Startup Product Analytics: Picking Your First Events
Most early startups either track nothing or track everything. Both leave you guessing. The smarter path is a short, deliberate list of product events tied to the questions you actually need answered. This guide shows you how to pick your first events, name them so they stay useful, and write a simple tracking plan that grows with your product instead of turning into noise.
Key takeaways
- Start from questions, not features: write down the three to five decisions analytics should help you make.
- Your first tracking plan usually needs only 10 to 15 events covering signup, activation, core use, payment and churn signals.
- Use one naming pattern, such as "Object Action" in past tense, and stick to it.
- Write every event in a shared tracking plan with its trigger, properties and owner before anyone adds code.
- Respect privacy: collect only what you need and follow consent rules where they apply.
Product analytics means recording what people do inside your product so you can see patterns: where new users get stuck, which features keep customers coming back and what happens just before someone upgrades or leaves. It is different from website analytics, which mostly tells you about visits and traffic sources. Product analytics is about behavior after someone signs up.
The temptation, especially for technical founders, is to switch on automatic tracking for every click and sort it out later. "Later" rarely comes. You end up with thousands of vaguely named events, charts nobody trusts and a team that goes back to gut feeling. A small, well-defined set of events beats a huge messy one every time.
Start with the questions you need answered
Before you list a single event, write down the decisions you expect to make in the next six months. Good questions are specific and lead to action. For example:
- What share of new signups reach the moment where the product clearly helps them?
- Where do people drop off during setup?
- Which features do retained customers use in their first week that churned customers do not?
- What do trial users do just before they convert to paid?
- Is usage of our main feature growing, flat or shrinking month to month?
Each question points to a handful of events. If an event does not help answer any question on your list, it can wait.
Pro tip
Agree on your activation moment as a team before you track anything. Activation is the point where a new user first gets real value, such as sending their first invoice, publishing their first page or inviting a teammate. Many of your most important events will sit around that moment.
The five groups of first events
Most startups can cover their early questions with events from five groups. Aim for two or three events in each, and you will land at a manageable 10 to 15.
1. Acquisition and signup
Record when someone creates an account and, where relevant, how they arrived. Typical events: "Account Created" and "Email Verified." Useful properties include signup method and referral source.
2. Onboarding and setup
Track the key setup steps that stand between signup and value. Typical events: "Onboarding Step Completed" with a step name property, "Integration Connected" or "Project Created."
3. Activation
Track the specific action that defines your activation moment. For an invoicing tool that might be "Invoice Sent"; for a scheduling tool, "Booking Page Published." This is the single most important event in your plan.
4. Core usage and engagement
Track the repeated actions that show ongoing value, such as "Report Generated," "Message Sent" or "Teammate Invited." These tell you whether customers are building a habit.
5. Revenue and churn signals
Track "Trial Started," "Plan Upgraded," "Subscription Cancelled" and, if you have one, "Cancellation Reason Submitted." Payment events often come from your billing system, so decide which system is the source of truth.
Common mistake
Tracking clicks instead of outcomes. "Save Button Clicked" tells you someone pressed a button; "Invoice Saved" tells you something actually happened. Buttons get redesigned and moved, but outcomes stay meaningful, so your charts survive the next interface change.
Name your events so they stay useful
Naming feels trivial until you have "signup," "Sign Up," "user_signed_up" and "Registration Complete" all measuring roughly the same thing. Pick one convention on day one and write it down.
A widely used pattern is Object Action, written in past tense: "Project Created," "Report Exported," "Plan Upgraded." It reads naturally, groups related events together alphabetically and makes it obvious that the action has already happened.
- Use the same case style everywhere, such as Title Case for events and lower_snake_case for properties.
- Put detail in properties, not in event names. Use "Report Exported" with a format property of "pdf" or "csv," not two separate events.
- Avoid internal code names that new team members will not understand.
- Never rename an event quietly. If you must change one, note the date and the old name in your tracking plan.
Write a simple tracking plan
A tracking plan is a shared document that lists every event, when it fires and what information it carries. It is the contract between the people who ask questions and the people who write the code. A spreadsheet or a page in a knowledge base such as Notion or Confluence is plenty.
