.
Sham Mahajan: That's an important insight to always dogfood and understand your customers very well, whether it's product-led or whether it's a sales motion. I think the key is to be able to get that customer feedback. How do you do that? How do you influence customer interactions and experiences at Pendo?
Michael Hoy: I love this question because, in full transparency, I don't actually believe this is something we've nailed until recently. Being a product-led company, trying to do product-led for the better part of a decade, it's kind of odd to say, "Oh man, there are still things that we haven't nailed, that we're not good at yet." But certainly, there are, and we've got a growth mindset, so we're very aware of where we still might be missing.
We kickstarted a project dedicated to building free and self-service products about two and a half years ago. In the process of building those, we really started to uncover the gaps in our feedback loop and how much we really started to devalidate how much we thought we knew about what our customers wanted.
We went with a strategy of, "Hey, our customers who are 50 employees and less, we're going to self-serve all of them. In fact, it's going to be very hard for them to talk to a human." Partly because this is what we thought we knew about our customer base, but it also made a lot of sense for our business and the scalability of our business.
We learned pretty quickly that even though people buy our product to become product-led, even though they want to use our product in a product-led state, they still very much need humans. We have a complex product. It serves a number of different people inside of your business, it does a lot of different things, and it helps you accomplish a lot of things. So it can be really challenging to eat the elephant, so to speak.
We were finding that even our smaller, more agile, and innovative customers struggled with full self-service. In seeing those conversion rates drop, we started to learn, "Oh my goodness, I don't think we exactly know our customer base, or at least in this realm. I don't believe that we are collecting the right data, the right insights, and understanding their feedback."
We used our own product a lot to help solve that problem. We've got a product internally here called Discover, which helps collect product feedback inside of the application. We also spent a lot of time talking to customers. The sales team was critical in this. Often it's the product team that spends a lot of time collecting this feedback. The sales team partnered with product to verbally collect feedback. We use great tools like Gong to record and send snippets of opportunities where we've been able to collect insight from customers.
We tried to triangulate all the relevant data, like self-guided walkthrough tours and conversion rates at other parts of our acquisition pipeline that just showed us, "Hey, customers who were product-led and had interactions with humans at specific points converted this much further, this much more." That's really what gave us the foundation to then go ask some of those questions of our customers in person.
Sham Mahajan: You guys are industry leaders literally in this space, and you still have such a humble outlook on this and also such a growth mindset.
Michael Hoy: I think, and you'll find this, we are so fortunate that we both work in this industry where it's super competitive, it's very capitalistic. If you're not open to improvement, if you don't have a growth mindset, you'll disappear or evaporate. We very much feel that internally. We've got great competitors, they push us to our best. To the extent that if we don't think like that, we're going to find ourselves being number two, number three, maybe number four.
Sham Mahajan: You mentioned that you use some self-guided tools. Are there any other strategies that you've explored to promote that self-service?
Michael Hoy: We have. One of the reasons why I think your product is so interesting is it does a lot of what we like to do inside of the product, deeper into the sales cycle, at the top of the funnel. We've certainly had success using strategies like that.
One of the reasons why I'm confident in the space and the challenge you guys are attacking is because we've had that challenge. We've applied similar strategies and we've seen great success from it. I think we've tried a lot of things and we've also failed in a number of different places.
I mentioned that self-service product initiative we had. Admittedly, that did not go according to plan and certainly isn't producing the way that we thought it would. Not to say that it's not successful, I think we're just picking up more learning than we thought we would. We very much felt like we had our arms wrapped around it.
A lot of the challenge for us has come in understanding what we can offer our customers in both a free package and then a paid package, where that jump from free to paid really makes sense. Similarly, we've struggled to completely give people the tools to self-serve.
I mentioned that we've got a complex product, and while the majority of our customer base still finds value in a human-assisted motion, there is a portion of our base that doesn't. We've done everything. We have a team internally that is meant to serve our customer base one-to-many in a way, through our application, through guidance, through other knowledge bases and other mechanisms.
I think you'll find, like most businesses our age and size, we've tried the gamut of documentation, help docs, things like that. All that to be said, those just take a lot of time. They take a lot of mental equity for the humans that need to work on those things.
So we're consistently trying to innovate in how we identify people who want to completely self-serve, and then educating them and moving them through the buying process, whether they've purchased already and we're moving them towards renewal or upsell, or if they're experiencing Pendo for the first time in the early stages and we want to move them towards an official contract or an official partnership with us. All that to be said, still testing and learning a lot of things.
