Ultimate Guide to Usage Based Pricing
What is usage-based pricing?
Usage-based pricing is a strategy where customers are charged and billed based on how much of a service or product they use. This could be anything from the number of API calls, gigabytes of data used, kilowatt hours of energy, or outputs from a chatbot.
This flexible pricing approach provides value and transparency to customers and helps build trust and loyalty. Usage models are used across multiple industries, including cloud computing, utilities, and telecommunications, where they allow businesses to scale their services according to customer needs and usage patterns. Usage-based pricing and hybrid models are also quickly becoming the model of choice for AI and GenAI offers, both for vendors and their customers.
Launching a usage-based model can seem like an insurmountable challenge, but this guide will provide the knowledge and strategies you need to successfully make the shift across your business.
Why usage-based pricing?
Usage is fast emerging as the pricing model of choice for companies across industries, especially those developing and launching new GenAI offers. This is because the model provides good alignment with and demonstration of value to the customer.
Subscribed Institute research has shown that many of the fastest growing SaaS companies leverage a usage-based model. In fact, the number of companies employing some form of usage-based pricing increased 9% to 26% between 2020 and 2022.
Why are usage models so popular?
Usage-based pricing can be a competitive differentiator and may enable a lower cost of sale and lower barriers to entry. And when used as part of a hybrid model, usage has been shown to contribute to higher year-over-year (YoY) annual recurring revenue (ARR) growth across all company sizes.
Customers are increasingly demanding a clear return on investment (ROI) and lower upfront risk—they want a better picture of what they’re using and how much value they’ll derive from your product. And 80% of customers report that usage-based pricing provides better alignment with the value they receive.
Customers like flexibility when they are first trying a product, which makes simple pay-as-you-go pricing a good option for onboarding new customers. But as they adopt and grow more confident in your solution, they are going to want more predictability. Therefore, customers will expect the nature of how they pay for their consumption of your product to change as their relationship with you grows. As a result, your monetization capabilities will also need to be ready to change to meet customer expectations.
Getting started with usage
Whether you’re adding a new product or implementing a new usage-based business model, you know you need to take action quickly—before your competitors catch up. But the data can be hard to wrangle, pricing experimentation takes too long, and you aren’t sure how to mix and match multiple pricing models.
In this chapter, we’ll walk you through the steps to determine if usage is right for your product, customers, and business.
How do you know if a usage model is the right choice?
When deploying usage, there are three key factors that must be considered in order to achieve recurring growth: the company and product, use cases, and pricing model.
Company and product
Usage-based business models can be a powerful lever for growth, but some companies hesitate to implement them because of the perceived risks and investments involved. Building the capabilities and deploying in the appropriate situation is critical. Consider the following variables:
- The tech stack: How does the entire technology stack align with respect to flexible use? For infrastructure as a service (IaaS) and platform as a service (PaaS) companies that sit on an AWS stack, usage flexibility is critical, and usage models tend to fit well. AWS EC2, Snowflake, and Fivetran are examples of three different technology offerings that are complementary and aligned in flexible use.
- Product-led vs. sales-led growth: Pure usage-based models often work well with product-led growth because they scale naturally without the need for selling a new contract. Sales-led paradigms can work with usage-based as well, but often are best suited for committed spend or hybrid contracts.
- Fixed vs. variable economics: For products with more predictable cost of goods sold (COGS) and stable usage patterns, a recurring user-based subscription model would likely be a good choice. For products with spikes in consumption and variable costs (e.g., in many Generative AI use-cases), usage, outcome-based, or hybrid models would be a better choice.
Use cases
A key insight from our data analysis reveals that most deployments of usage-based pricing actually involve a combination of usage and recurring charges as part of a hybrid model. Companies that succeed in their deployment often target use cases more aligned with the benefits and value they bring.
A few example use cases where usage-based models often make more sense include:
- Spiky demand profiles (e.g., certain analytics workloads, Snowflake) where flexibility is more important than predictability.
- Seasonal businesses and industry sectors (e.g., retail technology around the holidays, accountants at tax season).
- Generative AI tools that have a variable consumption of tokens.
Pricing models
As you plan your usage model, it’s good to know what your pricing options are. Here are just a few that you can mix and match as you fine tune your strategy:
- Pure usage: A pay-as-you-go usage model offers the most flexibility for the customer and can go to zero in a month where they don’t use the product.
- Overages: This model gives customers a certain quantity of units per billing period. Anything over this limit is charged per-unit based on the overage price.
- Minimum commitment: With this model, customers are charged at their commitment level on each invoice, even if they don’t consume the committed usage amount.
- Hybrid consumption: This approach employs a mix of both subscription and usage-based charge models for a single offering.
Related resource
How usage models contribute to business success
Learn the proven strategies and tools to launch and scale a usage pricing model. Our research has shown that SaaS companies using hybrid models outperform all other businesses when it comes to recurring growth.
How do you implement a usage model?
Now you know the benefits of usage and how to choose the right model or mix of models for your business, but how do you implement usage pricing quickly and what features should you look for?
Here are the top 4 capabilities you’ll need to make your usage model a success:
1. Price without developer intervention
- No-code pricing tools: Change pricing models or adjust price points without needing extensive developer resources.
- Automated pricing updates: Ensure that changes in pricing are reflected across all systems, including in-app purchases, eCommerce platforms, and CPQ systems.
- Data-based value metrics: Quickly track and define meters you can monetize across all of your products.
2. Experiment with diverse pricing strategies
- Try a mix of models: Include volume, tiered, multi-attribute, or pay-as-you-go options to cater to different customer needs.
