Conversion Tracking Debugger

Debug conversion tracking across GTM, GA4, Google Ads, and Meta Pixel. Diagnose discrepancies, find duplicate conversions, validate enhanced conversions, audit Consent Mode v2, and run BigQuery validation queries.

Full docs: https://cogny.com/docs/conversion-tracking-debugger

Usage

/conversion-debug                          # Full debugging overview
/conversion-debug duplicate conversions    # Diagnose duplicate purchases
/conversion-debug consent mode             # Consent Mode v2 audit
/conversion-debug meta vs ga4              # Cross-platform discrepancy analysis
/conversion-debug enhanced conversions     # Validate enhanced conversion setup
/conversion-debug server-side tagging      # Server-side GTM overview
/conversion-debug value wrong              # Debug incorrect conversion values

Instructions

You are a conversion tracking debugging expert. Use this reference and the available MCP tools to help users diagnose and fix conversion tracking issues across GTM, GA4, Google Ads, and Meta Pixel.

When the user asks a question, find the relevant section below and provide precise, actionable answers. When MCP tools are available, use them to pull live data from the user's accounts to validate findings.

If the user provides a specific topic as an argument, focus on that area. Otherwise, ask what platform or issue they need help with.

When MCP tools are available, follow this diagnostic approach:

1. Use GTM tools to inspect tags, triggers, and workspace status
2. Use GA4 tools to check conversion events, run reports, and verify data streams
3. Use Google Ads tools to query conversion action status and performance
4. Use Meta tools to check pixel configuration and compare conversion counts
5. Cross-reference findings across platforms to identify the root cause

---

The Conversion Tracking Stack

Understanding data flow is the first step to debugging:

User Action (click, form submit, purchase)
        |
        v
+-------------------+
|   Website / App   |
|   (dataLayer)     |
+-------------------+
        |
        v
+-------------------+       +-------------------+
|  Google Tag       | ----> |  GA4              |
|  Manager (GTM)    |       |  (Measurement     |
|                   |       |   Protocol)       |
|  - GA4 Config Tag |       +-------------------+
|  - GA4 Event Tag  |               |
|  - Google Ads Tag |               v
|  - Meta Pixel Tag |       +-------------------+
+-------------------+       |  BigQuery Export  |
        |                   |  (daily/intraday) |
        |                   +-------------------+
        |
        +----------> +-------------------+
        |            |  Google Ads       |
        |            |  (Conversion      |
        |            |   Tracking)       |
        |            +-------------------+
        |
        +----------> +-------------------+
                     |  Meta Pixel       |
                     |  + Conversions    |
                     |    API (CAPI)     |
                     +-------------------+

Key data flow points:

1. dataLayer push -- Website pushes event data to window.dataLayer
2. GTM triggers -- Tags fire based on trigger conditions matching dataLayer events
3. Network requests -- Each tag sends a separate HTTP request to its destination
4. Platform processing -- Each platform processes, deduplicates, and attributes independently
5. BigQuery export -- GA4 exports raw events to BigQuery (daily ~5 AM property timezone)

Common Discrepancies and Why

GA4 vs Google Ads Conversion Count Differences

GA4 and Google Ads will almost never match. This is expected.

Factor	GA4	Google Ads
Attribution model	Data-driven (cross-channel)	Data-driven (Google channels only)
Counting method	Configurable: once per session or once per event	Configurable: one or every conversion
Conversion window	Default 30 days	Default 30 days (up to 90 days)
Cross-device	Google Signals + User-ID	Google account sign-in
View-through	Not counted by default	Included for Display/Video (1-day default)
Data freshness	24-72h processing lag	Conversions appear within hours
Modeled conversions	Behavioral modeling for consent gaps	Conversion modeling for unobserved

Typical variance: 5-20% is normal. Over 20% warrants investigation.

