Steven Forth is Ibbaka’s Co-Founder, CEO, and Partner. Ibbaka is a strategic pricing advisory firm. He was CEO of LeveragePoint Innovations Inc., a SaaS business designed to help companies create and capture value.
In this episode, Steven delves into a report that includes research analysis on the Net Revenue Retention growth of various industries. The report explores the impact of factors such as organizational design, package architecture, pricing metrics, among others. Additionally, it highlights the role of churn, customer success, and a dedicated team in driving this growth.
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Why you have to check out today’s podcast:
- Gain important insights when it comes to Net Revenue Retention [NRR] performance growth for different industries based from a research report
- Understand how a company’s organizational design contributes to a low or high Net Revenue Retention [NRR]
- Learn how churn, customer success, and dedicated team greatly affects your Net Revenue Retention
“You need to have two pricing metrics so that you can grow in package. So, some form of usage-based pricing is going to be absolutely critical to a successful NRR growth.”
– Steven Forth
Topics Covered:
01:55 – What drives Ibbaka and PeakSpan to work together and come out with a report that gives insights to the pricing industry
06:01 – Why not include price increase when considering net revenue retention [NRR]
09:25 – Differentiating upsell from cross-sell
10:58 – Two reasons why NRR by API is high
15:07 – An explanation on what those chart and numbers mean on page 29 of the report
18:10 – Explanation to Mark’s observation on the package architecture with one data showing huge NRR
20:48 – The meaning behind having independent modules but low NRR [in reference to the two sections in the report]
23:04 – Steven’s response to Mark’s suggestion of redoing the chart [good, better, best version]
26:17 – Touching on the different pricing metrics for AI [ what he says about pricing based on input/output tokens]
28:50 – Pricing a solution and a platform [case in point: Zoom]
33:23 – Explanation to Mark’s question in reference to page 39 of the report about Pricing Metrics for API Integrators: Are APIs supposed to be a pricing metric?
35:10 – Two important points that these data report generates [also touching on churn, customer success, and dedicated team and how it affects NRR]
40:36 – Steven’s best pricing advice
Key Takeaways:
“If you’ve designed your packaging and pricing so that you don’t have growth in package, don’t have upsell, and don’t have cross sell, then you know in advance that the net revenue retention is going to be less than a hundred percent because there is always going to be some churn.” – Steven Forth
“API as a pricing metric is associated with high NRR performance. Why is that? And I think the answer is because of the verticals where it’s used.” – Steven Forth
“There’s lots of companies that are not very good at cross-sell. So the fact that, if you’re using independent modules and you have low NRR, that suggests that you’re not doing a very good job with cross-sell.” – Steven Forth
“When you really get into this data, even in the verticals that are generally having low net revenue retention, there are a few companies that have high net revenue retention. So you can’t just blame it on your vertical because there are probably some of your competitors in your vertical that do have maybe not 130, but 110 to 120% net revenue retention.” – Steven Forth
“The companies that have the best NRR performance are the companies that have dedicated NRR teams.” – Steven Forth
Resources/People Mentioned:
- PeakSpan: https://www.peakspancapital.com
- Webex: https://www.webex.com
- Zoom: https://zoom.us
Connect with Steven Forth:
- LinkedIn: https://www.linkedin.com/in/stevenforth/
- Email: [email protected]
Connect with Mark Stiving:
- LinkedIn: https://www.linkedin.com/in/stiving/
- Email: [email protected]
Full Interview Transcript
(Note: This transcript was created with an AI transcription service. Please forgive any transcription or grammatical errors. We probably sounded better in real life.)
Steven Forth
You need to have two pricing metrics so that you can grow in package. So, some form of usage-based pricing is going to be absolutely critical to a successful NRR growth.
[Intro]
Mark Stiving
Today’s podcast is sponsored by Jennings Executive Search. I had a great conversation with John Jennings about the skills needed in different pricing roles. He and I think a lot alike. If you’re looking for a new pricing role, or if you’re trying to hire just the right pricing person, I strongly suggest you reach out to Jennings Executive Search. They specialize in placing pricing people. Say that three times fast.
