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Speaker Details

Chris Mele

Managing Partner
Software Pricing Partners

Session Transcription

This next session is chock full of data and I was as I was talking to the speaker I was just blown away by some of his insights and very confident this will be a session this can't miss you're going to go back and look at it two or three times so with that I'm going to introduce Chris Mele he's the managing partner of software pricing partners I'm going to stay on stage with Chris and ask him some questions as he's going through all the information he's going to provide but Chris thank you so much for being a speaker here at SaaS Metrics Palooza 23 so this session I'm really excited to be here thank you for having me I look forward to many more detailed questions in the comments as we go through this but let's talk a little bit about where all of these insights are that we're going to share today are coming from Ray knows this I had a software company for 13 years and also a private or a previous customer of software pricing partners I was one of the logos in there but I was surprised also to learn not just that software pricing firms existed but that this one was the category creator back in 1982 now you might be wondering about some of these interesting things that have happened in SaaS so for those of us that have an on-prem background I have dated myself a little bit here Ray concurrent user licensing that was an invention of software pricing partners back in the late 80s that was the dominant scheme that many of us used and what I used to build my software company you probably read in the news a few years ago that Atlassian had made some headlines because unlike traditional software companies in SaaS they would bill you only for a user if it was active in that month you might also be surprised to learn that software companies were doing that as early as the late 80s those were called fair usage policies and then finally for another innovation they were called financial overlays again on the on-prem software days through Black Monday and the Reagan administration how software companies survived is they gave subscription billing to on-prem software and that's how they continue to make sales through that crisis the first market crash a lot of history here a lot of things to talk about but all the patterns and all the findings are over four decades in the making so put simply pricing is a science and mastering the science is really one that puts you back in control the economics of your company and if you're in control of the economics of your company then and only then are you in control of its valuation and its destiny and it turns out that that is a really great place to be in and that's really the purpose of this talk today so we're gonna cover three things and there's gonna be a lot some interesting charts and graphs we're gonna explain here in a moment but the first one is that pricing especially in this market or in any time of turmoil is an untapped opportunity for profitability then we'll cover that here in a second the next thing we're gonna get to is getting to what I call the truth on the ground this is your data what's what insights are hidden inside of your data and how to capitalize on it often the answer isn't out there the answer is right inside your own company and then we're gonna wrap up with three critical things to consider before executing a pricing change so for starters there is no other variable under management control that is going to move the needle on profits deal velocity and upside than the stuff we're gonna talk about today now there are many other things outside of pricing we can talk about packaging we can talk about what pricing metrics we use and how that stimulates sales but we're gonna focus just in on pricing and just in that one category if we better control discounts easy easy easy to pick up another 20 to 40 percent in profits you'll see why in just a second 10 to 25 percent of profits by just having better volume pricing mechanics anytime that we charge by more than one thing here we're gonna charge by storage plus CPU plus users we're just slowing things down on the sales process increasing deal velocity drives more revenue and profits better addressing outliers is crucial sometimes you have a game-changing deal very very very small tweaks to the pricing model can generate millions of upside for companies that are coming in and buying huge amounts of quantity of your software and then finally if we get more transparent in pricing we can really crank the revenue model and so we'll get really tactical here in a second but the thing I want you to reflect on is in my software company it was an ERP system in the remodeling sector we brought people from paper and then we got them into automation and the ROIs were ridiculously huge and I want all the CFOs to think about Excel as the equivalent of paper when you are doing things in pricing with that we're missing a lot of the texture of what's really happening and we're gonna show you some automation and give you some tactical things that maybe you can do a little bit differently in Excel to tease out some of these insights and as is often the case it gets complicated and it gets complicated quickly but we're gonna try to make it super simple and straightforward for you so getting to the truth on the ground before we dive into a chart that we're gonna explain here that might be a little bit confusing to see at starters but by the end of this presentation you'll be a master. Pricing is time series data this is often misunderstood we change prices throughout the years or within a year we retire SKUs or product codes that are no longer being