Follow the Workflow: Pricing at ServiceNow

Pricing is both an art and a science, weaving together many elements to drive growth and business success. There is no right answer or one size-fits-all approach, as every pricing exercise is highly situational—especially since it is so impactful. A firm has to carefully strike an integrated balance between things like market share capture, profit, and churn. This is particularly true of an FTW strategy, because multi-product strategies require an understanding of bundling economics. 

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Alex Saghatelian shared some strategic frameworks you can use, and perhaps most importantly, the questions you should ask: 

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1. Pricing is highly cross-functional: Within a firm, the pricing function touches almost all aspects of a company's success across product, sales, marketing, customer success, finance, and operations. When thinking about B2B pricing and packaging frameworks, it’s important to carefully consider the various components that culminate into pricing execution success.
2. Pricing should align to value: When pricing and packaging to value, it is critical to keep the customer benefits at the center, with an understanding of their next best alternatives and degree of choices you provide.
3. What features to package & price: What is a feature vs. a product? What degree of innovation fencing is reasonable to support expansion of customer lifetime value? How do you decide what is included in the product package? ‍
4. Multi-product value complications: How much should you anchor on pricing and packaging consistency when selling multiple products, each with their own value proposition and value drivers? How do you use pricing and packaging to facilitate cross-sell across the portfolio? ‍
5. Frequency of pricing changes: When do you change the unit of measure or introduce a new package tier? If you sell to multiple customers, should you maintain the same pricing levels and structures? How do you move install-base customers along the journey as you make changes—carrot or stick? ‍
6. Other big questions: When launching a new product, do you bias toward simplicity and adoption out the gate, or do you do more diligence to create a durable pricing model that balances simplicity, value capture and change management? As AI impacts accelerate, how do you quantify the value drivers to support making it a tailwind vs headwind for growth?  

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We hope you enjoy this interview with Alex.

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Dave: Alex, great to have you today. Really appreciate you spending time with Avanish and myself. This is a segment of a case study in our series Platforms of Compounding Greatness. For those who haven’t read the opening essays, our idea around Platforms of Compounding Greatness is that the path to sustainable growth and profitability for software companies is multi-product, and specifically multiple products that work better together—where each additional product compounds on each other. We generally see four patterns of multi-product: follow the workflow, follow the money, single source of truth, and data enriching data. For those who are curious what these terms describe, please read the opening essays.

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The topic today is ServiceNow, which is a case study in Follow the Workflow; it is probably the ultimate archetype of Follow the Workflow. When the company was founded, it looked for product market fit and found it in a relatively small market in the ITSM space—which at the time, I believe, was a market at sub-one billion in revenues. Today, ServiceNow, as a rough guess in 2023, will do something like $8 billion in revenue. You go from founding a small business in a sub-billion-dollar TAM to an $8 billion revenue business, growing quite rapidly still, and very profitable. It is the ultimate expression of this idea of Follow the Workflow. Today’s conversation is around pricing, which is an incredible driver of both monetization and adoption as people move from one product to the next and one end-constituent to the next. 

With that, let’s jump in. Maybe, Alex, you can start by giving a little bit of your personal background.

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Alex: Yeah. Super excited to be here. I’m Alex Saghatelian. I’ve been in the technology industry my whole career. I started in management consulting with Accenture, when digital transformation wasn’t as cool as it is now. But I got my feet wet there, even did some coding at the time, and got a good flavor of what technology can do to help drive innovation and help companies be successful. Throughout my career, I’ve always had passion for the convergence of technology and business. I’ve had the pleasure and opportunity in my career to work with some of the top technology companies and innovative companies in the world, from the likes of Cisco, Workday, Hitachi, ServiceNow, and now Okta. 

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I’ve spent a lot of time on the question, “How do you grow your business? What are the growth levers?” Monetization and pricing are a big part of that, to go along with go-to-market and product strategy, etc.

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Dave: Awesome. We’re really excited to have you today. 

