GTM Navigator: Billing & Pricing Best Practices 

GTM Navigator is our ongoing series where we break down the essential components of nailing the right go-to-market strategy. 

In this episode, Lauren Houpt, Associate at Fin Capital speaks to Riya Grover, CEO & Co-Founder of Sequence, which is automating billing for B2B teams with custom pricing, with revenue tools that span the quote-to-cash process. Backed by a16z and Fin Capital, Sequence is building a modern and innovative product for CFOs, reinventing how B2B finance teams automate their revenue workflows. Riya previously Co-Founded Feedr, a food tech platform acquired by Compass Group in 2020.  

We hope in this edition you’ll gain insights into how to choose the right billing vendor, emerging pricing trends, and how to prepare for pricing changes.  

Key Questions Discussed: 

• What is the current state of billing within B2B fintech? 
• How is Sequence solving for billing pain points? 
• When should you start thinking about bringing in a billing vendor or building a solution in-house? 
• When should you start thinking about bringing in a billing vendor or building a solution in-house? 
• How do you choose the right billing vendor? 
• What is custom pricing? How is it being defined? 
• How should “AI first” companies be pricing? 
• What pricing trends are emerging from the AI space? 
• How should companies prepare for pricing changes?

Transcription (edited for clarity): 

Lauren Houpt (00:01): Welcome to Go-to-Market Navigator by Fin Capital, our ongoing series where we break down the essential components of nailing the right go-to-market strategy. I’m Lauren Houpt, Operating Value Associate at Fin Capital. Today we’re diving into all things metering, billing, and pricing with Co-Founder and CEO of Sequence, Riya Grover. Sequence is a modern billing and contracts platform to help finance teams unlock error free revenue. Really looking forward to this conversation, thanks for joining us.   

Riya Grover (00:37): Thanks so much for having me on, Lauren, I’m Riya Grover. I’m the founder of Sequence. We’re a Fin Capital portfolio company and before this I was an entrepreneur. I built and sold a business in the food tech space, so this is my second run, and Sequence has been going for a couple of years. We’re a revenue automation platform for B2B finance teams. We help finance teams translate the terms of any custom sales contract into a structured data set, so that they can automate all of their downstream revenue operations like billing, invoicing, revenue recognition, and synchronization of data with their other systems of record like their ERP and the CRM. Really why we’re tackling this problem is that we see a lot of businesses today leverage more complex pricing models, particularly fintechs, leveraging usage-based pricing and hybrid pricing. There’s also a lot of B2B teams using custom deal terms and giving them a set of revenue tools that enables them to sell with custom deal terms. While then achieving automated billing and invoicing off the back, that’s what we’re going after.  

Lauren Houpt (01:51): Awesome. That sounds great. I would love to hear what the current state of billing is within B2B fintech from your perspective. What pricing models do you typically see teams using right now? 

Riya Grover (02:03): The fintech industry has been an early adopter of usage-based pricing. Fraud detection companies charging per API, other payment companies charging tiered volume-based fees. I think these pricing structures are very familiar to customers within fintech markets, be it platform fees usage or in some cases seat-based models. Most don’t reinvent pricing; they use and adopt pricing models that are intuitive and minimize friction for buyers. Obviously to stay aligned with market expectations, we of course, see a lot of these fintechs deploying usage based as part of a hybrid pricing strategy. Worth noting as well that I think this model typically creates strong alignment between the fintech and their customer success. As a customer processes more payments, or makes more trades, or grows their loan volume, the fintech grows proportionally and this really incentivizes them to help their customers succeed. Also, interestingly, I think it helps fintechs to serve both small and large customers effectively. So small businesses can start with low costs while their volumes are low. Larger enterprises obviously pay more as they use more services, and this kind of reduces barriers to entry, but it also means fintechs can protect their margins. Often the infrastructure layer that they’re paying for underneath is also charged per usage. For example, if a fintech is paying 10 cents to process a payment, they can charge 15 cents and maintain their margins regardless of volume. I think, obviously, usage-based pricing is very prevalent amongst fintechs. I mentioned use of this within hybrid strategies. We’ll often see this in combination with subscription pricing. What we also see with a lot of fintechs, which is really the market we’re playing in, is that fintechs will often deploy a sales led go to market motion and leverage custom pricing in real terms for the end customers. They’re potentially varying those pricing tiers depending on the customer segment they’re selling to or implementing trials or minimums or certain discounts alongside their pricing – that’s also extremely commonly deployed in B2B fintech. 

Lauren Houpt (04:26): Awesome, I appreciate that. That makes total sense. I would love to understand how Sequence is solving for this, or if you have products that are either in the pipeline or you’ve recently released, that are helping with these pain points. 

