Claude-code-marketing-skills conversion-debug
Conversion Tracking Debugger — diagnose discrepancies across GTM, GA4, Google Ads & Meta Pixel with live API access, BigQuery validation queries, and troubleshooting flowcharts
git clone https://github.com/cognyai/claude-code-marketing-skills
T=$(mktemp -d) && git clone --depth=1 https://github.com/cognyai/claude-code-marketing-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/conversion-debug" ~/.claude/skills/cognyai-claude-code-marketing-skills-conversion-debug && rm -rf "$T"
skills/conversion-debug/SKILL.mdConversion 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:
- Use GTM tools to inspect tags, triggers, and workspace status
- Use GA4 tools to check conversion events, run reports, and verify data streams
- Use Google Ads tools to query conversion action status and performance
- Use Meta tools to check pixel configuration and compare conversion counts
- 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:
- dataLayer push -- Website pushes event data to
window.dataLayer - GTM triggers -- Tags fire based on trigger conditions matching dataLayer events
- Network requests -- Each tag sends a separate HTTP request to its destination
- Platform processing -- Each platform processes, deduplicates, and attributes independently
- 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 | for browser+CAPI dedup | 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
- Consent Mode blocking -- Tag fires but sends no data when consent denied
- Ad blockers -- ~25-30% of users block
requestsgoogle-analytics.com - Race conditions -- Page unloads before request completes (form submits, outbound links)
- Measurement ID mismatch -- Wrong
in the tag configG-XXXXXXX - Data filters -- GA4 property filters hiding or altering events
- Draft vs published -- GTM Preview uses draft; live site uses published version
Duplicate Conversions
The most expensive tracking bug. Common causes:
- Missing
-- GA4 cannot deduplicate without a unique IDtransaction_id - Double-firing tags -- Multiple tags sending the same conversion
- Thank-you page reloads -- User refreshes the confirmation page
- Back button -- User navigates back to confirmation
- 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
exactly (case-sensitive)?dataLayer.push({ event: '...' }) - All filter conditions correct?
- No blocking triggers preventing fire?
Variable Values (in Preview mode):
populated and unique?transaction_id
andvalue
present and correct types?currency- 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):
-- GA4google-analytics.com/g/collect
-- Google Adsgoogleads.g.doubleclick.net/pagead/conversion
-- Meta Pixelfacebook.com/tr
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 |
|---|---|
| GA4 cookies and full measurement |
| Google Ads cookies and conversion measurement |
| Sending user data to Google for advertising |
| Remarketing and personalized advertising |
Behavior:
-- Full data collection, cookies set, user-level data sentgranted
-- Cookieless pings, Google models conversions (appear in UI, NOT in BigQuery)denied
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
on user choice?gtag('consent', 'update', ...) - GTM built-in consent checks enabled?
set (500ms recommended)?wait_for_update- Consent persists across pages?
- Denied state: cookieless pings sent (
in Network tab)?gcs=G100 - 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 |
|---|---|---|
| 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
(hashed email)?em=
Server-Side Tagging
Benefits
- Ad blocker resistance -- First-party domain, not blocked
- Longer cookie lifetime -- 2+ years vs 7 days (ITP)
- Reduced page weight -- Fewer browser scripts
- Data control -- Inspect/modify before sending to vendors
- 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