How to Price Your SaaS Product in the Age of AI

Sarah Elkins (00:00)
Welcome to Between Product and Partnerships, a podcast focused on bringing together product, partnership, and engineering leaders to discuss how to build, support, and scale SaaS ecosystems. This podcast is presented by Pandium, an integration platform for building native integrations.

Cristina Flaschen (00:19)
Hi everyone, and thanks for listening to our podcast Between Product and Partnerships, where we talk about the challenges and what it takes to build integrations, tech partnerships, and SaaS platforms more generally. And today we are so excited to have Roee Hartuv from Willingness to Pay join our podcast. Can you tell us a little bit about yourself and your background?

Roee Hartuv (00:39)
Yeah, let's start with the background. I started off in software sales. At some point I  decided that I no longer want to chase quotas and chase my team members to chase quotas.  I focused on processes and that's the area that I wanted to develop further and there

I became an advisor, go-to-market advisor, did that for a few years, and then found what I believe is the number one growth levers any software company has, which is pricing and packaging. And that is what I've been doing for the last two years, focusing strictly on that. Yeah, that's about me.

Cristina Flaschen (01:26)
I feel like pricing is a hot topic right now for a lot of reasons. I'm curious, what like stage companies do you typically work with?

Roee Hartuv (01:34)
Companies

that have already a motion in place. So they have customers, they know what works, they know the value of their products that allows us to actually tailor and refine their  pricing and packaging anywhere between a few tens of millions all the way to a few hundreds. Biggest is a billion dollar company  ARR-wise.

Cristina Flaschen (01:56)
Awesome. So you've seen all different all different stages. And yeah, I think pricing is a hot topic right now, especially with AI and some of the sort of like volatility around tokens and things like that. So maybe we'll start right there. What do you think has changed now that their AI is in the mix when it comes to SaaS pricing? And we'll just we'll just pretend that SaaS still exists for which which I think it does for this conversation.

Roee Hartuv (02:00)
Yes.

Yeah. Yeah. ⁓

What changes that all of a sudden the cost to serve our customers is no longer almost zero. If you think about it,  the marginal cost to serve the one hundred customer or the ten thousand customer in SaaS it's basically A it's the same, and in most cases it's almost zero.

And that's the game of SaaS, right? We develop one software and sell it, and just everybody gets access to the same platform. However, AI comes with a cost, and that completely changes how companies  define their monetization strategy. Because all of a sudden

yeah, again, marginal cost is no longer zero. Some say with AI it could be on an average 50%. Now the numbers keep on changing and AI is getting cheaper, et cetera. But it comes with a dramatic cost. Now, unlike SaaS, where not only was it close to zero, all the customers' cost to serve was pretty much the same.

Everybody used the platform. You might have different storage, different compute power, but that was  minimal. With AI, you might have superusers that are using the product 10, 20, 50 times more than the average customer. So all that completely changes how companies need to think about their pricing and monetization strategy in general.

Cristina Flaschen (03:55)
How do you advise folks think about like the unit economics and the margins in a world where both I feel like the hard costs as you're referencing can sort of increase at will? And also the usage price becomes, as you mentioned, like an important vector versus just like, you know, it's sort of an all-you-can-eat thing, as you mentioned, with a lot of SaaS. Like how should companies think about even starting to think about the unit economics?

Roee Hartuv (04:22)
So that's the point. They need to start thinking about the unit economics. Because in most cases, when when I come in and ask, like, what's what's your cost to serve? What's the unit economics of serving a customer or a segment, etc.? And usually they don't know. In some cases, they can extract from finance what is the cost of the CSM team. It is never done on a customer level. It is never done by

Cristina Flaschen (04:44)
Mm-hmm.

Roee Hartuv (04:51)
A) another metric that is not the total cost of where maybe our claw our AWS costs and CSM costs. So, first of all, that's start off with that. The need to understand what is the unit economics. And then we need to be able to measure that on an account and in some cases on a user level.

'Cause we'll maybe we'll get to that, but we eventually need to price on it. But anyway, we need to measure that and a lot of cases even in real time. And the best companies out there that are yes, excuse my language, but are AI native. So it's not the traditional SaaS companies that

Cristina Flaschen (05:20)
Mm-hmm.

