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The Margin is a podcast from MGI Research that explores the evolving world of business monetization. Hosted by MGI Managing Directors Andrew Dailey and Igor Stenmark, the show features candid conversations with founders, CEOs, product leaders, and industry experts at the forefront of pricing, billing, and revenue operations. Each episode dives deep into the strategies, technologies, and trends shaping how companies generate, capture, and grow revenue—from subscription and usage-based models to AI-driven monetization. Whether you're in finance, product, or IT, The Margin offers practical insights to help you navigate complexity and drive growth in the digital economy.
Andrew Dailey: Hello and welcome to The Margin, a podcast exploring the forces shaping business monetization. I'm Andrew Dailey, Managing Director and Analyst at MGI Research. If you're in the world of pricing and business models, you've undoubtedly heard of the subscription economy. Just a few years ago, seemingly everything was being offered as a subscription, from streaming services to automobiles. Today, however, consumers appear to be pushing back on subscriptions. In response, more B2C and even B2B companies are offering consumption-based pricing models, enabling customers to only pay for what they use. usage-based pricing offers buyers flexibility, reduces costs related barriers to entry, and helps customers connect value delivered to every dollar spent. But just as the shift to subscriptions forced companies to rethink their quote-to-cash model, usage-based offerings compelled businesses to reconsider customer acquisition and experience data. And the core of how value is delivered and monetized. Joining us today is the executive in charge of the company that coined the term the usage economy. I'm joined by Adam Howatson, CEO of LogiSense. Adam, welcome to The Margin. So for companies that don't currently have a usage-based pricing model, what are they missing out on?
Adam Howatson: Usage-based go-to-market models are special in a couple of different ways. Increasingly we're seeing fatigue around subscriptions. We're seeing increased pressure in B2B scenarios to ensure that value is delivered for every dollar that, terms are flexible. And we're also seeing vendors who want to increasingly put their products forward, believing they have a great product and drive growth by getting those great products into the hands of customers. usage-based pricing models allow you to settle on a point in a spectrum of usage-based pricing models. It's not an all or nothing proposition. Think of sort of the far-left side of the model as the traditional one-time sale or transaction all the way through to pure usage. There are many steps along the way, and for companies who aren't considering innovation around their pricing, or around their go-to-market models, they're missing out on a lot. And what they're missing out on are things like increased retention by customers who see better value for money on usage-based, go-to-market models who, they miss out on the opportunity to upsell more easily to customers who may have, in a usage-based model, put money on account and are happy to draw down money from that account across all of the products and services within a customer's portfolio, which reduces, removes a huge barrier to cross-selling. In addition to that, you're missing out on the competitive aspects of being able to shift the risk dynamic in the vendor-customer relationship and help your sales teams to shorten their cycles, to entice customers to come to try your products and services, or switch from a competitor and, lastly, though this isn't an exhaustive list, the very practice of implementing a usage-based go-to-market will introduce, by necessity, a type of discipline around your enterprise architecture, data management and retention, and the way that you contemplate your costs and the value that your customer receives from your products and services in an entirely new light. So I could probably go on for several minutes on an exhaustive list of benefits that you would be missing out on by not exploring a usage-based monetization or go-to-market model. But those are some of the highlights that you might be missing out on sales and revenue growth. You might be missing out on customer retention and lifetime value. You might be missing out on the wealth of information that a usage-based infrastructure can generate for your business and the insights that you could glean from that.
AD: What are the most common misperceptions that companies have about them?
AH: One of the common misconceptions is that usage is an all-or-nothing proposition, and it's not that. It's a very sophisticated spectrum. It is shades of gray. And finding the right shade for your business, for your product, for your customers is an important part of this practice. So sometimes business leaders will be tentative in embarking on this journey because they're not sure how their forecasting is going to change. And can I still produce a sensible and accurate budget for my board of directors? Or you may have a finance or IT leader who's got the systems that have been working fine for 20 years. Why would I change them now? Whilst you have a product or marketing leader screaming at the top of their lungs that this innovation is vital, or you will become a victim of your competition. So those that I think are some of the, some of the areas that are of great benefit.
AD: What are the most common mistakes people make when they move towards a, usage-based business model?