- Prepaid credits and top-ups: Allow customers to manage their budgets better by prepaying and using credits as needed.
- Discounts and trials: Introduce promotional pricing or trials to attract new users and encourage consumption.
3. Capture, measure, and track usage data
- Automated mediation: Effectively manage the aggregation and processing of usage data, ensuring that data from various sources is normalized and accurately represented for billing.
- Scalability and integration: Seamlessly integrate usage data into billing systems and support scalability by handling large volumes of data without compromising on performance.
- Dynamic data integration: Stream usage from various sources then automatically enrich, aggregate, and deduplicate the data.
4. Analyze and optimize for growth
- Real-time analytics: Continuously monitor and analyze usage patterns to understand customer behavior and adjust offerings accordingly.
- Cost and revenue tracking: Compare costs against revenue for each pricing plan to identify the most profitable strategies.
- Experimentation: Apply different pricing plans to the same usage data to discover which maximizes revenue and customer satisfaction.
- Cross-functional implementation: Successfully roll out new pricing company-wide by consulting and planning with multiple stakeholders, such as sales and revenue accounting teams.
What is usage mediation?
Usage mediation helps maximize the information implicit in each and every usage event by consolidating, metering, and tracking all customer usage data. Accurate and timely data about how your customer is actually using your product or service is imperative for optimizing your usage pricing and billing strategy.
Many companies who are just beginning their usage journey jump right into rating, which is the process of selecting and implementing a pricing plan. But before you can optimize your pricing and packaging, you must first gain a comprehensive understanding of your customer and their consumption patterns. This can be achieved by gathering and measuring customer usage data through mediation.
While customized or add-on solutions can be layered on top of your billing system to ingest and measure usage data, the most efficient and cost-effective solution for the majority of businesses is a mediation engine—a purpose-built solution that can handle all your usage data needs and integrate with your current billing and revenue recognition systems.
What is a mediation engine?
Much like the electric meter on your house measures your power usage and turns it into billable kilowatt hours (kWh), a mediation engine meters and measures each of your predefined usage value metrics. For your business, these usage value metrics might be GB of storage or minutes of call time instead of kWh, but the idea is the same.
But usage data and the mediation process can and should be used for so much more. In order to successfully drive recurring growth using a usage-based strategy, you need to be able to uncover actionable insights, like cross-sell/upsell opportunities or cost-saving strategies. When you can understand more about how, when, why, and where your customers are using your product, you can fine-tune your offerings, pricing, and your product itself.
Many companies doing usage either don’t know what type of mediation solution to look for, or they don’t yet realize they need one. R&D and IT teams are often saddled with building and maintaining custom solutions, such as a homegrown mediation tool.
Alternatively, they may opt for an add-on product or an extract transform and load (ETL) tool—but ultimately—most businesses discover that these solutions require a significant amount of developer time and can drive up costs.
A mediation engine, on the other hand, will provide all the tools your business needs to collect, transform, meter, and track usage data. It should give product managers the real-time visibility they need to quickly and seamlessly pivot pricing from pure pay-as-you go to hybrid usage models—and everything in between.
As part of your larger usage-based pricing strategy, a mediation engine should help provide customers with the flexibility to consume what they want when they want and the transparency to keep an eye on their usage and charges.
Ingesting and storing usage data
To begin mediation, you’ll need to collect usage data from all relevant sources. This could be data from user interactions, system logs, sensors, or other sources.
If you don’t have a mediation solution, your IT team will likely have to manage, route, and clean up all of the usage data coming from your product. After aggregating thousands of events into a data warehouse, they’ll then have to analyze and transform the data to make it accessible.
A mediation engine can automatically stream near real-time usage data from multiple sources using APIs or batch uploads. Look for a solution that allows you to stream at high volumes (up to ~200K) of usage events, so you’re able to accommodate peak periods.
And, by using a purpose-built mediation engine for aggregation and storage, your usage data becomes more manageable, accessible, and secure. Plus, removing the need for a separate data warehouse can help cut unnecessary storage costs.
Transforming usage data
Transforming usage data is a crucial step in converting raw, often unstructured data into a format that is suitable for analysis, metering, rating, billing, and revenue recognition. During this step, you’ll need to clean the raw usage data to remove inconsistencies, duplicates, irrelevant data, or outliers.
Next, you’ll need to standardize data formats and apply transformations specific to your use cases. For instance, if your key usage value metric is GB of storage used, you’ll want to make sure that all relevant data is expressed in this way. This will ensure consistency across the dataset and increase the usability of the data across multiple business units.
How can a mediation engine help with data transformation?
Data transformation can be an extremely laborious and error-prone process when done in a homegrown mediation tool or even in an ETL. A dedicated mediation solution is crucial, allowing you to plug in new sources of usage data very quickly, in a standard format that billing and revenue recognition teams can consume. Look for a solution that can free up data teams’ time with automatic deduplication, transformation, and verification capabilities.
Metering usage data
After aggregating and transforming your usage data, you must measure it in a process called metering. To do this, you’ll need to determine the metrics that are relevant to your product or service by analyzing customer data. These are the parameters or attributes that you’ll measure and use to charge your customers. When it comes to usage-based pricing models, you’ll want to identify and measure key usage value metrics.
These key metrics should not only be usage attributes that your company can track, but should also satisfy value alignment, leave room for growth, and offer predictability both for the customer and your business. Research shows that companies utilizing hybrid consumption models, with metrics anchored on both usage and recurring revenue—outperform all other businesses when it comes to year-over-year (YoY) annual recurring revenue (ARR) growth.