Mm-hmm.

Roee Hartuv (05:39)
added AI capabilities, but there are ... AI companies that grew as an AI solution, they have it already baked in. So mostly the challenges for the SaaS companies that are now introducing AI that never thought about unit economics now need to change how they operate.

Cristina Flaschen (05:47)
Mm-hmm.

And I'm curious, like it sounds like if you're thinking about it even down to like the user level, there's a lot of  input or there would be a lot of input from product as well. It's not just like a go-to-market necessarily like, we'll just price based on what the market will will bear. Who do you think ultimately should own a pricing strategy?

Roee Hartuv (06:21)
Everybody. ... Yeah, of course when you say everybody, that means nobody, but somebody needs to own pricing and packaging. It doesn't matter if that somebody sits under finance or sits under  commercial or sits under product or marketing, product marketing. At the end of the day, we need inputs from all these different groups within the organization because pricing and packaging touches everything.

Cristina Flaschen (06:22)
Great answer.

Roee Hartuv (06:48)
It touches how product built, the roadmap, how they measure the usage that we just talked about. Commercial, of course, makes sense. Like the the we need to understand the value and how to sell that value to customers. Finance. We need to be able to understand what that that means to forecast what's going to be the revenue moving forward.

Cristina Flaschen (06:53)
Mm-hmm.

Roee Hartuv (07:08)
And  marketing, of course, marketing traditionally marketing used to own pricing and packaging. I still that I think  it's still valid for companies that have very strong product marketing  roles. But yeah, everybody needs to come to the same table and make decisions and own pricing and packaging.

Cristina Flaschen (07:29)
I'm curious what you how you think companies should approach historically having like maybe annual or multi-year sort of all-you-can eat kind of contracts in a world where now consumption is variable and your costs are also variable, right? Like we don't actually even know how much tokens and stuff are gonna cost a year from now. So do you still think that multi-year contracts fixed

Roee Hartuv (07:54)
Yeah.

Cristina Flaschen (07:58)
Fixed fees like have a place? How do you I'm sure it depends on the company, but I'm just curious like how you think about advising folks through that.

Roee Hartuv (08:07)
So the first thing to look

is our is our

is our cost variable? So does it change? And in most likely when you do AI, it does change. It does change from user, from time of the year, et cetera. And in that that case, most likely you we need to tie our pricing to the cost. That means that we can no longer do fix or per seat or

yeah, that type of model that no longer in a lot of cases no longer holds. Usage, as you mentioned, is probably the right way to go, but I think a hybrid approach. So creating some sort of fix that will create that  forecasting capabilities that we have, you we know we're going to get this on a monthly basis, and then allowing based on usage, some sort of variable

Cristina Flaschen (08:56)
Mm-hmm.

Roee Hartuv (09:04)
cost or pricing that goes up and down based on the usage. So I think that's the way to go. You also mentioned multi-year. I think the duration does not necessarily change if we adopt this model. However, from a pure pricing, this is I'm putting my pricing  hat compared to my sales background.

Cristina Flaschen (09:25)
Yeah.

Roee Hartuv (09:30)
As sales commercial, we always like to do multi-year contracting because it secures the  contract and the customer for longer time. From a pricing point of view, I always advise not to do multi-year because you want to be able to flex, especially nowadays when everybody's learning. We as you said, I don't we don't know what is going to be the cost. We don't know the usage patterns, we don't know who the users are and how will they use our AI capabilities. I would recommend to leave a room to change

Cristina Flaschen (09:52)
Mm-hmm.

Roee Hartuv (09:59)
pricing and maybe even the models every contract period, every year, and not to lock ourselves in into a commercial engagement that causes us to lose money for two to three years because we haven't really anticipated how much usage and how much cost is associated with that account.

Cristina Flaschen (10:21)
Yeah, I guess depending on like what the model companies end up doing. And if you're running your own, it's obviously different. But  I would imagine until they come up with like  a  fixed fee, all you can eat kind of  pricing structure, it'd be very hard to have your own product

mimic that or or have that unless your margins are huge, right? If you could just absorb it, but that's, as we're mentioning, not really the case when you actually have like material costs to supporting folks now, which is it's just wild. I mean, I've been in tech for a long time and like I remember when compute was expensive, when you had server racks and stuff, but it hasn't been like that in so long. And also you can switch between  cloud providers if you need to, but there really isn't even like a material change in cost typically. Like we've kind of

normalized and like zeroed in on this is what things cost. And we're really at a new frontier, I feel like, with the with AI tokens or however it's gonna end up being metered in whatever way they end up deciding.

