From Clicks to Conversions: Pay Only for Measured Outcomes
Episode Summary
Clicking on software was an accident, not a destiny. Matthew Swanson, founder and CEO of Motion Enterprises, traces it to BASIC: the first computer interface asked people to type commands, the technology was not ready, and everyone fell back on graphical interfaces. Thirty years on, he thinks the first principles are worth revisiting, and his answer is that the natural interface is not clicking but talking. His agents sit on top of Salesforce and the rest of the marketing stack, translating natural language into clicks on behalf of employees and customers, and moving people through the customer life cycle from top of funnel to conversion. The second half turns to money. He prices the way he designs: come up with a KPI for a campaign, then charge only for measurable increments in it, rather than by the hour or by the seat.
Key takeaways
He scopes the work narrowly and explains the technology plainly, in the same breath. At Motion Enterprises agents are applied through customer lifecycle management, and what the Transformer really does, in his account, is decide what is the next best thing to do
The move he makes with that definition is to claim the enterprise is doing the same thing. Deciding what to do next is, at the end of the day, all any enterprise is trying to figure out as well, from the macro question of which customers to go after down to the individual, which is why he designs agents to take customers through each stage of a life cycle to maximize revenue
His contrast between the two interfaces is concrete. Today it is an interface you click on where you have to figure out these boxes; with Motion it is a service you speak with the way you would another person
The history he tells is the argument’s foundation, and it is a claim about accident rather than design. When BASIC came out the technology was not ready, so nobody could type all the commands and get what they wanted done, and everyone fell back to graphical user interfaces. Thirty years later he wants the first principles revisited, and his conclusion is that it is not clicking, it is talking
He positions the product as a layer rather than a replacement, using the stack’s own history as the analogy. Just as Salesforce and the other SaaS tools are a layer on top of databases, he sees the opportunity to layer on top of the SaaS tools
The mechanism underneath the conversation is unglamorous and he says so. Instead of employees clicking around software or customers working through navigation flows, the agents do it on their behalf, translating natural language into clicks
He looks at the life cycle holistically, and names a starting point rather than the starting point. A starting point for most organizations, he says, is the top of the funnel: reaching new customers, moving them into awareness, engagement and consideration, and ultimately into the purchase stage
His picture of where software is going is built on a word he chooses deliberately. The way he likes to look at the future of software, in his words, is as an anthropomorphic version of employees, designed the way you would train an employee on your best practices, your tools and the business processes your company follows
Onboarding starts with the agents reading the systems. They can now comb through an existing MarTech stack and get a pretty good lay of the land, which he calls pretty incredible
The second half of onboarding is conversational, and he says why. A bunch of nuance is stuck in people’s heads, so an orientation process is where the conversation really starts, and from there a user can ask for things like a new LinkedIn ad campaign aimed at a segment
Asked whether customers value the strategic view or the tactical execution, he redirects to a third answer. The place he sees people most excited is outcomes, a very numeric-driven relationship built on outcomes teams know lead to revenue, with the pricing model aligned there
The pricing mechanism is stated precisely enough to act on. They come up with a KPI for a given campaign, and they will only charge for measurable increments in that KPI
The reasoning behind the model is a claim about company valuation, which he flags as a bigger subject than the episode. His North Star is how you measure the value of a company, which he believes can be better broken down into incremental outcomes everyone can align on as known numerical KPIs. That is what takes him away from charging by the hour and traditional seat-based models
What actually moves a deal, in his account, is not the model but a specific wound. When a team has that burning pain point, his example being that they cannot get their MQLs to hop on the phone, a no-risk pay-on-performance model becomes very attractive
His advice to listeners is about the starting point rather than the technology. The biggest challenge he sees in the marketplace is getting started, and a great place to get started, in his words, is a use case you know already has an ROI model built around it
The habit he wants built comes before the capability. Getting your organization into the habit of measuring outcomes is what he says will pave the way for taking advantage of these new capabilities. He also asks for an open mind, and reaches for the last time you met a genuinely new technology, which he says does not come around every day: the first time you picked up an iPhone, or first touched a computer
He closes on the size of the change rather than the tactics. A paradigm shift is happening right now, he says, and we all need to think differently about how we run our businesses if we want to take advantage of agents
About Matthew Swanson
Matthew Swanson is the founder and CEO of Motion Enterprises, which applies AI agents to customer lifecycle management, taking people from the top of the funnel through awareness, engagement and consideration to purchase. Motion Enterprises is the trading name of Silicon Valley Software Group, the technology firm he founded. His argument on this episode is that clicking on software was an accident of history rather than a destiny, and that the natural interface is conversation. His company prices on the same principle: it comes up with a KPI for a campaign and charges only for measurable increments in it, rather than by the hour or by the seat.
