a16z Podcast - Predicting Revenue in Usage-based Pricing

Episode Date: June 10, 2024

Over the past decade, usage-based pricing has soared in popularity. Why? Because it aligns cost with value, letting customers pay only for what they use. But, that flexibility is not without issues - especially when it comes to predicting revenue. Fortunately, with the right process and infrastructure, your usage-based revenue can become more predictable than the traditional seat-based SaaS model. In this episode from the a16z Growth team, Fivetran’s VP of Strategy and Operations Travis Ferber and Alchemy’s Head of Sales Dan Burrill join a16z Growth’s Revenue Operations Partner Mark Regan. Together, they discuss the art of generating reliable usage-based revenue. They share tips for avoiding common pitfalls when implementing this pricing model - including how to nail sales forecasting, adopting the best tools to track usage, and deal with the initial lack of customer data. Resources: Learn more about pricing, packaging, and monetization strategies: a16z.com/pricing-packagingFind Dan on Twitter: https://twitter.com/BurrillDanielFind Travis on LinkedIn: https://www.linkedin.com/in/travisferberFind Mark on LinkedIn: https://www.linkedin.com/in/mregan178Stay Updated: Let us know what you think: https://ratethispodcast.com/a16zFind a16z on Twitter: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zSubscribe on your favorite podcast app: https://a16z.simplecast.com/Follow our host: https://twitter.com/stephsmithioPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

I happily accept some of the risks of a consumption-based model because I think that the benefits far exceed the cost. These providers need to be held accountable to continuously delivering value. It is not okay to simply sell a deal, walk away for 11 months, and then one month before the renewal is set to go. Then you re-engage and say, hey, how was the last 11 months? If we would have just asked that question, they would have told us. But instead, we put it down on our chart as a trend that would endure for the next year, and we called it ARR. And that's a mistake. I think, actually, what you're going to see is more hybrid pricing models.

It involves also telling them proactively how to spend less on your company by implementing some best practices that will reduce their consumption. There is no shortcut to creating long-term successful businesses. Pricing is hard, which is why so many companies, have defaulted to standard pricing models like subscription. And that should come to no surprise, because predictable revenue is the linchpin of any company's planning, execution, and ultimately valuation.

But it also happens to be one of the most difficult things to nail about implementing another pricing model. That is usage-based pricing, which is what we're here to talk about today. Because once you've established the right processes, org and compensation structures, and tech stack to operations, tech stack to operationalize it, your revenue can actually become more predictable with usage-based pricing than it might be with traditional SaaS over time. So today you'll hear

from A16C growth partner Mark Regan as he sits down with Travis Ferber, VP of Strategy at 5Tran, and Dan Burrell, head of sales at Alchemy, who both have implemented and embraced, you guessed it, usage-based pricing. So today they share guidance on best practices, the very real ups and downs of usage-based pricing, key metrics to hone in on both short-term and long-term planning, and ultimately why it's so important to orient your business around the value that a customer is getting. The first voice you'll hear is Mark, then Travis, then Dan.

Oh, and for more content just like this on usage-based pricing, make sure to check out A16.com slash pricing-packaging. Enjoy. As a reminder, the content here is for informational purposes only, should not be taken as legal, business, tax, or investment advice, or be used to evaluate any investment or security, and is not directed at any investors or potential investors in any A16Z fund. Please note that A16Z and its affiliates may also maintain investments in the companies discussed in this podcast. For more details, including a link to our investments, please see A16c.com slash disclosures. What I'd love to hear from you guys first

is your perspective on why usage-based pricing has become so popular in the industry and why is it working so well at each of your respective companies? I think it comes down to usage-based pricing allows customers to pay for what they use. It helps tie value directly to the product. I think from a customer standpoint,

