Revolutionizing Subscription Models: Logisense on Usage-Based Billing, AI Optimization, and the Future of Consumer Engagement

Unlock the secrets of the evolving usage-based economy with the visionary CEO of Logisense. Ever wondered if you could pay only for what you actually consume? Adam guides us through the transition from traditional subscription models to innovative, usage-based plans, especially for services like streaming. Learn how this model addresses subscription fatigue, offering a value-driven and transparent approach that both businesses and consumers can benefit from. We also explore the hurdles companies encounter during this shift and how overcoming them can lead to heightened customer engagement, increased revenue, and long-term satisfaction.

Imagine saving millions of minutes in human productivity with the power of AI. In a fascinating segment, we delve into how Logisense harnesses detailed telemetry data through its usage-based billing platform to optimize AI systems, creating intelligent chatbots that provide precise, real-time answers to complex business inquiries. We also spotlight the highly anticipated Usage Economy Summit, where the latest advancements and insights in the field will be showcased. Join us as we celebrate the pioneers of the modern economy and express our heartfelt gratitude for your continued support and engagement. Don’t miss this opportunity to stay ahead of the curve!

Transcript

Speaker 1 0:02

Hey everyone. We're diving into the world of the usage-based economy with the true innovator in the space today, at Logisense. Adam, how are you Doing well? Evan, pleasure to see you, great to see you. I've enjoyed watching your rise and success over many years, so I'm excited to dive into this topic. First of all, who's Logisense? And maybe introduce yourself as well.

Speaker 2 0:28

Yeah, absolutely. Logisense is a world-leading provider in usage-based billing and monetization technologies, and we help companies around the world to implement whatever their dreams are in terms of product go-to-market, their commercial interactions with their customers and how they're able to monetize their products and make them effectively competitive in market from a commercial perspective. And there's a lot more to it than that, but that's a high-level overview, and, as for myself, I've been CEO here at Logisense for five and a half years and come from a 20-year career history in the enterprise information management space a 20-year career history in the enterprise information management space.

Speaker 1 1:11

Well, great to have you here. Appreciate the time and interest in joining. Let's start with the big picture the usage economy. You wrote a book, maybe the book on the usage economy. Let's start with definitions. What is it? How do you define it, describe it?

Speaker 2 1:20

Absolutely. I think it may be the book, so far as Logisense is certainly an innovator in this space and we talk about the usage economy. You might also have heard this as a consumption economy or usage-based billing, usage-based go-to-market. Talking about is a shift in the economics of business and in our personal lives as well. For those of us of a certain vintage, we remember that there was a time when a transaction was just a one-time transaction I'll sell you a pencil and I will walk away from that and over the last 10 or 15 years, the drive towards recurring revenue to help cement longer term customer relationships, to increase customer lifetime value, has been largely driven by the subscription economy. And I think we all feel this nowadays in our consumer lives, where an average household may carry 9, 10, 11, 12 or more different subscriptions. Maybe that's for streaming media services, and maybe that's for streaming media services and maybe that's for other goods or services that you may consume regularly. But the usage economy is about an evolution from that concept of a subscription economy and I think a lot of us have experienced subscription fatigue where you may have. I know for me personally and I'll use these streaming services because I think it's a great colloquial example you have got seven subscriptions ongoing and you're probably not getting value out of all of them. I know there's a lot of people who will, like myself, hop from streaming provider to streaming provider so that you're not spending money on something that you're not using. They update their content catalogs once a year, or a franchise that you enjoy watching comes out with some new season or new episodes, and you may subscribe to that streaming provider for a couple of months, binge all of the content that you like and cancel your subscription and come back to them a year later Because you don't want to pay for eight different subscriptions to eight different content platforms that you're not going to be using to the fullest. It's a waste of money and, sooner or later, various providers. I think this is happening a lot in B2B scenarios now but these content providers are going to start to catch on to the fact that having a subscriber for two months out of the year every year isn't all that effective a business model and if I can keep that customer engaged and happy and getting value from my platform for the entire duration of the year A, I'm likely to get more revenue out of them. B, I'm likely to retain them for a longer period of time and C they're likely to enjoy the quality and the value that they get from my service more than the others. And that's really what the usage economy is all about is paying for what you use and allowing businesses to create and innovate on novel and enticing commercial models to sell these plans based on usage, rather than the concept of this opaque locked-in subscription where you may or may not get value, but I'm going to ensure that you pay me every month.

