Software Pricing Pitfall #2: Settling For a Suboptimal Price Metric


Software Pricing Pitfall #2: Settling For a Suboptimal Price Metric

20 Minute Read
Software startups often default to “industry standard” price metrics without considering whether they are right for the business. In this article, we explore some ideas on how they can pick more effective alternatives.

Boom Times for Pricing Metrics 

Price metrics are not a new concept. Defined simply as a scalable quantity to which one ties the price of a sale, they have been around in one form or another for as long as products have been sold. A price metric’s primary role is to allow a company to differentiate – to adjust prices to meet an individual customer’s (or group of customers’) willingness to pay. 

What is new is the breadth of price metrics that is now available for tech companies. 

In some cases, price metrics can almost transcend the field of pricing and become a key competitive differentiator. Several large markets have been disrupted by companies employing radical new price metrics. However, such creativity in price metrics is still more exception than the rule, and many companies succumb to the pitfall of not thinking beyond the status quo.

The options are so numerous we tend to think of five broad categories of price metrics rather than individual metrics:  

Seat based – metrics closely related to the number of people using the product
Usage-based – metrics related to how much or how frequently the product is used
Hardware-based – metrics based on the number of connected devices, or the amount of system resources required
Company business metrics – metrics based on the scale or performance of the customer (e.g., revenue, number of employees)
Success-based – metrics that align with the output or impact driven by the product (e.g., reduction in costs)

Startups Stuck in Their Seats

More than 20 years after the advent of the mainstream internet, pricing a product “per seat” – the metric closest to the license-based, legacy desktop software model – is still very common. In fact, the proportion of SaaS companies that use a variant of “number of seats” as their primary metric is 39%, making it the most common price metric category – according to a 2018 SaaS Survey by KeyBanc. 

While seat-based metrics can undoubtedly be the right choice for a subset of companies, it would be surprising if seats was the ideal metric for as many as 39% of SaaS companies. We frequently encounter startups that feel their seat-based models are not achieving their objectives. For many businesses, seats as metric fails to satisfy key price metric criteria:

  • Not linked to value – Consider an analytical product used by 100 users at an enterprise company, but with only 3 power users accounting for 95% of the usage. Beyond the initial 3 licenses, the value to the company would not increase consistently as more users are added.
  • Not scalable – Consider a tool aimed at a marketing team, which has remained the same size for 10 years, and shows no sign of changing. As the number of users is unlikely to increase, charging per user will likely never raise the revenue per customer, and so it is not a scalable metric for growth
  • Not auditable – How many times have people shared licenses (or credentials) with their colleagues for an online database? It can often be challenging to know how many users are truly using the product, and to set the price appropriately.

What seat-based models do have, however, is a higher degree of familiarity. This makes them easy to explain and implement, and therefore highly acceptable to the customer. So the very ubiquity of seats makes them the easy choice for companies without pricing expertise, which is often true of startups. In this way the selection is self-propagating. More seat models emerge, and seats beget seats.

Choose Value-Linked Metrics…

Still, does it really harm companies to price based on a metric that is not the best for their customers? The answer is yes. And in a number of ways. Most importantly, choosing the wrong price metric inhibits the ability to price differentiate. For example, if a company is selling some form of capacity when the buyer doesn’t value that metric, one of two things may happen:

  • Buyers will purchase fewer capacity units than intended, thereby pushing the purchase price down. 
  • Buyers will ask forthe needed amount of capacity for a lower purchase price, since they don’t want to pay the list price for the last few seats.

Either way, the buyer ultimately pays less than it is actually willing to pay. This was true of an online reference tool startup that priced its product based on concurrent user licenses (CULs) for their various content sets,  the expectation being that large Enterprises would purchase up to 8 CULs. Company research found that these enterprise clients were actually willing to pay the price levels that corresponded to eight CULs, and yet they purchased fewer than two CULs on average. Because the CUL metric was not value-based it did not work as a price differentiator, and customers were able to purchase a workable solution at a price significantly below their willingness-to-pay.  The vendor was missing out on signicant revenue it could have captured with a more value-based metric.

This can be avoided (or greatly mitigated) if pricing is based on a metric that is more strongly linked to the value that customers receive from the product. For example, a product that increases sales-win-rates might consider pricing on the customer’s baseline new business revenue, since the value realized will be a product of that revenue. A search engine might charge by the number of searches. An analytical tool might charge by the amount of analytical horsepower provided. Smart companies understand how they add value to the customers and align their commercial models.