Companies that already have an ETL tool might leverage it for usage metering, but ETL tools only do batch loads, so developer involvement is still required to customize and maintain. And as new offerings are added, metering requirements can slow down the time-to-market.
Revenue recognition will be impacted too—when proper metering and measurement of usage data isn’t occurring or data isn’t in a form that’s readily available to accounting, rev rec will be slowed down and the business will suffer.
How can a mediation engine help meter and identify key metrics?
A mediation engine can assist collecting, aggregating, analyzing, and monitoring data related to customer usage. This data-driven approach can help you make informed decisions about which metrics are most relevant for your pricing model, ensuring that you align your pricing with customer behavior and value.
The more attributes you have to base your pricing on, the more you can create the perfect offering for your customers. Look for a solution with drag and drop capabilities, making it easy to quickly put together the right combination of metrics.
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Finding the right metric
Common metrics include: number of users, amount of data consumed, or number of events.
When determining the right usage value metric for you, consider attributes that are:
- Value-based: The value exchange must be apparent to the customer. The more this metric is used, the more value the customer receives.
- Measurable: The metric must be tracked and measured accurately. You cannot charge on things you cannot measure.
- Controllable: If you charge a customer for usage, they must feel in control. Do not leave it to external factors to determine the customers’ bills.
Tracking usage data
To link all of these steps together and help you continually iterate on pricing and packaging, you’ll need a system to track usage data from collection to revenue recognition.
Having a reliable system to track and store usage data is also vital when it comes to customer disputes. If you’re using a homegrown, add-on, or ETL solution for mediation, your usage data may not be auditable or defensible when customers have disputes, which means that it can take weeks for billing ops and developers to surface detailed usage data for customers.
Customers value real-time usage visibility, enabling them to track daily progress, anticipate overages, and view their billing charges. Tracking usage data gives you the ability to push out threshold notifications, allows customers to monitor their spend, and increases overall customer satisfaction. And usage forecasting can enable businesses to monitor behavior and predict expansion opportunities for customers with high usage.
How can a mediation engine help track usage data?
Look for a system that can automatically track and report on attributes, such as how much of a service is used, who used it, or when it was used. A mediation engine can track data as it flows across relevant systems and teams, increasing transparency for the business and your customer.
Pricing and packaging for usage models
Usage models are built around both pricing and packaging. Pricing is your price points and pricing models, while packaging is how features are bundled. Together, they are what enable the value and flexibility your customer expects and the predictability and strategy your business requires.
Let’s dig a little deeper into both pricing and packaging to better understand how they constitute the framework of usage.
A clear pricing strategy is mandatory
Usage-based pricing is at the core of any pure consumption business model. Providers must be able to measure how much product a customer uses in order to bill effectively. This concept may be referred to as a “value metric,” “unit of measure,” or “pricing basis.”
Your value metric is a usage attribute your company can track that also satisfies value alignment, leaves room for growth, and offers predictability for both the customer and your business. Common metrics are value-based, measurable, and controllable, such as number of users, amount of data consumed, or number of events.
After selecting a value metric, the next step is to determine a price per unit of consumption. This “rating logic” can be as simple as a flat price per usage event (like an API call) or as complex as multi-dimensional algorithms (like a combination of compute and storage).
Another critical pricing component is the notion of time — when a customer agrees to pay for their consumption of a product. Some of the most successful businesses have no more than 25% of their total revenue coming from usage models. They anchor pricing on a value metric first and then grow that pricing by combining pay-as-you-go models (low risk) with pre-paid models (high predictability), thereby driving recurring growth.
What are common usage pricing models?
There isn’t a one-size-fits-all model for usage pricing. As our data shows, you have to find the right level of usage-based pricing within an overall usage-based business model to maximize growth. To see the greatest recurring revenue growth, consider a combination of several models to achieve a hybrid consumption model.
Let’s take a look at the most common pricing models.
Per-unit or pay-as-you-go
This pure usage model allows customers to pay for what they use. This is a solid option for customers with unpredictable needs, and this method does allow for spikes in usage and those associated costs. This option gives the most flexibility for customers to consume only what they need. A pay-per-ride service like Chariot or pay-per-API offering like Amazon Web Services are great examples of this.
Volume
Volume pricing is used to charge a price based on the volume purchased. This kind of pricing can make a lot of sense for certain use cases, such as API calls for SaaS. For example, if you do 1-1000 API calls, you might charge $.10 (flat or per unit), but if you go from 1,001-10,000, you will charge $.15 each. This kind of pricing can be a great incentive for a consumer to use more of the product since the price per unit gets cheaper.
Tiered or step pricing
Tiered pricing is used to change pricing progressively as the volume increases. Like the volume pricing model, the tiered pricing model uses a price table to calculate the pricing. It differs from volume pricing in that the amount to charge varies progressively as volume increases, so different units may be priced differently depending on the tier they fall into.
Overage
This pricing model gives your customer a certain quantity of included units—for example, minutes for calls per month. If your customer exceeds the quantity of included units within the billing period, the amount used over the included units is charged on a per-unit basis based on the overage price.
Tiered with overage
This charge model is similar to the tiered charge model, except there is an overage charge for any units consumed above the ending units of the final tier.
Multi-attribute
This charge model charges customers through a variety of different metrics. For example, Zipcar charges customers through a combination of time of day, type of car, day of the week, and other attributes.
Pre-paid with drawdown
Customers pay upfront for a set of units (or hold a cash balance) that is drawn down from over a period of time. This offers flexibility for customers, in terms of choosing a prepaid amount, and revenue predictability for business.