AH: But some of the common mistakes are to assume that all things are equal in business and to just take what you have been doing historically and try to translate that directly into a usage-based model. Implementing usage-based pricing allows you a flexibility to redesign your customer interactions as it relates to, commercials, where the money changes hand how the customer perceives value. So these models provide a great opportunity. To, to influence those aspects of your go-to-market.
AD: Why shouldn't every Salesforce CPQ and billing customer want to look at usage pricing?
AH: Usage pricing isn't right for every company and it's not right for every product either. So it's important that you understand the market that you're in, the product that you've got, what the competitive landscape looks like. What the risk tolerance or appetite for growth and experimentation is, in your business. And understand that though it might be very right for a large majority and increasingly so, as we see more economic pressure upon us in today's age and a need to deliver more value for money, usage-based model might not be right for every business, but I suspect it probably has elements of it that is right for the majority of businesses. But it's important that you're making the investments necessary to understand how this could affect you and what the potential upsides or pitfalls may be in implementing a usage-based model.
AD: For CEOs or CFOs whose organizations are adopting a usage model. What are the three questions they should be asking their teams to make sure that they're on a successful path?
AH: For businesses that are contemplating a usage-based model and, as a CEO or CFO thinking about how should I be sort of challenging my team to ensure that we're ready for such a transformation? I would start with asking questions around your product and market fit, and do you understand what it is that your customers are buying from you? When you use Uber to get from point A to point B, that is the value you are deriving from. It is a movement from where I am to my destination. I don't care how much fuel was burned, I don't care how long I sat in the car. I don't care if the car had air conditioning. I don't care about many of those details. My volumetric is a safe journey to the other end, and that's what's monetized. And that's what's put in my face as the customer when I when it's time to settle and ensuring that you take the same approach. And I hear you're asking questions of your product teams, do they understand what the dynamic is with your customer and your competition? What a usage-based model help you to differentiate, help you to attract new customers, help you to upsell existing customers, help you with your with retention issues you may be facing and understand of why it is that you're implementing a usage-based model. The second question I would ask is how is our data as an organization, and how is our understanding of our own enterprise architecture? And do we know in the systems that support and deliver our products and services what type of data those systems are generating, where that data is stored, in what format it exists, and how can I get to it being prepared from an architectural perspective? And asking your CIO, asking your CFO if your financial systems or your IT environment at large is ready for design for or prepared to start ingesting and marshaling usage telemetry around the organization is another vital part. So, customers and product market set pricing, certainly your environment and your maturity around your enterprise architecture, I think is another vital one. And third, I would ask, “what is the competition and market doing? Is this model relevant to us? Is it relevant to our competition? Could it be something that is a competitive differentiator, or could it be something that would help us to compete in the same way, but better relative to what we've been doing historically?”
AD: At what point does Salesforce, CPQ, and billing hit the wall? When do I need to add something to that? What are the characteristics of a business that would suggest to you that Salesforce, CPQ, and billing is not going to get the job done?
AH: In my opinion, Salesforce customers, Salesforce shops, will start to hit a wall around usage-based monetization within the Salesforce stack as you start to get into volumes and complexity, which may exceed what Salesforce native systems, perhaps even Salesforce billing within the Revenue Cloud are capable of supporting on their own. Also, the complexity of your catalog and the complexity of how you're going to charge for and arithmetically derive the value metric for your customers might start to fall down a little bit because you may not have access to all of the information that is being ingested and mediated by a usage platform inside of Salesforce. That mediation capability doesn't exist natively within the Salesforce stack. So that may be another trigger where you want to start to look at, expanding your technical breadth within the ecosystem to be able to satisfy some of the usage of usage-based use cases.
AD: A lot of companies lack a lot of sales discipline and end up pricing deals and a wide variety of ways under the guise of “this is what it's going to take to get this deal done.” And then the consequence of that is it becomes very difficult to implement from an operations from a billing point of view, one-way organizations solve that problem or think about solving, as they say, “let's adopt a CPQ tool and that'll enforce sales discipline.” Another way they look at is to say, “let's adopt, a billing system that has more flexibility and agility that can handle any type of sales arrangement that can be dreamt of.” CPQ or billing?