it's also an easy way to help customers come in and experience your product without making a big commitment to that. So it's really helpful in landing customers and bringing them in. And I think over time with that, you can build stronger relationships with those customers. You can see that growth or time. There's maybe one other thing I'll add to that, which is usage-based pricing forces you as a company to think about the customer all the time. Every part of the organization has to be thinking about the customer. In a bookings model where you come in and you get them a subscription, the salesperson's like, great, did my job. I'll see you in 10 months where we're getting ready to start talking about that renewal. And your engineering team is somewhat tied to them, but you don't get the immediate

feedback with the customer. You don't get the immediate, are they being successful? Have they adopted the product in the way that you thought? And with usage-based pricing, you can see that. You get the telemetry data. You get the information right away. And you can focus the entire organization to make sure that those customers are successful. And I think as a founder or an individual who wants to build a company that drives great value with customers and great relationships with that, UCBase pricing is a good mechanism for aligning all the organization around the success of the customer because your revenue is directly tied to the success of that customer.

I think you nailed that. I've been in Silicon Valley venture back companies for 12-ish years now. And what's really interesting when I think about this question is that I think back to my very first sales training ever out of college where I had not yet moved to Silicon Valley. I was in a Fortune 100 company and I was given sort of conventional sales training. In that training, I was taught how to gate information and access to information about our products and services behind all this process that we were supposed to put these prospects and potential customers through. And instantly, that never sat right with me. That never

felt like a reasonable trade. I felt like we should be freely giving more access to information. And I moved to Silicon Valley and I loved the updated philosophy that I saw. At the time, we were all talking about the consumerization of IT, of enterprise infrastructure and making sure that the tools that employees want to use inside a company to do great work match the great experience of consumer tools that were on the market, that were available for people. And there was this discussion of shadow IT and people bringing in their own technologies from outside that weren't necessarily sanctioned because these tools were so much better to use. And the key to that whole motion and what has driven this is the consumer preference. And the consumer in this case could be the enterprise customer, the enterprise knowledge worker.

They deserve great tools. Not only do they deserve access to information about the tools that they might buy. We've now taken it and progressed it over the last 10 years to include consumption of that. tool. So as part of this consumption-based pricing model, of course, we have different tiers and access to different tiers for these solutions, including free tiers, which the internet has helped democratize access to information about all these solutions. And of course, you can actually go use them, which I think is a huge benefit for customers, and I think is the right expectation for the industry to have. It's going to help ensure that companies are able to find

the right tool to meet their business cases and their actual needs. So I love that we've done that. Now, I may be cheating ahead a little bit on additional questions, but where I think this naturally goes is if we're giving out all this access to use our tools with very generous free tiers and we're spending money to provide that solution for free, what are we then trading in exchange for those scale customers and long-term relationships and commitments and how do we fuse product-led growth with the appropriate level of sales-led growth? And there's actually a ton of exciting stuff in that category where my perspective is you can do that in a really healthy way to manage your company's resources effectively. But to go back to the original intent of the question, why does this make sense?

Why is this so popular? Why is this not going away? Because it's the right thing to do for customers. They know it deep in their heart that they should be able to use these tools. They should be able to have complete access to information about these tools and these providers need to be held accountable to continuously delivering value. It is not okay to simply sell a deal, walk away for 11 months, and then one month before the renewal is set to go, then you re-engage and say, hey, how is the last 11 months? Hopefully you're ready to renew and expand. That's not an okay motion, and that's not the

way to maximize business value for anybody. I love both your perspectives on that, and it almost seems overwhelmingly positive, right? I think we all know living in the reality this, especially when you're going through that arc as these growth stage companies, there are a ton of challenges with this model in practicality. And I know you guys have lived through it and I'm really interested in what your key observations have been around those challenges. And just as importantly, what you've seen in the organization you worked in to try to mitigate those, to try to overcome those and to really be able to operate this model at scale. Oh, man, there's a lot there. So let's unpack on that one. So, yeah, a little bit of background. Five Trend, when it was started, it was a booking space business. We had a variety of connectors. We priced those connectors in different groups and said, congratulations. You go, you bought your connector, go forth, talk to you in a year. And then we switched to a usage-based pricing model using something called monthly active pros. And that switch, we had an established sort of sales culture that was this booking space business model that switched over to usage-based. And that was a