Tracking plan template
Copy these columns and add one row per event. The rows below are examples for a made-up invoicing product.
| Event name | Trigger (when it fires) | Key properties | Question it answers | Owner | Status |
|---|---|---|---|---|---|
| Account Created | Server confirms new account saved | signup_method, referral_source | How many people sign up, and from where? | Growth lead | Live |
| Invoice Sent | Invoice email successfully queued to a client | invoice_count, is_first_invoice | What share of signups activate? | Product lead | In development |
| Plan Upgraded | Billing system confirms paid plan change | from_plan, to_plan | What do users do before converting? | Founder | Planned |
The trigger column is the one most teams skip and later regret. "When the user signs up" can mean when they click the button, when the form submits or when the account is actually saved. Those can give different numbers. Be precise.
How to roll out your first events
- List your questions. Write three to five decisions analytics must support in the next six months.
- Define activation. Agree the one action that shows a new user got real value.
- Draft 10 to 15 events. Cover signup, onboarding, activation, core usage and revenue signals.
- Add properties sparingly. Two or three per event is usually enough at first.
- Review with engineering. Confirm each trigger is technically clear and, where possible, fires from the server for important events.
- Implement and test. Trigger each event yourself in a test account and check that it appears once, with the right properties.
- Build three charts. A signup to activation funnel, weekly active users of your core action and a simple retention view.
- Review monthly. Add events only when a new question needs them, and retire events nobody uses.
Example
Imagine a two-founder startup selling a booking tool to yoga studios. They suspect many studios sign up but never go live. Instead of tracking every click, they pick 12 events, with "Booking Page Published" as activation. After a month, the funnel shows that most drop-off happens at "Payment Provider Connected." They simplify that step and add a help video. The next month, more new studios publish their booking page, and the founders know exactly why. (This is a made-up example with no real data.)
Privacy, consent and data quality
Product analytics involves personal data, so treat it with care from the start. In the UK and EU, GDPR applies to personal data you collect, and cookie consent rules can apply to analytics cookies and similar tracking. Elsewhere, local privacy laws may apply too. Keep your privacy notice clear about what you track and why, and check with a privacy professional if you are unsure what consent you need.
- Collect only what you need. Avoid putting names, email addresses or free-text content into event properties.
- Use internal user IDs rather than personal details to link events.
- Decide how long you keep raw event data, and delete what you no longer need.
- Separate test and production data so your team's own clicking does not inflate the numbers.
This is general information, not legal advice. Privacy rules differ by country and change over time, so check the official guidance where you operate.
When you choose an analytics tool, compare current features, pricing, data location and privacy policies carefully. Many tools offer a free tier that is enough for an early tracking plan.
Common mistake
Tracking an event in two places. If both the app and the server send "Plan Upgraded," you will count every upgrade twice and wonder why revenue does not match. Pick one source for each event and write it in the tracking plan.
If you are planning next year's roadmap this autumn, this is a good time to set up your first events. A clean baseline over the quieter holiday weeks means you will start January with real numbers to compare against.
Your first events action plan
- Write three to five questions analytics must answer
- Agree on your activation moment as a team
- Draft 10 to 15 events across the five groups
- Choose a naming convention and write it down
- Fill in the tracking plan with triggers, properties and owners
- Check privacy notices and consent requirements
- Implement, test in a separate account and build three core charts
- Schedule a monthly review of events and questions
Frequently asked questions
How many events should a startup track at first?
For most early products, 10 to 15 well-defined events are enough. That covers signup, onboarding, activation, core use and revenue. Add more only when a specific new question requires them.
Is automatic click tracking a bad idea?
Not necessarily, but it should not replace a tracking plan. Automatic tracking can help explore behavior, while your named events give you reliable numbers for key decisions. Treat them as separate layers.
Who should own the tracking plan?
One named person, often a product lead or founder, should own it, with engineering responsible for implementation. Shared ownership with no single owner is how naming drifts and duplicate events appear.
When should we hire a data analyst?
Usually once your questions outgrow what founders and product managers can answer with basic charts. Until then, a clean tracking plan makes any future analyst far more effective.
Related reading
The bottom line
Good startup product analytics begins with a short list of questions and a short list of events. Define activation, pick 10 to 15 events across signup, onboarding, usage and revenue, name them consistently and write everything in a tracking plan that the whole team can read.
Start small this month, test carefully and review the plan regularly. A few trustworthy numbers will guide better decisions than a mountain of data nobody believes.