MCP diagnostic approach:

1. GA4: tool_list_conversion_events → check which events are marked as conversions
2. GA4: tool_run_report → pull conversion counts by date
3. Google Ads: tool_execute_gaql → query conversion_action metrics
4. Compare the numbers and identify the gap source

Meta Pixel vs GA4 Differences

Factor	Meta	GA4
Click-through window	7 days (default)	30 days (default)
View-through	1-day included by default	Not counted by default
Attribution	Last-touch within Meta	Data-driven cross-channel
Deduplication	eventID for browser+CAPI dedup	transaction_id parameter
Cross-device	Facebook login graph	Google Signals + User-ID

Why Meta often reports higher: View-through conversions. User sees Meta ad, doesn't click, later converts via Google search. Meta counts it; GA4 attributes to organic/CPC.

GTM Firing but GA4 Not Receiving

1. Consent Mode blocking -- Tag fires but sends no data when consent denied
2. Ad blockers -- ~25-30% of users block google-analytics.com requests
3. Race conditions -- Page unloads before request completes (form submits, outbound links)
4. Measurement ID mismatch -- Wrong G-XXXXXXX in the tag config
5. Data filters -- GA4 property filters hiding or altering events
6. Draft vs published -- GTM Preview uses draft; live site uses published version

Duplicate Conversions

The most expensive tracking bug. Common causes:

1. Missing transaction_id -- GA4 cannot deduplicate without a unique ID
2. Double-firing tags -- Multiple tags sending the same conversion
3. Thank-you page reloads -- User refreshes the confirmation page
4. Back button -- User navigates back to confirmation
5. Missing CAPI dedup -- Meta Pixel and CAPI both fire without matching eventID

Prevention:

// dataLayer push with transaction_id for deduplication
window.dataLayer.push({
  event: 'purchase',
  ecommerce: {
    transaction_id: 'T-12345',  // REQUIRED for dedup
    value: 99.99,
    currency: 'USD',
    items: [/* ... */]
  }
});

// Prevent duplicate pushes on page reload
if (!window.sessionStorage.getItem('purchase_tracked_T-12345')) {
  window.dataLayer.push({
    event: 'purchase',
    ecommerce: { transaction_id: 'T-12345', value: 99.99, currency: 'USD' }
  });
  window.sessionStorage.setItem('purchase_tracked_T-12345', 'true');
}

Debugging Checklist by Platform

Google Tag Manager (GTM)

Preview Mode Inspection:

• Correct workspace/container version active?
• Trigger event appears in the timeline?
• Tag shows as "Fired"?
• No unexpected duplicate tags firing?

Trigger Conditions:

• Event name matches dataLayer.push({ event: '...' }) exactly (case-sensitive)?
• All filter conditions correct?
• No blocking triggers preventing fire?

Variable Values (in Preview mode):

• transaction_id populated and unique?
• value and currency present and correct types?
• Custom JS variables returning expected values?

dataLayer Inspection:

// View full dataLayer
console.table(window.dataLayer);

// Filter for purchase events
window.dataLayer.filter(e => e.event === 'purchase');

// Check ecommerce data
window.dataLayer.filter(e => e.event === 'purchase').map(e => e.ecommerce);

Network Request Verification (DevTools > Network):

• google-analytics.com/g/collect -- GA4
• googleads.g.doubleclick.net/pagead/conversion -- Google Ads
• facebook.com/tr -- Meta Pixel

MCP diagnostic:

tool_list_tags → see all tags in the container
tool_search_tags → find conversion-related tags
tool_get_tag → inspect specific tag configuration
tool_list_triggers → verify trigger setup
tool_get_workspace_status → check for unpublished changes

GA4

DebugView:

// Enable debug mode
gtag('config', 'G-XXXXXXX', { debug_mode: true });

Then GA4 > Admin > DebugView: verify events, parameters, user properties.

Realtime Reports:

• Event count incrementing on trigger?
• Conversions card shows the event?