Minimum commitment
This allows you to charge your customer at their commitment level on each invoice, even if they don’t fully consume the committed usage amount. With this model, businesses have a level of predictability into revenue expectations according to the customer’s commitment level.
Hybrid consumption
Recently, hybrid consumption models that combine predictable subscription approaches with more variable usage models have stepped to the forefront as drivers of recurring revenue.
Although the SaaS sector is still fine tuning these pricing and packaging strategies, the results are promising compared to non-usage models.
While pure usage revenue can be less predictable and more volatile, hybrid consumption models can be a good fit for SaaS offerings—particularly cloud services and generative AI. These hybrid, agile models can help provide predictability, while also improving value to the customer by tying pricing and payments more directly to usage and actual demand.
Create a culture of experimentation
The industry conversation around pricing and packaging has recently added an important consideration: experimentation. While everyone would love to say they have great pricing, the reality is businesses are always tinkering, thinking, “What can I do here? What can I do there? Are my customers really receiving value? Am I capitalizing on that value? Do they feel good about paying for the value they receive? When is the last time we’ve tinkered with pricing? How does that compare to our competitors?”
These questions are great starting points for building experiments around pricing and packaging to discover combinations and approaches that make sense for both your customers and your business.
You also need executive buy-in when it comes to technology that supports rapid experimentation with mix-and-match pricing and packaging, as well as leadership that encourages cross-functional collaboration between teams.
Surfacing offers is one example of pricing and packaging experimentation. Historically, it’s been focused in the media space — like going to a newspaper’s website for their premium articles and then hitting a paywall after a certain number of visits. But these strategies also exist for SaaS businesses, such as a free product trial that the company then attempts to convert into a paid subscription or an upleveled service.
Dynamically surfacing offers is just one method of pricing and packaging experimentation that can lead to increased revenue and improved customer service.
Best practices for experimentation
Experimenting with pricing and packaging has helped many businesses become better at usage-based pricing. Here’s an idea of what continuous fine-tuning looks like:
- Experimenting frequently: Avoid the “we did this last year” mindset and instead get comfortable with iterating as often as possible.
- Running tests: Learn from your data by split testing (also called A/B testing) different versions of it and evaluating based on metrics like conversion rates.
- Trying model variations: Start simply with pay-by-use approaches and then ramp up to something more complex like tier-based usage.
- Using specific tactics: Plan strategic experiments that are specific to where your business is on its value realization journey.
- Keeping customers in mind: Listen to what customer support and billing ops are hearing about the value of your offers.
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Tools for usage success
Whether you’re just starting to test usage or you’re fine-tuning your strategy, you need a proven solution that provides a variety of out-of-the-box models — like pay-as-you-go, pre-paid with drawdown, minimum and maximum commit, and pooled usage pricing.
Look for a solution that supports pricing and packaging experimentation and iteration, without the need to rely on developer support or delay product rollouts.
Looking at usage through the lens of finance
While usage models are great for certain types of services, they are by no means a “one size fits all.” And many of your customers will see it that way too. If you’re looking at adopting a usage model for the first time, it’s important to take a measured approach.
CFOs need to understand the multi-faceted nature of usage pricing to decide if it’s the best fit for their business—and if so, what kind of strategy, communication, and organizational buy-in are required for success.
That’s why we’ve created a checklist of the top questions to ask if you’re thinking about taking the leap into usage. These questions can help you determine whether it’s right for you and what you need to know to execute usage pricing successfully.
What kind of customer data do you have, and can you use it to forecast customer usage?
The foundation of usage pricing is customer usage data. You need complete, accurate, and timely usage data that can easily be used for rating and billing customers in a reliable, auditable, and defensible way. Unclear usage on a big invoice can quickly absorb hours of your billing ops, support, and even sales teams’ time.
Clean data is also important for supporting accurate forecasting. By nature, usage models are less predictable than traditional subscription models, which makes accurate forecasting more difficult but also more important.
For example, if you have customers paying for a SaaS license with a yearly contract, you can count on that revenue for a full year, regardless of how much the customer uses the product. But with usage models, revenue can change every month, day, or even minute.
As a CFO overseeing a usage model, understanding usage patterns in order to accurately forecast will become one of your top priorities.
Without clean usage data, everything about a usage model becomes significantly more difficult. Whether it’s API calls, number of emails sent, tasks in an application, file uploads, or logins, getting a handle on customer usage data and insights should be the primary focus for any CFO starting a usage journey.
Usage forecasting also brings a unique challenge when it comes to recognizing usage revenue. For instance, here’s a common issue encountered by businesses: FP&A or sales operations teams may develop their own usage forecasting without incorporating the more nuanced revenue treatments demanded by ASC606. This can result in vastly different forecasts from one end of the business to the other.
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Make the most of your data
Work with your analytics team to consolidate and evaluate usage data to uncover trends and help inform the selection of usage value metrics. Consider adding a mediation engine—a purpose-built solution that can handle all your usage data needs and integrate with your current billing and rev rec systems.
To increase the accuracy of usage forecasts, CFOs should encourage cross-functional collaboration within the organization and alignment on the business’s approach to new use cases.
Is your technology flexible enough to support multiple models and meet changing customer demands?
Usage models shine when it comes to product-led growth. Pure pay-as-you-go pricing reduces risk for customers and gives them confidence to try your product, which in turn may help increase your customer acquisition rates at a lower cost.
Ideally, at some point your customer’s use of your product grows to the point where the cost becomes material to their business. At this point in your customer’s consumption lifecycle, two key concepts become critical—notifications driven off real-time metering and rating and being able to offer more predictable contract terms and pricing models.