Mark Stiving
Welcome to Impact Pricing, the podcast where we discuss pricing, value, and the intimate relationship between them. I’m Mark Stiving, and our guest today, once again, is Steven Forth, and here are, well, we’re not even going to go into Steven. You’ve seen him a hundred times here. So Steven, welcome.
Steven Forth
Delighted to be here, Mark, and to continue the conversation.
Mark Stiving
Yeah. Well, today we’re going to do something a little bit different, and you’d sent me a report that PeakSpan and Ibbaka put together for net revenue retention. And I just want to say, I see lots of these reports that come out from people. This is phenomenal. You guys did a fantastic job at gathering data and putting it in a format that really gives insights to an industry. So I’m going to send this to my clients. It’s that good. So, nice job. What made you guys want to do this?
Steven Forth
Well, I’m going to give you the unvarnished truth. So, about two years ago a company that we have worked with, their leadership, at a number of different companies came and said, look the world is changing. we are going to be held much more accountable for net revenue retention. We need you to show us how to use pricing and packaging to improve net revenue retention. And I’m embarrassed to say this, but until about two years ago, we had not been paying enough attention to this. And it was a customer that came and said, look, the world is changing, it’s getting harder to get new logos. And the SaaS model really only works if you have strong net revenue retention. So how can we address that? So that’s where it started with a customer coming and saying, this is important.
We do a lot of work together with PeakSpan, which is an important venture capital investor down in San Mateo supporting their portfolio companies and the PeakSpan team, especially Sanket Merchant and myself, had been having a conversation of where we could best help their portfolio companies. And improving net revenue retention, again, was one of the things that surfaced and PeakSpan said, look, one of the things that we look at and measure for to determine if we’re going to make an investment, if we’re going to make a follow on investment and if we are happy with the current direction of the company is net revenue retention. That’s one of the key numbers. And they actually have some benchmarks that they use to make those decisions about making an investment, follow on investment and whether the company needs to be focusing more on it.
But as we were having those conversations we realized two things. One is that net revenue retention has multiple components. So it’s not just a one-top line number. it’s composed of different factors, and you have to decompose it into those factors to understand it. And then the second thing is, it’s not, for a company that only sells one thing to SMBs, small, medium, businesses to hold it to the same benchmark as you are selling to holding a company that sells multiple things to large enterprises is silly. The benchmarking needs to be more nuanced because different business models, different target markets, different pricing structures are naturally going to lead to different net revenue retention numbers. And if you just throw everyone into the same bucket, companies that are actually doing pretty well for their situation are going to look weak. And companies that are maybe above average, but should be doing way above average, are going to look better than they actually are. So those are sort of the drivers first customers coming to us, and then investors saying that this is important and we need to understand it better.
Mark Stiving
Excellent. Let’s start easy. And by the way, if you’re okay, I may make this podcast go much longer than normal, only because I love this data. What you’ve put in here is amazing. But let’s start really easy. And net revenue retention is essentially, what’s our revenue growth look like if we only look at last year’s customers?
Steven Forth
Yes. No new customers.
Mark Stiving
We’re not looking at any new customers. And so then in your report, I only found two things that I didn’t like, believe it or not, and I read the whole darn thing. and one of them is you say these are the positive factors so you can grow the package, you can upsell the packages, or you can cross-sell to another package. So I’m going to take grow the package as meaning usage. So I’m going to use more of the product I could upsell and cross-sell. And you didn’t include, I could raise your price. How could you not include that into NRR?
Steven Forth
Well, okay. So that’s a great question. That’s one of the first things you have to ask, right? Will raising prices or raising prices for different packages increase NRR? We didn’t include that because what we actually have is… underlying this, we have a predictive engine. So at Ibbaka, I don’t know if it’s simple. We built a machine learning system that takes your historical data and makes predictions about future NRR and each of those different factors. So price is something that you act on to do rather than measure based on past data. So we were talking, before we started, we were talking a little bit about digital twins. Ibbaka is also building a digital twin engine for pricing. And one of the main reasons that one wants it to have a digital twin for pricing models is so that we can do what you just said, right? If we increase prices and understand how that impacts demand, it lets us run a ‘What if’ scenario. So I think your comment is good, Mark. It’s a fair comment. We didn’t include it as one of the six factors because it’s an action one takes rather than part of our analytics package.