MCP diagnostic:

tool_list_conversion_events → verify which events are marked as conversions
tool_run_realtime_report → check real-time event data
tool_run_report → pull historical conversion data by date
tool_list_data_streams → verify stream configuration

BigQuery Validation:

-- Check conversion events in BigQuery
SELECT
  event_name,
  COUNT(*) as event_count,
  COUNT(DISTINCT user_pseudo_id) as unique_users,
  MIN(TIMESTAMP_MICROS(event_timestamp)) as earliest,
  MAX(TIMESTAMP_MICROS(event_timestamp)) as latest
FROM `project.analytics_PROPERTY_ID.events_*`
WHERE _TABLE_SUFFIX BETWEEN
  FORMAT_DATE('%Y%m%d', DATE_SUB(CURRENT_DATE(), INTERVAL 3 DAY))
  AND FORMAT_DATE('%Y%m%d', CURRENT_DATE())
  AND event_name IN ('purchase', 'generate_lead', 'sign_up', 'add_to_cart', 'begin_checkout')
GROUP BY event_name
ORDER BY event_count DESC

Google Ads

Conversion Action Status:

• "Recording conversions" (green) = working
• "No recent conversions" = tag installed but not firing or data delayed
• "Tag inactive" = no hits in 7+ days
• "Unverified" = tag never detected

MCP diagnostic:

tool_execute_gaql →
  SELECT
    conversion_action.name,
    conversion_action.status,
    conversion_action.type,
    conversion_action.tag_snippets,
    metrics.conversions,
    metrics.conversions_value
  FROM conversion_action
  WHERE segments.date DURING LAST_7_DAYS

tool_get_gaql_doc → look up conversion_action fields

Google Tag Verification:

// Check gtag is loaded
typeof gtag === 'function'  // Should be true

// Check conversion linker cookie
document.cookie.split(';').filter(c => c.includes('_gcl'))

Meta Pixel

Events Manager Test Events:

• Enter website URL, perform conversion, verify event appears
• Check event parameters (value, currency, content_ids)
• Check Event Match Quality score (aim for 6+)

CAPI Deduplication: Both browser Pixel and CAPI events must share the same eventID:

// Browser-side
fbq('track', 'Purchase', {
  value: 99.99,
  currency: 'USD',
  content_ids: ['SKU-123'],
  content_type: 'product'
}, { eventID: 'purchase_T-12345' });

# Server-side CAPI
curl -X POST \
  "https://graph.facebook.com/v18.0/PIXEL_ID/events?access_token=TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "data": [{
      "event_name": "Purchase",
      "event_time": 1700000000,
      "event_id": "purchase_T-12345",
      "action_source": "website",
      "user_data": {
        "em": ["HASHED_EMAIL"],
        "client_ip_address": "1.2.3.4",
        "client_user_agent": "Mozilla/5.0..."
      },
      "custom_data": {
        "value": 99.99,
        "currency": "USD",
        "content_ids": ["SKU-123"]
      }
    }]
  }'

MCP diagnostic:

tool_get_pixels → verify pixel configuration
tool_get_insights → pull conversion data for comparison with GA4/Google Ads

BigQuery Validation Queries

Count Conversions by Day (Compare to GA4 UI)

SELECT
  PARSE_DATE('%Y%m%d', event_date) as date,
  event_name,
  COUNT(*) as total_events,
  COUNT(DISTINCT user_pseudo_id) as unique_users,
  COUNT(DISTINCT
    CONCAT(user_pseudo_id, '-',
      (SELECT value.int_value FROM UNNEST(event_params) WHERE key = 'ga_session_id'))
  ) as unique_sessions
FROM `project.analytics_PROPERTY_ID.events_*`
WHERE _TABLE_SUFFIX BETWEEN
  FORMAT_DATE('%Y%m%d', DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY))
  AND FORMAT_DATE('%Y%m%d', CURRENT_DATE() - 1)
  AND event_name IN ('purchase', 'generate_lead', 'sign_up')
GROUP BY 1, 2
ORDER BY 1 DESC, 2

Small differences (1-5%) between BigQuery and GA4 UI are normal due to thresholding, sampling, and modeled conversions (present in UI, absent in BigQuery).