sold we switch cloud architectures and so there is a bit of a shift in between who's buying what and what is ideal that time series data is not a variable in Excel you have to think about how prices have changed over time for the data that you're analyzing just something as simple as the list price change from last year to this year if you miss that the truth on the ground is gonna be wrong. I have a two funny stories for Ray I think one of these we talked about before one client engagement think of two products and we'll just keep the math easy there are $100 a piece per month $100 plus $100 is $200 so this company created a bundle where you could buy two products and they created a new SKU but they also factored in an incentive and so instead of putting that bundle at $200 which would be the sum of each of the products they put it at $180 and over the years as people began to discount they forgot that that bundle had a $20 hidden discount inside of it in fact they thought of that new SKU that new product code as $180 list price and all of the discounting behavior that they did was cast off of that so put another way pay attention to bundles because if you don't tease out the real picture then we start to have this information propagating out through the model or through the analysis and a lot like my brother is a pilot you know it's like 18 errors to crash a plane it's a lot like that to really screw up an Excel model outliers require different treatment I have another fun story here on an engagement this particular individual worked at a really well-named consulting company and had run an average and so what they were trying to do was to create a bundle of common things that people bought so again let's go back to the two product example and you could have certain quantities of those two products so he had run the math and he said well if five product a five quantity of product one and two quantity of product two this is the average and so this is going to be the bundle a problem is that nobody buys the average now in Excel we get very confident that we have achieved a truth on the ground but averages are not our friend in monetization averages if they include outliers are very misleading and averages also nobody buys the average so just just remember that that averages are just an approximation keep you from getting burned all right so now we have a little bit of a chart here to explain now I'm gonna zoom into this so we can take a peek here and the first thing I want us to pay attention to is the x-axis so this is just a scatter on the x-axis is list price you're gonna notice two dots an orange and a green dot and on the vertical axis is the discount percentage now an orange dot just means how did the company think that they were going to price this particular item so we're gonna look up the tiered schedule at the company we're gonna look up its list price and we're gonna calculate it before the negotiation occurs that's the orange dot as you can probably imagine every deal has two dots that has an orange dot this is where we thought we were gonna sell it and then we have a green dot which basically says this is where that deal was actually sold and we can actually see a lot of stuff right away so for starters you can notice there is virtually no overlap between the green and the orange dot so right away we know that the company has completely left the playbook and the price book so either the price book is out of date or there's some systemic issues here and how the company thinks that they should be pricing because when this gets out into the field nobody's following the playbook now if we look up onto the top here you'll notice that we are looking at new business about 37 million in list 10 million in net for 27 million in discount this is standard practice in the software industry the majority of the list price is a vaporized with what you're looking at right here so remember we said in the very beginning you can pick up a lot of extra margin by better controlling discounts when I see a picture like this which is 99% of the time I get really excited huge upside can be had if we get this under control to to negotiate away this much I think of a dollar of discount as an investment you're gonna spend that dollar to get a certain behavior from your customer preferably to buy and preferably to maximize their upfront commitment that's not happening here now the second thing I want you to notice are these dots arrayed at the top and we right away can see wait a minute you were not really in the business of giving away free this particular sample data set didn't really get designed with the idea of a freemium model if you look at that and we were to ask this company what was going on I can tell you those are partial term transactions and somewhere along the ride of the turmoil in the market instead of selling one year contract term salespeople decided well let me just land the deal let you lose it use it for three months with the assumption that they'll expand later into pay and of course the expansion never came that's the land and expand problem that plagues us we land we don't see the expansion now you might also be noticing some vertical stacks here this is a skew a common configuration that somebody bought think of it as a certain amount of users certain amount of API calls or whatever it is that they've bought in this configuration of product and services and that vertical stack represents an array of discounts everything in this case from down at 10% discount there's even surcharges many times all the way up to 80 90 and of course higher discounts than that this creates a lot of friction in the sales process and every one of those data points that you see right