In this episode
| 00:42 | Welcome, and who Matthew Swanson is |
| 01:33 | Customer lifecycle management, and the Transformer as deciding what to do next |
| 01:56 | What every enterprise is trying to figure out next |
| 02:36 | What would that look like |
| 02:51 | Clicking boxes, versus a service you speak with |
| 03:03 | A step back, and how interfaces came about |
| 03:26 | Why we click: BASIC, and the accident of the graphical interface |
| 04:07 | A layer on top of Salesforce and the SaaS tools |
| 04:20 | Translating natural language into clicks |
| 04:51 | Which parts of the customer life cycle this covers |
| 05:06 | Top of funnel through awareness, consideration and purchase |
| 06:31 | Sitting on top of the tools, and next to your employees |
| 07:01 | The future of software as an anthropomorphic version of employees |
| 07:34 | Do you train the agents, or do they learn by observing |
| 07:47 | Combing an existing MarTech stack during initialization |
| 08:03 | The nuance stuck in people’s heads, and the orientation conversation |
| 08:25 | What a former CMO would want to get out of it |
| 08:59 | Where people get most excited: outcomes |
| 09:43 | A KPI per campaign, and charging only for increments |
| 10:22 | Away from hourly and seat-based, toward incremental outcomes |
| 11:04 | What target customers say when the model is explained |
| 11:56 | The burning pain point, and MQLs who will not pick up |
| 12:21 | What listeners should take away |
| 12:36 | Where to start: a use case that already has an ROI model |
| 12:57 | Building the habit of measuring outcomes |
| 13:25 | The paradigm shift, and thinking differently about the business |
In Matthew’s words
“It’s an interface that you click on and you have to figure out these boxes, and with Motion, it’s a service that you speak with like you would another person.”
Matthew Swanson (02:51)
“We can revisit the first principles of what’s the best way to interact with software, and we think that it’s not clicking, it’s talking”
Matthew Swanson (03:26)
“Rather than charging by the hour and traditional seat base models, we’re starting from this, this level of, of measurable outcomes”
Matthew Swanson (10:22)
“The biggest challenge we’re seeing right now in the marketplace is getting started, finding that tangible use case”
Matthew Swanson (12:36)
Resources
Matthew Swanson
Matthew Swanson on LinkedIn: Where he posts, and the best place to follow his work on agents for customer lifecycle management
Motion Enterprises: Where he is founder and CEO, applying AI agents to customer lifecycle management. It is the trading name of Silicon Valley Software Group, the technology firm he founded, whose site the link goes to
Ideas and terms discussed
Customer lifecycle management: The scope he sets for his agents, and the reason the product is not a general assistant. Agents are designed to move a customer through each stage of a life cycle, from reaching someone new through awareness, engagement and consideration to purchase, with revenue as the measure
The Transformer as what to do next: His plain-language account of what the underlying technology does: it decides what is the next best thing to do. The move he makes with it is to say that this is also what an enterprise spends its time deciding, from which customers to pursue down to what an individual should do next
Not clicking, talking: The compression of his whole interface argument. Clicking became the way we use software because the first attempt failed, not because it was the right answer, and he thinks thirty years of progress is enough to revisit the question
The accident of the graphical interface: His history of how we got here. BASIC was the first interface for a computer, the technology was not ready for people to type commands and get what they wanted, so the industry fell back to graphical user interfaces. He presents this as contingent rather than inevitable
A layer on top of the SaaS tools: How he positions the product against the incumbents. SaaS tools are themselves a layer on top of databases, so he sees room for another layer above them. Underneath the conversation the work is mechanical: the agent translates natural language into clicks
