Product Led Growth or PLG is a very hot topic. But the PLG strategy and motion is very different from the traditional Sales Led motion. And the requirements from an instrumentation and operational perspective, as well as from a data and insights perspective, are very different.

In this episode of The Revenue Engine podcast, Momo Ong, the Co-Founder of HeadsUp, joins Rosalyn to discuss the differences between Product led and Sales led and what organizations should be thinking about when either shifting to this motion - or adding this motion.

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Connect with Momo on LinkedIn, or at HeadsUp.ai

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The opinions expressed in this episode are the speaker's own and do not purport to reflect the opinions or views of Sales IQ or any sponsors.

PLG or product led growth is a hot, hot topic right now, but the PLG strategy and motion is very different from the traditional sales led motion and the requirements from an instrumentation and operational perspective, as well as from a data and insights perspective are very different

So please take a listen to this data. Scientist turned founder to learn more. So super excited to be here today with Momo Ong, the co-founder of HeadsUp. HeadsUp is on a mission to help sales and revenue teams understand how companies are using their products and identify opportunities for revenue expansion.

So welcome Momo, and thank you for joining me.

And as you saw, you had a degree in physics from Princeton. So maybe, can you share more about your background and just your career journey, you know, prior to HeadsUp?

So I tried my hand at other things, specifically product and, and business. And I, and realized I was, I was much better at that. And so that, that led me to doubling down on product over my career. Yep. And so we're specifically my co-founder and I, we were early employees at this company called fiscal note.

B2B vertical SaaS company focused on the government affairs space based outta DC. And there I ran product that my co-founder Earl was responsible for setting up and owning analytics. And it's actually there where we saw firsthand the disparity in how the go to market teams were leveraging data compared to how engineering and product teams were leveraging data and saw an opportunity to build something six years down the road.

We knew there was an opportunity to help go to market teams, better leverage data, to drive revenue, to make better decisions. And so as we started running in that broad direction, and as we talked to more go to market and also data stakeholders, we saw that there were two themes that stood out. Number one was the rise of product led growth.

And number two was the modern data stack. So. You know, we realized that there was an opportunity to put the two together, right? How can we help product led go to market teams, which required more data than ever tap the modern data stack to make better decisions. And so that was the, the problem statement that led to the the founding of HeadsUp and our current iteration of the product and business.

They index heavily on usage based signals so that companies can, so that companies can identify accounts that can be monetized or are under monetized and can be further ups. so both MQL and P QLS feed into a sales motion, right? Sales development qualifies them into SQLs or sales qualified leads, and then they're driven through the sales cycle.

Okay. So now that we understand what P QLS and M QLS are, how are they different? Well, number one, product usage is much more intentional than, than marketing signals. People are already using the product, right? So we've seen that P QLS convert at a much higher clip compared to MQL. It's not uncommon to see PQL conversion rates in the 20, 30% while MQL conversion rates are in the single digits single digit percentage rates.

The, the next difference is that there's normally one MQL score, right? That score can take various values. Okay. Is this lead qualified? That's basically the, the binary question that that marketers seek to answer. And then SDR seek to verify, right? Mm-hmm but when you look at P QLS, there's a plethora of P QLS when, and that's because when an account starts to use a product, there's actually a lot.

That you can do as a salesperson, as a customer success rep as a marketer to further unlock value and drive monetization and adoption, for example, you could upsell number of seats, upsell the plant tier nurture accounts to unlock further usage so that they get more value from the product. Right? So many different types of P QLS, one MQL.

That can be engaged against that specific goof market objective, right? And against that objective, you do something about it. So you route it to a specific channel, say sales, customer success marketing, and you could even cut that much more finely. So this view of the world where you have different types of leads that are defined by different types of by different criteria is what we at HeadsUp the company that I'm building.

And it's exactly what we're building towards. We're building towards a tool that allows you to define leads based on multiple sets of data, multiple data sources, select which specific channel you wanna engage, the set lead, and to complete the feedback loop by measuring, experimenting, and improving your segment definitions and the channels that you you use against each segment or each set of leads.

Now that works from an 80 20 perspective. But at scale, we find that it actually. Is relatively low signal compared to machine learning. So we, we find that there's opportunities to lower the noise and also not miss out as many leads if companies are, were to leverage machine learning to surface BQL.

So I think that's one thing that companies can generally improve on now. Number two. , I think there's a lot of emphasis on how to define a PQL using rule based methods or using machine learning. And there's less emphasis on how to operationalize these P QLS. So what do I mean by operationalizing P QLS?

Well, how do we get these P QLS in front of maybe the hundreds of sellers or thousands of sellers and CSMs that you might have in your organization? Right. And how do you make sure that there's compliance? How do you make sure that sellers. Leveraging these leads, understanding why these leads are surfaced and adopting their talk track as appropriate to maximize close one.

So that's actually a very, very hard process. Once you have a go to market team at scale lastly, Defining PQS and managing them is not a one and done effort. It requires persistent measurement and iteration. And I think that's what a lot of folks might not do yet. Right. Your product changes. The market evolves.

