verb scoring (1)

An Introduction to Verb Scoring: What It Is and How To Leverage It For Product Acquisition & Monetization

Verb scoring is the starting point for competitive and strategic analysis specific to product monetization. Find out how to leverage it.

For digital leaders with unique product monetization strategies (free-to-paid, freemium, trials, etc.), it can be difficult to find the balance between creating friction and delivering value.

How do you understand if your features are supporting user exploration while leaving enough out of reach to incentivize conversion?  

Enter verb scoring.

A handy tool that evaluates and scores user actions based on permissions, verb scoring offers product teams an avenue to align on and improve their product monetization strategy.

The early payoff is to understand where the strategically placed friction is within a user experience. Then, once you are aligned on how your product’s features support your strategy, you can build a shared vision for the purpose of each feature.

Whether your goal is to gain share-of-voice, build a stable of free users, monetize existing ones, or connect with leads, verb scoring helps you build an intentional acquisition and monetization strategy.

In this article we will:

  • Define verb scoring
  • Review verb scores (with examples)
  • Demonstrate how to use verb scoring to evaluate your and/or your competitor’s acquisition, retention, and monetization strategy

Note: This is part one in a two-part series on verb scoring. Stay tuned for the follow-up on how verb scoring can support your product strategy (with examples).

What is verb scoring?

Verb scoring is the act of evaluating actions that users can take in your and your competitors’ products and then scoring them based on the level user of entitlements (or the amount of friction) required to perform the action. 

What are the primary benefits of verb scoring?

A verb scoring exercise allows you to evaluate your strategy. Then, you can produce an artifact that communicates it in a visual, shareable, and succinct feature matrix.  

This at-a-glance accounting of your product features allows you to:

  • Evaluate your acquisition, retention, and monetization strategy
  • Compare your strategy to that of your competitors, and
  • Build a smarter strategy that’s best suited to your unique product.

The output of your Verb Scoring Matrix might look something like this:

verb scoring matrix sample

What do we mean when we say verb?

In the context of verb scoring, verbs are the core features of your product broken down into discrete actions. They are actions users can take within your product, such as creating a ticket, editing a transcript, or sharing a document with a friend.

While in other contexts it’s advisable to stay focused on the core benefits of your product, scoring a product via discrete verbs is helpful in this context. It mirrors the ways users might talk about a product’s limitations. For example, users might say, “I love that I can create a poster, but it won’t let me resize it.” In this example, create and resize are the verbs.

Using verbs, rather than benefits or features, is a user-centered way to evaluate your product’s functional limitations from the perspectives of users with varying entitlements.

What products could benefit from verb scoring?

Verb scoring is especially useful for any product in which acquiring paying customers relies on some combination of having both free and paid features. It’s also useful for products with teams deciding whether or not to gate parts of the digital experience.

What are the various verb scores?

There are six different verb scores that represent growing levels of “friction” required to utilize them. Each serves a different purpose in your strategy:

Model - Verb Scoring Definitions

Let’s look at each verb score in more detail.


The verb score with the least amount of friction is scored as Anonymous.

Anonymous verbs are those in which a user can take an action completely for free, without giving away any information about themselves.

We call these verbs Anonymous because they don’t require any information (e.g., name or email address) to use them, so the user can remain “anonymous” and make use of the features.

Think of using an online PDF compression tool. If a user doesn’t need to give anything away to take the action and can do it an unlimited number of times, then the verb is scored as Anonymous.

ad for pdf compression tool

Example: PandaDoc’s Online PDF compression tool allows users to compress a PDF document for free without requiring an email address.

Anonymous verbs are the most frictionless ways users can take an action within your product.

Limited Anonymous Use

We add just a small amount of friction in the next verb score: Limited Anonymous Use (LAU).

With LAU verbs, users can take an action without providing information, but we impose limitations on its use in some way (or at some point).

Example: Adobe does this with their online PDF converter on the user’s second use. The first time a user converts a file, he can do so without giving away any information.

