GA4 Ecommerce Conversion Diagnostic

I checked the uploaded package.

The files can support a reusable GA4 ecommerce conversion diagnostic dataset. The package is structured like GA4 Data API exports combined with Shopify reconciliation and business diagnosis tables.

The strongest dataset direction is:

GA4 behavior data -> funnel problem -> page/channel evidence -> Shopify reconciliation -> reusable diagnosis rule

This should not be positioned as a generic traffic dashboard. It is better as a conversion diagnostic dataset that helps teams understand why traffic does not become revenue.

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The uploaded files support five recurring GA4 ecommerce analysis problems:

1. Paid Social brings many sessions but weak buying intent.
2. SEO blog traffic creates page views but few carts or purchases.
3. Mobile users start checkout but fail before payment.
4. Product pages get views but do not create enough add-to-cart behavior.
5. GA4 purchase revenue and purchase counts do not fully reconcile with Shopify orders and net sales.

This is a good GoalfyData use case because GoalfyData can preserve the business layer around GA4 metrics: definitions, table relationships, diagnosis rules, reconciliation logic, and Agent Skill routing.

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Uploaded Package Structure
Package: ga4_ecommerce_conversion_diagnostic_2026-08-04.zip
Source folder: /Users/zoey/Downloads/案例2/ga4_ecommerce_conversion_diagnostic_2026-08-04/
Source type: uploaded GA4 API-like files
Mode: manual import candidate for GoalfyData

Files

00_ga4_property_config.csv — 1 row
GA4 property configuration, ecommerce store context, timezone, currency, and schema status.

01_ga4_channel_daily_api_like.csv — 720 rows
Daily channel, source/medium, campaign, device, sessions, purchases, purchase revenue, spend, and ROAS.

02_ga4_landing_page_daily_api_like.csv — 5,760 rows
Landing page sessions, carts, purchases, engagement, page type, and diagnosis hints.

03_ga4_event_name_daily_api_like.csv — 7,200 rows
Event-level daily funnel signals from session_start to view_item, add_to_cart, checkout, and purchase.

04_ga4_item_performance_daily_api_like.csv — 4,320 rows
Item-level views, carts, purchases, item revenue, and refunds.

05_ga4_campaign_cost_daily_api_like.csv — 270 rows
Campaign cost, attributed revenue, spend-aware channel quality, and ROAS inputs.

06_ga4_shopify_reconciliation_daily.csv — 30 rows
GA4 purchases and revenue compared with Shopify order outcomes.

07_goalfydata_ga4_problem_rules.csv — 5 rows
Reusable GA4 conversion diagnostic rules.

08_diagnosis_findings.csv — 5 rows
Prioritized diagnostic findings with evidence and recommended questions.

09_goalfydata_ga4_skill_map.csv — 6 rows
Agent Skill routing for GA4 diagnostic questions.

Supporting files:

• README.md
• analysis_questions_and_sql.md
• schema.sql
• schema_import.sql
• schema_import_fojg6k6ragzf.sql
• validation_report.csv
• goalfydata_ga4_dataset_design_notes.md

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I will build the GA4 conversion diagnostic dataset from the uploaded structured files and keep the reusable business context inside GoalfyData.

Confirmed dataset:

GA4 Ecommerce Conversion Diagnostic
Dataset ID: fojg6k6ragzf
Source type: manual import from uploaded GA4 ecommerce files
Source files: GA4 API-like channel, page, event, item, campaign cost, Shopify reconciliation, problem rules, findings, and skill map tables

The goal is to show how GoalfyData solves recurring GA4 analysis problems such as inconsistent metric interpretation, unclear conversion friction, channel-quality diagnosis, page-intent diagnosis, Shopify reconciliation, and reusable agent routing.