AH: I would argue that more rigid rulesets cause sales to become more innovative rather than more disciplined, and particularly in enterprise dynamics, not necessarily in the consumer world or with a highly commoditized, high-volume product. But certainly in enterprise, almost every deal is bespoke, and the larger it gets, the more likely it is to have special terms and conditions. And if you're an enterprise B2B vendor and have 100,000 clients and each one has three special terms in their contract, that's 300,000 terms that need to be checked by person throughout the year, need to be enforced at the time of billing, need to be entered into the financial system, and then you have to repeat that process every 3 or 12 months, depending on what the billing frequency is. It can become very expensive and very prone to human error. When implementing a usage-based billing system, it's important to check if your vendor has the capacity to conduct automated contract enforcement, and that should be a core part of the platform. In the same way that mediation is a core part of a usage-based platform to ensure that as nuances, rent periods, termination fees are imposed or negotiated at the time of sale, they can be automatically enforced at the time of billing by the system and not by a human being who may be prone to make errors.
AD: A lot of companies say they can do usage pricing. For you, what's the litmus test to put to them to see if they really can?
AH: I think there are a few different tests of whether a vendor can actually do usage-based billing. One of them is going to be around the data and the way that they handle data. And if you're engaging with a usage-based billing vendor who is only capable of performing X times Y calculations, X units times Y price, they're probably not a real usage-based vendor. I would also draw attention to the data itself, and when implementing a usage-based pricing model, particularly in high technology, communications, IoT type segments having a handle on the data or having a system which can get a handle on the data of your business is paramount. If a usage-based billing vendor isn't capable of ingesting the API or file or serverless aggregation layer, billions of events a day and then transforming or mediating that data to deliver it to your financial systems, to deliver it to your CRM and CPQ systems, or to deliver it back to your general ledger, they're probably not a real usage-based billing vendor, and mediation is the capacity to ingest huge volumes of data and then transform it, or throw out perhaps zero balance records, or get rid of unnecessary data and then move the pure gold, the rocket fuel that which you are going to monetize into the usage-based billing engine to perform very complex calculations on it. So I would look for both a complexity of catalog and pricing mechanism, which is superior to simple X times Y calculations. Right? Because that's technically usage-based, but not really in practice. There's very few companies who will only do X times Y transactions. And the second major item is to look for a vendor's capacity to transform, ingest mediate data to deliver the end product that that information which you will monetize and report to your corporate systems back while getting rid of the billions of, errant or unnecessary pieces of data generated by your infrastructure.
AD: If I'm an existing Salesforce customer and want to adopt a usage pricing model, what do I need to do to make that happen?
AH: If you're a Salesforce customer and you're using CRM and CPQ today, which are probably the most prolific products in terms of the go-to-market or quick cash stack within the Salesforce ecosystem and you want to move from a traditional pricing model, maybe just one-time transactions or basic subscriptions or simple X times Y type usage to to true usage-based model, you'll want to contemplate a variety of different things. One of them is how are you going to price the product differently now that you have the ability to price it any way you want? And that's both monetizing discrete events that simple XY that we're talking about or by generating pricing and billing based on a value metric. Previously we'd spoken about some of these emergent generative AI vendors, and they've abstracted the computers and the source code and the training data to the concept of a token, which is very easy for a consumer to wrap their arms around. And they understand the value that they're getting there. So if you're moving from Salesforce to a more sophisticated usage type model, you'll want to contemplate the complexity of your pricing model. You'll want to complexity contemplate the volume and complexity of the data that you're going to be ingesting in order to charge a usage-based model and ensure that you've got a great handle on that information, you have the appropriate data transformation and mediation in place, and that you're sending over the 1 in a billion events. That is the gem that requires monetization in the right way. So as you're making a move in a Salesforce ecosystem, you're going to want to make sure that you have those abilities one around product catalog, two around data mediation and transformation, and three around scale to ensure that you can ingest and capture all of the raw events before you then move it on to mediation and then onto calculation.
AD: What are the characteristics or attributes of a business that when you see these characteristic or attributes, you say, “this is the kind of company that needs a sophisticated usage billing engine?”