there is discoverable by one of your other prospects to use in the negotiation coming up to buy your software buyers are very well informed about these stove pipes of their discounting behavior and then finally we won't spend a lot more time on this slide notice how in these little concave ribcage looking things there's just this really crazy thing that happens so we build a product CFO comes up with their their new pricing and they're really happy with it CFO leaves after a couple of years another product comes along except maybe now that product is in the cloud and it's got some consumption usage base kind of pricing but basically that pricing strategy of product number two is different in fact it's very different maybe the quantities are just a heck of a lot larger those those stow those rib cages there those are multi-product buys and it turns out that in the case of clashing pricing strategies clashing structures the more you buy of one product calculates out to be the less discount that you should charge and of course this is one of the reasons why the salespeople have completely divested from the scheduled pricing because why would you follow a playbook like that imagine explaining that to a prospect oh I see you want another 10,000 you know usage metrics over here and so I can lower your discount from 45% to 44% it just doesn't doesn't work and there's a mathematical phenomenon that occurs there and this is really common because of the way that we create product over time pricing is not a science it tends to be an event and nobody steps back and says wait a minute how will two or three of these products come together for the buyer to take down in a reasonable rational way this is confusing for salespeople also confusing for the buyer yes just for the audience to just remind them like you did at the beginning of this slide what the difference is between the orange dots and green dots I think it's very important to reinforce that yeah the difference between the orange dot and the green dot would be that if the price book that you have at your company says that you're going to have a $10 item that you're selling and at a certain quantity you should sell it at $5 the orange dot will be plotted at 50% it'll say hey you should sell this particular deal at this quantity at 50% but then the salesperson enters the show and the salesperson maybe you don't have great packaging or maybe there's some wacky use case or maybe it's the end of the quarter or there's a million reasons says look I know it's at 50% but I really you know he wants to sell or she wants to sell the deal and the deal lands with an 80% discount in other words the difference between that 50 and the 80% discount is discretionary and so this this gap is what we're trying to close when we shore up discount and what we really want to have is a formula like way to generate discounts the more you buy the better discount it is that you earn you would expect Ray the orange dots to look like that traditional stair step right that tiered schedule but you don't see that anywhere because we're in multi-product land and it's meaningless and remember the buyer is buying a configuration of things often it's more than one product or more than one skew including services and other things especially uncomplicated enterprise software and so this this picture that emerges that we look at this is by the way our level setter platform that we built it allows us to tease out what exactly is going on and why are we having so much leakage on discounts and you know what you have so much more data here but I know one of the questions that's going to be asked is Wow 70 75 80 percent discount this seems like a really messed up organization is this kind of what you see because I know a lot of CFOs are probably saying hey we never go above 40 percent discounts first answer yes more common than you think second answer is many times the executive team thinks it's not a problem but when discounts are recast for example we look at bundles for example remember when we rewind for just a second it's it's hard to get this data right Ray I mean it's buried in systems it's often not clean there may have been a system change over last year and we moved into some new billing system and so it's hard to see this there's a lot of time and energy that went in to get this picture normalized we find the wrong SKUs assigned to certain customers sometimes the deal shows a net price larger than the list price which is super wacky I mean zero quantities in the billing data it's you know if you were to take this in as a CFO raw I think in a lot of cases you're sort of struck with I can't get to the truth on the ground because I have to clean all this stuff up and so what you're looking at is a really clean picture and it's a really common picture and it's way more common than you think doesn't matter if you're publicly traded or privately help great thank you okay so of course this is new business let's take a little peek at renewal well now we see a whole bunch of other stuff going on and we see a whole bunch of different patterns and if we look over here we have 481 million the idea here is this is a larger company 83 million in net but look at the discounts again the numbers are absurd and this is procurements big problem right it was on the podcast for the art of procurement and everybody wants to have a better RFP vehicle they're not sure how to get there but you know buyers show up to the party and there's not a lot of trust going on because they know I want to be at the top of this stovepipe up in that 90% discount so I got to drag the sales process out right so every time that we divert or I have a poor structure here that the salespeople can't follow we