Riya Grover (04:37): Sequence has built this modern set of revenue tools for B2B teams who have custom or complex pricing models. What we do is we capture new contract upsell or renewal data. I’ll talk a little bit more about how we do this, but we seamlessly feed that to the finance team with perfect accuracy so that finance teams are then able to automate billing against those contracts, invoicing, and revenue recognition, as well as some of the other receivable’s operations like payment reminder workflows. I guess you’ll see a bunch of products out there which are really designed for very standard plans or very standardized pricing. Stripe is obviously in that world, but what we’re leaning into is when companies do have these custom deal terms, ultimately the data that lives in a sales contract, which can sometimes live as a sort of offline PDF artifact stored somewhere in a Google drive or attached somewhere in Salesforce. 

Ultimately for finance teams to be able to bill and invoice with accuracy, they need to be able to perfectly, in real time, capture that data. We’ve built the sales to finance workflow as a core part of our overall suite of tools just because it’s so important for accuracy of all the downstream revenue operations that upstream data holds the source of truth for every downstream operation that’s going to happen. The way we’ve done that is so we have a CPQ product that companies can adopt, sales teams can use our quote builder product to create pricing proposals, order forms, and then we perfectly extract that data into the finance engine. This upcoming quarter, we’re launching AI based contract ingestion where companies can just forward their sales contracts or drag & drop them into Sequence, and we can use AI to entirely extract all the commercial pricing terms, contract terms from that contract so that finance teams can automate their operations off the back of it. 

A couple of other pieces that we’ve leaned into very strongly – we’ve really invested a lot in designing a product which companies can onboard quickly. I think billing and pricing can sometimes feel like a big lift for companies. A lot of the legacy tools in the space, it’ll take you six to nine months to onboard and implement something that reflects your pricing structure, whereas we’ve just been very intentional about making it something that you can set up in a few weeks. This can be done through the dashboard for non-technical operators. Ultimately, finance and RevOps users are the users of this product, once it’s implemented, but it can also be done by API. I think this combination of supporting more hybrid or complex pricing structures alongside these custom deal terms that you might have in a contract, is something that we do really uniquely, and this is sort of the market that we’re leaning into. 

Lauren Houpt (07:42): I have been on teams where there’s no finance workload that exists and like you mentioned, contracts are just all over the place in Google Drive or SharePoint, so love that you’re solving for that huge pain point and saving teams a bunch of time.  I would also love to hear when you think companies should start to build out their billing systems in-house versus outsource to a provider like Sequence? For a lot of our portfolio companies that are joining in on the call, we have folks from early stage all the way to pre-IPO, when should they start thinking about that and how do you even choose the right vendor? 

Riya Grover (08:17): Our point of view is that you should never build in-house. A company should be focused maniacally on solving the problems for their customers, building product for their customers, and every bit of engineering resource that is not focused on that is that ultimately means that you’re not driving as much customer impact as you can. But I do believe that it’s important to have something scalable and automated in place – as early as your first 30, 40 contracts in the business, even less in some cases, you start to run the risk of missing things, especially when you have some slightly more complex pricing structures. It’s very easy to miss a tier or a minimum in a contract. That means that you basically miss revenue, leave revenue on the table, but also by having more streamlined workflow from quote to cash. Having the right kind of revenue system in place, it also means that from the early days you’re capturing much better data. You have a unified source of truth between old teams on your usage and your revenue data. That means whatever’s in your ERP is well aligned with what’s in your CRM, and obviously this gives you a ton of agility as you are thinking about your go-to market and equipping your Sales and RevOps teams with the data that they need. I think having a system in place early to streamline that revenue workflow is important, but I strongly believe that it doesn’t make sense for companies to build in-house. It’s a huge product surface area. I think companies set out building with their existing pricing model in mind. The truth is they’re probably going to change pricing, add new products, start leveraging certain custom deal terms, and it’s all the edge cases and billing that really add up to making it quite a complex product surface area, right? 

If your sales team uses a pricing ramp, thinking about how that plays out in your billing, if someone adds a seat or upgrades mid-month, thinking about proration of that in your billing logic, and obviously this becomes more complex if your pricing varies across your customer base, so it is a huge lift. I think we’ve seen, especially before products like this existed, a lot of large tech companies did build billing infrastructure and there’s tons of war stories on why it took them expected weeks to years in the end. It’s never done and it just kind of absorbs a huge amount of resources. 