And initially your rule based criteria, or even machine learning based criteria might not be optimal, right? The channels you use to engage the leads might also not be optimal. You have to tweak and experiment. To make sure that you have to optimal go to market bullshit over time.

That's all great advice. Thank you. Let's talk about data, right? Because we all know how critical it is to have the right data at the right time, right. To the right people, but with so many organizations moving, you know, even to consumption based, right. And this usage based model, which a lot of times, you know, this.

This PLG motion, you know, supports, you know, having those deep insights into how your product is being used and that data is incredibly important. What have you seen, I guess, in terms of, you know, SaaS companies moving more into this product usage model and what do you see as some of the key challenges to really bubbling up the right insights?

In a prior sense adopt instrumented and locked appropriate events. So I'd say that's one of the key challenges and that's actually that's structurally as within an organization, that's a difficult challenge because it requires a lot of engineering and data engineering time.

So are you. Are you seeing this trend in the market, you know, in terms of folks moving to more of this, you know, product usage, data and product led strategies.

Right. Cause we're seeing a lot of companies shift right. From sales led to product led or kind of doing both right in their business model. And are you seeing this trend in the market, you know, kind of, where do you see or where do you think it's headed? Right. Do you have any predictions maybe as to how this might evolve over the.

You know, 12 to 24 months. Yeah, absolutely. So HeadsUp has been around for almost two years and in our existence, we've definitely seen the, the upswell of interest and adoption of a product led sales. When we first started the market consistently mistook us for yet another say customer success tool. But now there's definitely no question about that.

Right? Now the market appreciates and understands that there's definitely a need to leverage product users, data to drive better, go to market decisions. Now on a go forward basis. I think this trend will definitely speed up given a, the, the macro climate today and emphasis on profitability, right?

That's, that's a massive tailwind for product led growth because at this point, most companies and their boards appreciate the efficiency of a successful product led growth ocean. So yes, there's definitely. Looking backwards. We've definitely seen increased adoption over, over the, over the months and years and going forward, we expect there to be much more adoption as well.

Right. Data tools are, are one example of that. If you have to, if you're a marketer or a product manager who wants to use a data tool, and in order for you to successfully successfully get value from that tool, you need, you need to ask, say data analyst or data science to give you access to the warehouse.

That's oftentimes not a, a product led motion or rather it, it can be an impediment. So number one, What does the product look like? What does the sales motion look like and how, how fast does, how, how fast can, can someone unlock value from this product? The second consideration is the DNA of the company.

So I was actually just speaking to someone who, who, who ran a company that got acquired by Microsoft. Right? And so Microsoft, as we all know is very, very, it's. It's a, it's an enterprise sales machine. Microsoft basically said, Hey, you, you should, you should stop yourself. Serve ocean at this point. So certain certain organizations have different DNAs.

And I think that's very important because product let's growth and product led sales is multi multidisciplinary, right? You need, you need product, go to market teams ops to work together, understand the customer journey and push accounts at the right point. Towards later stages of the journey. If not everyone is bought into this thinking it's very hard for product led growth and product led sales to be properly adopted. So DNA matters.

You know, how easy is it basically from implementation perspective and then what, how quickly they can gain. Right. Which is exactly what you said. So I think that makes a lot of sense. It's not for everybody, for sure. And like you said, the company needs to really buy into it because it's not just, you know, one person.

Yes. It has to be the entire motion to support it. That's great. As I think about, you know, the revenue engine, I think about this podcast, I'm always hoping others will be able to learn, you know, how to accelerate revenue growth and really power. Right. The revenue engine. So what are the, you know, maybe top two or three things that you think, Hey, all revenue leaders should really be thinking about today that will have the biggest impact on revenue growth.

And oftentimes it's not that difficult of an iteration. So I think pricing is oftentimes low hanging fruit for many organizations. Second, I think for sure if you're, if you're a product led growth company, figuring out how your go to market team. Since on top of your selfer motion is very important. Compared to enterprise sales, there's actually a lot here to figure out, right?

Enterprise sales is also very difficult, but oftentimes there's one process. And once that one process is nailed, it's repeatable. Right? Then you have, you have your sales team, you have your marketing team essentially work through those steps to, to consistently drive revenue. But there's so many different go to market motions in.

In, in PLS, right? In product led sales, you can there's sales serve there's sales assist. You can drive community, you can drive community leads, there's free or freemium accounts. And you have to think of ways to, for each of there's different interventions that need to be that need to be directed at different types of customers at different points in their customer journey.

And so it's as if you have to figure. Five or six concurrent go to market motions as opposed to just one. So I think revenue leaders definitely need to be thinking hard about that because a is definitely much more complicated and not as play bookable at least today compared to the traditional enterprise sales motion.

But if they successfully crack that a couple, if they successfully crack a couple of product led growth, go to market motions that can result in. Very efficient revenue growth.

So hiring and identifying really, really strong stake individuals and team teammates, both on the engineering and non-engineering sites. I say hiring and also market selection are probably the two most important things at the early stage.

This episode was digitally transcribed.