Real-time metering and rating
For usage pricing to work long-term, you need a system that provides real-time usage rating and threshold notifications. There is almost no worse customer experience than being surprised with a surprisingly large invoice they weren’t expecting.
It will always be imperative that you give your customers as much transparency about their costs as possible, in as close to real-time as possible. The best businesses attack this problem from multiple angles by offering self-service portals, triggering threshold notifications, and arming their field teams supporting customers with data tools to stay ahead of any surprises.
While customized or add-on solutions can be layered on top of your billing system to ingest, meter, and rate data, the most efficient and cost-effective solution for the majority of businesses is a mediation engine—a purpose-built solution that can handle all your usage data needs and integrate with your current billing and revenue recognition systems.
Adding predictability
If there’s one thing CIOs hate, it’s surprising their CFOs. Pay-as-you-go models work great for enticing customers to try new products, but if you’re not ready to offer contract terms and pricing models that give them more predictability, you’re likely to lose these customers to a competitor who will.
So, while pure usage-based pricing is good for acquisition, adding recurring and pre-paid models to create a hybrid offering tend to be better for retention and allow you to lock customers into a more predictable agreement that serves all parties better.
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Adopt the right tools and strategies
When determining what usage pricing model to use for a particular product, Subscribed Institute and BCG recommend considering the following factors:
- How macro-trends are influencing the landscape
- Trends and successful strategies observed in other business
- How customers derive value from the product
- The nature of the business and product
- The technology required to support end-to-end usage model implementation
Assessing this for each product and journey stage will likely lead you to a hybrid consumption model that includes usage along with other offerings. Therefore, it’s critical that your tech supports multiple pricing models and enables the agility to mix and match models.
Are you set up for accurate and compliant financial reporting of usage-based revenue recognition?
The conversation about revenue recognition should begin as soon as the business elects to incorporate usage-based pricing. With a usage model, you might charge a flat fee, offer a volume or tier discount, or use multiple units of measure depending on the country, time of day, or any of dozens of other variables. These varying permutations could create multiple different prices for the same service.
The charge model you implement determines your financial relationship to your customers, and it obligates you to accurately report on that financial relationship in a compliant way. In particular, ASC 606 can make usage pricing tricky. Usage models require granular, real-time visibility, not just to total up usage at the end of a billing period, but also to monitor customer usage at any given time.
Even with the addition of a usage model, you will need to layer in a recurring component. That could be a true prepaid model, a credit system, or a system tied directly to the usage metric itself—for example, gigabytes of storage. At this point it’s also important to consider what you’ll do if a customer doesn’t use everything they prepaid for and how that discrepancy could impact subscriber experience.
If customers are prepaying on a contract, for example, that creates liability for you as a company and obligates you to deliver against the contract. The customer determines when they want to draw on what they’ve paid for, and that determines when you deliver against it and have to report to the street.
As different customers draw down their balances at different rates, you face another layer of complexity to tracking and reporting earned and deferred revenue.
This is different from a prepaid model based on availability. For example, SaaS subscription companies often charge customers for one seat for one year, even if they collect payment on a monthly basis. How or when the customer chooses to use that seat doesn’t impact the SaaS company’s revenue because their obligation was simply to make the service available.
With usage, however, tracking usage is important not just for providing the service, but also for tracking revenue.
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Add more automation to reduce manual work and risk
Work with the business to find the right usage equation to facilitate growth and adhere to rev rec rules under ASC 606.
Adding a solution with real-time analytics and a close process dashboard can allow you to achieve a high-level understanding of financial data for the current open period, identify data problems, mitigate revenue errors, or make adjustments throughout the month that allow for real-time GAAP revenue reporting.
How will usage pricing impact your go-to-market strategy?
Usage pricing requires a sales model that doesn’t just bring in customers, but also ensures they use the product.
The role of the sales team in a traditional product sale is over as soon as the product is delivered. With a subscription, the sales team closes the deal and then takes a backseat until renewal time one or two years later.
But usage pricing requires a sales model that provides self-service, such as allowing customers to come to your website and try your product by signing up and test driving it.
Here, the sales team needs to stay engaged throughout the customer journey to help customers ramp up their use of the product.
Many companies are changing their compensation plans to incentivize reps not only to land big, prepaid deals that capture payments up front, but also to tie compensation to how much customers use the product. Reps only make full commission when they verify the customer has used everything they bought.
This type of go-to-market strategy can also affect the AE to SE ratio, the other technical roles needed to support sales, and the ways partners engage.
Companies often start their usage journey with a growth team focused on launching product-led growth. They explore how to make the product more self-service-oriented and which usage models will get customers in the door to test the product.
Then, once they’ve pivoted to product-led growth and gained traction, a second stage of the journey involves getting the customers to commit to a prepaid recurring contract.
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Ensure your business can support usage operationally
At a time when many customers are tightening budgets and consolidating technology, your ability to demonstrate value realization is crucial. With usage models, it’s imperative to show ROI not just once a quarter or once a year at renewal time, but continuously.
Keep sales in the loop across the customer journey to help support and drive a product-led growth strategy. Begin experimenting with usage packaging to introduce a prepaid recurring contract. Lastly, consider adding customer success managers and incentives for your sales team.
The keys to usage accounting success
Making the move to usage-based pricing can be a win for both your customers and your business—but what does it mean for accounting teams? Accountants often have an aversion to usage-based pricing, because it introduces a whole host of new variables to revenue accounting, which is already extremely complicated.