Roee Hartuv (11:17)
Yeah. Exactly.

Cristina Flaschen (11:21)
So one kind of hot topic that I've seen percolating around on LinkedIn mostly, because that's where I spend too much time, is pricing based on outcomes versus based on value. And my own brain, when I start thinking about this like too deeply, it becomes very meta. And I'm like, all of these things can kind of be traced back to value and outcome. But I'm curious how you distinguish between value based pricing and outcome based pricing.

Roee Hartuv (11:51)
Yeah. We can have one without the other or we can have both. Let's talk about outcome. Outcome-based pricing is the holy grail. Like from a customer, I pay only for outcomes. I don't pay for for all the inputs and everything that I need to have in order to get to that outcome. That is fantastic.

However, in real life, it's very, very difficult. Because what is an outcome? You might decide that one outcome is what how your company, but your customers will see the outcomes different. You might have different levels of outcome.

So a ticket closed, yeah, that's that's something that happens quite a lot. If a ticket closes, yeah, if I'm creating an AI agent that supports tickets, right? A ticket closed. What happens if the ticket reopens? What happens if the customer if it is closed, but the customer is not satisfied, etc. etc. So there's a lot of caveats and and things to watch out for.

Cristina Flaschen (12:53)
Mm-hmm.

Roee Hartuv (13:03)
Outcome based, let's take open AI. Open AI don't they cannot do outcome based pricing. So we're all  paying twenty, or if you're you're a heavy user,  I don't know, it's like a hundred dollars or two hundred dollars the next year, that's flat. And you pay per seat.

They are a vertical solution. So you and ... you and I, or let's take a very extreme example, myself and my mother. I probably I use it as an advisor. I do financial forecasting and and a very  deep Excel that would have  required an analyst to sit an entire week to do the analysis that I asked Claude to spit out in in just a few minutes.

That's my use case, that's my outcome. I get a lot of value out of it. But my mother that uses it to check out new recipes and how to do  Italian style kitchen cooking might get a different outcome. The value for me is maybe one week's work of an analyst that is very expensive compared to my mother that could have just Googled it and and found a  solution in

Cristina Flaschen (13:51)
Mm-hmm.

Roee Hartuv (14:13)
20 seconds. So the value there, the outcome is totally different. So how do you price where the  the outcome is completely different? So that's outcome. Value base, I think that's also something that we can do. And it's just aligning in how you price and how you package your solutions to what the customer is actually considered what value is. And I think that is in a lot of cases doable.

And that is what companies need to

try to do.

Cristina Flaschen (14:44)
So it sounds like you were talking a little bit about efficiency, right? When you're thinking about not having to hire an analyst or you not being the analyst or whatever. And I know efficiency can be a challenging thing to prove. So I'm curious, but and yet there's still a ton of software where their value that they purport is efficiency, or you know, underneath it, the value really is efficiency. So I'm curious how you think about pricing based on efficiency.

how it compares to value based pricing and if there are places where efficiency based pricing or cost savings are more effective than others. I know it's it's a  again, it's sort of like six of one half a dozen of the other, but the positioning I think is important.

Roee Hartuv (15:25)
Yeah.

It's a tough one. Especially when that efficiency gain is not clearly understood by the client. So as salespeople, again, coming from my my background, talking about cost saving efficiency is as you usually get it on risk reduction, also very hard to quantify.

Cristina Flaschen (15:47)
Mm-hmm.

Roee Hartuv (15:49)
It's hard to do the sale because you need to educate the customer, you need to use or the prospect, and you used to you need to use a lot of examples of other companies or other people in their situation. What was the results for them? From a pricing perspective, this is where I would come in and do a willingness to pay analysis. So I would  talk to customers.

What is the value that they actually provide? Now, hopefully they know. And you can come in. I had a customer, we did a manufacturing management, manufacturing floor management system. And before that they used Excel and with their platform, machine uptime was increased by this amount.