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Pricing is a really interesting topic. It’s a topic that a lot of people have opinions about. It’s also a really high-stakes lever, right? You get it right, and lots of money comes out. You get it wrong, you may damage your competitiveness. You may see monetization go down. 

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Maybe we can start with some basics. As a pricing and monetization leader, what do you think is really important to get right in pricing, particularly multi-product pricing?

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Alex: Understanding your customers and the market, and the value drivers of innovation that you have in your portfolio. How do you want to layer that in to the customer and opportunity base that you have in front of you? Being thoughtful about what’s a feature, what’s a product.

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In a SaaS business model, there’s an expectation of ongoing innovation. How do you actually support that innovation in a subscription business to drive continuous value, and ongoing increases in value realization, for your customers? But at the same time, [you want to] find enough opportunity for balance to fence off some innovation for upsell and expansion scenarios that drive truly incremental value to those customers and prospects.

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Dave: When you say “What’s a feature versus what’s a product,” the implication is, “What’s included in the current pricing [versus] what might be an added upsell?” Is there a typical rule of thumb for what clears the threshold of a new SKU or new product?

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Alex: I think some of it comes down to applicability from an addressable market. Obviously, there are broad TAMs that companies play, and then there’s serviceable addressable market. Then, when you take it to the next level in the serviceable addressable market, there are different segments, buyers, problems, and jobs to be done that you’re solving for. Sometimes you’ll have to do some quantitative/qualitative research, some triangulation against market maturity, and understand that balance. But there has to be enough what I call potential demand in the market, and a sizable-enough addressable market to go after that and fence that out. It could be a subsegment of a bigger market that you actually believe you can create discrete value for.

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Dave: Awesome. ServiceNow, as we’ve laid out, has gone from a single product in IT to selling multiple products in IT, [then went] outside of IT into buying centers like HR or the customer-facing side—and now increasingly so with developers. What’s your framework to think about whether you need to change your pricing model? How do you think through crafting your pricing model to these different jobs and personas?

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Alex: I think one of the important things, especially for a platform solution like ServiceNow—which has a lot of applicability broadly across the enterprise [in regards to] how do you digitize business processes—is understanding the intersection points of the user base in an enterprise. For internal use scenarios, as well as some of the customer-facing capabilities. 

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A great example was, as you started highlighting, the IT workflows business—with IT service management, operations management, etc.—and the intersection with employee experience and HR service delivery. What drives overall employee experience, and how do you optimize that? It’s not just HR aspects; it’s also onboarding, and how your technology gets onboarded. Your whole onboarding/offboarding process is related to your technology systems and tools, and how you interact. It can even extend to other aspects of how you manage your employee experience across the enterprise. We started seeing some convergence not only with the CIO having a stronger voice at the table to influence their colleagues at the CEO staff, but [also with] productivity benefits flowing into the HR use case. 

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The proposition, when you start thinking about employees, is more about how this solution is affecting the value of your entire employee base. Because everybody is going to interact, to some degree, with some of the workflow technology, versus in the context of, historically, IT service management. That was a lot about the service desk agents, the fulfillers of the service requests.

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Avanish: I think one of the fascinating things about that transition was that it alluded to fulfillers. Fulfillers, for those who are listening, is the term for someone providing a service. And the requester, which was the whole employee base, was in fact free. The transition to HR includes all employees—so now the whole employee base are paid users.

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What is a unit of measure, or metric, or value? As I go to the next product, I might be leaving a lot of money on the table, but I’m also struggling with transitioning the customer and the new buyer to the new model. Talk a bit about how to message it, how to really educate the market on that transition.

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Alex: That’s a great call-out. When we’re looking at this dynamic shear point, the change management, with our go-to-market teams and our customers, you’ve got to look at the value drivers, productivity benefits, and total cost of ownership. All the aspects. In the context of an HR service delivery, the requesters are the key recipients of value who fundamentally interact with the technology and experience it on a day-in and day-out basis with their various HR needs. At enterprise size, employee base is a good proxy for value. There are a lot of corollaries to support that talk track. 