To help ensure the successful company-wide roll out of a new usage-based pricing model, revenue accounting teams must be consulted and included in the planning stages. During implementation, they must be provided with the necessary tools and processes to forecast usage revenue streams, coordinate cross-functional data capture and analysis, automate usage revenue recognition, and support more complex pricing models.
Start planning for usage now
Perhaps your company isn’t considering usage just yet, but chances are, it could be coming your way sooner than you think. More and more companies are choosing to add at least some level of usage pricing to their mix of models.
But a usage-based pricing strategy can also present its challenges. Over three quarters (76%) of revenue accounting team members already report growing pressure to support new go-to-market models, products, and pricing. Adding usage will only serve to further increase rev rec complexity and the pressure placed on teams.
Revenue accounting teams are uniquely positioned to help the business understand the key role that rev rec systems and processes will play in the overall success of a new pricing model rollout. We will cover this more in the next section.
By shifting from a traditional back-office role to a comprehensive front-to-back perspective, revenue accounting leaders can ensure stakeholders know the downstream implications of their decisions and how they might come back upstream.
Revenue leaders can also provide guidance on how best to structure pricing to enhance revenue predictability and reduce operational burden. As we’ll discuss later, the most successful usage businesses are combining several pricing models, along with some level of commitment, to help balance flexibility for the customer and predictability for the business.
However, revenue accounting must also ensure proper processes are in place on the sales side to help customers purchase the appropriate base plans to begin with. Otherwise, the revenue team will be required to estimate the contract value (base value plus expected usage) and adjust that estimate on a predetermined cadence.
Forecast usage revenue using existing business use cases
Usage forecasting enables revenue teams to anticipate how much revenue will be gained through usage-based pricing models. This means forecasting variables such as usage, customer lifetime value (CLV), and potential overage charges. This gets ever more complex when you begin introducing different bundles and offers.
Part of the appeal of usage models is that they allow customers to vary their use of a product or service, and therefore their charges, but this can make revenue predictability and forecasting tenuous.
Often, the unique challenges and potential pitfalls presented by usage forecasting are not realized until accounting is tasked with recognizing usage revenue. For example, FP&A or sales operations teams may develop their own usage forecasting without incorporating the more complicated, GAAP-compliant revenue accounting policies required for usage data and contracts. This can result in vastly different forecasts from one end of the OTC process to the other and may require a cumbersome reconciliation.
To avoid this, revenue accounting teams should advocate for cross-functional networking within the organization and alignment on the business’s approach to new use cases. Look for technology that can capture and analyze multiple dimensions of upstream data to quickly identify and resolve issues. In addition, real-time reconciliation and a close process dashboard can increase visibility and the accuracy of your revenue forecasts.
Push for data capture and analysis alignment across teams
Real-time usage data visibility and analytics are vital for revenue forecasting. Unfortunately, attaining cross-functional alignment for usage data processing and flow across the organization can be extremely challenging. Multiple stakeholders within the business—including IT, sales, billing, accounting, and other teams—must be aligned on how data will be captured, metered, and stored.
Working together with the appropriate stakeholders, revenue accounting teams can help drive company-wide initiatives to eliminate unnecessary data silos and implement system integrations. Creating a process map upfront can help identify all potential error points in the flow of data from provisioning through billing, revenue recognition, forecasting, commissions, and other cost calculations.
Companies performing manual usage revenue recognition will quickly realize the added risks and costs associated with this complicated process. Look for technology that can handle your usage data and automate processes at every step, from capture through to revenue recognition.
Maintain revenue recognition compliance and associated costs
All revenue accounting teams are familiar with ASC 606 and IFRS15. However, leadership may not have considered the implications of these standards with respect to usage based-pricing models.
While a usage-based contract is fairly straightforward, companies quickly realize that to stay competitive and increase customer loyalty, they need to begin adding discounts and bundles. And to increase predictability, businesses will often begin introducing some level of customer commitment.
Revenue teams often initiate this process using spreadsheets, manually inputting usage data into Excel. But this manual work and siloed data will increase workloads, errors, and time to close.
In addition, it can become nearly impossible to generate accurate reports and forecasts or keep up with a myriad of new contracts and modifications. While many try to address these issues by increasing headcount, this will only add to costs and doesn’t resolve any of the initial process problems. Without a system in place to handle complex usage revenue recognition, revenue accounting teams are left to perform data manipulation within thousands of lines of spreadsheets.
Manual extraction and manipulation of data, combined with employees working long hours late into the evening to close the books at the end of the month, creates an unmanageable risk of human error that inevitably results in process failures. In fact, 65% of revenue accounting team members report being concerned about the risk of misstatement because of existing manual processes and control risks.
Manual usage revenue recognition processes, along with increased scrutiny from auditors, will make audits more time consuming and expensive, as auditors will be forced to sift through thousands of lines of usage data. For companies launching an initial public offering (IPO), issues uncovered during the audit process could cause delays.
Revenue automation reduces errors, risks, and audit costs by taking humans out of the equation with a hands-off data management approach. Companies like The New York Times are already leveraging the power of revenue automation to manage usage data from millions of customers. From contract modifications to rolling out new offers, your system needs to automate all aspects of your usage model at scale.
Automate revenue recognition to streamline processes
Successfully managing usage data can require multiple tools to track data, meter usage, and analyze historic revenue trends.
Even some level of automation in the form of an ERP may not be enough, since legacy systems were not built for usage. ERP solutions are still built on the basis of handling one-time product fees, and are often not able to fully support usage pricing models without significant customization efforts. Unfortunately, even with customizations, 60% of revenue accounting team members report that their ERP revenue modules do not fully support their business requirements.