Gif to convert to PDF

However, try to use the free online PDF converter again, and the user is required to share an email address to download their converted document.

log in page for pdf converter

Example 2: Many online media publications use LAU verbs when it comes to giving away content. New York Times readers can read one article for free, but once they try to read a second article, they are asked to create a free account to enjoy more content. In this example, the verb “Read Articles” is scored as LAU because users can do it anonymously, but only a limited number of times.

LAU verbs might have limitations based on the number of uses, number of free uses per day, or other variables. Because the user is allowed to take the action anonymously, but there are eventually limitations on that use, we score verbs Limited Anonymous Use.

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Free with Registration

When verbs can be performed for free, but only after users have provided personal information (like an email address), they are coded as Free with Registration.

sample of X profile when person is drafting a tweet

Example: Posting on X (formerly Twitter). Once a user has signed up for a free account, they can post, reply, and retweet without limitation.

To take advantage of Free with Registration verbs, the user must give some amount of personal information. This is typically only an email address and name.

Limited Registered Use

When verbs are free to users who have registered, but the capabilities of that verb are limited in some way, those verbs are scored as Limited Registered Use or LRU.

Many companies that have a large free user base rely heavily on LRU features.

canva working space

Example: Canva gives away a lot of free functionality, but most of their “free” features have limitations. Free users can add text to images, but not the fanciest scripts. Free users can utilize some templates, but not all of them

If an action can be taken by a registered user, but the full capabilities of the feature are reserved for paying customers, that verb is scored as Limited Registered Use.

Trial with Payment (TwP)

While some actions can be taken by users who have provided little more than an email address, others are reserved only for customers who have provided a form of payment in exchange for extra functionality. We call these verbs Trial with Payment, or TwP.

TwP verbs are typically high-value actions that users are willing to pay for. In exchange for their use, we ask users to put down some form of payment. But, as the name Trial with Payment implies, users are not charged during a “trial” period. Instead, their card is held and charged only when the trial period ends.

canva design in progress

Example: In Canva, users who want to export a design to an SVG must enter a trial period and provide payment information. As such, the verb “Export to SVG” is scored as TwP.


The word “Gated” is often used as a catch-all for features that have some level of friction. But in verb scoring, the meaning of Gated is specific and is reserved only for the most tightly guarded features.

In verb scoring, Gated features are those that users can’t leverage until they are paying customers.

Truly Gated verbs can’t be accessed by simply signing up for a free trial. They are behind a hard paywall, with up-front payment required to take advantage of them.

invoice sample for truly gated verb scoring

Example: Stripe, an online payment processing tool, opens up nearly all functional parts of its dashboard to registered users. Users can create products, draft invoices, create templates, and connect their bank accounts for direct deposits. But when it comes time to actually send an invoice to a client or get paid, those features are reserved for paying customers only. They will not be available via any form of a free trial.

When a feature is reserved solely for already-paying customers, we score that feature as Gated.

A framework for scoring verbs

To execute a verb scoring exercise, you can use the verb score decision tree. This tool helps you take what you just learned in this article and follow a logical process to score your and your competitors’ verbs.

verb scoring decision tree

You’ve scored your verbs. Now what?

Once you score your and your competitors’ verbs, you can plot the features/scores on a matrix to demonstrate shared understanding with your team in a crystal clear artifact.

The tool, called a Verb Scoring Matrix, is the starting point for competitive and strategic analysis specific to product monetization.

Plot the features in Verb Scoring Matrix to clearly compare your feature-gating strategy to that of your competitors.

verb scoring matrix sample

Now, you can get off to the races on developing a strategy as you have a better understanding of how the user experiences friction across your product experience. Additionally, you’ll know how that experience compares to that of your competitors.

To be clear, we aren’t advocating for adding unnecessary friction to a user’s journey. What we are advocating for is having a shared understanding of how your product’s features either support or inhibit your strategy through this friction.

But understanding your features is just the beginning. The next step is to build a shared vision for the purpose of each feature you’ve scored. Then, adjust your strategy accordingly. The second part of this series on verb scoring is available here.

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Natalie Thomas

About the Author

Natalie Thomas

Natalie Thomas is the Director of Digital Experience & UX Strategy at The Good. She works alongside ecommerce and product marketing leaders every day to produce sustainable, long term growth strategies.