How to select the best pricing metric?

According to a recent survey, the hardest part of deploying usage-based pricing is finding the right metric. The second most challenging part is finding the suitable systems to support it. (Coatue Partners, 2021)

Why is finding the right metric so tricky? One reason is that usage-based pricing might not be the best option for many SaaS businesses to begin with. And second, 70% of all companies that use usage-based pricing have done so from inception; meaning, that many UBP companies follow the obvious answer used by their competitors and never ask themselves what the best option might be. Please see “Is Usage-based Pricing Right for My SaaS Company” for more detail.

Life is a little harder for everyone else either transitioning to UBP or adding UBP.

So, how does a SaaS business select the right metric(s) for usage-based pricing?

One answer would be to hire a pricing consultancy – who will provide additional expertise and the right process to follow, but for early-stage companies that is often out-of-reach.  Even for others, there is a lot of value in building your pricing knowledge base internally as it is a competency all SaaS companies should have.

To help construct the criteria for a good usage-based pricing metric, we turned to pricing experts at Insight Partners, one of the most active and successful software investors of all time. James Wood, who leads their team of pricing advisors, provided the bulk of the content below. 

Let's jump in:

The best way to use the criteria below is to brainstorm various metrics from a cross-section of the company’s employees and then score each of the metrics based on the listed criteria. A downloadable scorecard with suggested weightings for is available here "Metric Selection Template"

Instructions on how to use the Metric Selection Template

The exercise is one of trade-offs and nuances. It’s unlikely you will stumble upon one perfect metric. More likely, you will find one or two metrics that are strong contenders, and you can further refine your thinking around these to align on the best metric for you and your customers. 

According to James, there are seven criteria to look at when assessing a potential usage-based pricing metric. The criteria fall into two categories: Market Acceptance and Internal Suitability.

Market Acceptance Criteria:

1. Value Aligned: Simply put, does the metric increase with the customer’s level of perceived value? This is the most important of all metrics, and teams should spend time carefully thinking through different options. For example, what metric scales with perceived value if you are an email marketing platform? Is it messages sent, messages delivered, messages read, messages acted upon, or something else?
2. Easy to Understand: Obscure metrics or derivative metrics (combinations of other metrics) limit customer buy-in because only a few individuals at the customer are likely to understand what they even mean. Hard to comprehend metrics also undermine billing transparency by making it difficult for customers to reconcile their bills with their known usage levels.  That said, it is possible to define new metrics, especially if the product category is unique. For example, Segment developed the metric of "Monthly Tracked Users." It was not something anyone had heard of at the time, but as the category grew, other companies such as Mixpanel and mParticle adopted the metric.
3. Knowable in Advance:  The metric level is known, discoverable, or easily estimated before deployment. Metrics not knowable in advance create economic uncertainty for the customer and friction in the sales process. If the specific metric can't be known in advance, proxy metrics or calculations may be used. For example, if your metric is “page impressions”, you can approximate that by the total number of page views of that prospective customer, multiplied by the percentage of pages that your product is likely to be running on.
4. Consistent Across Customer Segments:  The metric should align price and value consistently across all target markets and customer use cases. That said, changes in per-unit pricing can be used to adjust economics across different segments. For example, a pharmaceutical company might have low-volume usage compared to a retailer, but each interaction is more valuable. So while the metric remains constant, the per-use price might be 10X higher for one segment over another based on the value delivered.

Internal Suitability Criteria:

1. Usage Friendly:  The metric should not constrain the usage of the product. This is the second most important metric. For example, usage is unconstrained by pricing when the incremental cost is trivial, when it’s clear that each use drives more benefit to the company, or when usage is machine-driven. A clear example of usage-friendly is in ecommerce. Internet retailers will not refrain from selling more products because their platform provider charges them based on revenue. The value of the new revenue far outweighs the increased cost.
2. Granular:  Smaller measurement units allow for more pricing precision and help offset usage constraints. Granularity should be in the hundreds or thousands or millions per month. Pricing tiers undermine the usage-friendly benefits of granularity by creating artificial sticking points that customers will manage around. Atlassian, for example, credits improved organic growth to the elimination of pricing tiers.
3. Linked to Growth: The metric will scale with increased usage intensity of the product and, at a minimum, will rise at the same pace as customer revenue growth. The organic growth benefit of UBP over other pricing structures relies upon this criteria.  Example: A practice management platform migrated pricing from "doctor visits scheduled," which is relatively flat, to "outbound messages sent ." The latter metric scaled significantly as the practices found more and better ways to communicate with patients. 

Once you have brainstormed and scored the metrics, you should track as many of the top metrics as possible. The exercise of actually collecting the data will accomplish three things:

1. Give you insight into how the different metrics behave over time. This is particularly helpful in determining if the metric can scale faster than the underlying revenue growth of the customers. (Granular criteria) 
2. Allow you to model per-unit pricing. For example, one company providing a document review and approval product discovered that each document review would need to cost the customer $50 -- a prohibitively high unit price that would have curtailed usage.  
3. Identify data collection issues and systems needs for full implementation. Billing data must be accurate and timely to avoid surprising and erroneous bills. Most companies deploying UBP quickly outstrip the limits of an Excel spreadsheet.

Having tracked and analyzed several different usage metrics, you should now be able to identify the best one or two metrics around which you can build your pricing structure or, alternatively, realize that your product is not a good fit for usage-based pricing at all.