a hard switch, like making sure that you had all the systems in place and everything else that comes along with that. And I think there's a couple of different ways to think about the challenges of UC space pricing. So one is on your systems and internal systems and processes to be able to manage that. It's a bigger investment. Like it is much easier to run a booking space business from like a just a planning comp, your internal systems. All of that is way easier, way simpler. And therefore, you have to make a lot of investments into your operations teams, into the systems, into the data models that you have to run, all the telemetry data from your product. You have to have that information. You need that information to help drive that.

So that's one challenge. The other side of this is that it does introduce a lot more variability, particularly when you have fewer customers. It can introduce a lot more variability into your revenue because customers can change their usage. and you have less commitment from a customer. You can see customers come and go and move up and down, so you always have to focus on value. At 5Trend, we've seen a couple of different drivers of that. There are multiple drivers on predictability.

So we try to give a lot of flexibility with customers so that they can match what they need and their value to what the product is offering. But in doing that flexibility, that can drive a lot of variability and what customers actually are using and how they're changing that. So they can optimize a lot from the needs of their business,

and that can drive some unpredictability in the revenue. And there's this other factor that we see, which is just general macroeconomic things, like just things that happen in the world as we move data, like there's stuff that can be sometimes outside of the control of the customer that can impact their usage. So, for example, we see a lot of our retail customers

around November and December timeframe, huge spikes in usage because that's when all the POS systems are going. It's when all their cells are happening. So you have these big spikes in usage. If you have a diversified customer base, you can sometimes mellow out those spikes, through broader industry diversification or through understanding and planning for those spikes. But you have to have some history, some data history to understand that.

And then the final one is, depending on what your product is, so again, Fiatrendt, the kind of the unique thing is we're interacting with other products. So we pull data out of what's happening from other users or other applications, and then we move that data over. And so those applications make changes. And that impacts our product. So we have HubSpot, I think, a few years ago, made a change to their API. and it forced a complete re-sync for all of our customers,

which is a huge spike in the usage across the board for all of our customers that we're using the HubSpot Connection. It's one of those things where you have to be on top of that all the time. You have to be watching the interactions and stay on top of those things so you can kind of protect the customers from these unnatural spikes that can happen. That means more investment in your product and your engineering teams.

So I think if you want to know the complications of usage-based pricing and going from booking space where it's simpler to plan, it's simpler to use. The salespeople understand it. Quite frankly, the procurement people understand it better, too. They're like, I know what I'm buying. I know what this is going to cost me. I can predict this in my budget to a, hey, I'm not really sure how much I'm going to use. I'm not really sure what this is going to do for my budget over time. I'm not sure if I have control over that. So a lot of education that has to happen. Well, Travis, there's something else that I hear in that too, which I feel like our industry sort of loses side of this a little

bit in this discussion often, which is the idea that whether I choose to be a booking space business or a usage-based business, that somehow is the sole determining factor as to whether or not we're going to be a good company or a bad company. This is just a strategy. This is a strategy to unlock growth. I personally think that it's a very good strategy to unlock growth, but it also comes with costs, and we can talk about those, and we can talk about mitigations for those, and you should be eyes wide open. But there is no shortcut to creating long-term successful businesses. Fundamentally, at the heart of all of this, and you alluded to this, Travis, and I totally agree, your products and services have to deliver immense amounts

of value to your customers, plain and simple. And that is regardless of what growth strategy you choose or what sales model you choose to have. These software products are never done being built. Absolutely never done being built. And so consumption, actually, that growth strategy lines up beautifully with that because as long as you're continuing to build these software products and you're adding that flexibility, that feature set, that next generation of innovation, then you're able to command good margins, make customers wildly successful. And they're excited to come back and spend more and more and more on that consumption every period because they know they're getting more value than they're paying you. And that's how you build a great business. So I do think people lose