Speaker 2 4:21

People start to get fatigued by that.

Speaker 2 4:23

So that's where the usage economy comes in, and I would deposit to you this example that the first content streaming house who offers a usage-based plan where maybe I can put a couple hundred dollars on account with them and they'll deduct credits from my account as I actually consume content from their platform, rather than charging me a an opaque all-in subscription every month.

Speaker 2 4:47

That seems to be ever increasing. I don't know if you've been watching your bank account with these streaming services, but they've doubled in price over the past few years and I don't feel the value from the content that's coming for that doubling of price If they allowed me to have a usage-based model where I was paying as I was consuming content fairly, so they're required to put good product out there and I will consume it and I will happily give them my money. That's an example of the evolution that is the usage economy, and there's a lot more to it than that, but in basic terms, that's really what we're talking about is inventive, fair, transparent, engaging, good value for money commercial models that businesses and B2B and B2C vendors are both starting to embrace as the next incarnation of competitive go-to-market models.

Speaker 1 5:40

Wow, hallelujah. You're preaching to the choir here. Sounds fantastic as a consumer and prosumer, I guess. But you know there are a lot of challenges to usage-based monetization giving up that juicy recurring revenue SaaS typically, for example and to implementing usage-based billing on the back end, back office, side. What are those challenges from your perspective?

Speaker 2 6:07

You've articulated one of the challenges, which is, I think there's some trepidation or a notion that you might be giving something up in a move to one of these models and you're not. The notion of recurring revenue going away with the introduction of a usage-based element I think is a fallacy and that they're not mutually exclusive. In the usage-based world there are several different archetypal models of how you can create these go-to-market constructs, such as minimum commitment plus usage models, to ensure that you have a contracted value that the business can expect and plan around. And then you can introduce optionality, variability and some self-empowerment for your customers by including usage-based elements on top of that, either allowing them to self-select by putting promotions in front of them and allowing to consume those services on a usage basis, or by asking for a slightly larger commitment in terms of the minimum committed model that will keep your customers recurring revenue base contracted and secure, while introducing elements of usage in a hybrid model to help with that differentiation and novelty in the way that you go to market and appeal to fair value for money within your consumer base, consumer base. So one of the challenges is, as this is a new type of monetization and a new type of model that really we're seeing some of the leaders in the industry start to embrace and make available for their customers. Some education needs to accompany that within the executive ranks, product ranks and finance ranks of those same companies, to really understand what usage-based monetization is and that it's not a binary all or nothing approach to the way that you're taking your products to market, but can actually be used to supplement, to differentiate and to entice customers to this new world of fair value for money, of self-selection, of customer empowerment, of pay for what you use while still retaining some of the elements of a recurring and contracted minimum value.

Speaker 2 8:12

And I think that that education is one of the things that will help to increase the proliferation of these types of go-to-market models, but requires the executive ranks to understand that it's not an all-or-nothing proposition. And in fact, there are a multitude of different methods in which you can implement usage-based monetization to complement some of your existing revenue streams, to add to them or as a fundamental agent for transformation. As you're saying, perhaps you do want to do an all or nothing transformation. So there are degrees on the spectrum of usage-based monetization, from one-time transaction to pure usage-based monetization as you use it, and finding that right balance is part of the practice and part of the challenge getting that education out there, understanding it's not an all-or-nothing proposition and also growing education around the concept of a value metric.

