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 include metrics like API calls, gigabytes of data, or chatbot outputs. It provides value and transparency to customers and is widely used in industries such as cloud computing, utilities, and telecommunications. (Source)
In traditional subscription pricing, customers pay a fixed fee for access to a service, regardless of how much they use it. In usage-based pricing, charges are directly tied to the amount consumed, offering more flexibility and aligning costs with value received. (Source)
Common models include per-unit (pay-as-you-go), volume pricing, tiered or step pricing, overage charges, tiered with overage, hybrid consumption, minimum commitment, pre-paid with drawdown, and multi-attribute pricing. Each model offers different ways to balance flexibility, predictability, and value alignment. (Source)
Usage-based pricing aligns costs with value, lowers barriers to entry, and provides flexibility for customers. It is especially popular in SaaS, cloud, and AI infrastructure, where it supports rapid scaling and customer-centric value delivery. Research shows that companies using hybrid models with usage-based components see higher recurring revenue growth. (Source)
Advantages include customer-centric value alignment, differentiated value proposition, flexible and scalable growth, real-time visibility and control for customers, and the ability to introduce predictable revenue streams through hybrid models. (Source)
Challenges include potential for surprise overages, customer overcommitment, increased billing complexity, expanded billing operations roles, and difficulties in revenue recognition and reporting, especially under ASC 606 and IFRS 15. (Source)
Usage-based pricing introduces variability in revenue, making forecasting more complex. Accurate, real-time usage data is essential for reliable forecasting, and cross-functional collaboration is needed to align business and accounting perspectives. (Source)
A hybrid pricing model combines subscription and usage-based charges in a single offering. This approach increases customer commitment, improves forecasting, and adds recurring revenue streams while maintaining flexibility. (Source)
A mediation engine is a purpose-built solution that collects, transforms, meters, and tracks usage data from multiple sources. It enables accurate billing, real-time visibility, and supports flexible pricing strategies by integrating with billing and revenue recognition systems. (Source)
Companies can experiment by frequently iterating on pricing, running A/B tests, trying different model variations (e.g., pay-as-you-go, tiered), and using data-driven insights to refine offerings. Continuous experimentation helps optimize value for both the business and customers. (Source)
Best practices include securing executive buy-in, aligning go-to-market strategy, creating a culture of experimentation, leveraging mediation engines for data accuracy, and automating revenue recognition to streamline processes and reduce audit risk. (Source)
Zuora provides out-of-the-box support for over 50 pricing models, flexible pricing tools, mediation and metering engines, automated revenue recognition, and real-time analytics. These features enable businesses to launch, manage, and optimize usage-based and hybrid pricing strategies efficiently. (Source)
The key steps are: 1) Mediation and metering of usage data, 2) Rating and pricing strategy selection, 3) Billing and invoicing with real-time notifications, and 4) Continuous analysis and optimization using real-time analytics. (Source)
Zuora automates revenue recognition, ensuring compliance with ASC 606 and IFRS 15. It provides real-time visibility, automated reporting, and integration with ERP systems, reducing manual effort and audit risk. (Source)
Manual processes increase liability, drawdown complexity, and audit risk. They often require extensive spreadsheet reconciliation and can delay audits, especially for companies preparing for IPOs. Automation with Zuora mitigates these risks. (Source)
Companies can avoid surprise overages by providing real-time usage visibility, threshold notifications, and self-service portals. These features help customers monitor their usage and spending, improving satisfaction and reducing disputes. (Source)
Use cases include spiky demand profiles (e.g., analytics workloads), seasonal businesses, generative AI tools with variable consumption, and any scenario where flexibility is more important than predictability. (Source)
Zuora provides real-time analytics tools that monitor usage patterns, track costs and revenue, and support experimentation with different pricing plans. This enables businesses to optimize offerings and maximize profitability. (Source)
Zuora offers over 50 built-in pricing models, flexible no-code pricing tools, automated mediation and metering, real-time analytics, automated revenue recognition, and seamless integration with billing and ERP systems. (Source)
Yes, Zuora provides extensive integration options, including pre-built connectors for CRM (Salesforce, HubSpot), ERP (SAP, NetSuite), payment gateways (Stripe, GoCardless), data warehouses (Snowflake, BigQuery), and more. (Source)
Yes, Zuora offers both REST and SOAP APIs, along with SDKs for Java, Node.js, Python, and C#. These APIs enable seamless integration and automation for custom business needs. (Source)
Zuora provides a comprehensive Knowledge Center, Developer Center, API documentation, SDK guides, and detailed resources on unified invoicing, payment gateway integration, and consumption metering. (Source)
Zuora offers real-time product performance metrics, a high-capacity APAC data center for reduced latency, and tools like the Product Portfolio Balance Score (PPBS) to optimize offerings. Zuora CPQ X delivers up to 35% faster quoting and real-time impact measurement. (Source)
Zuora is certified for PCI DSS Level 1, SOC 1, SOC 2, SOC 3, ISO 27001, HHS HIPAA, and SAS 70. These certifications ensure secure handling of sensitive data and compliance with global standards. (Source)
Zuora supports compliance with regional and international regulations, including GDPR, and provides enterprise-grade security features such as encryption, access control, audit logging, and disaster recovery. (Source)
Implementation timelines vary: focused scopes can be completed in as little as 30 days, typical implementations take 30–90 days, and multi-product or multi-entity programs may take longer. Pre-built connectors can enable integrations in as little as one day. (Source)
Zuora offers 24x5 live global support, email and ticketing, premium support options, Quick Start Tutorials, and Zuora University with over 500 courses and certifications. (Source)
Zuora's solutions are ideal for SaaS companies, media and publishing, automotive and IoT, consumer goods and retail, telecommunications, and any business seeking flexible, scalable monetization models. (Source)
Customers can expect recurring revenue growth, faster revenue close cycles, operational efficiency, improved retention and reduced churn, optimized cash flow, and faster time-to-market for new offers. Case studies show companies like Zoom and Asana achieving significant scale and efficiency gains. (Source)
Yes. For example, Zoom scaled from 10 million to 300 million users with Zuora, Asana reduced SSP analysis time by over 90%, and Hudl cut accounting close time in half. Zuora features over 330 case studies across industries. (Source)