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But what we also were seeing was everybody engaging more and more in the platform. We started seeing that behavior becoming more prevalent. Actually, the ability to use a metric like “an employee” took out complexity for our customer on questions like “How do I scope? How do I size? How do I approach that?” As we started getting into more motions with enterprise licensing agreements, there were solution suites around multiple workflow technologies. That became an anchor point of the digital interaction in the platforms becoming more pervasive. Therefore, we could associate value.

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The tension would come up in a case like, “Hey, I have seasonal workers. I have front-line workers. I have workers that don’t really interact as much.” How do you balance that? That’s always a natural tension point.

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Avanish: There’s also the beginning of conversational AI. There’s this notion that there are fewer providers, fulfillers, responders—and more and more the person might be interacting, at first pass or maybe many passes, with AI. You couldn’t just leave that to the future-versus-product question; it was a new way to interact.

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Dave: I love your questions, Avanish. You’re going from IT to HR at the price-per-unit change, but also the unit change itself. I think that’s fundamental in this narrative of multi-product. There’s the product view, which is like, “Just keep following the workflow.” That’s easy; you encounter other users. But monetization is really challenging, with all the threads that Avanish was pulling on.

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As you’ve seen the product moving into different jobs to be done and different buying personas, how quickly did you start rethinking pricing? Or did you wait for there to be adoption and then start your move on pricing? How would you think about the trade-offs around timing?

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Alex: That’s a great question. During my tenure there, we established what I call a pricing and packaging architectural framework of how we wanted to do things, in terms of constructs like “good, better, best,” or our licensing metrics (in terms of the meters and how we charge). There was a lot of horizontal capability that, in the context of different use cases or buying personas, was applicable and had a unique opportunity to unlock value for those use cases. We wanted to make sure those felt consistent when you bought different packages from left to right. 

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Some of our advanced capabilities around automation and intelligence were being layered into those things. A customer had the context of, “Okay, when I’m doing the basic functions, but then stepping into higher levels of automation and optimization, I understand how that fits across the portfolio overall.”

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 Some of the feedback we were getting from customers as they were getting into multi-product buying with us was, “Make sure it’s simple enough for me to add on and have predictability, but understand that value needs to scale. Be clear on how you’re driving the balance of your innovation fencing with ongoing innovation in a consistent way, so I can understand that as a buyer, and understand it as I go left to right in the workflows.”

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Dave: Now, maybe I’m trying to get too tactical, but I do think people would be really excited to get your feedback on this. Is there a rule of thumb in terms of the adoption level at which you start moving the two knobs, the level and unit measure?

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Alex: Generally there’s a critical mass of customers. Is there enough market penetration, product market fit that’s viable, and are we seeing scale-up of that? 

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During my tenure, we were trying to be conscious of changes in pricing and packaging because customers despise it. Our go-to-market teams did not like it either. We tried to time those changes. Say we were going to change the pricing metric—we’d line it up with a new innovation that was going to market. Maybe we had a new tier package coming out; we’d combine the change into one event, but we’d focus on the value: “Hey, you’re getting all this new innovation and value! By the way, we’ve better calibrated the packaging and the licensing model to support your scale and adoption.”

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Dave:. It’s interesting how there are several constituents here, as it relates to pricing. Certainly it’s the customer. It’s your sales team. It’s also your executive team. 

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We get involved in companies as small as 10 million ARR up to billions in ARR. Somewhere in that transition, you go from founder pricing to more analytical pricing. At times we see founders really resist revisiting pricing, for good reason. As the head of monetization and pricing, what’s your advocacy case that now is the time to start thinking about a differential level or unit measure?

