Tech Handbook Null Yard

Web Analytics and Tagging - Practical Handbook

Analytics should answer concrete questions and support decisions. A tracking plan should define the event, trigger, parameters, business purpose and validation method. Without this, tagging quickly becomes a collection of unrelated events.

GA4 uses an event-oriented model, but implementation still requires consent handling, data-quality checks and consistent naming.

Related topics: A/B Testing and Experiments, Technical SEO, Browser DevTools and JavaScript.

1. Purpose of analytics

Web analytics should answer concrete business and product questions.

Typical goals:

  • understand traffic sources,
  • measure user behavior,
  • measure conversions,
  • find funnel drop-offs,
  • compare campaigns,
  • validate experiments,
  • monitor data quality.

Do not track everything just because you can. Track what supports a decision.

2. Page view

A page view records that a page was displayed.

Typical fields:

page_location
page_title
page_referrer
timestamp
user/session context

In traditional multi-page sites, page views usually happen on navigation.

In SPAs, page-view events may need to be sent manually when routes change.

3. Event

An event represents an action or state change.

Examples:

product_view
add_to_cart
form_submit
download
video_start
login
purchase

4. Good event name

Use names that are:

  • short,
  • descriptive,
  • stable,
  • consistently formatted.

Prefer:

form_submit
product_view
cta_click

Avoid ambiguous names such as:

click1
event_new
button_test

5. Event schema

Define what each event contains.

Example:

{
  "event": "product_view",
  "product_id": "ABC123",
  "category": "laptop",
  "price": 4999,
  "currency": "PLN"
}

Document required and optional fields.

6. dataLayer

A data layer separates application data from analytics tools.

Example:

window.dataLayer = window.dataLayer || [];

window.dataLayer.push({
  event: "purchase",
  transaction_id: "T123",
  value: 499.99,
  currency: "PLN"
});

The website emits structured events; the tag manager decides what to send where.

7. Tag manager

A tag manager lets teams manage analytics and marketing tags without hard-coding each integration directly into the application.

Typical concepts:

  • tags,
  • triggers,
  • variables,
  • containers,
  • environments.

Keep governance strict. A tag manager can execute code in the browser.

8. GA4 - event model

Google Analytics 4 uses an event-oriented data model.

Important concepts include:

  • events,
  • event parameters,
  • user properties,
  • conversions/key events,
  • sessions.

Do not invent a new naming convention for every campaign or page.

9. UTM parameters

Typical UTM parameters:

utm_source
utm_medium
utm_campaign
utm_content
utm_term

Example:

https://example.com/?utm_source=newsletter&utm_medium=email&utm_campaign=autumn_sale

10. Consistent UTM naming

Choose conventions once.

For example:

source: newsletter, facebook, linkedin
medium: email, paid_social, organic_social
campaign: autumn_sale_2026

Avoid mixing:

FB
facebook
Facebook
facebook.com

11. Source / Medium

Source identifies where traffic came from.

Medium identifies the channel type.

Example:

source = linkedin
medium = paid_social

12. Campaign

Campaign should represent the marketing initiative, not the individual creative asset.

Creative-level differentiation belongs in utm_content where appropriate.

13. Conversion

A conversion is an event important enough to represent business or product success.

Examples:

  • purchase,
  • lead submission,
  • account creation,
  • subscription.

Define conversions explicitly.

14. Funnel

A funnel is a sequence of steps.

Example:

landing page
→ product view
→ add to cart
→ checkout
→ purchase

Measure both completion and drop-off.

15. Attribution

Attribution assigns credit for a conversion to touchpoints.

There is no universally perfect attribution model.

Treat attribution as a model, not an objective truth.

16. First click / last click

First click: credits the first known touchpoint.

Last click: credits the final touchpoint before conversion.

Each answers a different question.

Analytics and advertising tracking may require user consent depending on jurisdiction and implementation.

Your tracking architecture should respect consent state before firing restricted tags.

18. PII

Do not send personally identifiable information into analytics tools unless explicitly permitted and required.

Avoid fields such as:

  • email addresses,
  • phone numbers,
  • names,
  • raw form contents.

19. Debugging

Use:

  • browser DevTools,
  • network requests,
  • tag-manager preview/debug mode,
  • analytics debug views,
  • console logging in development.

Verify both the event and its parameters.

20. Duplicate events

Common causes:

  • handler registered twice,
  • SPA route event + automatic pageview,
  • both frontend and backend sending the same conversion,
  • tag firing on multiple triggers.

Duplicates corrupt reporting.

21. SPA

Single-page applications require explicit route-change tracking.

Watch for:

  • virtual page views,
  • route timing,
  • duplicate initialization,
  • stale page metadata.

22. Server-side tracking

Server-side tracking can improve control and reliability.

Possible flow:

browser
→ your backend
→ analytics/marketing endpoint

It does not automatically remove consent/privacy obligations.

23. Data quality

Monitor:

  • missing events,
  • duplicates,
  • invalid parameters,
  • sudden volume changes,
  • broken campaign tagging,
  • impossible funnel transitions.

Analytics without data quality checks becomes misleading quickly.

24. Tracking-plan documentation

A tracking plan should include:

event name
purpose
trigger
parameters
required/optional fields
data source
destination
owner

25. Minimal workflow

define business question
→ define event
→ define schema
→ implement
→ test in browser
→ verify destination
→ document
→ monitor quality

26. What you should know

You should understand:

  • page views,
  • events,
  • event schemas,
  • dataLayer,
  • tag managers,
  • GA4 event logic,
  • UTM parameters,
  • attribution,
  • consent,
  • PII,
  • SPA tracking,
  • server-side tracking,
  • debugging,
  • data-quality monitoring.

The key rule: analytics is only useful when event definitions are stable, documented and trusted.

Official references

  • Google Analytics events: https://support.google.com/analytics/answer/9322688
  • Google Tag Manager: https://developers.google.com/tag-platform/tag-manager
  • Consent Mode: https://developers.google.com/tag-platform/security/guides/consent