Hi and welcome to the sixth episode of the Growth Machines podcast. I'm your host Vincent Jon, and today I'll talk with Todd Olson about how Pendo customers use in-app messaging to provide tailored user experiences. This interview is part of my book about product-led sales. If you're wondering how to introduce PLG in your sales operation, then this book is for you. For more info, visit plgandsales.com.

Now let me introduce Todd. He is the co-founder and CEO of Pendo, one of the leading providers of in-app messaging software with 2,500 clients globally and a team of 750 people. He has founded two businesses before this—a data integration company called Cellum and a company called Six Sense Analytics that had a focus on product data. Six Sense Analytics was acquired by R Software, after which he served there as VP of Product. These experiences led him to create Pendo in 2013 with the vision to empower product teams and improve software product adoption.

Alright, hi Todd, great to have you!

Thanks for having me, it's great to be here.

To set the stage of what we want to talk about today, can you give a brief overview of how companies are using Pendo today to grow their business?

Yeah, so look, Pendo is—we think of it like—a platform to help drive usage and adoption of software, and it has a variety of components. It kind of starts with data and analytics. So we collect product analytics and sort of collect everything. Fashion you drop us in, we know everything happening—from what they’re clicking on, to user journeys, etc. Then we combine that with a broader set of capabilities. Using that data, you could target users for in-app messaging. So we have a full in-app messaging platform—everything from interstitials that interrupt the user, to step-by-step guided tours, to widgets in the corner which help with self-service.

Then we have a whole set of qualitative features, like asking people what worked well or what features they want. And then, most recently, sessions, which is watching people use your software. We see this used for optimizing onboarding flows, like watching someone try to check out from your software and figuring out what they're clicking on and looking at. It’s a great way to look at growth.

So that's kind of what we do and how people use us. Look, we support a broad range of customers. We work with everyone from four-person startups to large enterprise organizations. I think we see folks use us a lot for what people would describe as PLG, or product-led growth. That’s everything from providing some level of guidance and assistance when they’re coming into a freemium product to driving nudges and campaigns to advertise areas of a product that maybe a user is not yet taking advantage of or using—which could either be for a conversion event and/or just exposing someone to expansion capabilities.

Self-service is another aspect of how people use us, which is a different type of growth, or maybe it’s more retention. When someone gets stuck or isn’t getting full value out of a software, the software intercedes to help nudge and help the user. And lastly, PLG Assist. I always think that being product-led is a spectrum. There’s full self-service—software does everything, humans aren’t involved. But I see a lot of our companies and customers using us, leveraging data or other means, to help the users be more proactive and efficient.

For example, if I’m trying to drive a more efficient go-to-market and I have, let’s use CS as an example, CSMs who have maybe a scale motion where they have hundreds of accounts. You’re not going to call 100 accounts every single week—you just can’t. But you can use signals from the product, you can use product data, to help inform where you spend that time. It could be everything from, “Wow, they’re spending a lot of time in this new area. Maybe I should offer to see if they want to upgrade.” Or, “They’re not using this area of the product much. Maybe I should go save this customer by making sure they do that.” That’s a way that PLG Assist is something pretty common in our customer base.

Yeah, you’re touching on something very interesting there, which is combining the best of product-led growth with the human touch of a sales team or CS team. And you mentioned some examples. A big topic nowadays is efficient growth, right? So what are the things that you're really seeing working?

If you'd go at some examples of what companies are doing—look, I think—look, going at the very, and I'm going to just take some simple abstractions so people think about it. Like, you know, like if you're a company and you serve a broad set of the market, meaning you serve both small customers and big customers, I am seeing folks in order to drive a more efficient go-to-market motion look at kind of under a certain size. It's different by company; you know, we actually look at employee size. Some people look at revenue; some, you know, look at spend.

Trying to find a way to create much more automation around servicing those customers both on the acquisition side as well as on the post-sale side—one company we work with, a large enterprise customer, they do have, you know, big companies using large enterprise sales. They started using us as a way to almost as product-led sales engineering. Someone gets into a trial, and they want to make sure within a trial the prospects are doing just, say, five things. They know that if they do these five things within a trial, they're more likely to convert to, you know, close one business.

So that's an area where using a set of organized guides, you can sort of like say, you know, your nudges—someone logs in and says, "Welcome to ABC's trial; you know, try this first. First, you know, check you did that. You know, try this second, check you did that." That's an awesome way to reduce the reliance on an SC by making sure people are seeing the product. If you think about it, a decent part of the humans in our go-to-market's job is teaching people how to use the product because people do want to try things before they buy it, and that is something that, frankly, is a commodity—teaching someone how to use something.

So if we can find ways to offload that from the humans so the humans are being used more for maybe the value or the negotiations or the heavy differentiation from competitors or things like that, then I'm seeing a lot of success with that. Better onboarding or getting people started on the right use cases will, of course, translate into better retention later on, right? Exactly. If we look beyond that, you mentioned something in your initial com already—there's also expansion. So there are different ways that contracts can grow after someone's properly set up on your product. Can you talk a bit about how that can be done?