An anthropomorphic version of employees: His design principle, and the phrase he uses for it. Agents are built the way an employee is trained, on the company’s best practices, its tools and the business processes it follows, and he describes them as sitting next to your employees rather than only on top of your tools
Initialization: The onboarding step, split into two halves. Agents comb an existing MarTech stack and get a pretty good lay of the land, which he calls pretty incredible, and then an orientation conversation captures the nuance that is stuck in people’s heads
Outcome-based pricing: The commercial half of the episode and the most unusual thing on this page. A KPI is set for a given campaign and the company charges only for measurable increments in it, replacing hourly billing and seat-based licensing. His reasoning runs through company valuation: if the value of a company can be broken into incremental outcomes, those are what everyone should align on
Paying only on performance: The form the pricing takes when a buyer meets it, and his account of when it lands. It is novel enough to need explaining, and what makes it attractive is a specific unmet need rather than the elegance of the model
Named on air
Salesforce: Named at 04:04 in the host’s question about whether this replaces it, and again in his answer at 04:07 as an example of a SaaS tool that is itself a layer on top of a database. His position is layer on top rather than replacement
HubSpot: Named by the host at 06:02, alongside Salesforce, in the question about what an agent layer would sit on. He accepts the framing at 06:31 and adds that it also sits next to your employees
Operator: Raised by the host at 04:35 as the closest familiar comparison, telling an agent what you want and having it do the clicking. At 04:44 he calls it a great first step in that direction and says they are basically sprinting in that direction
BASIC: His example at 03:26 of the first interface for a computer, and the starting point of his argument that graphical interfaces were a fallback rather than a design decision
Related AI Realized episodes and events
AI for Go-To-Market: The New Revenue Team Playbook: Jonathan Kvarfordt on how AI is rebuilding revenue teams, which is the organizational side of the change Swanson is selling into.
Agentic AI and Revenue Work: What Actually Pays Off: Christopher Penn on where agentic AI has actually produced revenue and how to measure it, which is the buyer-side counterpart to charging only for measured outcomes.
Zero to Campaign With Everyday AI, in Four Steps: Doug Bell on getting from nothing to a running campaign with everyday AI tools, which is the execution this page’s agents are meant to take over.
Frequently Asked Questions
-
Outcome-based pricing for AI software means setting a measurable target before the work starts and charging only for movement toward it. Matthew Swanson of Motion Enterprises describes the mechanism precisely: a KPI is set for a given campaign, and the company charges only for measurable increments in that KPI, in place of hourly billing or traditional seat-based licensing. His reasoning runs through company valuation, on the argument that the value of a company can be broken into incremental outcomes everyone can align on as known numerical KPIs.
Transcript 08:59 to 11:04
-
AI agents can replace the interface without replacing the software underneath, by taking the clicking on themselves. Matthew Swanson of Motion Enterprises reframes the question from sight to sound: he would almost say, what would it sound like, and the answer he wants is a conversation. Underneath, the mechanism is unglamorous. Instead of employees clicking around software or customers working through navigation flows, agents do it on their behalf, translating natural language into clicks.
Transcript 02:36 to 04:20
-
AI agents sit on top of systems like Salesforce and HubSpot rather than replacing them. Matthew Swanson of Motion Enterprises makes the analogy to the stack’s own history: SaaS tools are themselves a layer on top of databases, so he sees the opportunity to layer above the SaaS tools rather than compete with them. Asked directly whether it replaces Salesforce, he answers that he thinks of it as a layer on top, and adds that it also sits next to your employees rather than only above your tools.