AH: Sometimes you'll look at the product that the company is offering and the way that they're charging for it. And if those are not aligned with where their customers would perceive value. And for me, one example, I always fall back on it's poor old cable television where there is an absolute mismatch between the amount of content that I consume over that media and the way that they charge, which is an opaque, locked in flat fee. Take it or leave it. I know you only want this one channel, but I'm going to sell you 800 and I'm not going to do it any other way. That that's an example. That is right for disruption through monetization, even streaming providers today, when we think about, an example, we're all starting to get subscription fatigue. I know for myself, I've gotten multiple streaming subscriptions in the house. I cut my cable cord years ago, but now I've amassed a collection of flat subscriptions.
AD: One of the essential components to a sophisticated usage pricing model is the ability to do mediation. How do you define mediation? What is it? Why do I need it? Why is it so important?
AH: Mediation is probably one of the most underrated and undiscussed capabilities out in the market today as it pertains to usage-based billing or otherwise. And mediation comes from the telco industry. The term is where it was first applied. But today, more generally, I think it's known as data transformation. And what it is is a system's capacity to ingest, in our case, all of the usage events from all of the systems across an organization. And for LogiSense, this might mean thousands of databases, for our customer set in some cases 5000 or more databases or locations where information is collected from. You don't want to send all of that raw data, which might contain bad data, which might contain zero records, which might contain other information through the calculation engine of your core systems. And mediation is the capacity to ingest all of the raw data from the multitude of different sources throughout the organization, throughout your stack, and to be able to transform it into a format which is ingestible by the endpoint calculation engine. Again, that might be an ERP system, usage-based billing system, or other system. And to get rid of the unwanted or the dirty or the unusable records that come through in that raw ingestion of usage events throughout the organization. So mediation is a critical tool to be able to claim and transform and deliver information in the format it needs to be delivered in to the destination it must be delivered to.
AD: How easy is it to build a mediation engine? Is it something that somebody can do overnight? Takes a year or two? What's it take to make that successful?
AH: Building a mediation engine is is not an activity for recreation. It is complex. It must be capable of supporting and ingesting huge volumes of data. Think of a large public organization, 50 or $60 billion in revenue, tens of thousands of employees or more and how much data that organization generates in a day. Massive. Massive. Taking out what's not useful, first of all, being able to catch all of that data and then being able to extract what's useful in real time while delivering the result of the cleansed data, the product, what is desired by the calculation engine, or the, the destination application is incredibly complicated. Being able to get out to thousands of databases, being able to integrate with proprietary APIs from different vendors, being able to connect and ingest information from the broader IT ecosystem is absolutely vital. So building a mediation engine is a sophisticated endeavor and it's a it's a significant investment. And you can't be wrong because if your mediation engine is causing errors in the data, which it is, then feeding over for calculation as the old adage goes, garbage in, garbage out, so very important that a mediation or data transformation engine is built with the same care and attention from engineering that any other system would be
AD: What's the difference between mediation and an ETL tool?
AH: ETL is really about moving data from one spot to another in the right format. A mediation engine is capable of dynamically changing its behavior based on the information that it's processing at any given point in time. So when we think of ETL, we think of I'm doing a data migration, I need to move from format A to format B, I'm going to do this, transformation a billion times in the exact same way and populate the new database. I will move the data from one location to another, or load the data, into the new system that I desire or into the destination that it needs to reside in. In a mediation engine. You're capable of doing that but you're also capable of changing the logic on the fly based on the information that's being processed. And I would also say that a mediation engine has to work where an ETL tool can be run asynchronously. Often in most cases, we'll do it over the weekend, we’ll transform the data and populate the new database. The mediation engine has to be able to work in real time because it's monetizing your customer interactions as they're happening. And when it's applied to a concept like usage-based billing. So there's some important distinctions there where I think mediation is a higher volume, more dynamic and sophisticated capacity to cleanse and transform data for delivery, where ETL is more of a, if you design the route, the repeatable route, you can just keep firing huge volumes, expecting the same result at the at the other end.
AD: One of the key capabilities of a mediation engine is the ability to enrich data. How important do you think that is and can you comment on that as it relates to, say, some of the new AI models where you need to really enrich the data that's coming in, not just transform it dynamically as you described on the fly, do it in real time, but this whole enrichment piece?