side of that. So you need to be tightly aligned with your product organization and thinking about that product roadmap, because that's going to be a much bigger determining factor. Now, I think part of this question, too, is what are some of those costs? We should recognize that in good economic times, a consumption-based model can be a big accelerant because there is less friction to customers being able to use more, consume more, and therefore your company getting to make more revenue when they do that. In tougher economic times, where you've got percentages of your business and your revenue that is tied to full consumption where there are no bookings commitments in place.

Obviously, that represents a risk. And that's going to also be a less friction place for those businesses who are your customers to save money by pulling back their consumption on your service and lopping off use cases or shutting down one department's use of that solution. And we've seen that in the last couple of years. There was a ton written about that and a ton of analysis. For me personally, when I think about building a great business, first and foremost, I want that amazing product roadmap where we're going to be a ton of analysis.

we are so confident in the value that our solution provides. Secondarily, I happily accept some of the risks of a consumption-based model because I think that the benefits far exceed the costs, even knowing that there will be tough times ahead and our customers may, as a result of a need to save money and extend runway or drive more profitability, they may reduce consumption on us. I'm willing to accept that and deal with that turbulence and do right by our customers in those moments because I actually think those moments, even though they don't feel good because maybe revenue is pulling back on our side, those are incredible opportunities for us to build long-term trust and long-term relationships with those customers. They will remember how we

treated them when they needed our help. And that will factor into their decision when times are good again and they're ripping and they're investing in growth. They'll remember which providers stuck by them took good care of them and recognized that they were in a tough moment and they needed some forgiveness or some help or some actual assistance saving money with best practices that enabled them to lower consumption of your service. And that's a separate big topic of the role of account management and customer success. But hopefully that addressed the question. Definitely. And Dan, I'll go right back to you. Getting into a bit of the operational nitty-gritty of this, I'm particularly interested in your perspective as a sales leader when it

comes to forecasting the business, right? And just living in the presence of a quarter or a couple quarters ahead of you, how have you learned to confidently forecast the business? You're growing quickly, but you have all these challenges of just not a heck of a lot of data in the rearview mirror. You don't have perfect signal detection and hitting indicators. So how are you working through that? How have you learned to become confident in your forecasting? I really appreciate that question. My answer may surprise you slightly because the key to good forecasting, even in a consumption-based business, is a very healthy bookings element. And so the foundation of the relationship with our customers may still be entirely

consumption-based. That's how we have the conversation. That's how we leader their usage. That's how we talk about their usage. That's how we forecast their usage purely in the form of what they're going to consume. And as Travis said earlier, they're going to pay for what they use. That's the objective. Now, that being said, I think it's still totally fair and reasonable that my business values predictability, like you just talked about. I've got a job to do, which is to forecast accurately. We all know why those forecasts are so important. That enables us to make healthy, forward-looking decisions about the business, how we're going to invest, what teams we need. There's a ton that requires a great forecasting methodology. Therefore, because I'm going to get

a bunch of business value from a healthy forecast, I can return value to my customers who are willing to make commitments to us. And that's a super fair exchange of value. And it's a super fair exchange of value. And it's on this beautiful continuum. The more flexibility that my customer requires, the more fair it is for them to pay a premium for the consumption that they're going to use. The more they're willing to commit to me and my team and my company, which enables me to be better at forecasting, the more I'm happy to return discounts and commercial incentives to them and we'll execute that on a bookings contract. So this is part of the motion that you want a breed in the sales team, which is that you're continuously selling, you're continuously

