Pull GA4 reports, traffic data, and insights from the Google Analytics Data API. Use when asked about website traffic, user behavior, acquisition channels, conversions, or audience segments.
Library skill — the default version is maintained in GitHub; edits you make live in your own clone.
Pull reports and insights from GA4 using the Google Analytics Data API.
Requires Google OAuth credentials:
- GOOGLE_CLIENT_ID
- GOOGLE_CLIENT_SECRET
- A valid OAuth access token (refreshed as needed)
Set credentials in .env, .env.local, or ~/.claude/.env.global.
# Step 1: Get authorization code (user must visit this URL in browser)
echo "https://accounts.google.com/o/oauth2/v2/auth?client_id=${GOOGLE_CLIENT_ID}&redirect_uri=urn:ietf:wg:oauth:2.0:oob&scope=https://www.googleapis.com/auth/analytics.readonly&response_type=code&access_type=offline"
# Step 2: Exchange code for tokens
curl -s -X POST "https://oauth2.googleapis.com/token" \
-d "code={AUTH_CODE}" \
-d "client_id=${GOOGLE_CLIENT_ID}" \
-d "client_secret=${GOOGLE_CLIENT_SECRET}" \
-d "redirect_uri=urn:ietf:wg:oauth:2.0:oob" \
-d "grant_type=authorization_code"
# Step 3: Refresh an expired token
curl -s -X POST "https://oauth2.googleapis.com/token" \
-d "refresh_token={REFRESH_TOKEN}" \
-d "client_id=${GOOGLE_CLIENT_ID}" \
-d "client_secret=${GOOGLE_CLIENT_SECRET}" \
-d "grant_type=refresh_token"
Store the refresh token securely. The access token expires after 1 hour.
curl -s -H "Authorization: Bearer ${GA_ACCESS_TOKEN}" \
"https://analyticsadmin.googleapis.com/v1beta/accountSummaries" \
| python3 -c "
import json, sys
data = json.load(sys.stdin)
for acct in data.get('accountSummaries', []):
for prop in acct.get('propertySummaries', []):
print(f\"{prop['property']} | {prop.get('displayName','')} | Account: {acct.get('displayName','')}\")
"
The property ID format is properties/XXXXXXXXX.
POST https://analyticsdata.googleapis.com/v1beta/{property_id}:runReport
All report requests use POST with a JSON body. Always include Authorization: Bearer {ACCESS_TOKEN}.
Get sessions, users, page views, and engagement rate over a date range.
curl -s -X POST \
"https://analyticsdata.googleapis.com/v1beta/properties/{PROPERTY_ID}:runReport" \
-H "Authorization: Bearer ${GA_ACCESS_TOKEN}" \
-H "Content-Type: application/json" \
-d '{
"dateRanges": [{"startDate": "30daysAgo", "endDate": "today"}],
"metrics": [
{"name": "sessions"},
{"name": "totalUsers"},
{"name": "newUsers"},
{"name": "screenPageViews"},
{"name": "engagementRate"},
{"name": "averageSessionDuration"},
{"name": "bounceRate"}
]
}'
today, yesterday7daysAgo, 14daysAgo, 28daysAgo, 30daysAgo, 90daysAgo2024-01-01See where users come from (channels, sources, campaigns).
curl -s -X POST \
"https://analyticsdata.googleapis.com/v1beta/properties/{PROPERTY_ID}:runReport" \
-H "Authorization: Bearer ${GA_ACCESS_TOKEN}" \
-H "Content-Type: application/json" \
-d '{
"dateRanges": [{"startDate": "30daysAgo", "endDate": "today"}],
"dimensions": [
{"name": "sessionDefaultChannelGroup"}
],
"metrics": [
{"name": "sessions"},
{"name": "totalUsers"},
{"name": "engagementRate"},
{"name": "conversions"}
],
"orderBys": [{"metric": {"metricName": "sessions"}, "desc": true}],
"limit": 20
}'
| Dimension | Description |
|---|---|
sessionDefaultChannelGroup |
Channel grouping (Organic, Paid, Social, etc.) |
sessionSource |
Traffic source (google, facebook, etc.) |
sessionMedium |
Medium (organic, cpc, referral, etc.) |
sessionCampaignName |
UTM campaign name |
firstUserSource |
First-touch attribution source |
Find the highest-traffic pages on the site.
curl -s -X POST \
"https://analyticsdata.googleapis.com/v1beta/properties/{PROPERTY_ID}:runReport" \
-H "Authorization: Bearer ${GA_ACCESS_TOKEN}" \
-H "Content-Type: application/json" \
-d '{
"dateRanges": [{"startDate": "30daysAgo", "endDate": "today"}],
"dimensions": [
{"name": "pagePath"}
],
"metrics": [
{"name": "screenPageViews"},
{"name": "totalUsers"},
{"name": "engagementRate"},
{"name": "averageSessionDuration"}
],
"orderBys": [{"metric": {"metricName": "screenPageViews"}, "desc": true}],
"limit": 25
}'
Understand how users interact with your content.
