Consumption-based pricing models are rapidly gaining in popularity. In fact, recent research indicates that nearly half (46%) of businesses have implemented some form of a consumption-based pricing model in the last three years.
Whether you’re just considering a consumption-based pricing model or you’re already implementing one, you’ve probably spent a lot of time thinking about pricing, packaging, and your overall go-to-market (GTM) strategy.
Many companies who are just beginning their consumption 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 in a process called mediation.
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 consumption pricing and billing strategy.
While customized or add-on solutions can be layered on top of your billing system to ingest and measure this 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 consumption 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 consumption value metrics. For your business, these consumption 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 consumption-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 consumption 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 and data your business needs to collect, meter, and transform consumption 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 consumption models—and everything in between.
And, as part of your larger consumption-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.
In the following sections, we’ll look at each of the steps in the mediation process and examine how a mediation engine can help streamline your work.
To begin mediation, you’ll need to collect consumption 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 consumption 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 consumption 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 utilizing a purpose-built mediation engine for aggregation and storage, your consumption data becomes more manageable, accessible, and secure. Plus, removing the need for a separate data warehouse can help cut unnecessary storage costs.
Transforming consumption 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 consumption 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 consumption 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.
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 consumption 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.
After aggregating and transforming your consumption 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 consumption-based pricing models, you’ll want to identify and measure key consumption 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.
Common metrics include: number of users, amount of data consumed, or number of events.
When determining the right consumption value metric for you, consider attributes that are:
Companies that already have an ETL tool might leverage it for consumption 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 consumption 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 collecting, aggregating, analyzing, and monitoring data related to customer consumption. 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.
Having a reliable system to track and store consumption data is also vital when it comes to customer disputes. If you’re using a homegrown, add-on, or ETL solution for mediation, your consumption 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 consumption visibility, enabling them to track daily progress, anticipate overages, and view their billing charges. Tracking consumption 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 consumption.
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.
The benefits of consumption-based pricing are significant and the effort to get there requires an enterprise-wide focus on understanding and driving customer value. With greater automation of the mediation process, consumption data is more accurate, accessible, and manageable. Plus, pricing and packaging can be quickly fine-tuned using real-time insights into customer usage patterns.
See the resources below to learn how to implement the right consumption-based pricing strategy for your business, customer, and product.