Find Duplicate Transaction IDs

WITH purchase_events AS (
  SELECT
    PARSE_DATE('%Y%m%d', event_date) as date,
    user_pseudo_id,
    (SELECT value.string_value FROM UNNEST(event_params)
     WHERE key = 'transaction_id') as transaction_id,
    TIMESTAMP_MICROS(event_timestamp) as event_time,
    ecommerce.purchase_revenue_in_usd as revenue
  FROM `project.analytics_PROPERTY_ID.events_*`
  WHERE _TABLE_SUFFIX BETWEEN
    FORMAT_DATE('%Y%m%d', DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY))
    AND FORMAT_DATE('%Y%m%d', CURRENT_DATE() - 1)
    AND event_name = 'purchase'
)

SELECT
  transaction_id,
  COUNT(*) as occurrence_count,
  COUNT(DISTINCT user_pseudo_id) as distinct_users,
  MIN(event_time) as first_occurrence,
  MAX(event_time) as last_occurrence,
  TIMESTAMP_DIFF(MAX(event_time), MIN(event_time), SECOND) as seconds_between,
  SUM(revenue) as total_revenue_recorded,
  MAX(revenue) as actual_revenue
FROM purchase_events
WHERE transaction_id IS NOT NULL
GROUP BY transaction_id
HAVING COUNT(*) > 1
ORDER BY occurrence_count DESC

-- Find purchases with NULL transaction_id (cannot be deduplicated)
SELECT
  PARSE_DATE('%Y%m%d', event_date) as date,
  COUNT(*) as purchases_without_txn_id,
  SUM(ecommerce.purchase_revenue_in_usd) as revenue_at_risk
FROM `project.analytics_PROPERTY_ID.events_*`
WHERE _TABLE_SUFFIX BETWEEN
  FORMAT_DATE('%Y%m%d', DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY))
  AND FORMAT_DATE('%Y%m%d', CURRENT_DATE() - 1)
  AND event_name = 'purchase'
  AND (SELECT value.string_value FROM UNNEST(event_params) WHERE key = 'transaction_id') IS NULL
GROUP BY 1
ORDER BY 1 DESC

Check Conversion Event Parameters Completeness

SELECT
  event_name,
  param.key,
  COUNT(*) as events_with_param,
  COUNT(DISTINCT user_pseudo_id) as users_with_param,
  COUNTIF(param.value.string_value IS NOT NULL) as has_string_value,
  COUNTIF(param.value.int_value IS NOT NULL) as has_int_value,
  COUNTIF(param.value.float_value IS NOT NULL) as has_float_value
FROM `project.analytics_PROPERTY_ID.events_*`,
  UNNEST(event_params) as param
WHERE _TABLE_SUFFIX BETWEEN
  FORMAT_DATE('%Y%m%d', DATE_SUB(CURRENT_DATE(), INTERVAL 7 DAY))
  AND FORMAT_DATE('%Y%m%d', CURRENT_DATE() - 1)
  AND event_name IN ('purchase', 'generate_lead', 'sign_up', 'begin_checkout')
GROUP BY 1, 2
ORDER BY 1, events_with_param DESC

-- Check required ecommerce fields on purchase events
SELECT
  PARSE_DATE('%Y%m%d', event_date) as date,
  COUNT(*) as total_purchases,
  COUNTIF(ecommerce.transaction_id IS NOT NULL) as has_transaction_id,
  COUNTIF(ecommerce.purchase_revenue_in_usd > 0) as has_revenue,
  COUNTIF(ecommerce.total_item_quantity > 0) as has_quantity,
  COUNTIF(ARRAY_LENGTH(items) > 0) as has_items,
  ROUND(SAFE_DIVIDE(
    COUNTIF(
      ecommerce.transaction_id IS NOT NULL
      AND ecommerce.purchase_revenue_in_usd > 0
      AND ARRAY_LENGTH(items) > 0
    ), COUNT(*)
  ) * 100, 1) as pct_fully_complete
FROM `project.analytics_PROPERTY_ID.events_*`
WHERE _TABLE_SUFFIX BETWEEN
  FORMAT_DATE('%Y%m%d', DATE_SUB(CURRENT_DATE(), INTERVAL 30 DAY))
  AND FORMAT_DATE('%Y%m%d', CURRENT_DATE() - 1)
  AND event_name = 'purchase'
GROUP BY 1
ORDER BY 1 DESC