Speaker 2 9:04

If you're going to charge me for usage, that charge should be calculated on where I, as a consumer, perceive or know or understand the value of your product to me to be.

Speaker 2 9:17

Again, I'll come back to the very colloquial example of a content and media streaming house Me watching hours of well-produced, new, awesome sci-fi content is great value for me as an individual consumer and if I'm aware that I'm getting that for a fair price, that's not locked in and opaque, I'm more likely to align with your business. So that education around the fundamentals of business and how it's impacted, the notion of it not being an all or nothing proposition but rather a spectrum of different pricing models that can be tuned to appeal to your key consumer cohort and how you can implement those in a way which, depending on your intention, can either be hugely disruptive, such as in a competitive scenario, or can be complementary and can help to drive growth or help to drive customer relations or customer satisfaction, being at the other end of that spectrum. So that education around what is a new and quickly emerging type of go-to-market innovation? I think is one of the items that we're working to help tell the world about here at Logisense.

Speaker 1 10:28

Fantastic, great opportunity. And what are you hearing from your service provider customers and, in turn, their business customers on the importance of this, the potential impact interest? Where are we with the usage-based economy?

Speaker 2 10:48

I think, quickly proliferating. I remember a time back in 2019, 2020, where money was free. Imagine what a world that was. Four or five years later, in 2024, it's a very different scenario in business and interest rates have increased. I think that the notion of growth at all costs and the infinite growth fallacy the shine is starting to come off of those thought patterns and we're realizing that there isn't an infinite human population.

Speaker 2 11:18

So businesses need to get back into the concept of direct competition with others within their industry and the importance of this is that the way that you monetize your product and the way that you interact commercially with your customers is a part of your customer experience and more than that, it's a vital part of your customer experience. You can have a happy customer for years, send your bill every month, they pay it diligently, and you'll never hear from that customer positively or negatively. But if you get the economics wrong one time or if you have a negative commercial experience around your product, you're going to hear from that customer right away and probably in a way that you don't want to hear from them. So getting this right is of vital importance to businesses and understanding how they can implement these models and what the benefits can be can be. I think there are also factors that are motivating businesses to look to adopt these values because, again, it's no longer the concept of there is potential for infinite growth within a finite human population and within finite markets and that companies have to start designing those commercial interactions as a differentiator attached to their product, and we're starting to see more and more of that in the market.

Speaker 2 12:33

Additionally, from a consumer perspective or from businesses buying services from vendors, the landscape is very different in 2024 than it was five years ago and you need to convince the CEO and the CFO in 2024 why that money has to be spent. And if you're signing up for another software subscriptions and a lot of businesses will have hundreds of subscriptions from various vendors going on within departments, for individuals, company-wide you really need to make a strong case to the CEO and CFO as to how you're going to get value from this new subscription or this new service, this new technology, and be able to articulate that business case. And if you're providing B2B services, a business case where we only pay for what we're using and what we're getting value out of is far more compelling to a CEO or CFO's ears in 2024 than I'm just expected to pay a big lump sum to a vendor and I may or may not get value from that over the coming years.

Speaker 2 13:30

So I think there's a lot of importance in there, both in terms of how economics have changed over the past five years and the need for real value for money, for strong business cases and to satisfy the CEOs and CFOs of the world to get your project done but also in appealing to this this increasing shift in how aware people are of the economics and ensuring that they are getting value and ensuring that they're paying for the right things that their business is getting value from. So I think those are a couple of important factors to consider in this transformation and part of what's driving this push towards usage or consumption-based go-to-market models wow, impressive insights there.

Speaker 1 14:19

Um so, ai is the topic du jour, as we know um, and I imagine there are tremendous opportunities around ai for personalization customization on the user and and uh, provider side. But what say you? What are some of the practical applications of AI in the usage economy?