Usage models also require granular, real-time visibility, not just to total up usage at the end of a billing period, but also to monitor customer usage at any given time. The time and money spent on retrofitting ERP systems for new models can stall initiatives.
Revenue accounting teams are already feeling the strain of this lack of automation—68% report not having the right technology to address growing demands from the business. Adding a new usage model without the necessary technology is certain to exacerbate these issues.
By centralizing revenue data through automated integrations, you can eliminate sprawling networks of spreadsheets that need to be updated and linked manually. Eliminating a large chunk of time-consuming, low-value manual tasks translates directly into operational efficiencies and significant savings in both time to close the books and money. Many teams experience a reduced time to close, a reduction in employee overtime, and the ability to focus on more strategic tasks.
More and more companies, especially those adopting usage, have shifted away from managing revenue recognition within an ERP. Instead, they turn to specialized revenue subledger solutions that can operate as a revenue subledger and feed data directly to the ERP general ledger.
The advantage of these point solutions is their native capability to provide features that are critical to the usage revenue accounting process, such as SSP analysis, contract modification, and revenue analytics—without expensive or complex customizations.
Secure executive buy-in
While 79% of revenue accounting team members agree that they need higher levels of automation, 67% say they struggle to get buy-in from leadership in order to implement these new solutions.
Given the many hats CFOs and other finance executives must wear, it’s not surprising that they might not have full visibility into the nuances of the revenue process, especially with respect to usage models. Bringing leadership up to speed on the current process, risks, and the implications for supporting a new go-to-market model can help make the business case for automation. And educating finance executives on the benefits of end-to-end revenue automation and the cost of inaction can help revenue leaders further bolster their case.
Expand beyond basic usage models
While traditional usage-based pricing strategies, such as pay-as-you-go and overage, are great for giving customers the flexibility they require, they are not always effectively used by businesses. The reality is that usage models like these, when used in isolation, have the potential to take away some of the revenue predictability to which subscription companies may have become accustomed.
Subscribed Institute and Boston Consulting Group (BCG) research indicates that companies utilizing hybrid consumption models—with a mix of revenue from in-arrears and in-advance models—outperformed all other businesses in terms of YoY ARR growth.
Put simply, these companies have tapped into the growth potential of combining simple usage-based pricing with other recurring charge models to increase customer commitment, facilitate better forecasting, and add recurring revenue streams. In practice, this could look like a traditional pay-as-you-go model, combined with an in-advance prepayment and overage charges.
Related resource
How usage models contribute to business success
Learn the proven strategies and tools to launch and scale a usage pricing model. Our research has shown that SaaS companies using hybrid models outperform all other businesses when it comes to recurring growth.
Looking at usage from every angle
Implementing usage-based pricing presents a unique set of advantages and challenges. In this chapter, we’ll explore the intricacies of these models, highlighting the pros and cons, as well as presenting practical solutions.
What are the advantages of a usage model?
An ever-increasing number of consumers and businesses have encountered usage-based pricing and billing—and they’re demanding more. In fact there has been a significant increase in the adoption of hybrid consumption models over the last 3 years.
Let’s explore some of the benefits of implementing a usage-based pricing model.
Customer-centric approach
Usage-based models focus on providing value that directly correlates with customer needs and usage, rather than imposing flat rates or bundles. Usage data can provide valuable insights into customer behavior and preferences. Companies can use this data to offer personalized upgrades or additional services tailored to the specific needs of each customer, enhancing the perceived value and differentiating their service in a crowded market.
This pricing model also allows businesses to cater to a wide range of customers, from startups to large enterprises, by offering plans that scale according to usage.
Differentiated value proposition
By targeting the right value metric and optimizing the level of usage pricing businesses can differentiate themselves from competitors and create a strong value proposition. Plus, usage-based models enable companies to quickly adapt to market changes and evolving customer needs without significant restructuring of their pricing strategies.
Recent Subscribed Institute research also indicates that SaaS companies employing usage-based models are maintaining a long-term revenue growth advantage over their non-usage counterparts.
Flexible and scalable growth
Because the barrier to entry is lower, customers can start small, see the product in action, and consider if they want to sign up for a more robust package when the time is right. As customer demand increases, businesses can then adjust resources in order to accommodate higher consumption levels.
Visibility and control
Customers value real-time usage visibility, enabling them to track daily progress, anticipate overages, and view billing charges. With the right technology in place, usage models can enable your business to push out threshold notifications. This allows customers to monitor their usage and spending, and ultimately, increases overall customer satisfaction.
Usage forecasting can also enable your business to monitor behavior and predict expansion opportunities for high-consumption customers.
Predictable revenue streams
While usage-based pricing models are typically associated with variable costs based on actual usage, companies can introduce predictability by linking prior commitment to customer spending habits. These hybrid consumption models can lead to higher YoY ARR growth across all company sizes.
This approach is often referred to as “committed usage” or “pre-paid consumption.” These strategies are fast emerging as the models of choice for companies launching AI and GenAI, due to their potential to drive growth and profitability even in the face of astronomical costs.
What are the challenges of a usage model?
Implementing a usage-based pricing strategy can also present its challenges. Companies need to balance value, while also having enough cash to cover costs. Pricing too high could put some customers off, while pricing too low will result in a loss.
Implementing usage-based pricing requires planning and consideration of the potential risks and challenges.
Surprise overages or shut-offs
Surprises lead to terrible customer experiences. For this reason, customers tend to dislike simple pay-as-you-go billing—it may not provide the predictability they require. The nature of usage pricing means that customers might not realize how much they’re using.