taking care of them, you're continuously monitoring their use case, you're continuously forecasting with all of your customers. It is expected in any organization that I'm running, that if you're taking care of a customer, you are continuously not only monitoring their use case in the telemetry that Travis was talking about, which is very important that you give your sales team and your customer success team the monitoring capabilities to understand, in very granular detail how their customers are consuming products from a growth telemetry perspective. But you also expect that those folks are deeply understanding the dynamics within the customer business. What is causing that growth? It's not enough to just know what the

growth rate is. I want my team to explain to me why that growth rate is. Is it because they're aggressively expanding into a new market? Is it because they just acquired another company and now we've combined two teams usage. We actually have to know why, because that is the key to good forecasting. I can't tell you the number of times that I've seen this issue of massively over forecasting a given customer's usage because the team didn't understand that the behavior that customer was engaging in was a one-time thing. It was only ever going to last for one quarter.

And if we would have just asked that question, they would have told us. But instead, we put it down on our chart as a trend that would endure for the next year, and we called it ARR, and that's a mistake. So there's a whole lot. I could probably go on for another hour about what drives good forecasting. It's a combination of instilling in your team great discovery skills,

and an expectation that they're doing ongoing discovery to always know the business drivers behind the usage trends. You can't just know the trends. It's arming them with great telemetry tools, monitoring VI solutions to track it at a very granular level so they can get specific. And it is offering your customers fair,

contracts and discounts in exchange for commitments, which are really valuable for your business because you value the ability to forecast. You value certainty. And you're happy, in my opinion, to give discounts to customers who can sign up for that level of commitment, of minimum amounts of consumption. The point around bookings is spot on. We have a couple different components to our business. We have this great big self-service group of customers that come in, use the product, never talk to a salesperson. They just go there like pay as you. go. But then there's this other portion of the business, which makes commitment to, hey, I'm going to buy up front this much for a year. In exchange for that, the built-in discounts, as you use more,

we've discounts that come in and play for that. And that bookings helps drive predictability for a portion of the business and forecasting for like, how are we doing? So when we think about long-term planning, I think Snowflake is famous for their RPO, remaining performance obligation. Like, how much have people booked? How much have we got to? How much is left? And that because a big thing of monitoring, giving that information to your customer success teams to help make sure customers are getting what they say they want. They've made a commitment to you, and they've given you an indication of what is valuable to them and what their level are, and you can say, are we getting there? I think the mechanics of actually building the protectability,

what kind of systems you have to have in place, how do you do that? We've gone through many iterations of this, and this has been an evolution over several years. We had to make major investments in our infrastructure from a analytics standpoint. So FItrend moves a bunch of data, So we have a fairly large analytics team, and we've built a predictive model that says, okay, based on what usage has looked like, because we've got this cohort of customers that haven't made bookings. So based on their past usage, where are they going on an account level basis? When did they join us? So what kind of usage curve are they on based on historical data that we've looked at and said, like, okay, cool.

Customers that are about this size in this region, they perform on this kind of growth curve. If you have enough customers, those averages will work out and you can see that. And so we apply those curves to these customers that come in. And so you layer those cohorts together and that gives you a predictability about what's kind of going on from a revenue standpoint. And that's all like the data science side. And you can take into account what planterer are they on? We've got five or six different plan tiers. What's their discount for each individual customer?

You have to layer all that stuff in so that you can build a more accurate view of their performance over time and then take into account historical turn rates. Turn for us isn't a customer has left us. churn for us can be, hey, I've turned off a use case. So I've reduced that thing. So you want to look and take that that to account. That's our data science model. But the data science model only sees historical data and telemetry data from customers. They don't have that piece of data I'm talking about, which is the customer discovery piece, the sales insight side of this, which is the second part. The sales team has the insights on, are they going to add another use case? Are they going to turn a table off? They have the insights that the data team can't have. They don't

what the customers are going to do because they're not having the conversations with the customers. And so you give the sales team, here's the predictive revenue for your book, for your customers. And then the sales team can go like, well, actually, I know they're going to add a new use case. And it's going to come online in the next two months. And I know that that's going to be worth this amount of money. But that then gives you the insights to then modify your data science model. And that gives you a little bit more confidence. And I can tell you in the beginning, your sales team will get it raw.