Mark Stiving
Okay. I think that’s a fair comment. The other thing I would say though is that the other three, by the way, I’m talking about the positive factors. The other three are all dependent upon actions we take as in usages, did I get my right pricing metric or upsell, did I create good, better, best packages or something like that? And so they’re dependent upon actions that I’ve taken, but not actions I’m going to take in the future. Is that the way to think about this?
Steven Forth
Yeah, I think the reason that we did not include price increases or changes in pricing metrics or repackaging and all of those things is because the first thing we do is analyze the historical data. And we want to understand what the current state is. And those six factors, three positive, three negative define the momentum and the trajectory of how you got to your current state. Whereas, one of the things we see many companies that don’t have any mechanism for which you can grow in package. Their pricing structure does not provide for that. So they’ve taken one of the levers away from themselves. We also see companies that don’t have, say, a good, better, best architecture. So they have no upsell path. And other companies don’t really have any cross-sell path. So if you’ve designed your packaging and pricing so that you don’t have growth in package, don’t have upsell, and don’t have cross sell, then you know in advance that the net revenue retention is going to be less than a hundred percent because there is always going to be some churn.
Mark Stiving
That makes sense, unless of course we raise your prices a lot.
Steven Forth
You do have the price lever.
Mark Stiving
The price lever, exactly. Do me a favor, I struggle with this myself. Define the difference between upsell and cross-sell.
Steven Forth
Yeah. So upsell is when you have a clear set of packages where they are related and you upsell to get additional features or additional or to raise capacity limits, maybe add more users and so on. But basically, it’s the same value proposition but you are enhancing it across the good, better, best. Cross-sell, take HubSpot for example. HubSpot has both marketing and sales modules so they can upsell inside their marketing where they have basically a good, better, best architecture, but they also cross-sell from marketing to sales. And I would also suggest that in companies that provide professional services, they are cross-selling between the software and the professional services. Does that make sense?
Mark Stiving
It does. I just draw to find an easy way to describe it. In fact, I use the HubSpot example all the time when I’m defining cross-sell. And I think the difference might be cross-sell is two different standalone things. You could have one without the other, and you could have either one without the other. And upsell is, you need to start with this one and then get that one.
Steven Forth
That’s a good way of describing it. Yeah.
Mark Stiving
Yeah. Okay. Got it. So let’s jump into some NRR data that you put through here. I thought this was pretty darned interesting. Now, most of your data comes from B2B clients, is that right?
Steven Forth
B2B, but there is some from people who are selling to business professionals, which is sort of in between B2B and consumer. and there is some for people who are selling B2G, so business to government. So yes, it’s probably 90% to B2B, but there are some people selling to business professionals and there are some people that also sell to government.
Mark Stiving
Okay. And I just wanted to tell the listeners, this is available to you so you guys can all look at what it is that we’re looking at. We’ll put the link in the show notes. You could search for Steven Forth. I’m sure he has it all over his LinkedIn page because this is actually really, really good, as I go through it. One of the things that really jumped out at me was the fact that NRR by API seemed to outperform every other type of NRR. Is that an observation you made or that you would agree with?
Steven Forth
I think yes, but I think there are two reasons for that. one is because it’s one of the pricing models that the artificial intelligence companies are using and it’s also a pricing model that some of the data analytics companies are using. I think it’s a pricing metric that is popular in hot verticals. So one cannot generalize from that and say an HR company that switched to pricing by API would enjoy the same benefits. So I think there’s a confounding variable here, right? In the currently hot sectors of artificial intelligence and data analytics and data management, that’s one of their common ways of pricing. So I would love it if the world were so simple that we could switch everyone to API pricing metrics and their NRR would go up. But that’s not what would happen.
Mark Stiving
Yeah. Obviously, it only makes sense if it makes sense, right? I mean, if you have a business that doesn’t need an API, then who cares?