Optimizing AI With Usage Data

Speaker 2 14:34

It's certainly an area where I get very excited and I'll poke into one very salient example. Today, it seems this year, in 2024, that every business is hanging an AI shingle on its kiosk and its booth, and I've been talking to a lot of my peers. I've been certainly scoping out the competition out there, and what I find a stark shortage of is a clear articulation of the value proposition around implementing AI. And what are those use cases that truly create value for businesses? And I don't find a lot of them outside of using a large language model to generate pros, for marketing assets, for collateral, and even at that, you're still going to have a human reviewing and proofreading that to ensure that it is fit for market before it goes out. That's good, but that's not the panacea that we have been hearing the hype about over the course of the last year in terms of AI automation and its potential, and the reason for that, I believe, is an AI large language model that is trained on the wilds of the internet or whichever source material the vendor is using to create that model doesn't know about your business and chat GPT, or you can choose whichever example Lama and chat GPT, or you can choose whichever example, lama Titan. Whatever the case is, great valuable tools can't really automate anything beside pros creation inside of your business.

Speaker 2 16:04

In most cases, a usage-based billing platform like Logisense is at the center of the data flow within your business. So you can imagine to do what we do at Logisense. We're integrated with your environment and we understand who your customers are, what your products are, when the products were used by a customer, in which sequence, at which volume, for how long, in which location. We're also integrated with your ERP and financial systems to help with the full end-to-end billing process. How did the customer pay? When did they pay? Are they a good payer? And by virtue of being at the center of all of that telemetry around customers, products, consumer interactions, finances we can start to do something called prompt engineering with ai systems, and logic sense in particular has something called a data transformation or a mediation platform within it which allows us to ingest huge volumes of data, to enrich it, to take action on it, to reconstruct it, to supplement it and to marshal it to any other service within the business's environment. I say all of that to say this what we can do with the telemetry from all of your customers, products and financial interactions is to prompt engineer and large language model to be able to provide salient and accurate answers to questions about your business. And why is that relevant and why is that important and why does Adam believe that that's a real value proposition around AI versus a novelty?

Speaker 2 17:43

Logisense works mostly with large enterprise providers. That's sort of our area of the market Now. You can imagine if you've got 10,000, 30,000, 50,000 employees working every week and each one of them once a week and this is a very conservative estimate in my example here once a week asks a question which requires 10 minutes from another human being within the business to answer and become a very expensive proposition over time. But that's how businesses have been run for thousands of years. Who are my top 10 customers? By product, by usage, by industry segment, by country, by year.

Speaker 2 18:25

It might take somebody in the finance department 10, 15 minutes to spin up a spreadsheet, hook up a data source, fire up a pivot table, slice the data appropriately and email it back to a product manager, product marketer, a solution specialist within the business or a product marketer, a solution specialist within the business.

Speaker 2 18:48

What we do at Logisense is take that information that is available to us in all of the telemetry of the business and pipe it into a large language model as those questions are being asked.

Speaker 2 18:53

All of a sudden, the large language model is able to accurately answer questions about your specific business, your specific products, your specific customers in a mathematically accurate way, because Logisense and the usage-based monetization platform have provided that data via prompt engineering in real time to the language model to be able to accurately answer that question based on your company's real data.

Speaker 2 19:19

If I'm able to go to a chat prompt and ask the question who are my top customers, by product, by usage, by quarter, by country, and have it answered instantly by an AI agent with accurate data provided from the usage-based monetization system, versus consuming 10 minutes of human productivity times 50,000 employees, times 52 weeks a year, the real value in savings of that automation is tens of millions of dollars a year and fundamentally, we're providing simple solutions with accurate data to normal human questions that occur multiple times a week in every business.

Speaker 2 19:58

So, in terms of the usage economy and the usage-based monetization platforms impact on the emergence of artificial intelligence, what does it do and why is Adam so excited? We can take what is today in many cases a large language model capable of composing English prose for marketing and other purposes, which must be fact-checked by a human employee, and turning it into a natural language query chatbot which can accurately answer questions based on real data about your specific business, potentially saving millions of minutes of human productivity time, which is very expensive per year throughout the business. So that's one example of how does this usage-based monetization company get excited about AI and why does Adam feel like he's got a real value proposition, rather than the excitement of hanging an AI shingle and claiming to be?