Like, their predictions will be way off. And particularly, our model is, the more that you use, the cheaper your usage is. And therefore, unless you're a savant and you can do multivariable calculus in your head, you have to have these tools in place to do that. And so you run this rigorous process where data science model comes in, sales modifies it based on their knowledge of the customer and what's moving up or down. And then they've got the tools enabled to predict or to size those different opportunities. I love everything you went through there, Travis.

What I'm really curious about is how that extends when you need to do annual planning and you're thinking about your longer term investments. Obviously, that still requires you to forecast revenue going forward. How has that parlayed into longer term planning accuracy or what else do you need to do in addition to those key concepts to do that well? Yeah. Your capacity model is a very interesting thing that you have to build. And we shifted to more of a demand-driven capacity amount so we can look at historical demand. What have we been seeing? And then how does that demand translate into dollars for us? And then what ramp do customers go on when they come in? So you build these like waterfall ramps. The basic outline still is the same though. It's just you have more

assumptions that can go into that. We do a three-year long-term plan, which is as much more general growth rates, like what's the macro economy kind of look like. It's a roadmap for a product standpoint. It's more of a here's where we think we're going to get to. It's not this is the prediction. This is like really honed in. On the annual plan, it's much more detailed. And that's where we try to hone in and we work on these other assumptions because you're assuming things like churn within the product, not just churn of customers. You assume things of like expansion of growth rates over time, how have those been going. What have you seen in the past? You're not just doing like an NRA assumption. You kind of have to look at this cohorted basis for

each of your customers and how they're going to grow within that year. And how big of each of those cohorts coming into the year are there? So like Q4, Q3 of the previous year, where did you land? Where are those customers on their growth cohort? And that helps give you more predictability about your early stage revenue and then what your pipeline look like

of those new customers that could be coming in that will then land coming in Q1, Q2, and then their revenue that they're going to generate for you in Q3, Q4 as you're looking forward for that. So it's a lot of, it's the same kind of skeleton that you have from an annual planning basis. There's just this extra

layer of cohorts and the growth of that revenue over time and where are they and to those assumptions that you have to layer in. Well, I was just going to ask you a follow up there. Fundamentally, aren't you just taking all that extra rigor and analysis to normalize an account executives contribution in the form of a quarterly add to the business, whether you're entering that in ARR or whatever or MRR. You're still just doing all that extra rigor just to normalize what an incremental head is given to your business so that you can plan essentially in a normal way. Yeah, totally.

I think, oh, man, we think about it in terms of like there's kind of two parts to the business. There's this demand-driven part of the business, which is customers come in and they don't talk to sell people, so it's the self-service portion. And that part is not about adding salespeople. So you kind of have to look at the demand part of the model up front.

And on the enterprise side, when we look at larger organizations where it's actually the salespeople are driving demand. They're creating demand with customers. They're developing those relationships. That's a little bit more where you're like, cool, if I add another salesperson, I'm adding more revenue.

And it's not as constrained. But yes, to your point, broadly speaking, yes, you are kind of normalizing how much incremental revenue are you driving by each person that you're adding to the organization? Yeah. And then defending revenue too. Well, Mark, I think what we're both saying,

what Travis and I are a complete alignment on is that I think a very huge component of this planning exercise that you're talking about is attribution for your revenue. Yes. What was the source of that pipeline? Was that customer spending on their own? Yes. Did they self-serve and how far did they self-serve?

And then this is actually where I think the most important thing for any organization is to have really great communication and alignment among the business leaders between sales leadership, operational leadership, revenue excellence leadership. And of course, finance, those parties need to be in complete alignment about the relative value of these different buckets and where they come from. And is a dollar of revenue that was self-prospected entirely by an account executive, how does that relate to a dollar of bookings that was converted from somebody who was already spending? And you can even get as fancy and as nuanced as applying modifiers within a comp plan, for example, to different kinds of dollars of revenue. But it all goes back to having some basic systems of attribution to know what the evidence is coming from where it started out.