Sham Mahajan: You mentioned a key thing, which is educating the customer is important in this product-led sales approach. Have you explored AI tools or personalization or any strategies like that to educate customers or to create any sort of educational content for them?
Michael Hoy: I'd say that our exposure and experience with AI is a mixed bag. We have spent a lot of time internally ideating, building, and executing on plans to incorporate automated intelligence into our product. We've got a boatload of data that we collect from each one of our customers, and there is a lot of value we can drive by sifting through that data and making recommendations for our customers.
Admittedly, where we've struggled is finding great AI solutions to use here internally for efficiency sake. We've tried a few AI solutions at the top of our funnel with our SDR team and with our AE team, and they actually did not prove out positively.
But one of the things that we do know is that, especially at the top of our funnel, budgets in our customer base are shrinking. The value our product must produce must cross a higher threshold than it ever has to get approved by CFOs. Therefore, getting people's attention, educating people on why Pendo and why now, is going to be that much harder.
We found, especially with human-led activities, that personalization is now one of the most effective ways in which to engage people via outreach at the top of our funnel, to pull people into our self-service funnel, whether that's through our marketing page, our self-guided tours, things like that.
But there is not, that is not a nut that we have cracked. As someone who's a big fan of this innovation in this space and eagerly awaiting products and sets of products that drive a lot of value here, unfortunately, we don't deploy any AI in our motions today to acquire customers, to educate customers. Though I think we all have this feeling that there's a big opportunity there.
Sham Mahajan: What is Pendo's outlook on integrating AI into the product?
Michael Hoy: We have such an exciting roadmap when it comes to how we are incorporating AI into our product. It's pretty vast. Before the AI boom, we were working on integrating automated intelligence into our product to help surface really key pieces of action-oriented data to our customers. For example, which customers are at risk based on both qualitative and quantitative feedback, and what are some suggested actions you can take within your product build.
I think it's one of the biggest initial use cases for automated intelligence. When you have oceans of data to go through, it becomes very paralyzing. Actually, one of the challenges with our product for a long time was that we presented our users a lot of information, but we often didn't give them action or suggestion on action to take. It was really great to have a lot of information, but our customers didn't know what questions to ask yet. They weren't certain how to use the data, how to prioritize it, things like that.
We're finding use for AI inside of our product to go through all of that data and make suggestions to customers, like, "Hey, this segment of users is falling off of your onboarding after 60 days. We suggest this set of walkthroughs inside of the product." As a user, all you need to do is click "Yeah, that sounds good to me." The walkthrough is built because the AI is able to tag your product with them, is able to know the design of your application and build that into the guide. Of course, it's sifting through the data, is able to segment and target the users based on their adoption of the application.
So we're finding really great uses to not just drive efficiency in how people are able to go through their data, but then promote this action that ends up leading to the outcomes of why people buy Pendo and why they need us. For us, it's a bridge. It's a bridge to get from really great access to information to actual action that creates bottom-line impact for the business.
Sham Mahajan: I think that's a great way to use AI for insights, especially when you have tons of data for both building the product as well as for integrating it in your product and growth. Thank you for sharing so much about Pendo and your experience so far.
I have one last question for you. What advice would you give to those who are aspiring to lead in growth and strategy, especially in an AI and product-driven environment?
Michael Hoy: This may sound counterintuitive. The AI revolution has begun, absolutely. Technology is so exciting. This is going to change the way we work, it's going to change the way we interface with software. Our lives as we know it, it's going to be one of those inflection points. 20 years from now, we'll look back and our kids will tell their kids about life without AI, and it'll be like what life without the internet was like, hearing about that.
So my guidance to anyone looking to get into the space as a leader is a little counterintuitive, because it's, "Hey, still pay attention to the humans." One thing that AI doesn't have the ability to do right now is create net new. The way we use this technology, the way we apply it still depends on the creativity of a human. It still depends on one human listening to another human and taking feedback and going, "Oh, that's where we can use AI. That's where we can use this awesome, great technology to not just solve this problem, but force-multiply the output."
If you're getting into this space and you want to lead, one of the best things you can do is help guide and coach the creativity of those who are working with you and for you, because they're going to be the ones who build the ideas for implementing the solutions that, in turn, change this world. This technology is here and will change the world, but humans still need to drive the application of that.
Sham Mahajan: I absolutely agree. That is wonderful advice. Thank you so much again for your time and sharing all of this. I look forward to having you again on the episode soon.
Michael Hoy: Yeah, thank you so much. Anytime, tons of fun. Looking forward to talking more go-to-market, scaling, and AI next time we get together. Good luck with everything.
Sham Mahajan: Thanks, bye.