AH: It's a great question, Andrew, and enriching data through mediation platform is going to be increasingly vital to the way that we implement and educate in particular, these generative, large language AI models. If you think of a tool today like ChatGPT or another, widely available Bard or another generative AI tool, those publicly available systems are often educated on the publicly available information of the internet up to a certain point in time. And that's great when you want to have that. I generate content that is of general knowledge so I can ask questions about Earth history. I can ask questions about companies from two years ago, data that existed two years ago, or maybe less if I'm paying a little bit more for a more recent training model with those systems. But I would never be able to ask how should I modify the pricing of my products to improve my business? Which of my customers are likely to churn in the next 12 months and why? How can I stop that from happening? Could you recommend optimal pricing for me to go drive cross sales by 10% from product A to product B. A publicly available AI model will never be able to answer those questions because it has not been trained on the specific customer, product, and service interactions of your business and a mediation engine. We do this at a larger sense. We use the mediation engine in something called real time AI learning, where we ingest usage events, monetization events, billing and monetization data from our engine and others. And we can transform that and deliver it to a generative AI model to do what is called fine tuning, which is continued improvement of the AI model. So every day, as we get more and more information coming in, more products are purchased, more services are consumed, more interactions with customers take place, we can tell our AI about all of those things that have happened, and that's unique to our business because it's our monetization and our billing data. The mediation engine then takes that information and furnishes it to the generative AI model to teach it about what products your customers are using, which customers are growing, which are shrinking, when are they monetizing it? What is your seasonality? Every interaction that happens within the business that's relevant to training the AI can be mediated, transformed to a format that's relevant for the AI is fine tuning, and delivered to that AI. So mediation is not only a great collector of all of the multitude and various sources of data within your organization, once it's been ingested by the mediation engine, it can be transformed and delivered to an AI to help fine tune it every day on the specifics of your business, your customers, and your efforts in the market. Which means you'll start to be able to ask AI pointed questions about your business, your products, and your markets. Huge amount of opportunity around mediation to help train these generative AI models.
AD: A lot of companies have invested millions, tens of millions, hundreds of millions in data lakes. What's wrong, if anything, with a data lake approach versus using mediation for some of these use cases that we've been talking about?
AH: Data lakes, still very valuable. Wonderful. You stored and collected all of your data in one location. Typically, the types of interactions which are going to help to inform these AI models aren't a particular row or cell that you've captured and stored in a data lake because a business analyst or a data scientist thought they would be relevant to a report that they had in mind, and you're not necessarily going to be capturing every tacit interaction between your products, how they're delivered, how they're consumed, how they're monetized when they're monetized in a data lake, you might capture all of the invoices, all of the customer data, and other information. But the data lake itself isn't producing answers to your questions. It is a lake of data, and you need a very smart person. Data scientist or business analyst? PhD in mathematics, sitting on top of the data lake to produce meaningful insights for the business, somebody has to be able to look at the data and come up with or infer some action to be taken.
AD: You have a lot of experience working with Salesforce customers, often Salesforce CPQ on billing customers, that have hit a wall and need something more. Describe that wall. What is it that they're not getting from their Salesforce CPQ and billing their revenue cloud solution where they turn to someone like LogiSense to get that extra thing that they're not getting?
AH: It's a great question. Typically, if we're speaking with a Salesforce House or Salesforce shop that has sort of hit the limitations of what they're able to do within the native Salesforce stack Salesforce billing around, usage-based implementations. It's that they lack the capacity for data mediation for transformation and the ability to ingest usage-based data from a multitude of sources. So far as I'm aware, in Salesforce billing, you're going to be looking at. But some of the more, rudimentary X times Y equals Z type volume calculations. And then that will be billed as usage-based billing. Very important to consider whether or not the system Salesforce in this case is able to ingest your usage telemetry and mediate it. And deliver it for calculation. In an appropriate way. And, and so for us natively, I do not believe has a mediation or data transformation engine. So that's another element in the stack that you're going to have to go procure, probably from a from a third party. Once you've been able to capture and get your arms around that data, is there going to be a sophistication, a pricing model of contract terms and contract term automation and enforcement, or the ability to design go-to-market pricing models with a usage-based element? Because, again, it's not just X times Y equals Z, it is a spectrum where you may have a one-time sale and then an ongoing usage-based element which accompanies it like a consumable for a device which requires consumable. You might have a minimum commitment or subscription plus usage model to ensure some certainty for the vendor around sunk costs in delivering a solution with an upside on usage based on the size of the commitment that the customer is willing to make and a few stops in between all the way up to a pure usage-based model. But I would posit that if you are getting much more sophisticated than X times Y equals Z, or more sophisticated around your need for data mediation and transformation to prepare data for usage-based monetization, those are typically the scenarios where we've seen customers getting to the end of the capability natively within the Salesforce ecosystem and looking for a partner who's able to do that mediation or data transformation in addition to the more complex pricing and catalog requirements around usage-based go to market plans.