Validate Enhanced Conversions Data

SELECT
  PARSE_DATE('%Y%m%d', event_date) as date,
  event_name,
  COUNT(*) as total_events,
  COUNTIF(user_id IS NOT NULL) as has_user_id,
  COUNTIF(
    (SELECT value.string_value FROM UNNEST(user_properties) WHERE key = 'email') IS NOT NULL
    OR (SELECT value.string_value FROM UNNEST(event_params) WHERE key = 'user_data_email') IS NOT NULL
  ) as has_email_signal,
  COUNTIF(
    (SELECT value.string_value FROM UNNEST(user_properties) WHERE key = 'phone') IS NOT NULL
    OR (SELECT value.string_value FROM UNNEST(event_params) WHERE key = 'user_data_phone') IS NOT NULL
  ) as has_phone_signal
FROM `project.analytics_PROPERTY_ID.events_*`
WHERE _TABLE_SUFFIX BETWEEN
  FORMAT_DATE('%Y%m%d', DATE_SUB(CURRENT_DATE(), INTERVAL 7 DAY))
  AND FORMAT_DATE('%Y%m%d', CURRENT_DATE() - 1)
  AND event_name IN ('purchase', 'generate_lead', 'sign_up')
GROUP BY 1, 2
ORDER BY 1 DESC, 2

Cross-Reference Expected vs Actual Events

WITH expected_events AS (
  SELECT event_name FROM UNNEST([
    'purchase', 'add_to_cart', 'begin_checkout', 'view_item',
    'generate_lead', 'sign_up', 'add_payment_info', 'add_shipping_info'
  ]) as event_name
),
actual_events AS (
  SELECT
    event_name,
    COUNT(*) as event_count,
    MAX(TIMESTAMP_MICROS(event_timestamp)) as last_seen
  FROM `project.analytics_PROPERTY_ID.events_*`
  WHERE _TABLE_SUFFIX BETWEEN
    FORMAT_DATE('%Y%m%d', DATE_SUB(CURRENT_DATE(), INTERVAL 7 DAY))
    AND FORMAT_DATE('%Y%m%d', CURRENT_DATE() - 1)
  GROUP BY event_name
)

SELECT
  e.event_name,
  COALESCE(a.event_count, 0) as event_count,
  a.last_seen,
  CASE
    WHEN a.event_count IS NULL THEN 'MISSING - never received'
    WHEN a.last_seen < TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 48 HOUR) THEN 'STALE - no events in 48h'
    ELSE 'OK'
  END as status
FROM expected_events e
LEFT JOIN actual_events a USING(event_name)
ORDER BY
  CASE WHEN a.event_count IS NULL THEN 0 WHEN a.last_seen < TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 48 HOUR) THEN 1 ELSE 2 END,
  e.event_name

Consent Mode v2

How It Affects Conversion Tracking

Google Consent Mode v2 (required in EEA since March 2024) controls data collection based on user consent.

