Recommended Free Tools
Set up analytics by deciding which product decisions need better evidence, writing a small tracking plan, instrumenting only the events that answer those questions, and verifying the data before relying on reports. Then review what the system collects, who can access it, and how that collection fits your users and jurisdictions.
Start with the decisions your team needs to make
Analytics is useful when it helps the team choose what to change—not simply when a dashboard contains many charts. Begin with a short list of decisions, such as whether onboarding is too difficult, whether users reach the product’s core action, whether they return, or where failures occur.
For each decision, write the question in a way that data can answer. For example, “Do new users finish onboarding?” could become a funnel question about the proportion of users who start and complete onboarding. “Do users come back?” might require a defined return period and a cohort of users who first completed a meaningful action. Specify what counts as completion, return, or failure before collecting data.
Keep the first release narrow. Amplitude’s implementation guidance recommends choosing one data source, beginning with two or three high-value events, and writing a plan before expanding instrumentation: Plan your implementation.
The Tool Desk
Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →#1 Best Overall
Write a tracking plan before adding events
A tracking plan is the shared specification for what the product sends to analytics and what each event means. It reduces the risk that developers instrument similar actions inconsistently or that a dashboard later combines data with different meanings.
For every initial event, document:
- Event name: Use a consistent, readable naming style, such as
onboarding_completed. - Trigger: State the exact product action or system condition that causes the event to fire, including when it must not fire.
- Properties: List the additional context needed to answer the product question, and define each property’s meaning and type.
- Identity rules: Decide how anonymous visitors, signed-in users, and account changes should be represented, and how duplicate identities are handled.
- Test traffic: Establish how development, employee, or other test activity will be distinguished from real user activity.
For example, an event for onboarding completion should have one defined completion point. If one platform sends it when a user reaches the final screen and another sends it only after saving the last step, the resulting comparison is misleading even if both events use the same name.
Understand the data model: events and properties
Most product analytics starts with events—records of actions, system activity, or errors—and adds properties that provide context. Google’s Firebase Analytics documentation describes events as actions, system events, or errors, and user properties as attributes that help describe user segments: Get started with Google Analytics for Web.
Rank #2
- Wiley
- Language: english
- Book - storytelling with data: a data visualization guide for business professionals
Use event properties for facts about a particular occurrence, such as the feature used or the step reached. Use user properties for attributes intended to describe a user or segment over time. Keep both categories tied to a question the team intends to answer; a property that has no defined use still adds collection and governance burden.
Outdated Drivers Are Slowing You Down
One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchPC Slower Than It Used to Be?
A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11Choose an implementation that fits your product
There is no universally best analytics tool for every startup. Compare candidates against the questions and operating constraints you have actually identified, rather than choosing based on a feature list or a familiar dashboard.
| Decision area | What to check |
|---|---|
| Product questions | Can the tool support the funnels, retention views, cohorts, event exploration, or broader site and app measurement you need? |
| Platforms and effort | Does it support your web and mobile platforms, and what SDK, API, or engineering work is required to instrument them? |
| Events and identity | Can you maintain consistent event definitions and handle anonymous-to-known identity changes? If users move between products, can you analyze those journeys in a way that suits your identity model? |
| Validation and data flow | Can the team inspect incoming events, troubleshoot implementation, export data, and connect it to downstream workflows where needed? |
| Privacy and operations | Review collection controls, consent configuration, hosting or data-location options, access controls, operational complexity, and expected total cost at your likely usage. |
Google’s Firebase guide covers enabling Analytics, adding the SDK, logging events for web apps, and using suggested events when applicable. PostHog documents a product analytics installation path and says customer-facing products such as a marketing site, web app, and mobile app can be grouped in one project to follow journeys across them. These are examples of setup approaches, not a complete comparison of tools. Feature availability and implementation details can change, so verify them in the vendor documentation for your platforms and requirements.
Instrument a small event set
Once the plan is agreed, add only the events needed for the first product questions. Prefer the platform’s suggested event definitions when they fit; otherwise, define custom events consistently across platforms. Avoid adding a large catalogue “just in case”: it makes testing, interpretation, and privacy review harder without guaranteeing useful answers.
Keep the code and tracking plan aligned. When an event’s trigger or a property changes, update the specification and check any reports that depend on the old definition. Treat analytics instrumentation like product behavior that needs ownership, not a one-time SDK task.
Quick wins for a faster PC:
Clear out junk files and repair common Windows errorsFree Scan →Scan for outdated or missing drivers - takes under a minuteDriver Scan →Repair Windows errors before they cause bigger problemsFix Now →Verify collection before trusting reports
An SDK installing successfully does not prove that analytics is correct. Test every planned event in a development or otherwise controlled environment and inspect the received event data. Google documents DebugView for verifying events; PostHog’s installation guidance also says to test the setup after its installation flow.
Rank #4
- Perform the exact user action that should trigger the event.
- Confirm the event appears and fires once at the intended moment—not before, after, or repeatedly.
- Check that required properties are present, use the specified types, and contain the expected values.
- Confirm test activity can be distinguished from production user activity.
- Inspect the payload for information the team did not intend to collect, then correct the instrumentation before using the data.
For Firebase web implementations, use the vendor’s DebugView documentation to understand event verification. For PostHog, follow its Product Analytics installation guide and test the completed setup. A clean test of one event is not a substitute for checking the rest of the planned events and properties.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Make privacy and data handling part of the setup
Decide what the product sends before collecting real user data. Personal data can identify a person directly or in combination with other information; PostHog’s privacy guidance discusses analytics in relation to principles including a good reason for collection, unambiguous consent, and secure handling. It also places responsibility on the customer to decide what to collect and communicate that choice to users: PostHog privacy compliance.
Do not send credentials, payment details, private message contents, or other sensitive information merely because an analytics SDK can accept arbitrary properties. For each field, ask whether it is necessary for a stated product question, whether a less identifying alternative would work, and who needs access.
Best Value
Google says default Analytics collection includes user counts, session statistics, approximate geolocation, and browser and device information. Its documentation also describes website client IDs and mobile app-instance identifiers: Data collection. Review defaults and identifiers as part of data minimization rather than assuming that only the custom events you add are collected.
Set retention, access, deletion, and user-facing disclosure practices appropriate to the product and the places where it operates. Whether consent or another legal basis is required depends on jurisdiction, implementation, and context; vendor documentation does not establish a universal legal rule. Have qualified privacy counsel assess the startup’s obligations before relying on a particular collection practice.
Turn the first data into a reliable operating habit
After validation and privacy review, use the initial event set to answer the decisions that motivated it. Have product and engineering agree on the meaning of each report before acting on a change. If a question cannot be answered because an event is ambiguous, an identity rule is missing, or a platform behaves differently, fix the definition or instrumentation rather than treating a plausible-looking chart as proof.
Expand tracking only when a new decision requires additional evidence. Revisit event definitions as the product changes, and repeat validation when instrumentation, identity handling, or collection settings change. This keeps the analytics system understandable as the startup grows.
Quick Recap
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