It was hard for their customers to connect that uptime to the actual software. And again, we we had to do a lot of interviews to try to capture what that meant. That's the only way to do that. So to learn to talk to your customers to really understand what is the value gain, what is the efficiency gain. It might be in time. Eventually we need to  narrow it down to costs or to dollars. And then yeah.

Cristina Flaschen (17:06)
Mm-hmm.

Roee Hartuv (17:10)
try to price based on that and yeah we need to go into that consultative type of sales mode in order to try to articulate or have the prospect envision what is going to be the  efficiency gains.

Cristina Flaschen (17:27)
Yeah, I think it it's also challenging when you are like tech for tech or you're working in environments where companies are adopting a lot of technology because it's they often are not gonna have consistent data to compare to, right? Like, the manufacturing, I have a background in like ERP and manufacturing  consulting. And I actually feel like

That is one of the places where you can have that amount of data. Like if you're walking into a site, a factory floor that's been running for 20 years, you actually can see year over year in five-year chunks, like the efficiency of building that widget. But in most environments, you're not even able really to compare quarter over quarter sometimes because the people are changing, the tech is changing, the market.

Roee Hartuv (18:06)
Yeah. Yeah.

Cristina Flaschen (18:10)
Especially now the market is really volatile. ⁓ so I think it is challenging to be like, we're gonna save you time, and then as an operator, you're looking and like save me time from what? Like from last month? Like, well, we're already saving time doing all these other things. And I think, you know, AI being sprinkled in is an interesting challenge because a lot of the benefit is nominally supposed to be efficiency.

But then are you making trade offs in other places? And like how much of that efficiency would you have seen anyway without the it's just there's so much going on with a lot of that.

Roee Hartuv (18:44)
Yeah. I I think AI

I I think we're in a pivotal moment of AI and maybe we're all

Cristina Flaschen (18:54)
Yeah.

Roee Hartuv (18:54)
There are some companies

out there that have started to realize that, okay, we're past that hype, hype  of AI. And what is the real efficiencies? I think it was Uber CEO, two, three weeks ago, said something along. We have used and I don't know the numbers of AI across Uber, and we have ne we haven't really seen any efficiency gains. So

Cristina Flaschen (19:15)
Mm-hmm.

Roee Hartuv (19:21)
that is an example of an industry, the industry right now that companies are starting to realize we have spent so much on AI and their ROI, the gains that we were promised or we targeted did not achieve those targets. So it's a great example.

Cristina Flaschen (19:41)
Yeah, and I feel like there's just like a natural life cycle that you have to wait through, right? Like AI is is fun in this way because like you get that dopamine hit really fast. It like does a thing immediately, basically. And like that can feel really powerful, but like the sort of downstream impact of that can take weeks, months, maybe even years to really show up. Like, especially when you're looking at really large companies who do have that data, they're gonna want to look at at year end.

And see, like, you know, where were we from a product perspective, financially, whatever? And that can be during that entire period of time, you're spending money, right? To use these products. So I agree. I think we're like, we're looking, we're seeing right now the early adopters that went all in are starting to get that early data. And it'll be interesting to see where folks land. And also a lot of that is really hard again to  measure. Like, how do you measure

engineering efficiency. Like, sure, you could pick like lines of code or pull requests or defect rate, but like what was your defect rate last year at this time? Did you have the same amount of people? Was it the same products? Was it the exact same humans? Like, it's so I think it measuring those types of gains is really like a nuanced thing. And I think I posted on LinkedIn recently about how like I feel like there's gonna be a bunch of SaaS products that pop up that are like measuring the

efficiency per token and I'm really interested to see like what rubric they come up with. Like what is efficiency? To anybody, you know? Like you know it when you see it, but like I don't I don't know what the magic numbers are, you know. I don't know if you have thoughts, it's kind of far afield, but.

Roee Hartuv (21:18)
So again, coming back to the Uber example, the CFOs and CEOs,  when you look at a really high level and you have  like enough data. So there they just did, okay. So we spent this amount of money with AI in the last, I don't know what what was the period that they checked. How many new products? What's time to market? How did that improve time to market and the amount of features and functionalities that we're launching?

Cristina Flaschen (21:21)
Yeah, yeah.