Steven Forth
Yeah. But also if you’re in a vertical or a business that’s struggling in anyway, just changing, just adding an API metrical not necessarily improve the situation. Having said that, I do think that we will over the coming years move to much more use of APIs in pricing metrics and much more granular pricing based on APIs. I do think that’s an overall trend. I’m not sure that I have data to support that, but we will do this survey again next year and see where the trend goes. But, I think that if I had to answer that question right now, I’d say that the main reason that APIs are a pricing metric that correlates with high net revenue retention is because of the verticals where it’s popular.
Mark Stiving
And that’s API as a pricing metric. Because one of the things I find is that companies who have APIs, even if it’s not a pricing metric, they’re usually much stickier products. It’s much, much harder to get rid of them.
Steven Forth
Yeah. Agreed. I mean, we should all be moving towards API-centric architectures. We could probably have a whole additional session on the power of APIs and micro APIs and you know, applications that are made out of consolidating APIs or orchestrating them. I do think that’s a long-term trend in B2B enterprise software. But for the specific question, API as a pricing metric is associated with high NRR performance. Why is that? And I think the answer is because of the verticals where it’s used.
Mark Stiving
Got it. Do you have the report open by chance?
Steven Forth
Yes, go ahead.
Mark Stiving
Just jump to page 29 with me. I want you to explain what the chart means because I’m having a hard time interpreting the numbers. I kind of get the feeling of good and bad, but I don’t know exactly what the numbers mean.
Speaker 2
Yeah. Just give me a second to get to page 29.
Mark Stiving
And the top of this one happens to be industry vertical, but what I’m really confused by or curious about is the header that says comparing the top NRR performers with the lowest NRR performers. In this case it’s by industry vertical, but it’s that whole concept of top versus lowest and what the chart looks like.
Steven Forth
Okay. So this is the response to Q six. We probably should have removed that . Sorry.
Mark Stiving
It’s okay.
Steven Forth
So Q six is question six, right?
Steven Forth
Yeah. So I’m just filtering on question six. No worries. But anyway so on the left you have the respondent, so the companies that had NRR of more than 130%. And then on the far right you have companies with NRR of less than 90%. So you can see that the really challenged verticals here are EdTech, HR, and digital asset management, which kind of surprises me. So those are the verticals where you’re most likely to find companies with NRR. And then on the far left, you can see the one that sticks out above everyone else is general artificial intelligence. So these companies have very high NRR, whether that’s sustainable is another question. Because they’re in a hot market, right? But even 120 to 130%,you can see that data and lots of data analysis companies again, some of the general AI companies and so on. Did that help?
Mark Stiving
Immensely here. So let me tell you what my misunderstanding was, I thought we were dividing the number of people over 130% by the number of people who weren’t, or we were trying to compare top performers to the smallest performers.
Steven Forth
Yeah. No, nothing. Yeah. Nothing that fancy.
Mark Stiving
Yeah. Okay. So we might want to work on the title of that, if you can edit this at all.
Steven Forth
We might want to work on this. Yeah. And probably want to take out the Q six because that’s meaningful to the people who were doing the analysis work. It’s not meaningful to anyone else.
Mark Stiving
Yeah. So this is actually pretty phenomenal, right? So FinTech probably says there’s low switching costs, there’s a lot of growth in the industry. And so the winners are winning and they’re finding a way to monetize it.
Steven Forth
Exactly.
Mark Stiving
Very nice. Okay. This is excellent. Let’s jump down to package architecture.
Steven Forth
Yeah. Give me a slide number.
Mark Stiving
Oh, 31.
Steven Forth
Two slides down.
Mark Stiving
31. Yeah. 31. I found it. Yep.
Mark Stiving
There we go. So package architecture’s pretty fun because you’ve got a huge NRR, so greater than 130% for one big package.
Steven Forth
I know. That really annoys me. But the data are what the data are. The reason for that is that a lot of the general AI companies you know, are fairly early on and if not differentiated their offerings. If I backed the AI companies out of that, you’d see a pretty different result.
Mark Stiving
Yeah. So it’s almost like you want to run this data, I would say by industry because you probably don’t have enough data, but you probably want to run this data with all industries except AI. Yeah, because it’s such an outlier right now.