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Dataset Structure
GA4 Ecommerce Conversion Diagnostic
ID: fojg6k6ragzf
Schema: uds_fojg6k6ragzf
Source: uploaded GA4 ecommerce diagnostic package
Mode: manual import from CSV files
Validation: all 10 CSV files passed

Tables

ga4_property_config — 1 row
GA4 property and store configuration: property_id, property name, stream, website, business model, market, currency, date range, source type, source notice.

ga4_channel_daily_api_like — 720 rows
Daily channel performance by date, channel, source/medium, campaign, device, and country.
Key fields: sessions, active users, engaged sessions, item views, add-to-carts, checkouts, purchases, revenue, refunds, ad cost, ROAS, intent segment.

ga4_landing_page_daily_api_like — 5,760 rows
Landing page diagnosis by date, page, channel, campaign, and device.
Key fields: page type, page role, sessions, engagement, views, carts, checkouts, purchases, revenue, diagnosis hint.

ga4_event_name_daily_api_like — 7,200 rows
Event-level funnel data by date, event name, channel, campaign, and device.
Key fields: event count, total users, key events, total revenue.

ga4_item_performance_daily_api_like — 4,320 rows
Product/item performance by date, item, channel, source/medium, and device.
Key fields: item views, add-to-cart, purchases, item revenue, cart-to-view rate, purchase-to-view rate.

ga4_campaign_cost_daily_api_like — 270 rows
Campaign spend data by date, channel, source/medium, campaign, and device.
Key fields: ad cost, clicks, impressions, linked platform.

ga4_shopify_reconciliation_daily — 30 rows
Daily GA4 vs Shopify reconciliation.
Key fields: Shopify orders, GA4 purchases, order gap, Shopify net sales, GA4 purchase revenue, refunds, revenue gap, suspected reason, recommended action.

goalfydata_ga4_problem_rules — 5 rows
Reusable diagnosis rules.
Fields: rule_id, problem, trigger_logic, why_goalfydata_helps, tables_to_use.

diagnosis_findings — 5 rows
Prioritized diagnostic findings for the case.
Fields: finding_id, period, severity, problem, evidence, recommended_question, goalfydata_value.

goalfydata_ga4_skill_map — 6 rows
Agent Skill routing table.
Fields: skill_id, skill_name, ga4_problem, required_tables, core_metrics, relation_logic, analysis_question, why_goalfydata_skill_matters.

Relations

• ga4_channel_daily_api_like.event_date -> ga4_shopify_reconciliation_daily.event_date
• ga4_landing_page_daily_api_like.event_date + default_channel_group + device_category -> ga4_channel_daily_api_like.event_date + default_channel_group + device_category
• ga4_event_name_daily_api_like.event_date + default_channel_group + device_category -> ga4_channel_daily_api_like.event_date + default_channel_group + device_category
• ga4_item_performance_daily_api_like.event_date + default_channel_group + device_category -> ga4_channel_daily_api_like.event_date + default_channel_group + device_category
• ga4_campaign_cost_daily_api_like.event_date + campaign_name connects campaign spend to channel/campaign performance
• goalfydata_ga4_problem_rules connects to diagnosis_findings by business problem
• goalfydata_ga4_skill_map.required_tables routes each Agent Skill to the relevant tables

Rules

• purchaseRevenue is GA4 purchase revenue after GA4-recorded refunds and should not be treated as Shopify net sales.
• ecommercePurchases counts GA4 purchase events and can differ from Shopify orders because of consent, tagging, payment delay, duplicate or missing transaction IDs, and attribution timing.
• Paid Social should be judged by cart-to-view rate and purchase-per-session, not sessions alone.
• SEO blog pages should be separated from product and collection landing pages before conversion diagnosis.
• Mobile checkout should be compared against desktop baseline before concluding that the product has no demand.
• Campaign spend should be interpreted at campaign/date grain, not as direct order-level attribution.

Agent Skills

• Channel Quality Diagnosis
• Mobile Checkout Friction Diagnosis
• Landing Page Intent Diagnosis
• Product Intent Diagnosis
• Revenue Reconciliation
• Finding Prioritization

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Done. I created and deployed a dashboard app for this dataset.