Roee Hartuv (21:46)
They hardly saw any any effect. So when you look at it at a really high level, you can make those calls.

Cristina Flaschen (21:54)
Yeah, And I think Uber is a good example of a business that's been around, I don't know how many years it feels like it's a part of my like everyday life, but it's been around a decent amount of time. And it's been relatively static, right? Like they've brought in new features here and there, Uber Eats like all this stuff, like last mile delivery. But like the core value of the product has stayed pretty consistent. So I would totally expect to see that they could be really good at determining what those gains are.  I do think that

Roee Hartuv (22:00)
Yeah.

Yeah, mm-hmm, mm-hmm.

Cristina Flaschen (22:22)
God bless Uber for coming out and saying and saying it right on record. Cause I do think we're still in this like cycle of the like good money after bad to a certain extent, where like companies may not want to say that out loud quite yet, even if they're starting to get those inclinations. But  yeah, it'll be interesting to see over the next like, especially for public companies, because we can they have to report some of this stuff  to see what happens. But I could go on for forever about these things.

I am curious. This is sort of in along the same lines of  the AI spend. We've seen over the past few months a handful of these kind of large big fish companies like HubSpot and ServiceNow, Workday's another one. SAP did this too, I think. Where they're starting to provide some metering on agents for

external parties. So to my mind, like they want to both minimize like the technical overhead on their side and also try to capitalize on folks using agents and also potentially try to push people into more traditional integration methods because maybe it's less less difficult for their own internal systems. But do you have any thoughts on that as like a model? Do you think other companies are going to go in that direction where they're like, hey, if you want to hook up an agent to service now, like you got to pay extra for that.

Roee Hartuv (23:40)
Yeah, obviously that's that's  value there, right? That's value there and they are trying to see what else they can extract from that. And we will see more and more companies  that are going to do that. So that that API gateways and and all that there's value to capture there and that's that's why we're why they're doing it. So of course.

Cristina Flaschen (24:01)
Mm-hmm.

Do think people are gonna pay it? I mean, you'll have to pay it if you want to use it, but do you think and I ask this with the caveat that charging for API calls is more like my traditional world. And that's been a bumpy road. Like only a few companies have really been able to get away with charging their partners and then the partner, you know, eventually passes it down to the consumer for API access or a or like per request or something. It's it's really not.

Roee Hartuv (24:15)
Mm, yeah.

Cristina Flaschen (24:32)
It's tough to get folks to do that, but agents are much like snazzier looking, I think, than just API access. So I'm curious if you think folks are gonna do it.

Roee Hartuv (24:40)
So  the use case that I see

happening and I don't know if that that's your your what you mean by that but I see companies that you do you don't need to use our interface you don't need to use our AI capabilities bring your own AI like bring your own agents the agents that you've built to your organization and just hook up

Cristina Flaschen (25:01)
Mm-hmm.

Roee Hartuv (25:03)
to our services, to our data, the data that is yours in our platforms, et cetera. And yeah, it's the same, it's it's the same thing as you said, like trying to capture the value from there instead of you have to use our interfaces. So I think it makes sense.

Let's see let's see how the market reacts. But I do feel that it sounds fair from a consumer or from a customer perspective that you would charge for that.

Cristina Flaschen (25:38)
Yeah, I I agree. I mean, I think it is, it's like the value-based kind of kind of pricing. I I just wonder, and I don't have a strong opinion, but like if you're a company that uses workday and you already have like a hundred seats and folks are logging in, like, are you as the business then going to want to pay an additional X dollars per agent or per agent request to get access to that same data? Are you just gonna say and then like maybe cancel seats, or are you just gonna say like,

Roee Hartuv (25:59)
Mm-hmm.

Cristina Flaschen (26:05)
Hey Cristina, just go log in and pull your own time card. Like, we're not gonna have you chat your way there. I don't know. And I also don't know what the cost is. It could be like at this stage so incremental to get folks hooked into it, which would make sense to me. But I it's just like an interesting shift.

Roee Hartuv (26:21)
But let's take Salesforce, for example, the reason that they're doing this is because they understand that they will have the traditional market is seed-based or the traditional strategy is seed-based. And they understand that AI will replace some of those seats. So they need they are looking to find ways to capture or to keep the revenue that they're getting from their customers. So that's that's what they're doing. And I think more will follow.