Transcript 04:07 to 06:31
-
We click on software because the first attempt at a typed interface failed, not because clicking was the better design. Matthew Swanson of Motion Enterprises traces it to BASIC, which he calls the first interface for a computer: the technology was not ready for people to type all the commands and get what they wanted done, so the industry fell back to graphical user interfaces. His point is that this was an accident rather than a predefined destiny, and that thirty years on the question is worth reopening.
Transcript 03:03 to 03:26
-
AI agents learn existing workflows two ways at once, by reading the systems and by being told what the systems do not contain. Matthew Swanson of Motion Enterprises describes an initialization process in which agents comb through an existing MarTech stack and get a pretty good lay of the land, which he calls pretty incredible. The second half is conversational, because a bunch of nuance is stuck in people’s heads, so an orientation discussion is where the real work starts.
Transcript 07:34 to 08:25
-
Buyers react with interest and unfamiliarity in roughly equal measure, and what closes the gap is a specific unmet need. Matthew Swanson of Motion Enterprises says the model is novel, which is both a pro and a con, and that most organizations have not seen it at scale, so a lot of the conversation is education. What moves a deal along, in his account, is a burning pain point, his example being a team that cannot get its MQLs to pick up the phone, at which point a no-risk pay-on-performance model becomes very attractive.
Transcript 11:04 to 12:21
-
A starting point for most organizations is the top of the funnel, reaching new customers and moving them toward conversion. Matthew Swanson of Motion Enterprises is careful that this is a starting point rather than the starting point, since he says he looks at the life cycle holistically. The sequence he names runs into awareness, then engagement and consideration, and ultimately into the purchase stage.
Transcript 04:51 to 05:06
-
A use case that already has an ROI model built around it is a great place to get started. Matthew Swanson of Motion Enterprises uses that phrase for it, and names getting started as the biggest challenge he sees in the marketplace, and treats an existing ROI model as the qualifier that makes a use case a good first one. He pairs it with a habit rather than a technology: getting an organization used to measuring outcomes is what he says paves the way for taking advantage of the new capabilities.
Transcript 12:21 to 13:25
-
[00:42] Christina Ellwood: Welcome to AI Realized, the podcast for executives leading AI deployments. From addressing security, data, and operations challenges to managing the organizational changes, AI deployment presents the opportunity to redesign our organizations from the inside out. I'm Christina Ellwood, your host for today's episode, and today we're talking with Matthew Swanson, the founder and CEO of Motion Enterprises. Welcome, Matthew.
[01:09] Matthew Swanson: Hello, Christina. Glad to be here.
[01:11] Christina Ellwood: I am very excited for our conversation today because a lot has changed since the last time we talked. I would l- wonder if you would tell me a little bit about Motion Enterprises and how agents factor into your design.
[01:24] Matthew Swanson: Right. Yeah. Well, there has been a lot of development since the October conference, and the big topic is, of course, AI. And that's a trend that has been building for some time. The way we're applying agents at Motion Enterprises is through customer lifecycle management. So the way we like to think of it is, this really powerful technology just came out called the Transformer, and all it really does is decide what's the next best thing to do. But that's, at the end of the day, all any enterprise is trying to figure out as well. From a macro perspective, how do we as a company go after our next best customers, all the way to the individuals. Everyone's trying to figure out what to do next, and so that's how we are applying agents. We're designing agents that can take customers through each stage of a life cycle to maximize revenue.
[02:20] Christina Ellwood: So the agents are actually interacting with the customers in my funnel?
[02:25] Matthew Swanson: With customers and employees, and that's the key difference, is the human connection, the more natural interface that we're providing through these agents.
[02:36] Christina Ellwood: So what would that look like?