curl -s -X POST \
"https://analyticsdata.googleapis.com/v1beta/properties/{PROPERTY_ID}:runReport" \
-H "Authorization: Bearer ${GA_ACCESS_TOKEN}" \
-H "Content-Type: application/json" \
-d '{
"dateRanges": [{"startDate": "30daysAgo", "endDate": "today"}],
"dimensions": [
{"name": "pagePath"}
],
"metrics": [
{"name": "engagedSessions"},
{"name": "engagementRate"},
{"name": "averageSessionDuration"},
{"name": "screenPageViewsPerSession"},
{"name": "eventCount"}
],
"orderBys": [{"metric": {"metricName": "engagedSessions"}, "desc": true}],
"limit": 20
}'
| Metric | What It Measures |
|---|---|
engagementRate |
% of sessions that were engaged (>10s, 2+ pages, or conversion) |
averageSessionDuration |
Mean session length in seconds |
screenPageViewsPerSession |
Pages per session |
bounceRate |
% of sessions with no engagement |
eventCount |
Total events fired |
Report on conversion events (purchases, signups, etc.).
curl -s -X POST \
"https://analyticsdata.googleapis.com/v1beta/properties/{PROPERTY_ID}:runReport" \
-H "Authorization: Bearer ${GA_ACCESS_TOKEN}" \
-H "Content-Type: application/json" \
-d '{
"dateRanges": [{"startDate": "30daysAgo", "endDate": "today"}],
"dimensions": [
{"name": "eventName"}
],
"metrics": [
{"name": "eventCount"},
{"name": "totalUsers"},
{"name": "eventValue"}
],
"dimensionFilter": {
"filter": {
"fieldName": "eventName",
"inListFilter": {
"values": ["purchase", "sign_up", "generate_lead", "begin_checkout"]
}
}
}
}'
curl -s -X POST \
"https://analyticsdata.googleapis.com/v1beta/properties/{PROPERTY_ID}:runReport" \
-H "Authorization: Bearer ${GA_ACCESS_TOKEN}" \
-H "Content-Type: application/json" \
-d '{
"dateRanges": [{"startDate": "30daysAgo", "endDate": "today"}],
"dimensions": [
{"name": "sessionDefaultChannelGroup"}
],
"metrics": [
{"name": "sessions"},
{"name": "conversions"},
{"name": "totalRevenue"}
],
"orderBys": [{"metric": {"metricName": "conversions"}, "desc": true}]
}'
Break down traffic by device, geography, and demographics.
curl -s -X POST \
"https://analyticsdata.googleapis.com/v1beta/properties/{PROPERTY_ID}:runReport" \
-H "Authorization: Bearer ${GA_ACCESS_TOKEN}" \
-H "Content-Type: application/json" \
-d '{
"dateRanges": [{"startDate": "30daysAgo", "endDate": "today"}],
"dimensions": [{"name": "deviceCategory"}],
"metrics": [
{"name": "sessions"},
{"name": "totalUsers"},
{"name": "engagementRate"},
{"name": "conversions"}
]
}'
Replace deviceCategory with country in the dimensions.
curl -s -X POST \
"https://analyticsdata.googleapis.com/v1beta/properties/{PROPERTY_ID}:runReport" \
-H "Authorization: Bearer ${GA_ACCESS_TOKEN}" \
-H "Content-Type: application/json" \
-d '{
"dateRanges": [{"startDate": "30daysAgo", "endDate": "today"}],
"dimensions": [
{"name": "landingPage"},
{"name": "sessionSource"}
],
"metrics": [
{"name": "sessions"},
{"name": "engagementRate"},
{"name": "conversions"}
],
"orderBys": [{"metric": {"metricName": "sessions"}, "desc": true}],
"limit": 30
}'
Compare two time periods to identify trends.
curl -s -X POST \
"https://analyticsdata.googleapis.com/v1beta/properties/{PROPERTY_ID}:runReport" \
-H "Authorization: Bearer ${GA_ACCESS_TOKEN}" \
-H "Content-Type: application/json" \
-d '{
"dateRanges": [
{"startDate": "30daysAgo", "endDate": "today", "name": "current"},
{"startDate": "60daysAgo", "endDate": "31daysAgo", "name": "previous"}
],
"metrics": [
{"name": "sessions"},
{"name": "totalUsers"},
{"name": "conversions"},
{"name": "engagementRate"}
]
}'
GA4 API returns JSON. Parse with python3 or jq:
# Parse report into a table
curl -s -X POST "..." | python3 -c "
import json, sys
data = json.load(sys.stdin)
headers = [h['name'] for h in data.get('dimensionHeaders',[])] + [m['name'] for m in data.get('metricHeaders',[])]
print(' | '.join(headers))
print('-' * (len(headers) * 20))
for row in data.get('rows', []):
dims = [d['value'] for d in row.get('dimensionValues',[])]
mets = [m['value'] for m in row.get('metricValues',[])]
print(' | '.join(dims + mets))
"
When asked for a monthly report:
Present as a structured report with tables, trends (up/down arrows), and recommendations:
## Monthly Analytics Report: {Property Name}
### Period: {date range} vs {previous period}
### Traffic Summary
| Metric | Current | Previous | Change |
|--------|---------|----------|--------|
| Sessions | X | Y | +Z% |
| ...
### Top Channels
...
### Top Pages
...
### Conversion Summary
...
### Recommendations
- [Based on data patterns]
properties/XXXXXXXXX)