App: ga4-conversion-diagnostic
App ID: ga4-conversion-diagnosti-310a2b8c7aeb
URL: https://app-9c196c6289af-ga4-conversion-diagnosti-310a2b8c7aeb.goalfydata.app
Bound dataset: GA4 Ecommerce Conversion Diagnostic (fojg6k6ragzf)

The dashboard includes:

• Conversion workspace overview
• Insight and recommendation panel
• Issue priority
• KPI cards for sessions, purchases, revenue, and Paid Social ROAS
• Channel performance
• Paid Social diagnostic
• Landing-page and funnel diagnosis
• Relationship and Agent Skill views

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Analysis complete. I queried the GA4 conversion diagnostic dataset and found:

Dataset Snapshot

• Time range: 2026-07-01 to 2026-07-30
• Sessions: 228,994
• Ecommerce purchases: 485
• GA4 purchase revenue: $59,444.71
• Advertiser ad cost: $67,584.54
• Add-to-carts: 5,115
• Checkouts: 1,701
• Shopify orders: 591
• Shopify net sales: $65,475.19
• Reusable problem rules: 5
• Agent Skill routes: 6

Channel Snapshot

Channel	Sessions	Purchases	Revenue	Spend	ROAS / purchase rate
Paid Social	84,119	9	$753.63	$36,435.03	0.02 ROAS
Organic Search	55,309	18	$1,947.48	$0.00	0.03% purchase/session
Paid Search	33,586	141	$16,894.58	$31,149.51	0.54 ROAS
Direct	18,253	119	$15,298.06	$0.00	0.65% purchase/session
Email	15,247	198	$24,550.96	$0.00	1.30% purchase/session

Key Findings

1. Paid Social is the largest traffic source but the weakest commercial channel.
   It generated 84.1K sessions but only 9 purchases, with $36.4K ad cost and 0.02 ROAS.

2. Email and Direct traffic show much stronger buying intent.
   Email produced 198 purchases from 15.2K sessions, and Direct produced 119 purchases from 18.3K sessions.

3. Organic Search is mostly research intent.
   It produced 55.3K sessions but only 18 purchases, so SEO pages need to be separated from product and collection pages before conversion diagnosis.

4. GA4 and Shopify do not fully reconcile.
   Shopify shows 591 orders and $65.5K net sales, while GA4 shows 478 ecommerce purchases and $58.9K purchase revenue in the reconciliation table. The dataset records order gaps, revenue gaps, suspected reasons, and recommended GoalfyData actions.

5. The dataset shows GoalfyData's governance value.
   The metric rules, table relationships, and Agent Skill map preserve how future agents should analyze GA4 conversion issues instead of reinterpreting the CSV files each time.

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Done. I shared GA4 Ecommerce Conversion Diagnostic with u***@example.com.

Access scope:

• Included: ga4_property_config
• Included: ga4_channel_daily_api_like
• Included: ga4_landing_page_daily_api_like
• Included: ga4_event_name_daily_api_like
• Included: ga4_item_performance_daily_api_like
• Included: ga4_campaign_cost_daily_api_like
• Included: ga4_shopify_reconciliation_daily
• Included: goalfydata_ga4_problem_rules
• Included: diagnosis_findings
• Excluded: goalfydata_ga4_skill_map

Status: pending
Permission: read-only

The invitation email was sent. If they do not see it, ask them to check spam/junk.

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Done. I shared the GA4 conversion diagnostic dashboard with v***@example.com.

Dashboard: ga4-conversion-diagnostic
Bound dataset: GA4 Ecommerce Conversion Diagnostic (fojg6k6ragzf)
Visibility: specified email only
Permission: read-only
Status: pending
Email sent: yes

The dashboard stays bound to the governed GA4 dataset, so the recipient sees the same conversion, reconciliation, relationship, and Agent Skill context.

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Done. I shared GA4 Ecommerce Conversion Diagnostic with w***@example.com.

Access scope:

• Included: full dataset

Status: pending
Permission: read-only

The invitation email was sent. If they do not see it, ask them to check spam/junk.

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