Look, there's a couple ways to think about expansion, and one is every product has sort of natural levers built in that's going to drive expansion. For a lot of SaaS companies, the predominant measure, historically speaking, has been seats. Now look, I know there's a lot of conversation around utility billing and other mechanisms, and actually, we are not a seat-based product. We price on monthly active usage.

But generally speaking, these are well-defined expansion levers—a seat costs this; for us, a monthly active user costs that. And as I hit certain thresholds, the product itself can, like, one, start warning the customer, which, by the way, is a good experience. This isn't just a matter of driving a more efficient go-to-market message. The last thing any customer wants is a surprise—like, surprise, we're not going to charge you more money. No, it's great when the product itself can start warning you.

So a lot of our customers will use our messages to start warning customers, "Hey, you're within 75% of your contracted seats; start preparing to start thinking about it." Maybe it goes a little yellow, so it sort of, again, warns the user that you could be getting to a point. But at least it's preparing them for this eventuality. And then, of course, as this expands and eventually gets to, "Hey, you're out of seats," it could be a very easy button to say, "Upgrade to this package. Here's an offer. Get it transacted immediately." And that's one level of expansion.

Here's an offer, get it transacted immediately, and that's one level of expansion. The other level of expansion is new, net-new functionality or capabilities. We're seeing all sorts of cool stuff there. We work with a lot of large companies. Citrix is one of our named reference customers, a heavy user of this. If you think of Citrix's strategy, it was to buy up a bunch of companies, mostly in the collaboration space, and try to get cross-sell and upsell across all of them. They have dedicated marketers to just do in-app marketing. This is customers using our signature product; we want them to use our file-sharing product. Let’s drive them to use file sharing and describe why the benefits of having our file-sharing product combined with our signature product in the same platform are compelling.

A very basic example could be a message that says, "Hey, go try this; we'll unlock this functionality for 30 days while you try it." That's a great experience. Let’s go unlock that. Another thing we’ve seen people do is have the menu items right there in the product for all the other things you can expand to. When you click on it, it's kind of like a blank page or a teaser page, or maybe a flyover that says, "Hey, this is locked. Would you like to unlock it?" That could either be fully self-serve—where you can say, "Let me unlock this for 30 days and try it"—or "Let me go talk to an account manager where we can learn about the value of this and then eventually go down a more human-led path."

I think those are great ways to expose people to new capabilities. I gave you a few software examples, but we're also seeing this with banks. I was talking with a very large bank recently that was onboarding new customers. They realized that if you just pull a customer into a simple checking or savings account, they aren’t the stickiest of customers. However, if you start saying, "Hey, look at these rates on CDs," and you get them into a CD product—which of course has some sort of lifespan to it—that locks them in as a stickier customer. That’s something banks are doing, which is super cool and fully PLG.

If we look beyond expansion—beyond what we just discussed—what are some of the more advanced implementations you’re seeing happening with the tooling available? Some of the things we’re seeing involve a combination of signals happening within the product and messaging on internal apps like Salesforce. This allows sales teams to proactively follow up. For example, new customers join a bank, and during onboarding, they indicate they care about budgeting. This flags the bank to suggest budgeting solutions. A banker, who owns that geography, could then get a notification in their CRM saying, "Todd just signed up and is interested in budgeting."

The banker could then follow up personally, saying, "I noticed you’re interested in budgeting. Would you like to set up a consult?" That’s a great experience—someone proactively reaching out, knowing exactly what I want. Personalized experiences like this are more pleasant and have a higher chance of conversion. This combination of data and messaging is so powerful.

We’ve also seen customers develop advanced onboarding flows. During onboarding, users are asked what they care about. If they care about a specific feature, the onboarding flow highlights that part of the product to involve them in that use case. Another derivation is tracking website behavior. If a user was browsing certain features on the website and then signed up, the system could prompt them immediately, saying, "We noticed you were interested in X feature. Let us show you that part of the product."

This level of personalization creates a great experience. Technology is evolving to do this, and AI will play a big role. AI allows us to identify behaviors preceding conversion events, like free-to-paid conversions. It can auto-suggest campaigns and experiments based on these behaviors. Growth marketers today spend a lot of time sifting through data and forming hypotheses for experiments. With AI, we can automate these processes, enabling faster experimentation with more confidence in data.

For example, AI could identify patterns in retention data, compare behaviors of customers who stay versus those who churn, and suggest actions to improve retention. This could include designing onboarding flows or proactively reaching out to customers who haven't engaged in key activities. AI-driven segmentation and personalized campaigns could dramatically improve outcomes.

This doesn’t replace humans but augments them, allowing them to experiment faster and more efficiently. AI can drive segmentation, build user journeys, and automate campaigns, ultimately enhancing growth efforts.

Before we wrap up, I’d like to share that this is an exciting time. If your organization isn’t thinking about using product-led techniques, there’s a risk of falling behind. Users now engage with technology at all times—weekends, odd hours—which means relying solely on human support isn’t sufficient. Product-led techniques help meet users where they are, and advancements in AI make this even more exciting.

Thanks for joining today, Todd.

Thanks, Vincent.

That’s it for today. It’s been great to hear about how in-app messaging can enhance customer experiences and how even non-software companies like banks are adopting PLG techniques. For more insights, check out my book about product-led sales and PLG strategies.

Thanks for listening and see you next time.