Speaker 2 20:52

one of them. Logisense doesn't make its own AI model and not many companies will. I've heard some rumors that ChatGPT-5 is going to cost north of a billion dollars with a B to train that version of the model. That's a lot of GPUs cranking away to educate a large language model. Not every company is going to be able to spend a billion dollars to train their own model, nor will they have access to the information required to train the model.

Speaker 2 21:16

So take one off the shelf from the provider of your choice chat, gpt, microsoft, amazon, facebook, whomever it is and use this usage-based monetization platform and the telemetry it generates and has access to to prompt engineer your AI and make it smart enough to answer questions about your business in real time that would previously have taken conservatively a few minutes of human time to answer, but are conducted many times throughout the day, week, month, year. So that's where I start to get really excited. It's about making these AI models smart about your specific business with real data, and make them capable of automating real human tasks that are necessary to the function of a business, and doing so in a way which is pennies of electricity versus very expensive human time, and to do so accurately, with real data unique to your business.

Speaker 1 22:14

Wow, quite a mic drop moment. Well, I'm not sure we could probably end here. That was the takeaway, that's uh, but I do have more questions. But uh, really interesting opportunity for operational efficiency there. What about strategy? You know you talk to a service provider. They spend countless hours on on pricing strategies and modeling and, you know, talk about spreadsheets. You know you can't even begin to dissect how much effort goes into making something seem simple, but usually it's under the hood, it's not. How will this new usage based economy affect pricing strategy strategists and their job?

Speaker 2 22:54

I think, in a very similar fashion, in that up until today, it really is a human exercise.

Speaker 2 22:59

There's a lot of art and science that goes into pricing and a pricing team, a pricing office, and very few companies have dedicated pricing strategists. That's usually a big company game to have that level of expertise and to have a dedicated pricing office on staff. But even if you do have one of those, there's still art and science that goes into it. To be able to create effective pricing in an analytical fashion, you still need this data that I'm describing. It doesn't matter how many rows of one-time transactions you pipe into an Excel sheet or into a reporting engine without all of the contextual information supporting it, and then an engine like an AI language model to sit across it and infer the correlations necessary to come up with the right conclusions is inexpensive. It's hard to find those skill sets and it still is part art, part science. Today, when a large language model is fully empowered with this data around the monetization and specifics of your business, it can make inferences across a data set which is so large it is beyond the scope of human knowability.

Speaker 2 24:10

You're not counting on individual human brains to correlate a five petabyte data set of customer interactions, usage pricing, previous sales, sales pipelines and other information. No human being can keep that in their head, no matter how many pricing spreadsheets you've got. So become a very time-intensive, human labor and human brain intensive exercise to get to state-of-the-art pricing where, by using the usage telemetry out of a usage-based monetization system and combining it with the power of a large language model, ai, it can now start to make inferences across that vast data set, can explain to you why it's made them and because you're piping over information that is unique to your discrete business. In the approach that I'm advocating for and describing, the AI can start to make recommendations.

Speaker 2 24:59

Which product did customers purchase after they purchased product A? How long was it between the purchase of product B and product A? What did the monetization pattern look like just before product B was purchased? If we were to create a bundle, how many customers would have product A, b and C? And those are the types of questions that you can start to ask an AI to help provide that overarching visibility, to create those inferences that are beyond the scope of human intellect and knowability, because the data sets are so large and extract real value to help inform your pricing practice and then help inform the decisions that you're making, the products that you're creating, you're bundling, you're discounting behaviors. But you can't do any of that and you can't use a large language model to do any of that If you aren't furnishing it with the data from your discrete business to make it smart about you and your customers and your products.

