data-extraction-patterns
Common patterns for extracting and combining analytics data from GA4, GSC, and SE Ranking.Includes API patterns, rate limiting, caching, and error handling.
When & Why to Use This Skill
This Claude skill provides advanced technical patterns for extracting and merging analytics data from GA4, Google Search Console, and SE Ranking. It focuses on optimizing data pipelines through parallel execution, robust error handling, and efficient caching strategies to streamline SEO reporting and performance analysis.
Use Cases
- Automated SEO Reporting: Merging GA4 engagement metrics with GSC search performance to create comprehensive organic traffic dashboards.
- Data Pipeline Optimization: Implementing parallel API fetching and session-based caching to significantly reduce latency and bypass rate limits during large-scale data extractions.
- Cross-Platform Performance Audits: Synchronizing keyword rankings from SE Ranking with landing page data from GSC to identify high-potential content optimization opportunities.
- Reliable Data Collection: Utilizing exponential backoff and graceful degradation patterns to ensure data integrity even when specific API sources are temporarily unavailable.
| name | data-extraction-patterns |
|---|---|
| description | | |
Data Extraction Patterns
When to Use
- Setting up analytics data pipelines
- Combining data from multiple sources
- Handling API rate limits and errors
- Caching frequently accessed data
- Building data collection workflows
API Reference
Google Analytics 4 (GA4)
MCP Server: mcp-server-google-analytics
Key Operations:
get_report({
propertyId: "properties/123456789",
dateRange: { startDate: "30daysAgo", endDate: "today" },
dimensions: ["pagePath", "date"],
metrics: ["screenPageViews", "averageSessionDuration", "bounceRate"]
})
Useful Metrics:
| Metric | Description | Use Case |
|---|---|---|
| screenPageViews | Total page views | Traffic volume |
| sessions | User sessions | Visitor count |
| averageSessionDuration | Avg time in session | Engagement |
| bounceRate | Single-page visits | Content quality |
| engagementRate | Engaged sessions % | True engagement |
| scrolledUsers | Users who scrolled | Content consumption |
Useful Dimensions:
| Dimension | Description |
|---|---|
| pagePath | URL path |
| date | Date (for trending) |
| sessionSource | Traffic source |
| deviceCategory | Desktop/mobile/tablet |
Google Search Console (GSC)
MCP Server: mcp-server-gsc
Key Operations:
search_analytics({
siteUrl: "https://example.com",
startDate: "2025-11-27",
endDate: "2025-12-27",
dimensions: ["query", "page"],
rowLimit: 1000
})
get_url_inspection({
siteUrl: "https://example.com",
inspectionUrl: "https://example.com/page"
})
Available Metrics:
| Metric | Description | Use Case |
|---|---|---|
| clicks | Total clicks from search | Traffic from Google |
| impressions | Times shown in results | Visibility |
| ctr | Click-through rate | Snippet effectiveness |
| position | Average ranking | SEO success |
Dimensions:
| Dimension | Description |
|---|---|
| query | Search query |
| page | Landing page URL |
| country | User country |
| device | Desktop/mobile/tablet |
| date | Date (for trending) |
SE Ranking (Official MCP Server)
MCP Server: seo-data-api-mcp (official SE Ranking MCP)
Repository: https://github.com/seranking/seo-data-api-mcp-server
Installation (via claudeup TUI - recommended):
npx claudeup
# Navigate to: MCP Server Setup → SEO & Analytics → se-ranking
Manual Installation:
git clone https://github.com/seranking/seo-data-api-mcp-server.git
cd seo-data-api-mcp-server
docker compose build