This whole product-led growth motion, it is another example with how it can accelerate, but how it can add some cost, because now you have this whole new bucket. I remember the first time I heard the acronym PQL. It was probably around 2016 that I heard that for the first time. And prior to that, we'd only ever talked in MQLs. And it's now this mega funnel of opportunity for your business if you're driving a consumption model of product qualified leads.

And so what's the definition of that? What are the expectations for follow-up? What are the expectations for compensation when a seller closes a deal with somebody who was already using? Lots of good considerations there. The advice I would give is there is no one-size-fits-all solution. I've been across three or four different businesses now that have some element of consumption-based pricing. the key to getting that right is to actually listen to the needs of your customers and the dynamics of your business. I have seen this change dramatically. And therefore, the compensation plans that we write is custom based on the competitive pressures that we're feeling, the market dynamics that we're feeling, our stage of growth, our orientation towards profitability.

There just really is no one size fits all, like piece of advice here. You've got to respond to what you're seeing, where churn is happening. where growth is happening, what competitive pressure you're facing. It's got to be custom every time. Really good stuff, guys. I want to hit you with one more question. Looking into your crystal balls, where is this all going? A lot of new technology out there. Be remiss if I didn't at least make quick mention of generative AI.

But there are an array of things out there in addition to the innovations there. But where do you see this model going over the next few years? Let's break this question into two pieces. So where is like conceptual-based model going? model going. We've been in this construction-based model for four years, and a lot of the businesses around, like, how do you try and find the intersection of value with customers and value for the business? And pricing is like this mechanism that you can use for that. And consumption-based model is one that I don't think is going to go away because it is so valuable to customer,

and it aligns everything together. But it's not the only tool that you have. It's not the only pricing tool. And we've heard since we started the consumption-based model from a lot of, like, larger customers, like our big enterprises really, we want some more predictability. And so I think actually what you're going to see is more hybrid pricing models where you have consumption base to allow customers to come in and understand the product. And some customers will love that. And you'll have, for example, ELA's enterprise license agreement that sets like set price for all you want. That gives more predictability to other customers, and you're going to see some of these hybrid mixes that'll come around because you've got different types of customers that are looking for different solutions and different pricing for them. And you want to be responsive to what customers need, and you want to meet them where they are.

So that's part one of your question. The second one around generative AI. I mean, holy cow, this movie is so fast. I talked about data science models earlier around predicting where customers' usage is going to go. And I think that generative AI, in particular the predictive part of that can be quite. quite valuable to us. So it can shortcut. The long time it took us to figure out what was driving customers' usage

and what are the key indicators and how do we know when to intervene with a customer or when not to intervene or what's an expect to action, generally and I can help drive that part of the business and help give smaller companies advantages that we didn't have smaller companies. We've had

to earn over like a long period of time just working at it and having work in these models. And then also just making sure that using generated could give sales teams insights into when they should reach out to customers, what's actually happening? Dan talked about this. Why are customers doing the things that they're doing? What's happening? And I think that's what genera of I can start to parse all this data, all this telemetry information. We have tons of data on our customers, tons of data on usage, but not everything

is valuable. There's gems out there, and you're searching for those gems all the time. It's the diamonds in the rough. And I think General of I can help identify what are those gems, and then give actions to the sales team so that they can go out and have closer relationships with their customer. It's never going to replace a human-to-human relationship. Business, particularly at enterprise space, that is a human-to-human business. And we want to make sure that we maintain tight ties to the people that are involved. And so it's not a replacement. It's a supplement. I personally love this. And I agree with everything Travis said, too. First of all, I think that consumption-based usage models and pricing models are here to stay. These are the kinds of solutions