AD: In your experience, you get called into Salesforce shops where they've hit a wall. What are the three most common things that companies encounter? Where they get frustrated by what they have with the Salesforce tools and where they're looking for some additional solution?
AH: A, it doesn't support the volume of usage events that we need to ingest in, and not that every one of those events is going to be, used to perform a calculation, but it will need to be cleaned out. It will need to be intermediated or mediated, and it will need to be transformed and then delivered to the system which is going to do the, the actual billing. I think also the complexity and sophistication of the pricing catalog and the platform's capacity to deal with high volume scenarios where you may be ingesting billions or multiple billions of events per day are where you'll start to see some limitations, and that's where customers may want to start to engage to engage with more of a pure play, usage-based billing vendor.
AD: For organizations in which the sales and product teams really want to move towards a usage model. And yet finance is looking for predictability in the business. How do you balance that conversation of “we want to have this usage model, we don't necessarily know what revenue is going to look like in 6 or 12 months” with the finance need to model the business and forecast?
AH: Predictability is important. And some of what I will say next, I say tongue in cheek. However, I think in its majority it is true. And if you're sole intention as a business leader or you're the CEO of one of these businesses, and the only thing that matters to you is predictability, you should be asking yourself, what is the future and trajectory of your business? And we see huge disruption happening and have for the last 20 years. The world's biggest hotel and accommodation provider doesn't own a building. World's largest transportation and logistics firm doesn't own a tire. And it's the information around those services and a novel way of delivering those services, which has helped, in this case, Airbnb and Uber to move to the top of their categories because they have disintermediated the competition, they have consolidated and provided a digital experience, and that came with risk. How can we start a transportation and logistics company that owns no cars? How can we start a hotel and accommodation chain that has no bricks? And they did, and they were wildly successful in doing it. Though, finance and often the CEO really like predictability because it's very easy to show up to a board meeting where you have done what you said you would do, but the risk in not innovating in this space could be catastrophic to you. What happened to the competition of Uber and Airbnb? But what happened to upload some very, very colloquial examples? But what happened to Blockbuster when Netflix showed up and started monetizing DVDs through the mail? What then happened to other traditional letter mail providers when Netflix decided to start streaming online? Look at the emergence of this entire class of streaming providers that all popped up around the concept of a new model that was different than mailing physical media back and forth, different than having cable infrastructure piped into your house and paying for large, expensive, opaque packages from cable providers that was commercial innovation within that industry, and it completely changed the competitive landscape in some cases completely bankrupt the number one in the industry. So while it's important that the CEO and CFO have a feel good, fuzzy, warm feeling that there is predictability, not listening to the product leaders, innovators, engineers within the organization and the customers outside of the organizations, I would contend, carries more risk than upsetting a board meeting by not having been 100% on plan from last year's projection. So there are ways that you can get accurate, which is to use all of this data that you're collecting to model before you implement and take these solutions to market, to speak to experts like at LogiSense and ask them, how is this done? What variance should we expect? What is the best model for us? The most dangerous thing you can do is just adhere to the status quo. So I would encourage those sales and product leaders to keep making noise. And if you have a nervous or a risk averse CFO and CEO, paint it through the lens of competition, and what happens if one of your competitors makes this change first? Do you want to be the hook, the leader in the category, or do you want to be one of these folk tales of a company like blockbuster that just started to disappear from the earth? Because the aversion to change and to take a risk on these new distribution channels, which happened to be letter mail and then digital, meant effectively that the entire business model degraded, rather quickly in their case.
AD: What's the penalty for not looking at some type of usage pricing model? Why can't I just ignore it and forget about it?
