In this podcast interview, Ajit Ghuman discusses the most common pricing pitfalls SaaS companies face as they scale and outlines a systematic, sequential framework for building and evolving pricing models. He explains how early‑stage pricing—often a simple low‑price SMB plan—can become suboptimal when a company grows into mid‑market and enterprise segments, leading to missed revenue if packaging and pricing variables aren’t updated. Ghuman emphasizes that the core levers are (1) creating well‑defined packages for distinct customer segments, (2) selecting the right pricing variable (per‑seat, per‑account, consumption‑based, etc.) that aligns with perceived value, (3) choosing an appropriate pricing structure (single‑part, two‑part, three‑part tariffs) to balance predictability and usage‑based revenue, and finally (4) setting the price point based on competition, discounting expectations, and market data. He recommends a top‑down, sequential approach—review packaging first, then variable, then structure, then price point—to avoid local‑maxima thinking. The conversation also covers practical signals that indicate a pricing problem (stagnant ASP, long sales cycles, shelf‑ware, low product adoption) and suggests a cadence for pricing optimization: a full revamp no more often than every two years, with quarterly tactical adjustments. Metrics to monitor include product adoption rates, average selling price (ASP), churn, LTV, and revenue predictability. Throughout, Ghuman stresses the importance of aligning pricing with customer value to capture the full demand curve and avoid the overhead of custom‑scoped deals.
Chapters
Cool. So I mean, your expertise and what the kind of heart of this podcast is all about pricing, um, right, you know, specifically for software and SaaS companies, what's kind of the number one mistake or what do you see go wrong about pricing? And can you share some of the best strategies you've seen from You know, pricing being in the Valley?
Yeah, so what tends to happen in Valley companies is either a company starts at an enterprise scale and sales makes up the pricing as they go, and it's bound to happen, there is nothing wrong about it, that's how things evolve. Or your startup is more of an SMB startup, you know, with a lower price point and you're selling it for like $10 a month, $9 a month, and so on. And as your company grows, either you go from being an enterprise company to more also having a mid-market segment, or if you are an SMB company, then you'll start to go upstream a little bit. And what you want is a more consistent way in which to capture revenue and value from the market. And that's where pricing packaging becomes important, because if you were doing it how you started as a company, then you become suboptimal because If you grow and you have, let's say, 100 customers, then some customers are going to be big customers. Some, you know, just to make it simple, some are big, some are small. The big customers have different needs. They may use different use cases. The smaller customers may use, you know, your most high-velocity packages. So then pricing and packaging for a SaaS company typically is about how do we automate and create these structures such that we can— when we go to market, we are clear about our communication as to what offerings and packages are good for which segments, such that we are able to maximize our value in kind of this demand curve. That's really what the evolution is. And the mistakes tend to be when companies grow, they don't evolve fast enough. So in one direction, there are companies who just have like this traditional good, better, best model, but they actually have an enterprise motion and they leave money on the table. So that's one way they leave money on the table. The other way is if they're bigger and they have like this, just, you know, every deal is just going to be custom scoped, that creates a lot of overhead and that also inhibits scaling because your deal lengths keep getting longer, you're not sure about what is your consistent price points and you're just reinventing the wheel every time when you're doing pricing. And that is also confusing for customers and creates a lot of overhead. So in both ways, companies then end up leaving money on the table if they don't evolve their pricing fast enough.
And what do you mean evolving pricing? Are you talking about increasing or are you just kind of adjusting and pivoting based on kind of what your conversion rate is?
Yeah, it's mostly like the price point is almost the last part of this whole equation. The biggest problems are are, do we have the right packages for the right type of customers? And then within the right packages, are— do we set the right pricing variable, right? Is it a per-seat pricing? Is it a per-account, per-email sent, contact, whatever, depending on your product, whatever the pricing variable is, have you set that correctly and have you aligned it to customer value? So packages and variables, uh, that you use to charge for your product are the most important things to scale pricing basically. And once you scale it properly, That's where you get the bang for the buck.
It makes sense. So obviously, you know, the SaaS model is becoming more popular, you know, both from SMB perspective and then also enterprise, you know, it's growing at a fast rate and pricing models are kind of maybe outdated as well. How do you kind of recommend SaaS founders to think logically and systematically about their pricing model when they're looking to build that out?