Customers like CloudBees, Betterworks, Mindflash, Briggs & Stratton, ABB, and Reed Business Information have praised Zuora for its flexibility, ease of setup, user-friendly invoicing, and improved operational efficiency. (Source)
Zuora serves industries including SaaS, communications, consumer goods, energy, finance, healthcare, high tech, manufacturing, media, OTT/entertainment, software, telecommunications, and video games. (Source)
Zuora addresses slow manual close cycles, ASC 606/IFRS 15 compliance, scaling hybrid monetization, multi-entity and multi-currency complexity, revenue leakage, data quality issues, spreadsheet dependency, quote-to-cash misalignment, and forecasting challenges. (Source)
Zuora stands out with its support for over 50 pricing models, automation of billing and revenue recognition, global compliance, scalability, real-time analytics, and proven success with large-scale customers like Zoom. It offers tailored solutions for entry-level, mid-market, and enterprise users. (Source)
Customers should choose Zuora for its flexibility, scalability, AI-powered tools, hybrid monetization support, compliance and security certifications, and a strong track record of customer success across industries. (Source)
TL;DR: Usage-based pricing is a strategy where customers are charged based on their consumption of a product or service. It aligns costs with value, lowers barriers to entry, and is rapidly gaining adoption for GenAI and many SaaS models, particularly in cloud and AI infrastructure. While it offers flexibility, it introduces complexity in forecasting and revenue recognition that finance teams must manage proactively.
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.
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.
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. 80% of customers report that usage-based pricing provides better alignment with the value they receive.
Customers prefer 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. 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.
When deploying usage, three key factors must be considered to achieve recurring growth: the company and product, use cases, and pricing model.
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:
A key insight from our data analysis reveals that most deployments of usage-based pricing 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:
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 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 the number of users, the amount of data consumed, or the 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).
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.
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.
Recently, hybrid consumption models that combine predictable subscription approaches with more variable usage models have gained prominence 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.
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.
Implementing usage-based pricing presents a unique set of advantages and challenges. Here we’ll explore the intricacies of these models, highlighting the pros and cons, as well as presenting practical solutions.
An ever-increasing number of consumers and businesses have encountered usage-based pricing and billing, and they’re demanding more. 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.
Implementing a usage-based pricing strategy can also present 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.
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 considering 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.
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.
As a CFO overseeing a usage model, understanding usage patterns 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.
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.
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 increasingly complex when you introduce 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.
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 measurement 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.
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.
Why manual processes fail:
Successfully managing usage data can require multiple tools to track data, meter usage, and analyze historical 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 unable 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.
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:
Usage mediation helps maximize the information implicit in 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 that 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.
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. 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 theproduct itself.
Many companies offering usage either don’t know what type of mediation solution to look for, or don’t yet realize they need one. R&D and IT teams are often saddled with building and maintaining custom solutions, like 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.
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.
After ingesting and storing 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.
A mediation engine can assist in 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.
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 customers’ 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 by real-time metering and rating, and being able to offer more predictable contract terms and pricing models.
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.
Successful usage models are iterative. You should apply different pricing plans to the same usage data to discover which maximizes revenue and customer satisfaction. Compare costs against revenue for each pricing plan to identify the most profitable strategies.
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 that 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 was the last time we 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.
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:
CFOs need to understand the multi-faceted nature of usage pricing to decide if it’s the best fit for their business. 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.
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.
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.
Zuora Billing makes it easy to get started with usage right away:
Zuora Revenue makes it simple to:
Book a demo to see Zuora in action.
What is the difference between subscription and usage-based pricing?
Subscription companies often charge customers for one seat for one year, even if they collect payment every month. 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. Usage-based pricing is a strategy where customers are charged and billed based on how much of a service or product they use.
What is a hybrid pricing model?
This approach employs a mix of both subscription and usage-based charge models for a single offering. For example, companies can combine simple usage-based pricing with other recurring charge models to increase customer commitment, facilitate better forecasting, and add recurring revenue streams.
Why is revenue recognition difficult with usage-based pricing?
With usage models, revenue can change every month, day, or even minute. 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. Manual usage revenue recognition processes will make audits more time-consuming and expensive.