[02:39] Matthew Swanson: I would almost say, what would it sound like? And it would sound like a conversation, and that's the paradigm shift that we're helping companies navigate, which is today, you're right, it would be what it, what does it look like? It's an interface that you click on and you have to figure out these boxes, and with Motion, it's a service that you speak with like you would another person.
[03:00] Christina Ellwood: Gotcha. So it's replacing the UI.
[03:03] Matthew Swanson: Yeah, it is. And just as a, a quick tangent, because it's actually really important to sometimes take yourself out, step back for a second and look from the top down, and if you think of the way that interfaces came about, it wasn't some sort of predefined destiny that we would be clicking on software. It was an accident. It was because when BASIC came out, the first interface for a computer, the technology wasn't ready. You couldn't type all the commands and get what you wanted done, so we fell back to graphical user interfaces. And now, 30 years later, we can revisit the first principles of what's the best way to interact with software, and we think that it's not clicking, it's talking.
[03:51] Christina Ellwood: So if I were using your product, I would be talking to it as a marketer, or I would be talking to it as a customer of the Motion Enterprises customer. Is that right?
[04:03] Matthew Swanson: Correct.
[04:04] Christina Ellwood: Is it a replacement for something like Salesforce?
[04:07] Matthew Swanson: We think of it as a layer on top. Just like Salesforce and all the SaaS tools out there are a layer on top of databases, we see the opportunity to layer on top of SaaS tools. And so instead of having employees click around software or customers going through all these navigation flows, the agents can do that on behalf of people, translating natural language into clicks.
[04:35] Christina Ellwood: Okay. I gotcha. So it's I think of that as how Operator works, that I tell it what I want it to do and it does the clicking for me. Is that right?
[04:44] Matthew Swanson: I think Operator is a great first step in that direction, and we're basically sprinting in that direction.
[04:51] Christina Ellwood: I see. Okay, and you're specifically focused on the customer life cycle, so the initial sale, the upsell, cross-sell, and the end of life. Is that right?
[05:02] Matthew Swanson: We do look at the life cycle holistically. A starting point for most organizations is top of funnel, so finding ways to reach new customers, finding ways to move them into awareness stages, consi- engagement consideration, and ultimately into the purchase stage.
[05:23] Christina Ellwood: So in the marketing organization, who would be your user?
[05:28] Matthew Swanson: We service the department as a whole, and it is a team activity. So just in the same way that marketing teams have a CMO who's thinking strategically and really designing as best as they can crisp prompts for the rest of their team, we're integrated into that flow under the CMO and alongside the individual contributors across the marketing roles to assist with tasks.
[06:02] Christina Ellwood: So can I think of it as an agent layer on top of the existing systems we're using in marketing, or we could pick sales or some other group if you prefer, but it would sit, say, on top of our HubSpot or Salesforce or Insight or whatever system we're using for our workflow? Would these-- Would your system sit on top as an agentic layer providing that verbal interface and the, the clicking, if you will, by the agent instead of the people?
[06:31] Matthew Swanson: Yeah, I would say it's, it-- Yes, it's sitting on top of all those tools, and another way to look at it, it's sitting next to your employees.
[06:40] Christina Ellwood: Okay. And so w- talk to me a bit about how you envision this stack looking. You mentioned agents and the database and the APIs. Maybe you could just describe how you envision the agent architecture looking against our existing systems and teams.
[07:01] Matthew Swanson: The way we like to look at the future of software is as a anthropomorphic version of employees. And so what we mean by that is just in the same way you would train an employee on your best practices, on your tools, on the business processes that your company follows to move customers through a life cycle, that's how we're designing the components of our agents.
[07:34] Christina Ellwood: Okay. Does that mean that if I were a customer, that I would train those agents on our existing workflows, or do the agents observe what we do and learn from observing?