Steven Forth
Yeah. I think that’s a fair comment. That’s why we’re having this podcast with you, Mark, so we can know where we need to dig in and see how we can improve the presentation. Because there are literally hundreds of slides we could generate.
Mark Stiving
Absolutely.
Steven Forth
From the data.
Mark Stiving
Absolutely. Yeah.
Steven Forth
But yeah, the one big package, one, is highly skewed because of its frequency within the general AI vertical. I’m pretty sure if you back that out, you get very different results. And I will do that for you over the weekend and send you what that looks like.
Mark Stiving
Okay. It just seems kind of interesting because most companies don’t have one big package. But if you think about the evolution of products it always starts with a package and we grow it, and then we figure out, okay, how do we split it? How do we make it do more? How do we get different willingness to pay? They’re still in the, ‘we don’t really know what we’re doing phase.’
Steven Forth
Yeah. Package architectures evolve. It’s actually one of our major areas of work right now at Ibbaka is defining how package architectures evolve and change and how that impacts your pricing. But these companies are, we’ll probably start to see that, and we may see that happening more next year. I mean open AI right, does have different packages. But I think open AI’s challenge is that they’re running so fast on GPT 4. I don’t think they’ve actually updated their package architecture for GPT 4. And by the way, OpenAI did not respond to this survey. So this does not include OpenAI.
Mark Stiving
Okay. what else jumps out at us? So at the greater than 130, we have the API integrator, which we might say that’s the AI companies again. Yeah. So if we skip that, we jump to the independent modules two or more. And I got to tell you, that frustrates me.
Steven Forth
Well, what I think what this is saying is two things. One is that there’s lots of companies that are not very good at cross-sell. So the fact that, if you’re using independent modules and you have low NRR, that suggests that you’re not doing a very good job with cross-sell. And, again, we could go deeper into the data and look for differences by vertical. I think, from your own experience, right, Mark, that people generally speaking, lots of companies do not execute well on cross-sell for a variety of reasons.
Mark Stiving
It’s hard.
Steven Forth
Well, I think part of it is poorly designed packaging and pricing, frankly. If your modules are priced and packaged in very, very different ways, which is often the case, if they’re the result of mergers and acquisitions, it can be really hard to construct an invoice because the pricing metrics are all over the place.
Mark Stiving
Yep.
Steven Forth
So I think that’s something that is fixable. Of course, you’re always going to have companies that have sort of randomly acquired products and they don’t make sense as a coherent package. So you’re never going to be able to fix cross-sell because they’ve got different buyers and different value propositions, and they might as well be different companies. But for companies that have a sort of coherent market vision I think you can generally reprice and repackage to improve cross-sell.
Mark Stiving
Yeah. What’s really interesting about the data that you’re showing here is because just for the listeners, we’ve got two different sections. One section is two parts. So it’s 130% plus growth, and then 120 to 130. So you would actually think of that as anybody with fast NRR or high NRR, and then two sections with really low NRR. So 90 to 94 and anybody below 90. And if you look at the independent modules, what you’re seeing is that in the growth ones, the independent module leads, other than of course, the one big package in API integrator that we just talked about. But if you go to the far right and you look at the really slow growth companies, it’s by far the biggest one. And, so it’s like, if companies do it well, it works well. And if companies don’t do it well, it’s horrible.
Steven Forth
Yeah. And I think that the criteria for doing it well are pretty well known, right? So one is you’re selling to the same buyer. two, the value drivers are either the same or are complimentary. And that the pricing metrics are also easy to put together in a way that makes sense for the buyer. But if you fail on any of those three things, if you have different buyers, if the value drivers are totally different or even contradictory, or if the pricing is hard to aggregate then it’s going to be a drag.
Mark Stiving
Yeah. The other one that really bothers me on this chart, Steven, and if I could ask you to redo this, by the way, you don’t have to do this for me. But if I were going to ask you to redo this for the way I think about the world, I would want a single good, better, best line, and then I’m okay if you break it up because you’ve got it broken up into four different settings.
