Estd 4.22.2023
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As Managing Partner, North America, for the global strategy consulting firm - Simon-Kucher & Partners, Joshua Bloom elaborates on the pricing engagement process for SaaS companies, how it is structured, and the challenges and dogma that can potentially crop up along the way.
There are a few hallmarks of our approach at Simon-Kucher & Partners, when it comes to structuring the process of starting a pricing engagement with any software company.
The classical approach to that is conjoint analysis. It’s a gold standard, but conjoint analysis is not the perfect answer for every project. It works really well when you have a certain number of features or project options to test, or when you can get a significant sample size. It works best in consumer settings and works okay in small business software settings, but it does not work very well in enterprise software settings, or the further you get down to the B2B end of the spectrum.
There are different methods that can be used. We use fixed trade-off screens or ask a series of probing questions. But ultimately, we’re just getting reactions to some of the straw-man concepts we’ve come up with. We’ll often have a couple of different scenarios to walk people through, because that’s where we start to get not just feedback, but also begin to make projections about how the market will respond. These depend on which path we go down, and what the price sensitivities may be.
The time spent on the three phases ends up being pretty equal for each, but depends on the level of research complexity in a project, too. We could be doing research across multiple channels in 10 different countries for various products, it can get pretty complicated. But for a plain vanilla organization with a relatively simple product set, the time spent per phase probably looks more evenly distributed, like a month each or around that, for a month-on-month project.
We contend with different challenges at varying stages of the company’s life cycle. In the very early stages of development, a lot of questions are asked on how to price. At this juncture, companies are often still struggling with the underlying measure of pricing and what their business model looks like.
As they develop into the growth stage or become multi-product and multi-segment entities, we get a lot of questions around packaging and pricing, and how to pull together a newly complex product portfolio.
When you talk of really mature companies, we get into more of the pricing operations piece, or how to think about discounting and channel management.
Pricing structures can be on a spectrum, on one side, you can have a continuous consumption-based pricing structure where companies pay for what they use.
On the other end of the spectrum, it can almost be a fixed price structure sized almost using a t-shirt sizing approach M, L, XL etc. The sales person just has to get it generally right with a generous buffer. Here the usage may be based more on the honor system.
In the middle you can have more of the cell-phone plan models, where you purchase blocks of ‘usage’, with incentives to move to higher tiers.
In order to select which pricing structure to use, here are a few ways which can help to decide:
I’m not a believer of the dogma that the good-better-best packaging structure is a one-size-fits-all.
There are different structures, like use case packages and so on, and there are lots of different ways to think about the traditional concept of packaging or bundling functionality that aren’t necessarily good-better-best. To boil it down pretty specifically, good-better-best means that there was one land-and-expand path for a customer to go through with it. It basically assumes that there is a natural level of sophistication that you can stratify your customers into, and they get there in one direction. It assumes that they start quite simple, and it is easy to say what’s next with their needs.
But that is not the case with every product portfolio. Some have multiple entry points for people to start at. Others have multiple point places where they can achieve a different level of sophistication needed to go in directions B versus C - which essentially breaks the good-better-best model. We’ve seen often that the good-better-best model works, but not for every company, because all of them don’t have one land-and-expand path.
Good-better-best also implies that the answer is in having three tiers of packaging. Again, that is not always the optimal outcome. In some companies we’ve worked with, a simplified two package lineup makes sense. There are others where there’s one upsell path, but they need four or five tiers to cover all of the different segments of customers that they’re reaching. It is useful as a tool in the toolkit to be able to say that we have a playbook for how to think about good-better-best, and set limits and fences between the packages, but it’s not the only packaging decision.
Our research shows that less than half of all SaaS companies have public pricing pages. If the optimal structure is not a good-better-best lineup because your product portfolio has more complexity, you’re more likely to put that behind the firewall or have a salesperson walk you through it, because it’s more complex. I would say that the majority of companies that do not have published pricing, are doing something other than good-better-best.
I’m wary of my own selection bias because I tend to work with companies who feel that they have pricing power, but that’s not always the case. In about 20 percent of projects I work on, we’re being asked to come in, because they want to get more aggressive, or try to find ways to simplify or gain share, or potentially price more aggressively and figure out how to do that in a controlled manner. The majority of companies I work with, feel that they’re leaving money on the table. And we often find that they are, and their pricing elasticity is pretty low. It’s a bit of a self-fulfilling prophecy, if you feel you’re leaving money on the table, you probably are.