Cristina Flaschen (26:50)
It's so funny. It's like six, again, it's like six of one, half dozen of the other. We're like slicing and dicing like a lot of similar kinds of like the use cases at the end of the day are this are similar, right? It's like the person using Salesforce still wants to get to the customer record in Salesforce, but figuring out ways to like creatively both add value and then, as you said, try to like extract as much

Roee Hartuv (27:10)
Mm-hmm.

Cristina Flaschen (27:12)
as the market will allow, which is what pricing is all about, right? Like any entrepreneur and anybody that runs a business or works in sales knows that like you're trying to hit that sweet spot of like, what will the market accept for this cost to align with what they're getting out of it? It sounds, I think when I say it out loud, it feels kind of gross, but that is really like what pricing is, right? Like it's being competitive, and speaking of, so to bring it back to my neck of the woods.

Roee Hartuv (27:21)
Bring.

Yep. Yep.

Cristina Flaschen (27:39)
integration related stuff. I think pricing for integrations, and this kind of goes with agents, which are themselves a kind of integration, but if we think about more traditional integrations as like data transfer between two SaaS products, there's always a conversation about like the unit economics of integrations, depending on how much your customers pay you, and then whether or not it's something that should just be included in your product fee, should be a premier feature in an enterprise tier, or

something that you just offer for free given your industry. Like, how do you do you run into those types of questions when you're talking about pricing strategy, especially for the companies that are the size that you work with? and how would you advise folks to like think about that when they're running a B2B software company, maybe like a mid-size, maybe not billions of dollars in revenue, but you know, a few million bucks and up?

Roee Hartuv (28:29)
So back to your earlier point, it might sound gross, but yeah, monetize it as much as you can. However, you do have some use cases or verticals that it sounds funny to  charge for those connectors. For example, might be a simple example. I'm currently working with a marketing automation platform. So they send emails out or or

SMS, WhatsApp kind of messages. that type of

platform solution needs to connect to your CRM database. There's no way around it. For them to say, hey, we're charging the platform, and if you need to connect it to Salesforce, you need to pay us, I don't know, $500 a month, it sounds stupid. And they're they're giving it away for free.

Cristina Flaschen (29:06)
Yeah.

Roee Hartuv (29:22)
So that is that is how I I think about it. So basically we do want to charge, but every everything that is already commoditized, that is basic, then you just give. Usually you give assuming that there's no adaptation and no strict maintenance because everybody connects to Salesforce nowadays.

It's not

⁓ specifically built for a use case, etc. So yeah.

Cristina Flaschen (29:50)
How do you think about that with like PLG or freemium type products?

Roee Hartuv (29:55)
⁓ that's that's

where it gets ⁓ tricky, right? So so freemium again  generally speaking, and I put that under  the context of freemium.

Freemium usually does have a certain cost to the company. And the question is how much cost are you willing to bear?

Cristina Flaschen (30:11)
Mm-hmm.

Roee Hartuv (30:18)
How much money are you generating for your paying customers, etc.? And that's that's like a balance, right? So it's the same type I put it on the same kind of bucket. How much does it cost you to maintain that API to make those connections? And do you have enough revenue for your paying customers, or can you justify the conversion of free to paid in order to subsidize those those freemium accounts?

Generally speaking, again, at some point you want to create different features that are only available on the paid. gut feeling again with talking like all the different use cases out there without going into details. I feel that usually connections integration justify a monthly pay. But again, that's the general kind of

Cristina Flaschen (30:52)
Mm-hmm.

Yeah, I'm I'm with you. I think I think it's much easier to bundle integrations into like a feature set versus trying to charge like for Salesforce, it's twenty dollars a month for, you know, QuickBooks, it's thirty dollars a month. Just say like if you're enterprise, you get 10 or you win unlimited or whatever it is. And I also to  your point about like the vertical in the industry, there are like some industries where like that Salesforce connection, you just have to have it. If you don't have it, you're not competitive.

Roee Hartuv (31:24)
Yeah.