Environment Variable: SERANKING_API_TOKEN
Available MCP Tools:
| Tool | Description | Use Case |
|---|---|---|
domainOverview |
Domain performance metrics | Overall domain health |
domainKeywords |
Keyword rankings for domain | Track ranking positions |
domainCompetitors |
Identify competitors | Competitive analysis |
domainKeywordsComparison |
Compare keywords across domains | Gap analysis |
backlinksAll |
Retrieve backlink data | Link profile audit |
relatedKeywords |
Related keyword discovery | Content expansion |
similarKeywords |
Similar keyword suggestions | Keyword clustering |
Example MCP Calls:
MCP: seo-data-api-mcp.domainOverview({ domain: "example.com" })
MCP: seo-data-api-mcp.domainKeywords({ domain: "example.com", limit: 100 })
MCP: seo-data-api-mcp.backlinksAll({ domain: "example.com" })
Parallel Execution Pattern
Optimal Data Fetch (All Sources)
## Parallel Data Fetch Pattern
When fetching from multiple sources, issue all requests in a SINGLE message
for parallel execution:
┌─────────────────────────────────────────────────────────────────┐
│ MESSAGE 1: Parallel Data Requests │
├─────────────────────────────────────────────────────────────────┤
│ │
│ [MCP Call 1]: google-analytics.get_report(...) │
│ [MCP Call 2]: google-search-console.search_analytics(...) │
│ [WebFetch 3]: SE Ranking API endpoint │
│ │
│ → All execute simultaneously │
│ → Results return when all complete │
│ → ~3x faster than sequential │
│ │
└─────────────────────────────────────────────────────────────────┘
Sequential (When Needed)
Some operations require sequential execution:
## Sequential Pattern (Dependencies)
When one request depends on another's result:
┌─────────────────────────────────────────────────────────────────┐
│ MESSAGE 1: Get list of pages │
│ → Returns: ["/page1", "/page2", "/page3"] │
├─────────────────────────────────────────────────────────────────┤
│ MESSAGE 2: Get details for each page │
│ → Uses page list from Message 1 │
│ → Can parallelize within this message │
└─────────────────────────────────────────────────────────────────┘
Rate Limiting
API Rate Limits
| API | Limit | Strategy |
|---|---|---|
| GA4 | 10 QPS per property | Batch dimensions |
| GSC | 1,200 requests/min | Paginate large exports |
| SE Ranking | 100 requests/min | Queue long operations |
Retry Pattern
#!/bin/bash
# Retry with exponential backoff
MAX_RETRIES=3
RETRY_DELAY=5
fetch_with_retry() {
local url="$1"
local attempt=1
while [ $attempt -le $MAX_RETRIES ]; do
response=$(curl -s -w "%{http_code}" -o /tmp/response.json "$url")
http_code="${response: -3}"
if [ "$http_code" = "200" ]; then
cat /tmp/response.json
return 0
elif [ "$http_code" = "429" ]; then
echo "Rate limited, waiting ${RETRY_DELAY}s..." >&2
sleep $RETRY_DELAY
RETRY_DELAY=$((RETRY_DELAY * 2))
else
echo "Error: HTTP $http_code" >&2
return 1
fi
attempt=$((attempt + 1))
done
echo "Max retries exceeded" >&2
return 1
}
Caching Pattern
Session-Based Cache
# Cache structure
SESSION_PATH="/tmp/seo-performance-20251227-143000-example"
CACHE_DIR="${SESSION_PATH}/cache"
CACHE_TTL=3600 # 1 hour in seconds
mkdir -p "$CACHE_DIR"
# Cache key generation
cache_key() {
echo "$1" | md5sum | cut -d' ' -f1
}
# Check cache
get_cached() {
local key=$(cache_key "$1")
local cache_file="${CACHE_DIR}/${key}.json"
if [ -f "$cache_file" ]; then
local age=$(($(date +%s) - $(stat -f%m "$cache_file" 2>/dev/null || stat -c%Y "$cache_file")))
if [ $age -lt $CACHE_TTL ]; then
cat "$cache_file"
return 0
fi
fi
return 1
}
# Save to cache
save_cache() {
local key=$(cache_key "$1")
local cache_file="${CACHE_DIR}/${key}.json"
cat > "$cache_file"
}
# Usage
CACHE_KEY="ga4_${URL}_${DATE_RANGE}"
