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What events should you track to answer product questions?
Choose events by working backward from a question the team needs to answer. For example:
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- Where do new users abandon onboarding? Track meaningful onboarding stages, such as starting setup, completing a required step, and finishing onboarding.
- Which feature use precedes repeat usage? Track the feature action that represents meaningful use and the later return or repeat-use outcome, with a consistent time window if the analysis requires one.
- Which checkout step loses buyers? Track entry into checkout, completion of important steps, and purchase completion so the points of exit can be compared.
These are examples of questions and observable actions, not claims about measured product outcomes. The key is to make the question answerable from behavior: a vague goal such as “improve engagement” needs a defined outcome and a specific user journey before it can guide instrumentation.
Amplitude recommends beginning with the insights a team wants and selecting events that support those questions. It groups useful starting points around actions that complete a process, guide users through a product’s main mechanics, or enable in-app purchases. Those categories are a starting framework, not a complete taxonomy for every product. See Amplitude’s event-selection guidance.
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What events do you need?
Use the product question to distinguish essential events from incidental interactions. An event should represent an action whose occurrence or absence helps explain a meaningful stage, outcome, or decision. A click is not automatically useful simply because it is easy to record.
- Process completion: Capture the stages that show whether a user advances through a meaningful flow.
- Core product mechanics: Capture actions that represent users experiencing the product’s principal functionality.
- Purchase or conversion: Where relevant, capture the actions that lead to and complete a purchase or other defined conversion.
Amplitude warns that too little tracking can leave questions unanswered, while tracking everything can bury useful signal in unnecessary events and properties. Its documentation gives illustrative estimates of around 20 events for a focused app and 200 for a feature-rich product. These are vendor examples, not a universal quota or a research-backed target; use the questions your team must answer to set scope.
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How to create a practical event tracking plan
1. Write the question and the decision
State what the team wants to learn, then name the decision or outcome the analysis should inform. Define success in terms that can be observed. For a checkout change, for instance, the question might be which step users fail to complete; the outcome could be completed purchases. Amplitude’s planning and instrumentation workflow recommends connecting instrumentation to the metrics a feature affects and its definition of success.
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2. Map the user journey
Lay out the meaningful stages between the starting point and the outcome. Select events that distinguish those stages or show completion. Avoid adding every button press by default: include a low-level interaction only when it helps explain a decision, diagnose a failure, or answer a stated question.
3. Define events and properties
An event records an action; its properties describe the context in which that action occurred. For example, an event might record a plan selection, while properties could provide the plan tier or acquisition channel. The event name alone should make the action recognizable, and each property should have an agreed meaning and expected type or values where those constraints matter to analysis.
Document each event’s stable name, plain-language definition, firing condition, source, and reason for collection. For each property, record what it means and its type; note allowed or expected values when needed for consistent reporting. Amplitude’s data-team quickstart and tracking-plan documentation describe plans as shared specifications for implementation and analysis, including descriptions, categories, sources, and expected property types.
4. Decide how users and accounts are represented
For products used by teams or organizations, determine whether a question is about an individual user, an account, or both. Decide whether an account association should apply persistently to a user or only to particular events; those choices affect how activity is grouped. Amplitude’s account-instrumentation guidance distinguishes event-level group association from persistent user-level association and says changes apply to new data rather than rewriting historical records.
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Keep development or staging traffic separate from production, then check events against the tracking plan before relying on dashboards. Amplitude recommends a testing project for each production project. Its documentation also warns that event naming and historical data have limits: raw historical records cannot always be renamed or repaired retroactively. See Amplitude’s getting-started documentation and instrumentation workflow.
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6. Inspect real events and revise deliberately
Verify that each event arrives with the expected name, properties, identity, and timing. Google Analytics provides Realtime and DebugView for inspecting events and parameters; its event setup documentation explains recommended and custom event setup through the Google tag or Google Tag Manager. Amplitude likewise recommends validating incoming data against the plan. If the data differs from the specification, fix the instrumentation and document the change rather than silently changing the meaning of an event.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How many events should you track?
There is no evidence-based universal event count in the cited guidance. Amplitude offers two different contextual heuristics: around 20 events for a focused app and 200 for a feature-rich product on its event-selection page, and a range of 15–200 events for developing a fuller understanding of app engagement in its chart guide. These are separate vendor recommendations with different contexts, not a single target range or a quota for every product. See event selection and the chart guide.
A more useful test is whether each event supports a named product question or a necessary operational check. If the team cannot say what decision a proposed event helps with, leave it out until a real need emerges. If an important question cannot be answered from the current plan, add the missing action or context deliberately.
Where should events be instrumented?
Events may come from a product SDK, a server-side or API implementation, or a third-party integration. The right source depends on where the action is authoritative and which system can capture its context reliably. For example, a client may observe an interface interaction, while a server can be the appropriate source for a confirmed transaction. Whatever the route, the plan should document the source and the team should validate the actual payload.
Amplitude documents SDK and integration routes; its getting-started material names Segment, mParticle, and Tealium as examples of third-party options for sending data. These are documented examples, not endorsements. Compare approaches on schema review and validation, debugging visibility, identity and account handling, and the limits on correcting historical data. Capabilities and availability can vary by product plan, and no current pricing or plan entitlements are established here. See Amplitude’s data setup overview and product overview.
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