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Alex: I think part of it is getting the voice of the customer, voice of your partners, the go-to-market team in general. As you scale, it gets harder and harder to grow and meet expectations, at times, to penetrate the market further. Make sure you have a model that can scale as you’re expanding your routes to market, or your channels, or your sales function in general—that you have a model where, as new people come on board, they can quickly get productive, ramp up, and be effective at selling.

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I’ve found that sometimes you can be really elegant and nuanced about things, but then it fundamentally doesn’t land with a customer prospect or your field. Typically I look at markers from the voice of the customer. What are we hearing from customers? We get feedback from the field teams—[use that to] understand what’s working well in the sales cycle and what isn’t. Look at some of our analytics on ramp-up and adoption of SKU launches. How are things doing from a market perspective? What are we seeing competitors do? As new innovations are coming along, test your base hypothesis. As you go do market studies—whether it’s advanced things like conjoint studies, etc.—aim to reevaluate some of your baseline constructs and ask, “If we evolve this this way or that way, based on where we see some opportunity to be, what does that mean overall?” I think it’s multi-pronged, where you’re looking at the balance of that. 

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Advocacy with the C-staff is definitely important. One of the things that became clear in my journey, to the point about getting into multi-product from a single product, is the more products you have—the more units to sell or things to sell—the more inherent complexity could be perceived, regardless of anything. There are more options, [which] bring more choices and more discussions, and the more things differ in terms of how you monetize and license and package. More incongruencies create more friction in the process. As ServiceNow was growing, for example, it became very, very clear that, as adoption scaled, there was inherent complexity that we had to streamline going forward.

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I think there are a lot of indicators that you’ve got to bring together to get a comprehensive view, and then be able to quantify the impact of potentially changing. That’s doing some of that market testing and customer research to get a better sense of what the value prop would look like if a customer did move down that path.

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Dave: Awesome. I’d love to just pull on the thread of increasing value price per unit, and then move to the master class question that Avanish brought up, in terms of changing the unit of measure. I think what we heard from you is that the easier step is increasing value per existing unit of measure for pricing. 

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I’d love to talk about strategy and tactics. From a strategy standpoint, we’ve seen two modalities. We think about compounding products: one plus one equals five. If that’s the value to the customer, we’ve seen people price to that second product, the combined two products, at 1.5, and also at 4. Either 1) you not only give your customer compounding value, but you take the overall cost of ownership down for the two products. Or 2) you recognize that there’s compounding value, and you extract some of that compounding value and take the total cost of ownership up. Do you have any viewpoints on when each of those strategies is appropriate?

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Alex: Yeah. There have been many discussions during my tenure at ServiceNow about some of our automation and intelligence capabilities, like AI, Virtual Agent, and whether we should license that once as a platform offering versus licensing it in the context of each use case. Applying it in the context of a specific use case, versus doing it just once as a platform—that became really, really powerful for monetization.

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The flip side of that, at times, is just convenience bundling. Like, can you get more cross-sell or pull-through of lower attached products? You tend to see that as being more of a discount: “Give me a better value the more I buy; give me a better deal.” There are times for that, when you’re trying to get penetration in some of your cross-sell motions and accelerate the sales motion around that. There can be value in that. 

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I think the amplifier or multiplier effect you were alluding to is really contingent upon having enough innovation that you can say the sum of the parts is better and accretive to the customer, versus the individual pieces being more of an economic incentive. I think the beauty of a platform like ServiceNow is that there is interplay across the platform offerings.

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Dave: Awesome. Let’s take the thorny question of raising prices. You can do it all sorts of fancy ways, but at the end of the day there’s a like-for-like raise. Any tactics around raising price?

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Alex: You’ve obviously got to look at the data and what you’re seeing in terms of price realization, what’s happening in the market, and how your share capture is going. Assuming you’re generally seeing healthy trends, there are multiple ways to get at this.

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One is how you manage your discounts. There are aspects around innovation indexes, around at-renewal, or between CPI, inflation, and ongoing innovation—back to the point about how, as a SaaS service, we’re delivering a lot of innovation. You can have that as a lever embedded in the renewal motion and the expectation that you set with your customers, and use that as a commercial lever to balance the trade-off between adding new SKUs and cross-selling it to other product categories, or just raising the price on your apples-for-apples run rate spend. 