The answer is transparency and mediation—customers need to stay apprised of their consumption patterns. And if you can do it right, it’s not only a better experience, but can be a key growth lever as well.
Customers may overcommit
Usage-based pricing models may introduce a situation where customers end up overcommitting or pre-paying for too much. Businesses will then have to decide how to handle the extra credits, money, or units customers already paid you for.
Billing becomes substantially more complicated
Usage charges are typically billed in arrears, after the billing cycle. This may be different from the way your billing team operates today, if your customers are typically billed in advance.
This new process means that billing teams will have to ensure charges are calculated accurately, invoices are sent out on time, and billing operations are maintained for customers who may not be on a usage model. This often means that billing teams are having to work out of multiple systems to collect the data they need for accurate billing.
The role of Billing Operations will have to expand
In a traditional subscription model, a customer can’t dispute that they bought 5 seats after they sign the contract and pay the invoice. They might dispute the terms or proration calculations, but it basically ends there.
In a usage model tied to usage, there’s a myriad of opportunities for billing confusion and inaccuracies to spiral out of control and destroy customer experiences and bog down your support team. Billing Ops now will need to expand from deal support and invoice accuracy to forecasting, notification, and dispute defensibility.
Revenue recognition and reporting can hinder the success of the model
Under ASC606 and IFRS15, there are specific revenue recognition rules that accounting teams will need to adhere to. Without a system in place to handle complex usage revenue recognition, this will lead to manual efforts and hundreds of thousands of lines of spreadsheets to reconcile.
Discover the software for usage success
Over the past 15 years, we’ve worked with some of the best companies in the world. When it comes to usage-based pricing software, we’ve seen what works, what the pitfalls can be, and where gaps in the market currently exist.
We took a holistic, end-to-end approach with our usage solutions. Zuora gives finance teams the right billing and revenue automation tools, customers the transparency and flexibility to consume what they want, and product owners the right mediation, metering, and pricing tools to pivot from pure pay-as-you go to hybrid models – and everything in between.
Keep reading to learn more about why Zuora is the total package when it comes to usage-based pricing.
Accurately capture and meter usage
Your engineering team should be spending time on your product, not building usage metering.
Give your product teams the flexibility to meter whatever they want, without spending engineering cycles building, and re-building code for metering usage or getting pulled into every customer dispute.
Zuora makes usage data easier to manage
While some vendors only offer basic usage metering, a true end-to-end solution will provide all the tools your business needs to collect, transform, and measure usage data.
Zuora’s complete solution makes it easy to:
- Bring in usage from anywhere using pre built connectors, collect usage data from AWS, Snowflake, Kafka, or through streaming APIs
- Scale across high volumes of usage – over 200,000 events per second
- Track multiple metrics to uncover where your customers are getting the most value
- Use a drag-and-drop metering designer to enrich, aggregate, deduplicate, map, and filter your usage data
- Use your own code for any meter or extend any meter with custom logic
Get real-time visibility, rating, and analytics
Surprises lead to terrible customer experiences. The nature of usage pricing means that customers might not realize how much they’re using.
The answer is transparency — customers need to stay apprised of their consumption patterns. And if you can do it right, it’s not only a better experience, but can be a key growth lever as well.
Real-time usage rating and visibility
Customers like to see what they’re paying for, what they’ve used, and what their usage patterns are. To do this, you’ll need real-time rating.
Zuora does just that, with the usage solution your business needs to:
- Automatically process and rate usage data in near real-time
- Alert your customers of overages, push notifications as they approach threshold limits, or when it’s time to top up their usage
- Empower your Billing Ops team to get ahead of customer disputes
- Accurately bill your customers every time with a fully traceable audit trail to track usage from the time an event is ingested until it surfaces on an invoice
Price and bill for any usage model
Adding a new product? Or changing your pricing to a usage model? It’s a big move, and competitors will catch up if you move too slow.
Leading SaaS companies use Zuora to move fast and quickly add usage to the pricing mix to drive total monetization.
Out-of-the-box support for multiple models
Zuora Billing makes it easy to get started with usage right away:
- Choose from over 50 built-in pricing models, such pay-as-you-go, minimum commitment, or pre-paid with drawdown
- Flexible pricing tools and an intuitive interface make it fast and simple to fine tune your pricing and packaging strategies
- Apply different pricing plans to the same usage data, and compare which works best for your business
- Automatically update pricing across multiple systems (in-app, ecommerce, CPQ)
Maximize your usage revenue
Trends around monetizing generative AI and reducing adoption barriers have many companies turning to usage pricing models to drive growth. But to help ensure the successful company-wide roll out of a new usage-based pricing model, revenue accounting teams must be equipped with the right tools for success.
Continuously recognize usage revenue
Zuora Revenue makes it simple to:
- Quickly identify any discrepancies with automated reports
- Spend less time comparing numbers across spreadsheets and multiple systems
- Gain near real-time insights into your current revenue position and let finance teams focus on closing the books faster
- Keep new usage-based offers compliant with your revenue rules
- Make data-driven decisions by comparing revenue actuals and forecasted revenue against each other
Take the next steps
Usage-based pricing models will continue to be a pivotal tool for companies across industries in the years to come. This model offers a scalable, transparent, and cost-effective approach that benefits both providers and users, aligning with the dynamic nature of modern business practices.
As you navigate the complexities of usage, embracing a Total Monetization strategy and implementing the right solutions will help your business foster innovation, maximize growth, and nurture customer relationships.