Steven Forth
I regret that now. And it caused us no end of grief when we were doing the analysis. so I think in the future, we’ll just have good, better, best in the next year’s version of the survey. I want to point out though that good, better, best there’s an anti-pattern there. There are lots of people who think they’re doing good, better, best because they have a free offer, a priced offer, and a call-us enterprise offer. and they think that’s good, better, best. But that’s actually, I call that truncated good, better, best. And it’s an anti-pattern. So my fear here is, well, is that just say good, better, best, we’re going to get a lot of people who think they’re doing GBB, but are not.
Mark Stiving
Yeah. So maybe there’s a way to define it to get clean data. Yeah. But what I don’t like about looking at this chart is that I teach and thrive on good, better, best in terms of how do you get companies to do upsell? How do you get them to come into your low package? And this says the good, better, best is horrible.
Steven Forth
Yeah, which, it’s not right because it’s distributed across the different types of GBB. Fair comment again. I will look at consolidating the different GBB. I wanted to get into the nuance. When we’re designing the survey, maybe we’re trying to do too many things. But there’s nuances around GBB as you know, right? Because you coach people on it. And I wanted to try to tease out some of that nuance, but I realized when we started analyzing the data, that I’d caused a problem because then the GBB stuff is distributed over multiple answers. So we had to consolidate the answers and so on. So, yeah, I hear you and I apologize.
Mark Stiving
Oh, you don’t have to apologize. This is awesome work. So let’s jump to the fun thing. The thing that just really struck me is fascinating and it doesn’t surprise me, you have it in here. And that is NRR for AI companies.
Steven Forth
Yeah.
Mark Stiving
And you’re going to ask me to give you a number, and I have to find the page number for a second.
Steven Forth
I should know, right? Yeah.
Mark Stiving
Oh, here we go. 38, we have pricing metrics for AI.
Steven Forth
Yeah. Super interesting area, right? There are two interesting things. One is, AI companies are using a lot of different pricing metrics. and second is they’re also using some unique pricing metrics. One of the most common pricing metrics is input tokens and output tokens, which is basically how open AI prices for most of its offers. that’s not really meaningful for anyone other than an AI company.
Mark Stiving
Not a huge fan of token or credit pricing. You see that in other companies. So Databricks does that and I’m not a fan because I think it’s almost like the company’s using cost-plus pricing, right? They’re trying to say, hey, we don’t really know what the value is, so we’re just going to charge you based on how much it’s going to cost us, or how many AWS cycles you’re going to use, or whatever the heck it means to them.
Steven Forth
I think there’s a lot of truth in what you just said, Mark. It can be difficult to get from number of tokens to value. Let me give you an example. So Ibbaka is working on a new application right now that uses generative AI to evaluate a pricing recommendation. Basically there are a lot of tokens going in because there are a lot of different forms of content and data used to generate the pricing recommendation. But the output tokens is a very, very small number. It’s tiny. but the output token, that’s where the value is, right? The value is not from pulling together all these data. The value is in the recommendation. And the recommendation has a trivial number of tokens. So pricing that based on input and output tokens would be hard to really get mapped properly. Maybe not impossible, but it’s such a remove from what’s creating the value that it’s not really a good pricing metric.
Mark Stiving
Yeah. I think this brings us to a problem that I haven’t solved in my own mind on how to price. And that is the difference between a platform and a solution. So a solution I can quantify value for a platform, it’s often really hard to figure out what the value is. And so how do you price it? It’s kind of like cost-plus type pricing.
Steven Forth
Well, I can tell you how we approach this problem anyway at Ibbaka because we actually like the platform plus extensions packaging architecture. So we use it fairly often. and then you have this question, which is the one you just addressed, right? So you’ve got a platform and there are solutions built on top of the platform and there is usage as well. So how are you going to parse out price between those three different things? And it could actually be to this, to make it complex, because sometimes you have to go through complexity to get to simplicity. You could have a platform that has some form of usage metric. then you can have a solution that also has some form of usage metric. So the way that we try to do this at Ibbaka is we say, okay, so we’ve got a number of value drivers.
Are there value drivers that are closely associated with the platform? And you could get some of that value even if you didn’t have the solution. and vice versa, are there value drivers that are really unique to the solution that okay, you have to have the platform, but the platform is almost a commodity. And then we parse out what we think is the contribution of the solution and the platform, and try to align the pricing with that.