put a little data point out in the marketplace that things can be negotiated if things can be negotiated in extreme cases buyers buy at the end of the quarter buyers buy at the end of the year all right let's have some fun exploring a change in pricing metric now I think we spoke earlier Ray that many companies are exploring other things than user models and sort of location based models and this idea of charging for some aspect of usage a transaction model or some form of a higher quantity metric is in order and there's a million reasons why that can be a great thing one of the things that happens when you change a metric is it's a massive risk so the first thing that we have to connect ourselves over to is on the sales floor when you change a metric you literally pull the carpet out from underneath the salespeople and put a new carpet in of all new objections if I'm selling it's pretty easy to estimate my users because I know my employee counts and now you're gonna estimate the number of times I run my AI model whoo good luck with getting me comfortable with that so mitigating risk is about picking the right metric but not just picking the right metric it's picking one that actually delivers the right revenue we'll talk about that in a second secondly is let's go back to Excel I'm sure you've seen the hundred tab Excel model with a gazillion variables really hard to understand but that's just a model you don't want to build just a model you want to build a range of scenarios that's really crucial to understanding pricing and then finally vetting everything across those scenarios and understanding the revenue impact is absolutely crucial if you're taking PowerPoint slideware from somebody that says use this metric because it sounds great and we did a bunch of surveys and customer research if you haven't done your homework by recasting all of those deals in the new model all of your legacy customers and really computing what is the revenue ramifications for them both in renewal as they make their way over to the new model and how they're going to do that and also for new business well then we're really flying blind you have to vet everything this is the homework assignment down to the penny so let's take a look again we'll see level setter here's our new business in this case now we see something a little bit different up top here and we see a new number here now what the software is doing is we have laid in a price book called a consumption metric so we've zeroed out and executed a metric swap and we said now this gets a little thorny you have multiple invoice transactions occurring expansion upsell etc but you have a count level usage data and that gets a little gnarly if you try to marry it but what we're doing is we're marrying that and timing it you don't want to be looking at customers that just started you want to look at customers that have come up to value and are at full usage execute a metric swap and what the system is telling us is the old world list net and discount is at the bottom and the proposed new world list net and discount is at the top remember we have a new metric which means new quantities for everybody which means all of our outliers change you know we thought the guy that bought in the old world with a ton of users maybe he has a little bit of usage we don't know right the whole world changes not just in the sales dialogue but in the texture of the data that's the key so here we can see a net price impact and just a few seconds of hey that looks pretty interesting right that's new business well why don't we just go ahead and cast that against renewal oops imagine the company that rolls this strategy out let's take a look up here in the upper right tank 29 million because in renewal that's the that's the account that's the core right and it turns out that that core has very different usage patterns than the new business core so a lot of times what we see Ray is somebody crafts it's really excited about the new metric for a new business they don't do the homework assignment the company that rolls a metric out like this is gonna lose their shirt as those customers come on over they're gonna be paying a heck of a lot less let's take a ride on another metric this is a usage based second one just think of it as any other metric we want to combine and take a look at execute the metric swap we have now 36 million in new business and list because remember we have a new metric your list price your net price new discount hey that's a 5.8 million dollar impact that looks pretty interesting let's take that one for a ride let's go take a look and see what it looks like with renewal oh look at that 6.7 million on renewal so this one has some legs in it so what we would do is we would proverbially take this metric for a ride this is where the scenario planning comes into account what happens if we have this list price what happens if we have that less price what happens if we have this tiered schedule or this discounting schedule or this other one what happens that we have this minimum quantity versus that minimum quantity what if we're shooting for a 5% 10% 15% or 17 and a half percent upside which one do we like the best and you want to be able to do this very quickly and I think what we've seen a lot is all the time and energy is spent trying to get to the truth on the ground and that really prevents us to get to the scenario planning which is really where we're going to risk risk mitigate all of this to determine if the model really going to work so Chris this is really interesting because I know a lot of our audience probably have been considering do we introduce some level of consumption or usage based pricing and number one just the marrying of the data