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I think list price transparency is mixed in various technology companies. Some markets are very transparent on list price; some obfuscate it. In a case where there isn’t list price transparency, obviously you have a lot more latitude and a lot of it comes down to how you manage that internally with your stakeholders and partners. When there is list price transparency, it’s a lot easier to counterbalance that with your discount management as well as some of your renewal motion around inflation and innovation trade-offs with growth and cross selling.

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Dave: I’ve talked to some pricing experts that have done successive price increases or regular price increases. One actually showed me a curve of NPS. It comes down X%, and then in nine months it comes back up. That’s a good price action. 

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Any learnings over the years, in terms of how to think through NPS and the cycle of NPS post-price increase? What is the right level of pressure on NPS temporarily? How long should that last? How do you manage a healthy customer relationship while maximizing monetization?

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Alex: I think, at times, NPS can be noisy around pricing and cost. It means a lot of things. If you’re driving ongoing and incremental value to customers, they’re getting to the right value realization, you have differentiation in the market, and you continue to bring innovation to bear, you have a strong right to manage that over time and reflect that through. As long as customers are getting a great return on their investment and they feel like you’re being reasonable about those price increases…

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There are differences in optics that could affect perception and market. Back to transparency in pricing: list pricing versus how you manage the renewal cycle. If NPS has a lot of sensitivity around pricing cost because of the market you’re in, and maybe your core products will have less differentiation, then you’ve got to be quite sensitive to that. The share and elasticity trade-off could be more material versus if you have a commanding differentiation in the market and you have a right to play, in terms of that pricing power. You can get more leverage out of that. I think it depends on the state of the market, state of the competition, and how much value and innovation you’re driving into your customer base. You can’t go in too heavy-handed with your customers. It’s got to be a continuous process over time to improve price realization and value capture.

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Avanish: Hey, Alex? Tactically, would you do a price-specific NPS? Because NPS is an aggregation, right? How do you attribute the pricing element to it, and say, “This is about pricing versus about the new innovation and features?”

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Alex: That’s a great question. I actually have done supplemental voice of customer studies that go deeper beyond NPS. You have to peel the onion back on some of these things, because sometimes it could be a case of, “I bought beyond what I actually needed, and I over-licensed for things I’m not adopting, therefore my run rate spend is too high. It’s not because of the products that I have adopted that I’m not getting value out of.” There could be lots of reasons for it. Being able to decipher which is what is important. 

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To your point, unpacking underneath that is very critical. I’ve actually done that on multiple occasions, and I found that a very fruitful way to really get at the drivers. Then you always have triangulation with the industry analysts too, like the Gartners of the world, who share their observations and feedback. [But] going deep yourself with your customer base is important on this topic.

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Avanish: Probably even more so in the multi-product world, where your economic buyer starts to become distributive too.

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Alex: Yeah. That’s right.

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Dave: Avanish went straight to the head of the class on the key pricing issue I believe people are thinking about today. Maybe we can end on that topic: changing the unit of measure. Avanish pointed out the extreme example in the marketplace today, where software can replace certain parts of the value delivery. Let’s start with the basics and then move to AI specifically. When do you know it’s time to change the unit of measure? What are some best administrative practices around managing that?

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Alex: You know, I’ve done this a few times and seen some of the dynamics at play here. I think a lot of it comes down to what’s happening around your unit of measure. I’ll use a great example of an IT operations management space. Core licensing used to be on physical or virtual servers. But as workloads got distributed and moved into cloud environments and hybrid cloud scenarios, PaaS, containers, microservices, and other resource types became more relevant to that. The growth was coming from those vectors, and not necessarily data centers within a customer’s environment where they’re adding more server workloads. 