Mark Stiving
I’m going to give you a chance to explain it in the following sense. Zoom, I pay for my Zoom account. Zoom is a platform. They actually have a few solutions or a few applications that they offer. But as far as the platform and what I pay for, how would they ever know how much value I get and how would they charge me based on value? How would you price that if you get to price Zoom?
Steven Forth
It’s a great question. I have not thought about how I would price it. but where I would start is by talking to as many Zoom customers as I could and mapping use cases. So I would probably want to build a value model, talk to 15, 20, 30 Zoom customers, understand a collection of use cases, and then forgive me, but then I would probably want to do some form of conjoint or other survey because Zoom has such a huge market. There’s a lot of variation in it. I would probably use some form of conjoint to do a larger market survey, but only after I’d built an initial value model and validated that value model with again, probably in Zoom’s case, 15 to 20 customer interviews, and then use that to inform the design of the conjoint. and then once I’ve done that I might look at doing per-use-case-based pricing. But there’d be a lot of value in customer research that would need to be done, which I assume Zoom is doing, right. They’re a big successful company, right? But they’re not doing it with us, so I don’t really know. That’s where they need to go, right? Because they’re getting commoditized out by Google and Microsoft. If Zoom’s not careful, it’s going to become another Webex.
Mark Stiving
Yep. I just use them because it’s fascinating. I mean, another great example, that’s AWS. You pay for AWS by the cycle or something, who knows what it’s for.
Steven Forth
You know, what’s super interesting and beyond the scope maybe of our talk today is to compare Microsoft Azure Google and Amazon and AWS pricing. Uh we’ve done some research into that. And when you do that, you can see how they’re segmenting the market between those three different services you might think are direct competitors, but in fact, I don’t think they really are direct competitors. and the way that they’ve designed their pricing and their architectures speak to different parts of the market. So I don’t think Amazon is pure cost-based pricing. I think it’s much more market-driven pricing.
Mark Stiving
Someday we’ll talk about that.
Steven Forth
Yeah.
Mark Stiving
I have one more thing I want to talk about on your survey before we move on, before we wrap this up. Yeah. Go to page 39 and explain this page to me for a second. So the title is Pricing Metrics for API Integrators. And so APIs are supposed to be a pricing metric. Is that also a market segment that you chose?
Steven Forth
It’s also a packaging pattern. Yeah. So you can price per API, but you can also have a package architecture that is based on just doing API integrations. I should probably have been more clear about that when I was writing the report. So there’s a class of companies whose business model is API integrations. and they use a variety of different pricing metrics. The most common ones being nodes connected and number of transactions. And in fact many of them combine those two metrics. They have a hybrid metric that combines nodes connected and the number of transactions.
Mark Stiving
Yeah. And that makes a lot of sense because you could imagine that some people get a lot of value from being able to talk to a lot of things, and some people get a lot of value from having a lot of communications with very small numbers of things.
Steven Forth
Yeah. Yeah. I was working this morning on a pricing model for an Internet of Things company, and the scaling part of their pricing model is based on devices connected and the amount of data that is collected about that device every hour. And I was surprised at how much data is collected on some of these internet of things platforms. So they have some customers where they’re collecting 30,000 different data points per hour about each device.
Mark Stiving
Hmm.
Steven Forth
And they have other customers where they’re only collecting five or six data points per hour for each device. So the range is striking.
Mark Stiving
Yeah. So you can see that, okay. Steven, we’re going to have to wrap this up. Fabulous job. I really, really like this data.
Steven Forth
Can I just reinforce a couple of points that I think are really important?
Mark Stiving
Please.
Steven Forth
So I think one thing, when you really get into this data, even in the verticals that are generally having low net revenue retention, there are a few companies that have high net revenue retention. So you can’t just blame it on your vertical because there are probably some of your competitors in your vertical that do have maybe not 130, but 110 to 120% net revenue retention. So this is one of the things that I really found interesting in the data is that there are high performing and low performing companies in almost every vertical.