Required signals:

Signal	Controls
analytics_storage	GA4 cookies and full measurement
ad_storage	Google Ads cookies and conversion measurement
ad_user_data	Sending user data to Google for advertising
ad_personalization	Remarketing and personalized advertising

Behavior:

• granted -- Full data collection, cookies set, user-level data sent
• denied -- Cookieless pings, Google models conversions (appear in UI, NOT in BigQuery)

Implementation

// Set defaults BEFORE GTM snippet
gtag('consent', 'default', {
  analytics_storage: 'denied',
  ad_storage: 'denied',
  ad_user_data: 'denied',
  ad_personalization: 'denied',
  wait_for_update: 500
});

// Update on user choice (called by CMP)
gtag('consent', 'update', {
  analytics_storage: 'granted',
  ad_storage: 'granted',
  ad_user_data: 'granted',
  ad_personalization: 'granted'
});

Implementation Checklist

• Default consent set BEFORE GTM snippet loads?
• All four v2 signals configured?
• CMP calls gtag('consent', 'update', ...) on user choice?
• GTM built-in consent checks enabled?
• wait_for_update set (500ms recommended)?
• Consent persists across pages?
• Denied state: cookieless pings sent (gcs=G100 in Network tab)?
• Granted state: full measurement resumes?

BigQuery: Consent Impact Analysis

SELECT
  PARSE_DATE('%Y%m%d', event_date) as date,
  COUNTIF(user_pseudo_id IS NOT NULL) as events_with_user_id,
  COUNTIF(user_pseudo_id IS NULL) as events_without_user_id,
  COUNTIF(
    (SELECT value.int_value FROM UNNEST(event_params) WHERE key = 'ga_session_id') IS NOT NULL
  ) as events_with_session,
  ROUND(SAFE_DIVIDE(
    COUNTIF((SELECT value.int_value FROM UNNEST(event_params) WHERE key = 'ga_session_id') IS NULL),
    COUNT(*)
  ) * 100, 1) as pct_likely_consent_denied
FROM `project.analytics_PROPERTY_ID.events_*`
WHERE _TABLE_SUFFIX BETWEEN
  FORMAT_DATE('%Y%m%d', DATE_SUB(CURRENT_DATE(), INTERVAL 7 DAY))
  AND FORMAT_DATE('%Y%m%d', CURRENT_DATE() - 1)
GROUP BY 1
ORDER BY 1 DESC

Enhanced Conversions

What Data Is Sent

Hashed first-party customer data sent alongside conversion tags for better matching.

Field	Format	Required
Email	SHA-256 hashed, lowercase, trimmed	At least one of: email, phone, or name+address
Phone	SHA-256 hashed, E.164 format	Optional but recommended
First/Last name	SHA-256 hashed, lowercase	Optional
Address fields	SHA-256 hashed	Optional
Country	ISO 3166-1 alpha-2, unhashed	Optional

Setup via GTM (dataLayer method)

window.dataLayer.push({
  event: 'purchase',
  user_data: {
    email: 'user@example.com',       // Auto-hashed by GTM
    phone_number: '+11234567890',
    address: {
      first_name: 'John',
      last_name: 'Doe',
      street: '123 Main St',
      city: 'New York',
      region: 'NY',
      postal_code: '10001',
      country: 'US'
    }
  },
  ecommerce: {
    transaction_id: 'T-12345',
    value: 99.99,
    currency: 'USD'
  }
});

Setup via gtag.js

gtag('set', 'user_data', {
  email: 'user@example.com',
  phone_number: '+11234567890',
  address: {
    first_name: 'John', last_name: 'Doe',
    street: '123 Main St', city: 'New York',
    region: 'NY', postal_code: '10001', country: 'US'
  }
});

Validation Checklist

• Google Ads > Conversions > Diagnostics > Enhanced Conversions status = "Recording"?
• Match rate visible after 48-72h?
• GTM Preview: "User-provided data" tab shows hashed values?
• Network request contains em= (hashed email)?

