In Daniel Pertu’s account of one application, five of its ten analytics event groups were never called by the code. Insights that depended on them stayed at “no data”—and waiting longer could not fix the problem. The cause was not low traffic or a broken integration: the events were defined, but the application did not emit them.
How a defined event turned into “no data”
Pertu says the project’s analytics file listed around 50 custom events across ten groups. Payment, feature, engagement, error, and marketing events had no call sites in the application. Because no runtime event was sent for those groups, insights built on them remained empty.
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The important distinction is between an event name appearing in a catalog and code actually emitting that event during an application flow. A dashboard can offer an event for analysis even when no user action ever sends it.
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These figures describe Pertu’s project, not how common the problem is across analytics implementations. The account’s publication year and the implementation’s current state are not established.
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What the team removed—and what it kept
Pertu says the event set was reduced to 11 entries. The surviving list included game starts and completions, sign-out, a checkout-start event, onboarding lifecycle events, and review-prompt events. The account does not establish that every retained event was independently tested or that this list is still current.
Keep an event only when it can change a decision
Pertu’s rule for adding an event was that the answer should affect a decision the team would make. An interesting question alone was not enough. That rule makes event review concrete: identify what action would change if the result were high, low, or absent. If no decision changes, the event may add maintenance and data collection without helping the team act.
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Check whether an existing source already answers the question
For the signup funnel, the application already recorded pageviews for /signup, /signup/success, and /dashboard. Pertu says the team removed separate signup-started, signup-completed, signup-failed, and sign-in events because those routes could support the funnel. Hand-fired funnel events can drift out of sync with the application’s routes as the product changes; a pageview funnel instead follows the routes being measured.
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The report’s other choices were specific to that project: errors were handled in Sentry, revenue was tracked in Stripe as the system of record, and per-user history lived in the application database when the product needed it. Those are architectural choices in this case, not universal requirements for every team.
Retain events with a distinct operational purpose
Sign-out stayed in the list for a reason separate from measuring a funnel. Pertu says its handler captured user:signed_out and called resetIdentity(). On a shared browser, failing to reset identity can leave the prior person’s distinct ID in place and merge the next person’s activity with theirs. The account describes why this mattered in that application; teams should check how their own analytics SDK handles identity across sign-out and account changes.
Verify events in application paths, not just in a catalog
A practical audit starts by tracing each event from its definition to the user action that should trigger it. Search for its call site, then exercise that flow and confirm the event is sent. A declaration, chart, or configured event name does not prove emission.
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- Find a real call site: identify the handler, route, or lifecycle path that emits the event. If none exists, the event cannot populate an insight.
- Exercise the intended path: perform the action in the application and confirm a request containing the event reaches the analytics endpoint.
- Inspect identity and properties: confirm the event has the expected identity and only the properties the analysis needs.
- Check the insight’s dependency: make sure it uses an event that is actually emitted, or a pageview or system of record that already answers the question.
Pertu describes inspecting same-domain /ingest requests, including an event endpoint. In that implementation, the SDK was not exposed as window.posthog, and payloads appeared compressed in the browser’s Network tab. The report cautions that this view did not reveal which events had been sent, so seeing ingestion traffic alone was not proof that a particular event fired.
Collect only properties needed to answer the question
The account says the project limited identification to a plan_tier property and deliberately did not send email. For onboarding, it used taxonomy IDs and derived booleans—such as whether a selected employer or role appeared in the available list—instead of transmitting free-text responses. That let the team assess whether its taxonomy covered people’s needs without collecting the company name someone typed.
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This is a useful design test: define the decision first, then send the least detailed property that can support it. A property that does not change the analysis is a candidate to omit.
Preserve useful event history when names change
Pertu kept the existing category:action naming pattern because retained events already had history; renaming them could leave established charts without their expected event names. When changing instrumentation, account for how existing insights depend on event names before replacing them.
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