AH: I think it's like any other innovation in business. Increasingly, we're seeing more and more attention being drawn to usage-based monetization of products and services. In 2024, now facing probably the most challenging economic and business environment we have in decades, cash is no longer free for businesses. The concept of growth at all costs is a fallacy, and a lot of those companies are being made to pay the piper for having pursued some of those paths over the course of the last ten years and now need to adjust their strategies to revisit the fundamentals of business. A business should grow. A business should be profitable. A business should be competitive. The business should retain customers. And growth, I dare say, is probably no longer the single or the single most important calculation in a company's valuation. A lot of these other metrics are starting to be contemplated and usage-based go-to-market models can affect everything from the length of your sales cycle, the risk presented to a customer looking to engage with your business to make it easier and more accessible for a customer to try your product, try your service to see if they're going to get value out it. Every person, every business has to do more with less. The value of a dollar today is not the same. We have a record M2 money supply. Value of a dollar is not the same as it was even a year ago, maybe 10% less. Certainly 20 or 30% less than it was three years ago. In both in business and in the consumer world, there's more and more pressure to ensure that we're getting value for the money that is spent.
AD: You've written a book on the usage economy. You've got a whole long list of customers that you've helped. What are some of your favorite examples of companies of businesses that have a usage business model?
AH: There's a number of companies out there that have interesting usage-based go-to-market models. And we're seeing more of them come out over time as usage-based GTM becomes more and more prevalent out of necessity, I think, or out of competitive environment. One broadly available example that I think everybody in technology can resonate with certainly is Amazon Web Services. Amazon originally started with a full consumption-based model where you would be directly charged for how much CPU you're going to use or how much memory are you going to use, how much storage to require, what type of system. Over time, that's evolved into a much more sophisticated what we would call a consumption drawdown. And AWS has a significant cost to operating their data centers and the investments that they need to make and look for the customers with whom they're engaging, certainly on the enterprise side, to make as large a commitment as they feel comfortable to make. And for that, you will get a better discount. But from a usage you perspective, what it has evolved into is something akin to a usage-based drawdown model.
AD: Now, what advice would you give to a product manager who really wants to have the usage data and better insights into how customers are using their product or service? What advice would you give to them when they're trying to justify the investment in proper tooling?
AH: Well the fastest way to go out of business is to never listen to a customer. And simultaneously, one of the fastest ways to damage your business is to only listen to customers. So, I think I think Steve Jobs have described that as the innovator's dilemma. Had a point in time and a product manager can help to offset the unknown and the risk, around changing product go-to-market configurations around changing the product itself, around changing the commercial model if they have the data necessary to support their opinion. And I was a product manager in my career, for many years and know how the how tricky this is to stand up and make an assertion with no data but for the notes that you've collected, but for the anecdotal interactions that you've had with customers. I went to a user group and there were ten biggest customers in the room. Ten isn't a statistically significant sample. It's an anecdote, right? And it's hard as a product manager or product marketing manager to make that case for that investment. But what I would encourage those product managers and product marketing managers to do is to articulate the accuracy that you're going to gain fundamentally understanding how your products are consumed and monetized. When are your customers using them, what is your seasonality? And you can trade these things with CEOs and CFOs, which is to say I can improve our price point and make sure that we're getting top dollar for it. I can ensure that we're competitive. I can preempt churn events by our customers. I can take a look at where we need to be able to offer new product. I can do all of these things, but I have to have access to the data, and we need to invest in getting access to the data because today it is a mishmash. So, for product managers in similar roles looking to invest in a usage-based monetization, go-to-market, and the systems necessary to do that within their organization, it's not just about your one product. Though, that might make the case if it is a darling product or there are high hopes around it. But in addition to that, you're going to get direct visibility into your specific customer and product interactions that you have never had before as a business and where you have been showing up to date, voicing opinions around priorities within the product line based on opinion, anecdote, conversation with–what is a human's capacity? If you met with one customer year, you could meet with 356 of them. But no product manager can just meet with customers. However, I can have a usage-based monetization platform gathering billions of events and summarizing those, and I can glean insight from them and inform my product decisions based on that actual data. And I think that's the point upon which to, in your case, for a business to make investment, one of these technologies.
AD: Thank you for listening to The Margin. If you have questions about today's episode, or if you'd like to schedule a call with an MGI analyst, reach out to us at insights@mgiresearch.com. You can also reach us on LinkedIn, Facebook, and X, and you can find more information about our research and advisory work at mgiresearch.com. Until next time.