In terms of what companies should think about when thinking about choosing the right vendor. Does the vendor support your pricing models and give you flexibility to adapt pricing as you scale? Does it support your go-to market motion? Are you primarily a PLG company or sales led? Are you hybrid or between the two? If you are hybrid or sales led, something like Stripe probably isn’t going to work for you as well. If you’re entirely PLG, it probably would work pretty well. Then, also, I think looking at onboarding and setup, and the user experience for the people who are operating it. How quick is it to onboard and get going given your finance team and your RevOps team is probably going to be the primary users, can they make changes in the dashboard without needing to lean into engineering support? And then another kind of key piece, I think that’s extremely important for the modern tech companies, how easy is it to get data out and orchestrate this to other places where you might consume this data? We talked about other critical systems of record like the CRM and the ERP companies own data warehouse. 

If you think about it, revenue data is so critical for informing decisions, for informing sales, commissioning, even informing feature flags on product access – contract data is essential for that. Thinking about how easy it is to get data out of a system and orchestrate that to the other places you need it, I think is also important. One of the things we actually do is we have an RFP sheet that we’ve created. Sometimes when companies come to us and we want some help in thinking about all the different things that they should consider, we actually share a standard RFP with them, giving them all the things that they should be thinking about when choosing a billing vendor, because I think there’s a number of considerations, and once you put something in place, you want it to be able to scale with you for a long time. 

Lauren Houpt (13:05): I thousand percent agree there, and I love that you called out the data piece, which I think is especially important for RevOps teams, especially as they’re putting together their KPIs and everything. Would love to shift the conversation to get your thoughts on pricing. Specifically curious, what are some of the challenges you’re seeing companies face when implementing custom pricing? What does custom pricing even mean? How is it being defined? Would love your thoughts there. 

Riya Grover (13:30): Custom pricing really means that each customer might be on slightly different pricing. Pricing is custom at an individual contract level. That doesn’t necessarily mean you’re deploying a different pricing model for every customer. Often your pricing model is consistent, but larger customer, you’re taking up the price of certain tiers or you are embedding certain incentives for multi-year terms. This is extremely common and it’s what it takes ultimately to get deals over the line. No two customers the same. I think the custom pricing doesn’t have to be challenging. It’s a very natural part of a sales led go-to-market motion. It only becomes challenging when you have billing infrastructure constraints, your ability to leverage custom pricing where, for example, if a sales team deploys a minimum or they deploy a free trial, if your billing engine can’t handle that, I think that’s where it really creates friction downstream. 

It also means that either your operation is extremely manual, or in some cases, you can’t bill or charge for that. Obviously, companies who are deploying usage-based pricing and need the infrastructure to be able to define the value metric that they’re charging on, measure it, but also then connect that usage event data to whatever terms were agreed on in a custom contract. So when every customer is on slightly different pricing, making sure that you are billing for the usage against the terms, the pricing terms agreed for them is really critical. That’s sort of pieces that we’re putting together. Whatever was sold in a contract connected to whatever usage was actually consumed and connecting those two things. The right infrastructure, the right tooling is needed, but it doesn’t necessarily mean that the use of custom pricing must drive complexity. 

One other piece to think about is, again, the contract determines so much of all the revenue operations downstream – with custom contracts also comes the need to adapt revenue recognition. For companies who are using usage-based pricing and custom contracts, finance teams need to think about things like usage-based revenue accrual, and tracking, and recognized outcome-based revenue complying with the right accounting standards for the complex or the custom pricing that they’re deploying.  

I think another interesting piece as well is, in a world where you’re just using subscriptions like the implications on the CS team, the sales team are relatively well, the management of that is relatively simple. You have an end date and then there’s a notification in your CRM as to when that end date is and you reach out for a renewal. In the world where companies are deploying usage-based pricing, the signals required for customer success and account renewal also change. 

CS teams now need access to usage monitoring. They want to be understanding how value is being realized across that contract. They’re going to get signals for upsells and renewals. I think it’s important to think about this connection here, between sales and finance, it’s important both ways. It’s important both for finance teams to be able to have accurate data and capture that seamlessly with whatever sales are doing, but it’s also critical for sales, customer success, and RevOps to have access to billing usage revenue data back in the places that they’re working, so that they get the right signals to grow revenue further. 

Lauren Houpt (17:12): Yeah, totally. I really appreciate that insight and I think it’ll be really helpful for earlier stage companies that are tuning in to this session as well. As we know, most companies now are implementing AI offerings, and so I’d love your opinion on how “AI first” companies should be thinking about value metrics and how to charge for those. 

Riya Grover (17:32): We’re seeing a ton of pricing evolution by virtue of the insane growth that we’re seeing with AI companies, and I think there’s some interesting trends that are I guess just starting to unfold, but I think we’re going to see a lot more innovation around. One thing we’re starting to see more of is outcome-based pricing. Meaning, you charge customers only when your product is successfully achieving a business outcome. Imagine buying a marketing tool and paying only when it generates qualified leads, or a customer service platform that charges per resolve ticket rather than per seat. This is gaining traction across the software industry, but particularly with AI powered software and agents where typically tying the payment to an actual outcome is a really effective way to sell the product. Obviously, this is great because it massively aligns incentives with customers and appeals to decision makers who don’t want to make big, upfront investments for software. 