if ! RESULT=$(get_cached "$CACHE_KEY"); then
RESULT=$(fetch_from_api)
echo "$RESULT" | save_cache "$CACHE_KEY"
fi
Date Range Standardization
Common Date Ranges
# Standard date range calculations
TODAY=$(date +%Y-%m-%d)
case "$RANGE" in
"7d")
START_DATE=$(date -v-7d +%Y-%m-%d 2>/dev/null || date -d "7 days ago" +%Y-%m-%d)
;;
"30d")
START_DATE=$(date -v-30d +%Y-%m-%d 2>/dev/null || date -d "30 days ago" +%Y-%m-%d)
;;
"90d")
START_DATE=$(date -v-90d +%Y-%m-%d 2>/dev/null || date -d "90 days ago" +%Y-%m-%d)
;;
"mtd")
START_DATE=$(date +%Y-%m-01)
;;
"ytd")
START_DATE=$(date +%Y-01-01)
;;
esac
END_DATE="$TODAY"
API-Specific Formats
| API | Format | Example |
|---|---|---|
| GA4 | Relative or ISO | "30daysAgo", "2025-12-01" |
| GSC | ISO 8601 | "2025-12-01" |
| SE Ranking | ISO 8601 or Unix | "2025-12-01", 1735689600 |
Graceful Degradation
Data Source Fallback
## Fallback Strategy
When a data source is unavailable:
┌─────────────────────────────────────────────────────────────────┐
│ PRIMARY SOURCE │ FALLBACK │ LAST RESORT │
├──────────────────────┼─────────────────────┼────────────────────┤
│ GA4 traffic data │ GSC clicks │ Estimate from GSC │
│ GSC search perf │ SE Ranking queries │ WebSearch SERP │
│ SE Ranking ranks │ GSC avg position │ Manual SERP check │
│ CWV (CrUX) │ PageSpeed API │ Lighthouse CLI │
└──────────────────────┴─────────────────────┴────────────────────┘
Partial Data Output
## Analysis Report (Partial Data)
### Data Availability
| Source | Status | Impact |
|--------|--------|--------|
| GA4 | NOT CONFIGURED | Missing engagement metrics |
| GSC | AVAILABLE | Full search data |
| SE Ranking | ERROR (rate limit) | Using cached rankings |
### Analysis Notes
This analysis is based on limited data sources:
- Search performance metrics are complete (GSC)
- Engagement metrics unavailable (no GA4)
- Ranking data may be 24h stale (cached)
**Recommendation**: Configure GA4 for complete analysis.
Run `/setup-analytics` to add Google Analytics.
Unified Data Model
Combined Output Structure
{
"metadata": {
"url": "https://example.com/page",
"fetchedAt": "2025-12-27T14:30:00Z",
"dateRange": {
"start": "2025-11-27",
"end": "2025-12-27"
}
},
"sources": {
"ga4": {
"available": true,
"metrics": {
"pageViews": 2450,
"avgTimeOnPage": 222,
"bounceRate": 38.2,
"engagementRate": 64.5
}
},
"gsc": {
"available": true,
"metrics": {
"impressions": 15200,
"clicks": 428,
"ctr": 2.82,
"avgPosition": 4.2
},
"topQueries": [
{"query": "seo guide", "clicks": 156, "position": 4}
]
},
"seRanking": {
"available": true,
"rankings": [
{"keyword": "seo guide", "position": 4, "volume": 12100}
],
"visibility": 42
}
},
"computed": {
"healthScore": 72,
"status": "GOOD"
}
}
Error Handling
Common Errors
| Error | Cause | Resolution |
|---|---|---|
| 401 Unauthorized | Invalid/expired credentials | Re-run /setup-analytics |
| 403 Forbidden | Missing permissions | Check API access in console |
| 429 Too Many Requests | Rate limit | Wait and retry with backoff |
| 404 Not Found | Invalid property/site | Verify IDs in configuration |
| 500 Server Error | API issue | Retry later, check status page |
Error Output Pattern
## Data Fetch Error
**Source**: Google Analytics 4
**Error**: 403 Forbidden
**Message**: "User does not have sufficient permissions for this property"
### Troubleshooting Steps
1. Verify Service Account email in GA4 Admin
2. Ensure "Viewer" role is granted
3. Check Analytics Data API is enabled
4. Wait 5 minutes for permission propagation
### Workaround
Proceeding with available data sources (GSC, SE Ranking).
GA4 engagement metrics will not be included in this analysis.