I happily accept some of the risks of a consumption-based model because I think that the benefits far exceed the cost. 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 evaluation. 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, Oregon compensation structures, and 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 Reegan as he sits down in Travis Furber, VP of Strategy at 5 Tran, 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 way so here is Mark, then Travis, then Dan. Oh, and for more content just like this on Usage-based pricing, make sure to check out A16C.com slash pricing dash 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 A16C fund. Please note that A16C and its affiliates may also maintain investments in the company's discussed in this podcast. For more details including a link to our investments, please see A16C.com slash Disposers.
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. 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.
It's really helpful in landing customers and bringing them in. 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 sales person is like,
great, did my job. I'll see you in 10 months where we're getting ready to start talking about that renewal. 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. Usage-based 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. What's really interesting, what 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 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 in 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 I was talking about the service, the 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. And the company could be able to provide 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 what I think this naturally goes is if we're giving out all this access to use our tools, we're giving out all the resources that we've been using to provide the tools that we've been using for a long term and long term relationships and commitments and how do we fuse product-led growth with the appropriate level of sales-led growth.
So there's 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.
Love both your perspectives on that, and it almost seems overwhelmingly positive. I think we all know the living in the reality of 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.
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. Still less unpack on that one. So, yeah, a little bit of background, five-trend, when it was started, it was a book in space business. We had a variety of connectors, we priced those connectors in different groups, and congratulations, you go by 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 rows, and that switch, we had an established sort of sales culture that was this bookings-based business model, that switched over to usage-based, and that was 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 usage-based pricing. So one is on the 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 bookings-based 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, and all the telemetry data from your product, like 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 5.3 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 in what customers actually are using and how they're changing that, so they can optimize a lot for 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, so as we move data, like this 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 retail customers around November and December timeframe, huge spikes in usage, because that's when all the POS systems are going, so when all their cells are happening, so you get these big spikes in usage, if you have a diverse by customer base, you can sometimes nallow 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, five to end the kind of anything is we're interacting with other products, so we pull data out of what's happening from other users or other applications, and 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 resync for all of our customers, which like 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 watching the interactions and stay on top of this thing so you can kind of protect the customers from these unnatural spikes that can happen.
That means like more investment in your product and your engineering teams. So I think if you want to know like the complications of usage based pricing and going from booking space, we're simpler to plan, simpler to use the sales people 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 sight of this a little bit in this discussion often, which is the idea that whether I choose to be a booking space business or our usage based business, that somehow is the soul determining factors to whether or not we're going to be a good company or a bad company.
This is just the 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 mitigation. So 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 the software products and you're adding that flexibility that features 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 sight 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 road map where we are so confident in the value that our solution provides.
Secondly, 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. Remember which providers stuck by them took good care of them and recognized that they were at 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.
That's a separate big topic of the role of account management and customer success but hopefully that addressed the question. Hey, it's Steph. You might know that before my time in A16Z I used to work at a company called The Hustle and then we were acquired by HubSpot where I help build their podcast network. While not there anymore, I'm still a big fan of HubSpot podcasts, especially my first million. In fact, I've listened to pretty much all 600 of their episodes.
My first million is perfect for those of you who are always trying to stay ahead of the curve or in some cases take matters into your own hands by building the future yourself. Posted by my friends Sam Par and Sean Curry who have each built and sold eight figure businesses to Amazon and HubSpot, the show explores business ideas that you can start tomorrow.
Plus, Sam and Sean jam alongside guests like Mr. Beast, Rob Deerdeck, Tim Veris and every so often you'll even find me there. From gas station pizza and I carten businesses doing millions all the way up to several guests making their first billion. Go check out my first million wherever you get your podcasts. 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 eating indicators. So how are you working through that? How have you learned to become confident in your forecasting? I 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 eat 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 it 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 are we 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 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 to 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.
And as 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 yourselves 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 uses? 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 still Scott 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 the I 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 of my 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 talked to self person.
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 want to buy upfront this much for the year and exchange for that built in discounts as you use more we've.
Discounts that come in 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 of people book how much we got to how much is left.
And that 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 made a commitment to you and they've given you an indication of what is valuable to them and like what their level are and you can see are we getting there I think.