from actual customer usage existing customer usage with the new pricing variables very big challenge number one number two I think one of the things I've heard you say is if you're considering going from a more traditional subscription to consumption based pricing it's probably best not to start with your existing customers is that still part of your hypothesis or recommendations well I think this kind of gets into customer transition right so first you have to do your homework assignment on those legacy customers on any pricing change because what you don't want to have happen is that you inadvertently trap them and by trapping them is is you've crafted a strategy that will inadvertently deliver to them such a great price increase that they're just not going to move over or worse yet you're gonna have to discount everything down to get them to move over and customer transition is one of those moments that you get to right the ship and in fact many times you're executing a pricing change because you're looking back at those legacy customers you're saying they're extracting enormous value and they're paying very little for it and so in general you kind of broaden the horizon over the next three years and we come up with good upgrade plans for them and so the new strategy will be for new business we don't want to rush if you rush customers to the new pricing and packaging and that's all you have no real new features it just kind of moves some pegs around in the carton they're gonna figure that out pretty quick and it turns out customers get really upset when you change the price the quid pro quo has already occurred they bought into the net price that they've paid negotiated heavily you gave them a stream of futures off the roadmap and what it is that they're getting in the software and so they bought into that if you go back to them and say oops high interest rates oops we haven't raised our pricing for a while you just get really everybody upset it's like pouring salt into the wound what you want to do is come out with new packaging new pricing new value from the roadmap new strategy and often what's happening there especially with the on-prem customers is a contract vehicle swap you know there's some things in the older contract vehicle that you want to swap out and get them on to the new contract vehicle and that's the general pattern that you want to apply you just want to go slow to move fast and I think a mistake and maybe this is the private equity playbook Ray I don't know is that you know we have a change of hands and everybody just BAM doubles the price because you know their theory is who cares if a bunch of them churn out and that's really unfortunate because although you might drive some profit I think it's also damaging to the brand you can drive a heck of a lot more profitability being a lot more thoughtful and careful about the transition your approach is let's make sure that that scenario planning is back with usable all the data you can from both usage and the new price scenario so great chart yeah what's under here of course is the map right you can click into any customer or if you were in Excel and you wanted to do this on your own you need to see the bill material what they bought here's what they paid currently here's what we're going to be asking them to pay in the future based on their new usage in this example and therefore I'm okay with that kind of an ask to my customer provided I get them enough value to upgrade and I think what happens is if you don't do the homework assignment your customers could get trapped just nobody's going to upgrade because the price differential is way too high so that's what I had for you today Ray but I'm happy to dig into questions at this point that was a lot of information I encourage the audience to go back and of course watch this on demand to really get into it but Chris you've been doing this for so long and there has been this phenomena of product led growth assumption based pricing over the last two to three years and the SaaS subscription model any other unique insights you you have of companies trying to migrate from a subscription to a usage based model and both the cautions and any best practices that you've seen yeah I mean it goes back to that go slow to move fast you know a lot of maybe the best way to describe this would be with an example so let's take the AI space you know a lot of the early participants in that space wanted to charge you based on the number of model runs which sounds great right like how many times you're gonna run the model and I think we get excited as software companies on this usage based phenomenon and we forget that there's a buyer on the other side that needs to like come to grips with the model right and so in this one example this is a real example this particular buyer had I don't know how many hundreds of thousands of cameras located all across the US and this was a facial detection algorithm and the question was well you know how many times are you going to run the model well how on earth would you ever know the answer to that question and if you as the buyer can't estimate the use the first thing that you're going to do is you're gonna say I need to mitigate this let's do a pilot now if you do a pilot and that usage becomes so astronomical that the bill jumps 20-fold and the pilot gets terminated and I think what you see which nobody really talks about Ray and some of these usage based approaches when you look at the competitive intelligence and you look at how that strategy actually plays out in the field what's happening is a lot of those deals are oscillating to a flat fee that is not a usage based contract anymore because customers are just not it's just untenable