Choosing the wrong price metric can also negatively affect the value proposition and sales confidence. A price metric, intentional or not, communicates to customers how a business adds value to them. As a result, choosing an inappropriate metric means misrepresenting the source of value creation, or at least not presenting it in the best possible light. This can complicate sales messaging and detract from the sales team’s confidence, ultimately leading to lower sales volumes and more frequent and dramatic discounting. 

… With Sufficient Predictability

One caution when choosing a highly value-based metric – ensure that it meets predictability requirements.  Usage-based metrics (e.g. API calls, # downloads, # site visits etc.), for example, are frequently seen as value-based, but they can be hard to estimate over time.  Even if the customer agrees that additional usage is value-linked and worth paying for in principle, tieing the price to an unpredictable metric results in unpredictable pricing. Budgeting is frequently important to customers, especially large enterprises, and uncertainty here can inhibit sales velocity. 

Predictability can be enhanced by either buffering against fluctuations – providing more usage for the same price, fixing price within a “band” of usage, and/or resetting price based on usage less frequently (e.g. annual price resets as opposed to charging on a monthly meter) – but all of these methods share the downside of reduced future upsell potential.  An unpredictable metric can still be the right choice overall, but should be chosen with visibility of these potential consequences, and with an execution strategy to mitigate them.

Unlock Significant Value

The impact of changing to value-aligned pricing metric is frequently immediate and dramatic. Consider the following examples from the public eye, as well as our own experience.

  • A cloud-based content management provider with rapidly declining growth implemented a new pricing metric which improved correlation with willingness-to-pay by over 10X, and resulted in an almost immediate 10% revenue increase.  
  • Through switching from seats to “active users,” an analytics provider managed to reduce churn by 3 percentage points and saw a large improvement in sales rep satisfaction.  
  • Mention, a social media monitoring tool, raised their average revenue per account by 269% by switching from seats to the number of “alerts” that an organization configures.  
  • An appliance-based network software vendor realized an 8 percentage point  YoY revenue  growth rate increase through switching from a traditional hardware-linked metric to a measure of network connection speed
  • Even Google is an example here, since a big part of its success came from changing the standard price metric for online advertising from cost-per-impression to cost-per-click.

How to Pick the Right Metrics 

The way to find a price metric that could deliver the kinds of results mentioned above is through a combination of brainstorming and evaluation:

Brainstorm possible metrics
Use the categories defined within this article and attempt to think of several metric options that would fit in each. Look to companies in adjacent industries for inspiration. Consider how the company creates value for customers (i.e., does value increase per user?  Per session? Per gigabyte?) and look for metrics that align with the amount of value created.

Evaluate the shortlist
Teams should evaluate the shortlist of metrics against the 5 key criteria for a price metric:

  1. Link to Value – A great price metric aligns with the amount of perceived value that customers receive from the product. If customers agree that as the metric increases, they get more value from the product, they will not question that the metric is a sensible basis for pricing.
  2. Scalability – Ideally, a price metric provides a pathway to future growth.  If a metric is scalable, it is expected to grow following the initial sale, and so tying it to growth will help increase revenue per customer over time.
  3. Predictability – Being able to budget is important to customers, so a metric that does not allow them to predict what their prices will be in the short- and long-terms can be a barrier to adoption.
  4. Auditability – To prevent abuse of the system and/or ambiguity around prices, a metric should be able to be objectively measured, without relying primarily on the customer to provide the relevant information.  
  5. Acceptability – Finally, for the metric to be successful it must be acceptable to the customer. Even if the metric satisfies the above four criteria, if customers don’t feel it is fair to tie this metric to price, the customers may reject the pricing model, hampering initial sales velocity.

Rigor and confidence can be added to this step by launching customer research to achieve an ‘outside-in’ perspective of the metrics.

Select the best overall metric(s)
Given a business’ objectives and strategies, some of the criteria defined above will be more important than others. Startups should agree on which criteria are most important and create a weighted performance score for each metric.  The metrics with the top overall scores will be your best candidates.


Reach out to us for more information on how we can help you with pricing optimization.

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It is worth mentioning that, having picked your preferred metric, you still have work to do in (a) deciding how price scales with that metric, and (b) verifying through careful revenue modeling that converting to the new metric will be revenue positive. But aligning on an optimal metric is undoubtedly a hugely important step that is trodden too infrequently.

Choosing a price metric doesn’t have to be difficult or complicated. But for the reasons we have discussed, startups shouldn’t just make the easy or default choice. By being thoughtful and taking these few simple steps, startups can choose a price metric that can be a critical lever to accelerate growth.

In our next article in this series, we will be exploring the startup Pricing Pitfall #3: off-target value communication.

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