Yeah, well, I kind of take a sequential approach in Going through pricing, right? So let's— first of all is like you identifying there is a need to solve the problem, right? So that will show up in your metrics, that will show up in either longer sales cycles, that may show up in ASPs that are not increasing, that may also show up in shelfware. If you have products that you sell but people are not using parts of those products, so it will start to show up in your— you can't upsell them again. So at some point it will— your account, you have to look at how are your accounts growing in time? Is the product adoption good enough? And most likely an under-optimized pricing model will lead to challenges there. So now once you've identified there's a problem, and that is a natural phenomenon, you will identify once you start looking at your numbers that, okay, there's a problem. The way to solve it, like I like to solve it sequentially. So I start, you know, there are 4 or 5 main decisions that you have to make and I would say review these in order, right? First is review your packaging. Are you really creating offers and packages for the market that are very specific to use cases and customer segments such that you have the enterprise plan, it really solves the need for enterprise customers and scales appropriate to their needs. Then you have the SMB offerings. Are they customized enough to their needs, right? So look at the packages. There is a whole set of literature that you can read to better understand it. I'm including some of that in my book as well. And then when you go, you figure out that you have the main structures, right? Then you figure out your key pricing variable. So there are a couple of approaches. You can price based on capability. You can say, hey, this is a product we charge, you know, $20,000 or $200,000, depending on what the product is. And there is consumption-based pricing, right? So if you're Twilio, you say per SMS cost are X, or if you're AWS, you say per GB storage or compute power, this is how much we use. Or it's like a CRM software, say this is how much my product is per seat. So pricing variable is really important because if the customer looks at the variable, appreciates it, intuitively understands it, then it will be a well-aligned pricing model that you can get enough revenue back. And there's also some interesting things you can think about to actually maximize the value of the pricing that you get from customers. So that's a high-leverage decision, packaging and pricing variable, and then is the structure. So even after you have the pricing variable, you can say, well, you know, it's pay for what you use. That's one option, right? Young companies say that, so as a prospect you'll be like, well, it's great, I will pay for what I use, if I don't use it I won't pay. As your business grows you want more predictable revenue and that starts to be less helpful, then you want to have some part of the structure that is a platform fee as well as a transactional fee so that you have more predictability in your revenue. So there are different pricing structures, single part tariff, 2-part tariff, 3-part tariff and so on. So these 3 decisions actually are account for major leverage points in the pricing structure. If these are good, then you really are optimizing for it globally. And then locally optimizing for pricing is lastly the price point. What is the per-seat price or the per-API-call price, for example? So that you can, you know, that, that can be more discovered. And it has to do with your competition, it has to do with how much discounting your customers want and bunch of other variables. So that's that, that final decision. But that's what I would say is to go through it in this order, because if you sequentially solve it, then you will— you're ensuring that you're solving it from a top-down rather than a locally, you know, local maxima. Because if you just look at the price point, it's always constrained by the overall structure of your model. And if your structure isn't really well designed, then your price point variable, you know, if you change it a little bit, it's not going to give you the biggest bang for the buck.
And then when founders are thinking, you know, you have 2 sides, right? One are saying, okay, this is our price point, we're gonna stick to our roadmap, and then you have other founders who are maybe looking to kind of optimize their maximum, you know, revenue and LTV, which is kind of what we talked about at the beginning of this episode. How would you suggest to them to effectively adjust maybe increase their pricing? And what are they basing that key points or metrics upon? And how often should we be looking at this?
I mean, in general, a complete pricing revamp is often not done, you know, I would expect it to not be more often than every 2 years, but with some amount of optimization every month, every month, sorry, every quarter. Okay, so that's the frequency in which they should do it. Now, in what was— let me ask you to repeat your first part of the question, please.
Yeah, so if they're looking to, I guess, maximize their LTV or, you know, versus compared to sticking to a price and sticking to the roadmap, how do you adjust and increase their pricing? And then what are they basing that on? What key points or metrics are they making that decision?
So the LTV really is, you know, LTV is the lifetime value of the customer, right? So the lifetime value is going to be optimized if one, the customers think they're paying the appropriate amount for your product, and 2, they are actually using the product for a long term, right? So coming up with the right structure will ensure that, you know, the packages, if the packages are well designed, Then they will be well designed both for your first land, like what are the initial MVP the customer wants, and the expansion motion in a SaaS offering. If you give the customer all of your features in one go, they may not even be able to use it. So it will lie as shelfware for a while. And then they will say, well, I'm used— you know, I have this plan, which is this high-end plan, and I'm not using 10 things. I want to then churn or downgrade to a lower plan. Or they may start looking around, right? That happens quite often, right? So that's something you don't want. You want them to have the right plan for them that's well aligned to the value that they're getting to maximize their LTV, right? So the structure solves a lot of that. The other point to price point is an interesting phenomenon that in some cases pricing too low reduces demand for software products. So I follow this VC called Tom Tungus, and his blog is like a wealth of information on pricing and many other aspects on SaaS. One of the points he notes is that pricing acts a little bit like a Veblen good, where if you reduce price, then the demand starts to go down, and the perceived value of the product can actually be much higher if the price is higher. So specifically, let's say you have an enterprise product and you price it really low, even, you know, in total, many enterprise companies may just distrust your price if it is too low, right? So let's say you're a downmarket competitor, you're trying to go after an SAP or Oracle, and you charge, you know, you are 100x cheaper than them. Fortune 500 companies will not take you seriously, right? They will understand that, you know, intuitively they will get you probably don't have enterprise capabilities or support and all of that. So it If you have the right offering, you are doing yourself a disservice by reducing price because you may think that you'll get more market share, but you will get less market share depending on the segment.