Server-Side Tagging

Benefits

1. Ad blocker resistance -- First-party domain, not blocked
2. Longer cookie lifetime -- 2+ years vs 7 days (ITP)
3. Reduced page weight -- Fewer browser scripts
4. Data control -- Inspect/modify before sending to vendors
5. Better consent -- Single enforcement point

Architecture

Browser                    Server                          Endpoints
GTM Web Container  --->  GTM Server Container  --->  GA4 / Google Ads / Meta CAPI
                         (Cloud Run)
                         gtm.yourdomain.com

First-Party Domain Setup

// GA4 Config tag: set server container URL
gtag('config', 'G-XXXXXXX', {
  server_container_url: 'https://gtm.yourdomain.com'
});

# DNS: CNAME to Cloud Run service
gtm.yourdomain.com  CNAME  your-cloud-run-service.run.app

Troubleshooting Flowcharts

Conversions Not Showing Up

Tag installed? --NO--> Install tag. Publish GTM container.
  |YES
  v
Tag fires in GTM Preview? --NO--> Check trigger: event name exact match?
  |YES                              Conditions met? Blocking triggers?
  v
Network request in DevTools? --NO--> Consent Mode blocking?
  |YES                                Ad blocker? CSP blocking?
  v
Request returning 200/204? --NO--> Check endpoint URL, measurement ID, credentials.
  |YES
  v
Platform-specific:
- GA4: Wait 24-48h. Check DebugView. Check data filters.
- Google Ads: Wait 24h. Check conversion action status. Is it "Primary"?
- Meta: Check Events Manager > Test Events. Check event match quality.

Conversion Count Mismatch

Difference > 20%? --NO--> Normal variance. Document baseline.
  |YES
  v
Which platform shows MORE?
- Google Ads > GA4: Counting "every"? View-through? Longer window? Modeled?
- GA4 > Google Ads: All channels vs Google-only? Action set to Primary?
- Meta > GA4: View-through included? iOS modeling?
- GA4 > Meta: Ad blockers? No CAPI? Low match quality?
  |
  v
Run BigQuery validation queries to get ground truth.

Conversion Value Wrong

Value always 0/NULL? --YES--> Check: 'value' in dataLayer? 'currency' present?
  |NO                          value is number not string? Variable mapping?
  v
Value consistently wrong? --YES--> Static value override? Currency conversion?
  |NO
  v
Value doubled? --YES--> Duplicate events. Multiple tags. Double dataLayer push.
  |NO
  v
Check: tax/shipping included? cents vs dollars? string formatting? locale?

Quick Reference: dataLayer Examples

E-Commerce Purchase

window.dataLayer.push({ ecommerce: null });  // Clear previous
window.dataLayer.push({
  event: 'purchase',
  ecommerce: {
    transaction_id: 'T-12345',
    value: 99.99,
    tax: 8.50,
    shipping: 5.99,
    currency: 'USD',
    items: [{
      item_id: 'SKU-001',
      item_name: 'Product Name',
      item_brand: 'Brand',
      item_category: 'Category',
      price: 99.99,
      quantity: 1
    }]
  }
});

Lead Generation

window.dataLayer.push({
  event: 'generate_lead',
  value: 50.00,
  currency: 'USD',
  lead_source: 'contact_form'
});

gtag.js Direct (No GTM)

// Google Ads conversion
gtag('event', 'conversion', {
  send_to: 'AW-XXXXXXXXX/CONVERSION_LABEL',
  value: 99.99,
  currency: 'USD',
  transaction_id: 'T-12345'
});

// GA4 purchase
gtag('event', 'purchase', {
  transaction_id: 'T-12345',
  value: 99.99,
  currency: 'USD',
  items: [{ item_id: 'SKU-001', item_name: 'Product', price: 99.99, quantity: 1 }]
});

Resources

• GA4 Conversion Setup: https://support.google.com/analytics/answer/9267568
• Google Ads Conversion Tracking: https://support.google.com/google-ads/answer/6095821
• Enhanced Conversions: https://support.google.com/google-ads/answer/9888656
• Consent Mode: https://developers.google.com/tag-platform/security/guides/consent
• Meta Conversions API: https://developers.facebook.com/docs/marketing-api/conversions-api
• GTM Server-Side Tagging: https://developers.google.com/tag-platform/tag-manager/server-side
• Full Cogny Docs: https://cogny.com/docs/conversion-tracking-debugger