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Based on the shift in the market, how do we best capture that value while making sure we can link back to our install base of “servers are still important”? Because that’s the lion’s share of what customers have on their install base, in terms of how we monetize that product capability. We went through a journey of building a ratio-based model that accounted for all those different categories and the corresponding value. 

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Avanish: I would just point out one operational thing there, Alex, which I think is also important in this context. As we talk about innovation, there’s also the issue of a container, or virtual server, and common ground. How do you track that? How do you ensure that there is monetization tied to that, or not? Customers are smart; they’ll say, “Hey, they’re charging me for this much, but I’m only going to use this much.” I think that’s one of the fascinating parts of this type of transition of price structure. 

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In your own systems, and perhaps in third-party systems and the public cloud, how the heck do you get that data? I think that’s maybe the most challenging part of this.

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Alex: Yeah. Part of it is looking at trailing, historical use patterns and setting the terms around how you define measurement, based on a window of time, that is representative of true utilization. It’s hard to gamify in that sense.

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I’d say one of the big things that is very important with pricing models and pricing packaging in general is having the telemetry and instrumentation built to ensure that your sales and customer success teams can understand and work clearly with the customers on, “This is what you bought. This is what you’re using. Here’s the value you’re deriving.” Otherwise, the growth you’re seeing in that model, like the example of the subscription, it would be dead in the water because you couldn’t actually action that growth.

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Dave: I feel like there’s another hour to be spent on the headline of “My Billing Software Sucks.” [Laughter] That does tend to come up a lot when we have these types of discussions. 

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Avanish referred to something very early on, which is, in theory, AI could reduce the seat count 80%, yet the value may be the same or even higher. Maybe I’ll let you, Avanish, jump that conversation, but that seems like the story today.

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Avanish: Well, I brought that up because when Alex and I were doing this together back when, it was the early days, 2017-ish. AI was not part of most commercial applications. ServiceNow was one of the first ones. I was hoping to tee up how that was the beginning of the journey. It snowballed tremendously. I think that is going to become an element of a lot of pricing and monetization considerations for any enterprise vendor.

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Alex: The short-term answer was, you can put some caps in place, like entitlement caps or secondary licensing metrics for utilization on Virtual Agent sessions, things of that nature. Or potentially adjust pricing a bit to capture some incremental growth. 

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I definitely think it’s something that, depending on consumption and utilization, and how you look at the value of the platform, you get way more productivity longer term. Fewer users having to support the system means more speed, agility, productivity, all that. To your point, the value is growing, so your unit of measure needs to evolve as well to what the sources of value are around that.

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Dave: Yeah. There’s a bear and bull discussion on this, right? The bull perspective is that it’s like the iPhone. People used to never pay for content prior to the iPhone, and then all of a sudden you got these apps and people got habituated to paying for content because of the delightful experience and all the magic associated with the iPhone. AI is sort of the same way, where people are willing to pay much more on a consumption basis.

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The bear case is that all these license models have to go to consumption. If you look at some of the precedents, like RPA—where they tried to basically price it to a replacement agent, a human agent—there was really strong growth initially but then the barriers to entry competed that pricing away, as lots of people could create RPA agents. It’ll be a really interesting path forward, in terms of how this shakes out.

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Alex: I was just going to make one more related comment. I do think some of that gets nuanced by industry. When it comes to AI and automation and virtual agents and these sorts of things, there are purpose-built use cases in certain sectors of the market, and industries that are moving faster, and others moving slower, and the value prop can be well codified. The more explicit thinking that can go into what problems you’re solving and how repeatable and scalable that is with automation, then you can have that discussion. That’s something where I was even seeing quite a bit of differential in some industry verticals and industry solutions, and how the applicability of some of the AI technology was coming to bear on those.

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Dave: Awesome. Alex, thank you so much. Thank you for spending time with Avanish and I, and sharing all this wisdom and knowledge. This is incredible. I really appreciate it.

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Alex: Always appreciate the opportunity to chat. Thanks for the time.

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