Learn how to create a clean event naming convention so product analytics events stay consistent across code, dashboards, and documentation.
Project BS
Privacy-first apps
A product analytics event naming convention is a shared set of rules for naming the actions users take inside a product.
The main problem is that analytics becomes hard to trust when event names are inconsistent across code, dashboards, and documentation.
One developer tracks "Signup Completed." Another tracks "user_signed_up." A third event is named "Account Created." In a dashboard, those may look like three different actions, even if they describe the same moment.
For indie makers, solopreneurs, and SaaS founders, this matters because early product analytics should reduce confusion, not create more of it. If event names are messy, it becomes harder to understand activation, onboarding, retention, and the first meaningful user action.
Bad event names make analytics hard to trust.
Inconsistent event names create doubt.
When a founder opens a dashboard and sees multiple names for the same action, the next question is not "what did users do?" It becomes "can I trust this data?"
That is a bad place to be. Product analytics should help answer product questions. It should show whether users reach signup, complete onboarding, perform the key action, or come back after the first session.
When names are inconsistent, every metric becomes harder to interpret. Event tracking becomes a cleanup project instead of a learning tool.
This is especially painful in early-stage SaaS analytics, where the team may not have many users yet. Small data sets already require careful interpretation. Messy event taxonomy makes the signal even weaker.
Event names are labels on the product map.
A clear label helps everyone understand what happened. A vague label forces people to guess.
For example, "clicked_button" is technically true, but not useful. It does not explain which button, where it was clicked, or what user intent it represents.
A clearer event might be:
"waitlist_signup_completed"
That name tells a better story. It describes the object, the action, and the completed state. It can be used in code, dashboards, and a tracking plan without much interpretation.
A good event naming convention should make events easy to read before anyone opens the documentation.
A clean event naming convention usually defines structure, case style, verbs, objects, and rules for states.
The structure tells the team how events should be formed. A common pattern is:
"object_action_state"
For example:
The case style keeps names consistent. Many SaaS teams use snake_case events because they are readable in code, analytics tools, and data exports.
The verbs describe what happened. Common verbs include created, updated, deleted, submitted, completed, opened, viewed, sent, and failed.
The object describes what the action happened to. This could be project, user, dashboard, invoice, waitlist, subscriber, report, or checkout.
The state clarifies the result when needed. For example, started, completed, failed, or skipped.
An event naming convention helps everyone describe product behavior the same way.
The simplest way to name product analytics events is to use a consistent pattern:
"object_action_state"
That means:
For indie makers, this means product data becomes easier to read without building a heavy analytics system.
Start with the user journey.
Before writing event names, define the key steps that matter for the product. For an MVP, this may include landing page visit, signup, onboarding, first project creation, first key action, and second session.
Then name events around meaningful user behavior.
A weak event name is:
"button_clicked"
A stronger event name is:
"project_created"
The first name describes an interface interaction. The second name describes a product outcome.
This difference matters. Product analytics events should usually track meaningful actions, not every small click. A dashboard full of low-value click events can make the product look measured while still failing to answer important questions.
A strong SaaS event tracking setup should help answer: did the user reach the value moment?
A practical event taxonomy should be simple enough to follow.
Use one format for all events. If you choose snake_case events, use snake_case everywhere.
Use past tense for completed actions. For example, use "report_created" instead of "create_report." This makes the event read like something that already happened.
Use clear nouns. "project_created" is better than "item_created" if the product object is a project.
Avoid mixing product language and technical language. If the user knows the action as a "workspace," do not call it "tenant" in analytics unless the whole team uses that language.
Document every event in a tracking plan. The tracking plan should include the event name, description, trigger, properties, and owner.
This does not need whole team uses that language.
Document every event in a tracking plan. The tracking plan should include the event name, description, trigger, properties, and owner.
This does not need to be complex. Even a small table is better than undocumented analytics.
The first mistake is tracking the same action with multiple names. This breaks trust quickly.
The second mistake is using names that are too generic. Events like "clicked," "submitted," or "opened" are rarely useful without an object.
The third mistake is naming events from the interface instead of the user outcome. "primary_button_clicked" may matter for debugging, but "trial_started" is more useful for product learning.
The fourth mistake is changing names without a migration plan. If old dashboards use old names and new code sends new names, data becomes fragmented.
The fifth mistake is skipping documentation. Event names may feel obvious when they are created, but they become harder to understand weeks later.
The key takeaway is simple: clean event names make product data easier to trust.
A good event naming convention helps SaaS teams keep analytics consistent across code, dashboards, and documentation. It also makes product metrics easier to discuss because everyone uses the same language.
If analytics feels messy, do not start by adding more dashboards. Start by cleaning the names of the events that matter most.
An event naming convention is a shared rule system for naming product analytics events consistently across code, dashboards, and documentation.
A practical format is "object_action_state" in snake_case, such as "signup_completed" or "project_created." The best format is the one your team can apply consistently.
Event names matter because they shape how teams read product data. Consistent names make activation, onboarding, and retention metrics easier to trust.
Project BS built a free Event Naming Convention Generator to help founders create clean product analytics event names, example events, and simple naming rules.
Use it as a starting point, then adapt the convention to your product, tracking plan, and data workflow: https://data.project-bs.com/tools/event-naming-convention