But I think one thing to note on this is it’s not always easy to define the specific outcome your product provides. Also proving the product is directly contributed to the outcome for the customer can sometimes be challenging – so I think the other thing is once you’re charging based on the outcomes, the people almost start to question those outcomes and the efficacy of them as they unfold. It comes with its challenges, but certainly it’s a model that’s gaining traction.  

We’re also seeing output-based pricing emerge quite a bit. So this is case where you can charge customers on completed tasks or outputs rather than input metrics like API calls or compute time. So, it is a usage-based pricing model, but whereby you’re looking at the output as opposed to the input metric. An example of this is Jasper AI, they charge based on the number of words generated or some fraud detection tools charging for flag transaction. 

Again, I think in the previous case, this works if the outputs can be measured transparently and align closely with the value the customer is trying to derive from the platform. I think one of the quite neat things about this is that it really positions the AI as a direct replacement for human FTEs by virtue of choosing that kind of pricing model, which is kind of directly linked to the tasks being completed or the outputs being generated. You’re essentially, mentally positioning this offering as sort of an alternative to human labor, and that gives the ability to charge 20 to 35% of the fully loaded cost of a human as opposed to what you may be able to from a software perspective.  

The other interesting thing about this is it also allows you to tap into hiring budgets as opposed to software budgets. So, people typically spend a lot more on hiring people than they do on software, and you can tap into those budgets and use signals like open job posting as a powerful prospecting signal. 

I think it’s an interesting approach, and this is a great example of where the pricing model is directly framing the perceived value in the minds of the user. One other kind of interesting piece on the new pricing models we’re seeing is this skills-based differentiation. So OpenAI introduced chat, GPT Pro at $200 a month is 10x the price of GPT plus. And what this is really saying is we’re shifting from feature-based to skill-based value propositions. In this case, the AI capability levels, the reasoning, the problem solving, the enhanced memory is so much more adept than the base version that you are paying for, again, more skilled labor essentially. What’s quite interesting is historically we’ve always seen people charging more SaaS companies, fintechs charging more for the good, better, best notion for more features. The better plan has just more features included. Whereas if you’re hiring an AI to do the job, you almost want to ungate access to whatever features are needed to get the job done. And so in some ways, you’re paying more for higher skills, but actually it’s not at all grounded in how many features you’re getting access to and you’re gating as much as possible for the AI to work. So just some very, very early examples of some pricing evolution that we’re seeing. On the point of hybrid pricing, I do think we’re going to start to see even more hybrid pricing implemented where companies are deploying some of these new pricing models on potentially a new AI feature that they launch whilst retaining some of that existing pricing that they’ve been using. 

Lauren Houpt (22:30): Amazing. Your perspective is super helpful, and I appreciate the examples as well. A follow-on question to that would be – how should companies prepare for pricing changes, whether they’re AI focused or not? 

Riya Grover (22:38): One thing I think is important to remember is that pricing is never done, and it’s really critical that teams have the ability to adapt pricing approaches as their product evolves and their go-to market evolves as well. The billing and invoicing engine, the finance engine should never constrain the go-to-market team in seeing new trends and capitalizing on them or leveraging the deal leavers that they need. And I think it’s important to remember when pricing does change. This does have implication really across the business. We talked a little bit about sales, CS teams, ops teams. Obviously finance need the right infrastructure to be able to actually build an invoice against whatever pricing model has been chosen, but if you are adopting some of these new pricing models, whether usage-based or outcome-based pricing, being able to track and measure that, being able to connect it to the contract terms, and then actually being able to orchestrate that data that’s being generated, that usage and revenue data and how customers are using you to actually then be able to make smart decisions off the back of it. I think pricing does have widespread implications, but it doesn’t mean it needs to be hard. And what you want is the agility to do what you need to do to win. 

Lauren Houpt (24:02): Well, thank you so much for joining this edition of Go To Market Navigator. Really appreciate all your insights. And for those that are tuning in, just make sure you check out Sequence to help solve all those billing and metering pain points. If you had any closing remarks, feel free to share, but I think we’re all set on the Fin side. 

Riya Grover (24:21): Great, it was great to be on. Only closing remark is that we’re leaning very strongly into leveraging AI in thinking about how we can help teams automate more of this multi-step workflow capture smarter, intelligent insights on their revenue and lots to come from sequence in this space. So yeah, excited to share more over the coming months!