But I have seen elasticities across numerous studies that are fundamentally different than those you get in a consumer study. As a company, one of the benefits for Simon-Kucher & Partners now is that when we take a step back, we have vertical practices across different industries. Yet, the elasticities are different. Another way to think about a proxy for elasticity is, just how important is pricing as a value driver, or as a purchase decision criterion.
If you do a consumer study, price is typically the number one factor for consumer-packaged goods or suchlike. But if you do the same study in B2B software, it will not be surprising to see that it becomes something like the third to seventh most important factor. It’s a proxy for saying, “Yes, pricing matters.” It’s not that it doesn’t matter at all, but on a relative basis, I think the software industry has much more pricing power than other product types.
If you’re really creating a new category, this is one place where I actually think that economic value analysis makes sense. It’s a bit textbook, but it is about really understanding what value you are creating for your customers through their business outcomes, operational efficiencies, etc. and then remembering that even after you calculate all that, you still need to have a typical software return on investment (ROI) sharing those gains. Even if you calculate the entire value capture and you’re able to document that, I still think you’ll only get like 10-25 percent of that in pricing. This is because you need to leave a 4x to 10x ROI benefit to the customer. One thing that people miss, is that they do economic value analyses and say they’ve created all this value, so they need the corresponding price. Well, not really. You not only have to share gains with your customers, but also make it compelling for them to invest as well.
That’s a useful framework to think about. If nothing else, the work done in putting that together, becomes your marketing collateral in discussions when there’s no anchor and no differentiator. This is where you don’t need to ask what your unique selling proposition (USP) is, versus your competitor’s mentality for a market perspective. Instead, you think of how a new category or a new software changes your business operations. Speaking that language and gathering those numbers, really make a difference.
There are a few challenges in pricing operations that are pretty common. One pitfall is having a discounting policy where everyone is just going through the motions, it lives on a piece of paper but nobody follows it, or it didn’t lock down in a system, but you have 99.9 percent of requests just being rubber-stamped. A well-run process will maintain some tension! This could be in terms of different stakeholders getting involved, not just salespeople.
It could really ideally surface in escalation discussions – what are the key strategic factors that would cause us to discount in situations where we ordinarily wouldn't? is it that you're up against a different competitive set than maybe normal? Is it that you are trying to land an account where there's significant opportunity for growth in the future? You need to document what is different about this deal; you need to list out the number of units being purchased, the pricing you’re testing, and the relative discount; and then get it approved. You’re not really approving a number. The ideal scenario there, is that you’re proving the deal strategy, or thinking of why you are deviating in a particular case. The vast majority of organizations do not have this in place. They either have nothing or they have a process that just looks like they are going through the motions. This is a big factor to consider.
The other thing from the pricing operations standpoint is, when it comes to new product pricing, companies often create fairly robust processes around it. They’ll have stage gate processes of how the initial list price gets approved, but often forget that they should be regularly reviewing the pricing for their existing products on an annual basis. When you have a lot more information on your existing products, in some ways it should be easier and a more fruitful discussion on contemplating pricing change.
Some CPQ tools are an overkill for software companies, too. I’ve dealt with companies where they have 100 Stock Keeping Units (SKUs), and need a CPQ tool to be able to capture the levels of complexity, and come up with the right quote. But by and large, the more common challenge I would attribute to those companies (and what I’ve seen from those companies asking for help with) is - doing away with 100 SKUs, and maybe taking a more structured packaging approach to turn them into 12-15 packages, at the most. This is enough so that you don’t need to CPQ anymore, but just need really good marketing and discovery material for your salespeople, to train them on the different options.
This may be a bit of a controversial answer, but actually large public companies often have teams devoted to pricing, and do a very good job with it. To some degree, the highest leverage we have is getting in with earlier stage companies, where we really usually have the pricing experience to turn the knobs on their business model, and the returns can be huge. It can transform the trajectory of the company, at a point when it is fairly unknown.
If you’re a large public company, you sort of know where the ship is headed. If you’re a startup, you still have to deal with how much more equity must be raised, how much dilution will be faced, what the business model looks like, and what the revenue rate is going to look like, say in two years.
If we get in early, we have a really strong ability to change the trajectory of the company, which I find rewarding and I think others do as well. To be blunt, usually the first pricing is set by the founder of the company, but most such founders are technology experts. They are technology founders. So that is usually another key point, what is the first inflection point where the founder is willing to give up a little control or look at outside advice and say, “I set this based on research that I did a few years ago when we were first launching. But now that we have a robust product and we’ve proven product market fit, what is next in monetization?”