Speaker 1 25:57

So well said. That was a great insight. I guess let's chat next about implementation. Where the rubber meets the road, rolling out this across. You know thousands, hundreds of thousands, millions of customers in a real-world environment. You work with hundreds of service providers around the world. About a decade-plus ago I worked at Oracle. You know implementing anything in these networks took a year or two and maybe millions of dollars. We've come a long way since then, but what are some of the opportunities to implement a usage-based model and what are the first one, two, three steps? I mean, how do you typically embark on a?

Speaker 2 26:52

transformational project like this, and how does one get started? And your customers, because a usage-based monetization system can monetize anything, whatever your heart desires, whatever your imagination can conceive of. It's very important that you understand where your customers perceive value from your product. And if you're selling kilowatts of electricity, it might not be kilowatts of electricity that customers care about. It might be that the lights are on or off. It might not be the kilometers traveled or the tonnage stored in transportation and logistics. If you're transporting a medical or a scientific cargo, you might care about the temperature. You might care about other factors.

Speaker 2 27:35

So, understanding what we call the value metric what you should be charging customers for might not be what your cost basis is built upon. And in the old timey days we would used to take the cost of the raw materials and labor and we would add a sensible margin to it and we would check that the competition was a little bit more expensive and we would settle in on that as being effective pricing. Whether or not the customer's perceived value in the cost of our raw resources plus a margin, they might not care at all about that. So, understanding where your customers see value that might be in our streaming services example, I see value when there's something in your catalog that I want to watch and I turn it on. So charge me for that, instead of a flat fee to pay for you to produce content that I'm not concerned with as an example. So understanding your value metric and understanding exactly what your customers see value from in your business and in your products is vital because that's going to become the centerpiece of how you build a usage-based monetization strategy.

Speaker 2 28:38

The second element I'll give a top two here is your own awareness of your enterprise architecture. Do you know where your data lives and is your data clean? And if it's not, even before you begin a usage-based monetization journey, these types of usage platforms can be useful in helping you to understand the data that resides within your own company. It's hygiene, whether or not it needs to be enriched, whether or not it needs to be deduplicated or transformed. And knowing how your business works from a technical perspective you think of sort of the traditional approach to enterprise architecture I would say is a vital number two in embarking upon this journey. And number one is understanding deeply your market, your customers and where your customers see value in your product, and then designing that architecture around that point.

Speaker 1 29:34

Understood. Well, you and your team at Logisense have a lot going on, to say the least. What are you looking forward to the rest of the summer into the fall season? I see you have a lot going on, to say the least. What are you looking forward to the rest of the summer into the fall season? I see you have a lot of events, meetings and other activities on the radar. What's what's next?

Speaker 2 29:49

We do got a lot of exciting things going on and I'm probably most looking forward to. We're hosting a forum this November in San Francisco called the Usage Economy Summit, and we're hoping to get thought leaders out.

Exploring the Usage Economy Summit

Speaker 2 30:01

We're hoping to get customers and partners to join us those in the industry X as a service providers out in the valley, come join us, and we want to get all of the best minds in the industry together to talk about this usage-based monetization transformation, to share experiences with each other, to share best practices and to elevate this knowledge I talk about in being able to identify your value metric, understanding what the wealth of data within your organization represents and how it can be used, in conjunction with tools like AI, large language models, to help drive your business into the future and ensure that you're capitalizing on these quickly emerging transformative technologies that are gracing the marketplace presently, and making sure that you're just not just caught up in a buzzword soup, but that you understand how you can practically apply these, and to share stories with other experts to really get the most out of this economic transformation that is happening.

Speaker 2 31:00

So I think I am most excited about the forthcoming usage economy summit and hopefully we'll have some of those watching this stream join us for that and learn a little bit more.

Speaker 1 31:11

That would be fantastic. Well, congratulations on all the success and innovation and leading the charge towards this new, brave new world we find ourselves in. Thanks so much, adam.

Speaker 2 31:22

Really appreciate it, Evan. Thank you.

Speaker 1 31:24

Thank you and thanks everyone for listening and watching. Take care.