Cristina Flaschen (31:40)
And if you are a product that like requires these connections, then you just have to bake it in and maybe freemium is not the the right move for you because there is an overhead cost to that, right? Like if you're doing like email

if you're doing email deliverability as a service or something, like those email addresses need to go somewhere and come from somewhere and like your product is not really useful unless you're getting those addresses from somewhere. And in that instance it's like you just have to do it and just eat it, but it is interesting how folks think about it. And I've definitely worked with companies that charge thousands of dollars for these connections a month.

Because they're working with like million dollar contracts and like they figured out that hey, that like SAP connector, these companies that use SAP are used to paying for this and like they will pay for it. So it is like a kind of a delicate dance, I think, and requires some more nuanced and specialized knowledge about your customer and the market that you operate in.

Roee Hartuv (32:41)
Yeah.

Interesting that you're bringing SAP, because usually SAP I would also advise, hey, SAP connectors, this is your world, not mine, but usually it comes with a lot of complexity. It's SAP, right? it usually is tied to emission critical software. So the SLA needs to be point nine nine, right? So in order for that to happen, you need to have

Cristina Flaschen (32:45)
Yeah.

Yes.

Roee Hartuv (33:07)
People maintaining that. I don't know what goes into maintaining that SLA, but there are real costs associated to that. Usually it's not SAP, it's not plug and play. There needs to be some sort of adaptation to that specific customer and their ERPs and their system. So specifically SAP is one of those things that I say usually I would chart premium for that connector.

Cristina Flaschen (33:33)
I agree with you as with SAP for sure. And there are also like some systems that there's a perception that that is the case when it's actually not. And yet there is still like because those customers that use those systems are typically more expensive. They're just like used to paying for it. So like there are some small companies, I mean, I've been doing this work forever,

where like connecting to their systems is a nightmare. Their APIs are garbage. Like everything about it just sucks. The overhead about it sucks. It's really complicated. And their customers are teeny tiny. So like they just expect it for free. And if you want to be competitive in that segment, you just have to do it. Versus others where they're like really well adopted, well documented. The teams are great. Like, and like sure, setting it up might be a pain, but then it's actually like a lot less work. But the customer base is

for whatever reason, maybe they're like really stuck in that industry or that specific software's really good for like that one thing. They're just used to paying for it. So it is this like again to go back to like what the market will tell you about it type of thing.

Roee Hartuv (34:37)
This is what we call customers' willingness to pay. And that's also the name of our company, willingness to pay. Because at the end of the day, we want a price based on how much different customers are willing to pay, exactly as you said. Like if you're a small company, you don't expect to pay for those integrations. Probably I need to give it away for free. But if I'm selling to those enterprises that do expect to pay for those integrations, it's common practice. Of course I'm gonna charge for it.

Cristina Flaschen (34:42)
Yeah.

Yeah, it's just it's funny how like the the value isn't always necessarily tied to the effort in terms of like it within the sometimes it is. Like sometimes you're looking at SAP, like that's annoying. But like sometimes it's the specialization can be the value in the even if the actual effort is not as high.

Roee Hartuv (35:23)
Yeah. So again, let me put you in into my world. Different ways to price, right? We can price based on costs. And like we can do cost plus and make sure that we have a certain margin that we want. Or we can again price on the customers willingness to pay. So some customers we will charge them more, although the cost stays the same, but they are willing to pay more. And that's how you build a more

Cristina Flaschen (35:27)
Yeah.

Roee Hartuv (35:49)
intelligent pricing and packaging strategy.

Cristina Flaschen (35:55)
It takes the expertise of someone like you to come in and help figure out what those things, what those vectors are. All right, so I think we are up at time. This has been such a great conversation. I could talk about this stuff forever. Where can folks find you? ⁓

Roee Hartuv (36:09)
LinkedIn is it's great. I'm there I  try to post interesting

posts from time to time, but yeah, that's where I am.

Cristina Flaschen (36:17)
Definitely be on the lookout. I'll continue to be on the lookout for your posts. to our audience, thanks so much for joining us. This has been really fun. If you guys listening, watching, reading are interested in learning more about integrations, APIs, pricing, AI, all the things. We've got all kinds of great content, ebooks, other podcast episodes on our website, pandium.com. Thank you again so much for joining us today. This has been really fun. And I'm sure I will see you out there. Thanks again.

Roee Hartuv (36:45)
Thank you for having me.

Sarah Elkins (36:46)
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