risk right and then I think you want to take that into account a minute you know as we've talked before with PLG and other motions how you combine self-service partner channels direct sales etc you know conversion we know is really hard and I think you want to be very careful and thoughtful about what strategy makes the most sense for you and not just plow forward you know you got to do your homework you got to do the modeling you gotta ask yourself the question if you're gonna buckle up for the complexities of what you're going to be about to embark on and there's just a lot of things you want to think about before we just pull the trigger on that I know it's exciting to say we're a PLG company now but that carries with it a host of business model changes that I'm not sure everybody fully comes to grips with as that little quip comes out the mouth. It's interesting I was just reading a research report from the Maxfield Growth Institute on the change in year-over-year growth rates between traditional subscription price companies and usage base and starting in Q2 22 you started seeing a significant decrease in the usage base because customers could actually decrease usage versus if they were on a subscription maybe it was still enforced another 6, 9, 12, 18 months so the other thing I guess I would ask you is have you seen this consumption based pricing actually seem great in the Excel model but after it was rolled out it really had negative impact do you see a lot of companies making that mistake and if so beyond just great scenario planning how do you prepare for that potential decrease in usage or even churn of those bigger customers who say that 200% increase in my charges over the last one year is just untenable. Yeah it's not for it's not for everybody but in answer to the first question yes people have gotten hurt on consumption you know it's a double-edged sword you pay for what you use but then when we have a crisis and things are maybe constrained in some way you'll see that you know people are going to right-size that usage right and this is the same phenomenon that happens when I sell you a big bundle of units and I get to the end of the year and you only used some of those units you know maybe when times are good nobody cares but when times are bad you're gonna see people start to right-size the ship so consumption you know isn't the right answer for everybody and I think we should define consumption or usage based to me that those are the wrong terms to put on it what we're really talking about is what are the range of quantities that the salespeople should be presented with and the range of deal sizes that they that we want them to deal with you know in one example I'm between you know a zero and a hundred or zero and a thousand or I'm sorry one in a hundred one in a thousand one in ten thousand if I'm quoting a counts in the millions or counting page views or site visitors you know the numbers become astronomical pretty quick in market ecosystems and I think we can I think we talked last time about the HubSpot example the first one in defines the strategy right and the first one in that defines the strategy largely made it up and then everybody else looks to that one and says oh they must be doing something right I'll copy it because we're all built you know to copy in the coding world so why not copy the pricing strategy even though it's a terrible idea and then we end up with this ecosystem where everybody's charging by for example the number of responses to your survey okay so imagine that you had 700 or 700 thousand surveys you're gonna run this year as a big corporation now somebody's gonna ask you Ray how many responses are you gonna have to those surveys which are a mix of internal surveys and external customer surveys you know stuff to your employees and stuff to the customers and prospects you don't know what that number is and often what we see in the ecosystem of the players trying consumption we move our client back you back to something that's a little bit easier to estimate because it stepping away from consumption is sometimes a better strategy than jumping all in and again there is we all want the best practice but it turns out that what makes the best practice is this example we have two companies they're identical identical down to their people identical down to the line of code but there is one thing that makes them very different and that is the customers they've attracted those problems those customers are trying to solve and their usage patterns that's what makes that that's the the blood underneath the body of the company that makes them so unique so unique those nuances of their DNA profile are contained within that customer base that's why that strategy has to be different even those of those companies literally in that fabricated example would offer theoretically the exact same thing and that's what I mean by inside out the answers to how you want to drive more profitability are not out there the answers are in here right inside your company and how those customers of yours are deriving value and returning that value back to their organizations and Chris 30-minute sessions like it's really hard to basically provide insights to all the unique experience in perspectives you have happen to listen the audience go ahead and contact you after this if they want to learn more about different pricing strategies maybe the perfect lead-in for the last slide software pricing calm a Chris Mele at software pricing calm a managing partner thank you so much for being a speaker at SaaS Metrics Palooza 23 have a great rest of the show everyone and Chris thank you again what's wrong with me right.

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