[07:47] Matthew Swanson: It's both. We go through a initialization process where it's pretty incredible how agents can now comb through an existing MarTech stack and get a pretty good lay of the land. But at the end of the day, it-- there's a bunch of nuance that's stuck in people's heads, and so that's where the conversation really starts, like an orientation process, and then you can start asking all sorts of things. "I'd like to create a new LinkedIn ad campaign to reach this segment of customers," et cetera.
[08:25] Christina Ellwood: I see. Actually, as a former CMO, I would just like to be able to know what the actual flow is that people are following, because often that can be challenging. That would identify tools we're not really using or we're barely using. It would identify places where we have friction. I could see a lot of things that you would provide that would be valuable to the strategy elements. Are you finding that's an area that people are deriving value from your system, or are they primarily deriving value from being able to do better the, do better do the things that we're already doing tactically?
[08:59] Matthew Swanson: The place where we see people most excited is outcomes. It's being able to have a just very numeric-driven relationship where we can accomplish outcomes that teams know lead to revenue and align our pricing model there. Um, and everything else is nice to have in our, in, in our experience.
[09:31] Christina Ellwood: Oh, I see. So I'm able to tell you, "I want to reach this audience with this budget in this channel," and then you charge me based on the success of that- outcome?
[09:43] Matthew Swanson: That's right. We will come up with a KPI for a given campaign, and we will only charge for measurable increments in that KPI.
[09:56] Christina Ellwood: That's a very different business model than we're enjoying today from most software providers. How did you come up with that, and what's the, what's your thought process behind why that's the ideal model for this go-to-market?
[10:12] Matthew Swanson: It's really looking at first principles of where we're heading at in the future of work, aligning on outcomes. And it's, this is probably a much bigger subject for a different day, but the North Star for us is how do you measure the value of a company? And we believe that can be better broken down through incremental outcomes where everyone in the organization can align on known numerical KPIs. So we wanna align with the long-term trends, and we're starting, rather than charging by the hour and traditional seat base models, we're starting from this, this level of, of measurable outcomes.
[11:04] Christina Ellwood: And what are you hearing from target customers when you explain your model to them?
[11:09] Matthew Swanson: It's, it's novel and which is pro and a con. It always gets a ears perk q- question marks, "Wait, tell me more." But it is an unfamiliar territory. Most organizations haven't seen this model at scale. There's definitely a lot of education type of discussions going on.
[11:31] Christina Ellwood: Yeah. I would think you've got agents which are new, you've got a business model that is new, and you're a new company. I would think those are all things that are creating, uh, a different flow in the sales conversation. Where are you finding the greatest receptivity to your story?
[11:50] Matthew Swanson: Honestly, it's as specific as we can get about use cases. So it's important to be able to lay the groundwork and give confidence to teams that the model's gonna scale. But at the end of the day, what moves the ball along is when you have that burning pain point and, "Oh, we just cannot get our MQLs to hop on the phone." Okay, a no risk, no pure paid on performance model, that becomes very attractive.
[12:21] Christina Ellwood: Gotcha. Gotcha. So for our listeners, what would you recommend that they take away from our conversation about agents and about using them in the customer life cycle?
[12:36] Matthew Swanson: Yeah. I think the biggest challenge we're seeing right now in the marketplace is getting started, finding that tangible use case. Setting up a use case that you know you already have an ROI model built around is a great place to get started. Getting your organization in the habit of measuring outcomes is going to pave the way for taking advantage of these new capabilities. And just keep an open mind that try to remember the last time you interacted with a novel technology. These don't come around every day. But think about the first time you picked up a, an iPhone or the first time you touched a computer, if you can remember that far back. That's the sort of paradigm shift that's happening right now, and we all need to think differently about how we run our businesses if we wanna take advantage of agents.
[13:34] Christina Ellwood: Makes good sense. So Matthew Swanson, CEO and founder of Motion Enterprises, thank you so much for joining me today on AI Realized.
[13:45] Matthew Swanson: This was fun. Thanks for the great questions.