How Tech Product Managers Can Inject Flexibility Into Usage-Based Pricing Strategies

Today’s tech pricing models typically incorporate usage metrics with mutually desirable business outcomes — offering value to customers and growth potential to providers. But many also lack the flexibility to respond to sudden or temporary changes in usage. For the sake of customers, tech providers should prepare a pricing strategy for common strains on usage limits. 

“Hitting customers with unexpected bills risks dissatisfaction, churn and missed growth opportunities for the provider,” says Ron Burns, Senior Director Analyst at Gartner. “By assessing common unexpected usage scenarios, tech product managers can come up with more flexible pricing options and strategies to accommodate customers and maximize product profitability.”

Download now: How Technology Product Leaders Can Drive Revenue Growth

Traditional usage metrics include the number of end users, number of data transactions, or volumes of data throughput, with purchases made via tiers and yearly subscriptions. But Gartner research indicates three types of unpredictable situations that commonly afect these types of contractual usage limits:

• Exceeding a tier
• Unexpected or temporary spikes
• Unpredictable usage across products

These situations are not mutually exclusive, so you need to accommodate all three to maximize product use and profit opportunities.

Read more: 5 Impactful Technologies From the Gartner Emerging Technologies and Trends Impact Radar for 2022

Exceeding a tech usage tier

 By definition, tiered pricing models have a scope and ceilings. There are, however, some controversial market perceptions with these pricing models, overage policies and approaches for moving customers to higher tiers, including:

• Vague definition of tier metrics, making predictability a concern
• Unlimited use, resulting in a perpetual risk to the provider
• Implied per-unit volume discount at higher-level tiers, which can encourage usage growth but can also cause friction because it masks poor predictability for customers who grow into higher tiers
• Excessive penalties for exceeding a tier limit, which can increase short-term revenue but damage long-term annual recurring revenue if perceived as price gouging

With clear and fair policies that enable customers to estimate usage more accurately, we can minimize unexpected surprises.

Therefore, plan to make product metrics accessible to customers with configurable administrative dashboards, usage reports, and notifications or alerts that can predict overages. Work with your sales and revenue operations teams to create flexible terms that allow easy movement from one tier to another during a contract period.

This kind of transparency and flexibility is key — and can often be a competitive differentiator.

Unexpected or temporary spikes

Sudden unexpected demands on technology can result from a customer’s business variability, seasonality, cyberattacks and workforce adjustments, or even as the result of a provider’s marketing campaign. The following policies and pricing plans provide attractive paths to handle unexpected or seasonal usage spikes:

• Burst pricing per-unit pricing for specific overage volumes addresses sudden, relatively brief or unexpected spikes in demand.
• Spot consumption provides lower unit-based pricing for excess usage capacity that the customer forecasts. Savings can be significant if the customer is willing to operate in an unpredictable environment, where availability is not guaranteed. 
• Reserved capacity provides a fixed inventory for a customer, whether used at or below the reserved capacity threshold. It’s like a savings plan or insurance that provides lower per-unit costs for unpredictable events. The customer must commit to a specific tier of volume instead of specific instance configurations or time frames.

Three of the leading cloud service providers — Amazon, Google and Microsoft — all offer variations of burst, spot or reserved capacity pricing. Take note of how these providers use the functionality, policies and price points of these models to differentiate among their competitors.

Unpredictable usage across products

In a credit (or token) pricing model, customers commit to a usage level for the licensed term, usually a year. A set number of purchased credits apply to several products in a provider’s portfolio. Overages are not a factor, and some providers offer a rollover of unused amounts up to the contract anniversary. Among the most advantageous scenarios for this model are:

• Large product and service portfolios, resulting in diverse pricing models, and complicating how a customer can buy more from the provider (e.g., extending budgeting, evaluation and approval processes)
• Difficult- or impossible-to-predict usage demands, causing a need for customers to allocate budget flexibly across multiple product and service options
• Desire to incentivize customer “stickiness” by providers accommodating cloud migration credits, “bringing your own license,” or securing budget for use in training and professional services

There are some potential drawbacks to credit pricing models, as they may discourage usage, lead to hoarding behavior or cause customers with unused credits to demand a smaller renewal. Prepaid credits, however, should enable customers to preemptively select what they feel they need, instead of instinctively leveraging the right product or service for the task at hand. Technology providers that have rolled out credit models include Sumo Logic, Oracle Cloud and Snowflake.