Mark Stiving
So if we jump back to slide 29, which was the industry vertical you could see the worst performing industry by far is EdTech. But yet you jump over to the 120 to 130, and there’s 5% of companies in EdTech that are doing that. And greater than 130, there’s what 3% of companies that are doing that. And so it’s absolutely possible, even if you’re in an industry that doesn’t generally perform well. So you said two points. That was one. And that was a very good one.
Steven Forth
Yeah. And then the other thing that I thought was really interesting was this organizational design question, which is that the companies that have the best NRR performance are the companies that have dedicated NRR teams. So rather than just making it something that maybe sales does when the renewal comes up or customer success does as it’s trying to support customers, they actually have a team that is responsible for driving net revenue retention, and that includes renewals upsell, growth and package cross-sell. So it draws in customer success and sales and product strategy and pricing and packaging. But that organizational design, now obviously you have to be a reasonably… you can’t do that if you have a 10-person company. but the best practice appears to be having a dedicated team. And one of the things that we want to dig into deeper is, okay, how are those teams constructed? Who do they report to? What are their metrics? Well, I think their metric is NRR, who’s on the team, how do they work together, that sort of thing. So I think that’s worth noting that just relying on sales or just relying on customer success to drive NRR is probably going to be suboptimal, especially once you reach scale.
Yeah, I think that makes a lot of sense. What frustrates me, I’m looking at page 32, which is the organizational design chart. And if we look at the companies that have more than 130% NRR, what over 70 some percent of those have a dedicated team, right? So that just screams what you just said, but it also says that 2% or some tiny number are using customer success. But I will bet you huge money that that’s 70 some percent have a great customer success team that’s part of that dedicated team.
Steven Forth
Absolutely. Yeah. For sure. Which is why I think we need to dig into this more.
Mark Stiving
Yeah. So it may be that customer success is the only thing we’re trying there and that’s not working well for the few people.
Steven Forth
Yeah.
Mark Stiving
Mm-hmm… but without customer success, I think it’s really hard to have a high NRR.
Steven Forth
Yes. Because we haven’t talked much about churn here, but if you have high churn it’s almost impossible to have a good NRR. So the first thing you have to look at is your churn. Every industry and customer base is going to have a natural level of churn beyond which it’s going to be very hard to get, but if your churn is 30%, you’re almost guaranteed to have negative NRR no matter what you do.
Mark Stiving
Yeah.
Steven Forth
So customer success is probably the key to reducing churn.
Mark Stiving
Yeah. And it’s funny, I do appreciate that you say that, but in my mind, when I think of customer success, I’m always thinking of how do I get companies to want to go to the next package, not sell them, how do I get them to use more of the product and get more value out of it so that they’re excited and can’t wait to get to the next level?
Steven Forth
Yeah, absolutely. Yeah. And that should be a big part of customer success’s role. So customer success should be making a really important… So assuming that you have a pricing and packaging model where growth in package and upsell is possible, then customer success should play a big role in pushing on both of those factors.
Mark Stiving
Yeah.
Steven Forth
I think cross sell is a bit trickier.
Mark Stiving
Yep. Definitely. Cross-sell customer success probably doesn’t own that, sales probably owns that.
Steven Forth
Which I think is probably the best.
Mark Stiving
Steven, fantastic job. Let’s ask the final question anyway, what’s one piece of pricing advice you give our listeners that you think could have a big impact in their business.
Steven Forth
You need to have two pricing metrics so that you can grow in package. So some form of usage-based pricing is going to be absolutely critical to a successful NRR growth.
Mark Stiving
Nice, In fact, we even went through a number of pricing metrics as we were looking through the charts. Excellent advice. How can they contact you if they want to?
Steven Forth
Either through LinkedIn, Steven Forth or by my email [email protected].
Mark Stiving
And I’m sure that will be in the show notes, as well. And to our listeners, thank you so much for your time. If you enjoy, would you please give us a rating and review? Get instructions by going to ratethispodcas.com/impactpricing. And finally, if you have any questions about the podcast or pricing in general, feel free to email me at [email protected]. Now, go make an impact!
Mark Stiving
Thanks again to Jennings Executive Search for sponsoring our podcast. If you’re looking to hire someone in pricing, I suggest you contact someone who knows pricing people contact Jennings Executive Search.