The mechanics of actually building the predictability 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 5 to 5 to move a bunch of data so we have fairly large analytics team and we've built a predictive model that says okay based on what you should just look like because we got this code word 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 to 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 work out and you can see that as we apply those curves to these customers that come in and so you layer those chords together and that gives you a predictability about what's kind of going on from a revenue standpoint and that's a it's all like the data science side.
You can take into account what plan to you are they are 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 term rates.
Turn for us isn't a customer has left us churn for us can be had turned off a use case so I've reduced that thing so you want to look and take a fact to account that's our data science model but the data science model only sees historical data and the telemetry data from customers they don't have that piece of the data which is the customer discovery piece the sales inside 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 know 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 particular revenue for your book for your customers and then the sales team you 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 a rough 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 multi variable 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 and they've got the tools and they've got the tools and you can do it.
And I've got the tools and able 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 you have to build and we shifted to more of a demand driven capacity model 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 to 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 for general growth rates like what's the macro kind of look like to road map for a product standpoint it's more of a here's where we think we're going to get to it's not a this is the prediction this is like really hone 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.
Turn within the product not just turn of customers you assume things of like expansion of growth rates over time how those been going what have you seen the past you're not just doing like an NRR assumption.
You kind of have to look at this cohorted bases for each of your customers and how they're going to grow within that year and how big of each of those courts coming into the year are there so like you for Q3 of the previous year where did you land where those customers on their growth cohort and that helps give you.
And then you're going to have more predictability about like your early stage revenue and then what your pipeline look like of like those new customers that could be coming in the will then land coming in Q1 Q2 and then their revenue that they're going to generate for you and Q3 Q4 as you look forward for that so it's a lot of the same kind of skeleton that you have from an annual planning basis which is extra layer of cohorts and the growth of that revenue over time and where are they and those assumptions that you have to layer in.
So you can ask your fellow 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 or 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.
So I think that 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 sales people.
So you kind of have to look at the demand part of the model up front and on the enterprise side we look at larger organizations where it's actually the sales people are driving demand they're creating demand with customers are developing those relationships.
So I think that's a little bit more where you're like cool if I add another sales person 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.
So what we're both saying what Travis I 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 when you're coming from where started out this whole product led growth motion and as another example 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 MQ else 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 the market.
The first time I heard that the 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 but 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.
This changed 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 are stage of growth or 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 as when it's with one more question looking into your crystal balls where is this all going that lot of new technology out there you remiss if I didn't least make quick mention of generative a i but you know 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 we're as like consumer based model going we've been in this concept of this model for four years and a lot of the businesses are like how do you try and find the intersection of value with customers and value for the business and pricing is like this this mechanism that you can use for that and can something 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 ELAs.
And a price 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 we'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 I think that's part one of your questions. Second one about gender to AI. I mean, holy cow, that's movie so fast. I talked about data science models earlier on predicting where customers usage is going to go and I think that generative I in particularly the predictive part of that can be quite valuable to us so it can short cut 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 and when not to intervene or what's the next
part of the business and help give smaller companies advantages that we didn't have small companies. We've had to earn over like a long period of time like just working at and having these work on these models and then also just making sure that using gender to buy to give sales teams insights into when they should reach out to customers. What's actually happening. They talked about this. Why are customers doing the things that they're doing. What's happening. And I think that's what gender to have I can start to parse all this data, all this telemetry information.
So 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 and the rough. And I think gender to AI 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 the customer. It's never going to replace a human human relationship business, particularly enterprise space. That is a human 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 to 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 thing for the customer and it's the right alignment of incentives for my employer and the company that I represent to.
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 uses 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.
I include account managers, account executives, customer success representative, 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 surgeon 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.
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 we'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.
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. Then the third, where I hope that all of this culminates is in the product road maps. 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 road map, 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 of 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 and be able to use it as much as possible to predict the future of the way that your products 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 that we 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, I can't decide 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 and enablement to be really good at this and to be just great partners with customers and to try to understand the way they're going to consume value of 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 you today. Thank you. Awesome. Thanks for having us, Mark. Thanks. If you liked 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 ratethispodcast.com slash asccc.
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. We'll see you next time.