that I want to sell and represent as a sales leader, as an employee, because I believe it's the right think for the customer, and it's the right alignment of incentives for my employer and the company that I represent too. So I don't think it's going anywhere. I think it makes way too much sense. I would bucket where I think this is going in three different categories. The first is in the tooling. We talked about that. I know that the companies that are building software to support the sales and marketing stack are very focused on modules and advanced tools for usage-based pricing specifically. We talked about all the challenges in that category. I'm looking forward to seeing advancements in the tooling that helps us with the telemetry, that helps us with the triggers

for outreach, that helps us with the measurement, the forecasting, all of that. I think there's plenty of room for advancement there. And AI definitely plays a role. The second, I would say that we're going to continue to need to push hard on the seller skill set. And I include account managers, account executives, customer success representatives, sales engineers, all of that in the sales skill set. We've joked a couple of times about if only you would have just asked that one customer, hey, what's behind this massive surge in consumption that you just had? Well, we're talking about the proliferation of this model. We need to recognize that you are not the only person asking that customer, what's behind that blip? And so there is risk of fatiguing these customers. You're asking

them to explain themselves and their business drivers to everybody all the time. That means that we need a necessary improvement and evolution in the skill set and how you're making sure that the folks on your team that are engaging with your customers are doing so in a way that is continuously adding value. And that includes showing up with helpful tips, showing up with insights about their usage that they might not have known on their own. That actually involves, I alluded to this earlier, but it involves also telling them proactively how to spend less on your company by implementing some best practices that will reduce their consumption. There's a myriad of ways that you can make sure that you're continuously adding value while maintaining a very high touch engagement

with those customers. We need to continue to progress that playbook as an industry, make sure that we're doing right by ourselves and our customers in the process. That's the second category. And then the third, where I hope that all of this culminates is in the product roadmaps. And if we've done these other categories well, if customers are driving consumption towards you because you're the highest value solution for them at that exact moment in time, you know that you can continue to earn that right and earn that business by delivering more and more value through great product roadmap, delivering more value in your products, including more value, competing hard against your competition.

So I hope that all this results in fierce product competition so that the best product is always the one that's winning. The one that is offering the most value to customers is the one that they should be going with at all times. For me, I hear three things occurring over and over. It is the tight interlock between customer value realization and what they're actually paying for the product. And if you even think into the future, what you guys just described a bit,

it's really just making that even tighter and more predictable. It's not changing the algorithm. You're still trying to just get to that same exchange and trying to optimize that. And then the other thing I'm hearing a lot around is just the significant investment and dedication you have to have around the mastery of the data and the tooling on top of that to just be able to take all of this data, remove the clutter, see the signal, see the signal and be able to use it as much as possible to predict the future of the way that your product's being used. And that just carries forward, right? AI will be great, right? But it's just

yet another way to further tweak that. And I particularly like what Travis was saying around the empowerment for the smaller companies, too, who have a lot of challenges with this and don't have as much of the ability to invest infrastructure right away. This is empowering for them if they are able to get AI into the fight early on. And then finally, Canada's side of the people, right? This is a big thing that you guys kept coming back to as well as just giving your customer facing folks the tools and the expertise, the enablement to be really good at this and to be just great partners with the customers and to try to understand the way they're going to consume value with the product. I appreciate you guys giving us your valuable time to go through this.

I can talk all day about this. You guys have so much insight. So my sincere thanks for dedicating the time that you gave us to here today. Thank you. Awesome. Thanks for having us, Mark. Thanks. If you like this episode, if you made it this far, help us grow the show. Share with a friend, or if you're feeling really ambitious, you can leave us a review at rate thispodcast.com slash A16C. You know, candidly, producing a podcast can sometimes feel like you're just talking into a void. And so if you did like this episode, if you liked any of our episodes, please let us know.

I'll see you next time. Thank you.