# Metrics Update Process

**Last Updated:** 2025-12-02  
**Purpose:** Step-by-step guide for updating metrics in strategy documents

---

## When to Update Metrics

### Monthly Updates (Required)

- **Timing:** First week of each month
- **Data:** Previous month's performance
- **Documents:** `ACTUAL_METRICS_2025.md`, `CHANGELOG.md`

### Quarterly Updates (Required)

- **Timing:** First week of each quarter
- **Data:** Previous quarter's performance
- **Documents:** All strategy documents (MAIN_PLAN.md, MILESTONES.md, etc.)

### Ad-Hoc Updates (As Needed)

- **Timing:** When significant changes occur
- **Triggers:** Major initiatives launched, data quality issues resolved, methodology changes
- **Documents:** Relevant strategy documents

---

## Update Workflow

### Step 1: Extract New Data

1. **Export Data from Sources:**

   - Google Search Console: Export previous month's data
   - Google Analytics 4: Export previous month's data
   - HubSpot: Export previous month's Marketing KPI Report
   - SISTRIX: Export previous month's trend data

2. **Save Files:**
   - Save to `/Users/hadyelhady/Desktop/Ordio/Strategy/Screenshots/`
   - Use consistent naming: `[Source]_[Report Type]_[YYYY-MM-DD].csv`

### Step 2: Run Analysis Scripts

```bash
cd docs/strategy-2026/scripts

# Extract metrics from all sources
python3 extract_metrics.py

# Calculate conversion rates
python3 calculate_conversions.py

# Validate data quality
python3 validate_data.py
```

### Step 3: Review Results

1. **Check Validation Report:**

   - Review warnings and errors
   - Investigate any data quality issues
   - Verify conversion rates are reasonable

2. **Review Conversion Analysis:**

   - Check monthly trends
   - Identify anomalies
   - Compare to previous periods

3. **Review Extracted Metrics:**
   - Verify data completeness
   - Check for missing months
   - Validate totals

### Step 4: Update Manual Data (If Needed)

If HubSpot CSV parsing fails or data is incomplete:

1. **Update Manual Data File:**

   - Edit `scripts/manual_hubspot_data.py`
   - Add new month's data
   - Run script to generate JSON

2. **Re-run Analysis:**
   ```bash
   python3 extract_metrics.py
   python3 calculate_conversions.py
   ```

### Step 5: Update Documents

#### 5.1 Update ACTUAL_METRICS_2025.md

1. **Add New Month Section:**

   - Copy previous month's format
   - Update with new month's data
   - Calculate conversion rates

2. **Update Overall Summary:**

   - Recalculate totals
   - Update overall conversion rates
   - Update growth trends

3. **Update Key Insights:**
   - Add new insights from the month
   - Update trend analysis
   - Note any anomalies

#### 5.2 Update Strategy Documents

**Priority Order:**

1. `CURRENT_STATE_ANALYSIS.md` - Update traffic and conversion metrics
2. `MAIN_PLAN.md` - Update current state metrics and success metrics
3. `MILESTONES.md` - Update performance milestones if needed
4. `QUARTERLY_BREAKDOWN.md` - Update success metrics if quarterly
5. `EXECUTIVE_SUMMARY.md` - Update growth targets if significant changes

**Update Pattern:**

- Find metric tables or sections
- Replace with latest data
- Update growth percentages
- Add notes about trends or changes

#### 5.3 Update CHANGELOG.md

Add entry with:

- Date of update
- What was updated
- Key changes or findings
- Impact on strategy

**Format:**

```markdown
### YYYY-MM-DD - Monthly Metrics Update

**Updated:**

- ACTUAL_METRICS_2025.md with [Month] data
- CURRENT_STATE_ANALYSIS.md with latest metrics
- MAIN_PLAN.md success metrics

**Key Findings:**

- [Finding 1]
- [Finding 2]

**Impact:**

- [Impact on strategy or targets]
```

### Step 6: Quality Checks

1. **Consistency Check:**

   - Verify all documents use same metrics
   - Check for discrepancies
   - Ensure date ranges are consistent

2. **Accuracy Check:**

   - Double-check calculations
   - Verify data source alignment
   - Review for typos or errors

3. **Completeness Check:**
   - Ensure all required documents updated
   - Verify all months included
   - Check for missing data

### Step 7: Archive Data

1. **Save Raw Data:**

   - Archive CSV files with timestamps
   - Save JSON outputs with dates
   - Keep for historical reference

2. **Document Changes:**
   - Note any methodology changes
   - Document data quality issues
   - Record any manual corrections

---

## Quality Standards

### Data Quality

- **Completeness:** All months should have data
- **Accuracy:** Cross-reference multiple sources
- **Consistency:** Use same calculation methods
- **Timeliness:** Update within first week of month

### Documentation Quality

- **Accuracy:** All numbers must be correct
- **Consistency:** Same metrics across all documents
- **Clarity:** Clear explanations and context
- **Completeness:** All relevant documents updated

---

## Troubleshooting

### Issue: HubSpot CSV Parsing Fails

**Solution:**

1. Check CSV structure hasn't changed
2. Update parser if structure changed
3. Use manual data entry as fallback
4. Document issue in CHANGELOG

### Issue: Conversion Rates Seem Unreasonable

**Solution:**

1. Verify data source accuracy
2. Check for data quality issues
3. Compare to industry benchmarks
4. Investigate anomalies
5. Document findings

### Issue: Missing Monthly Data

**Solution:**

1. Check if data source has data
2. Verify export dates
3. Use estimates if needed (document)
4. Flag for follow-up

---

## Automation Opportunities

### Future Improvements

1. **Automated Extraction:**

   - Set up API connections
   - Schedule monthly extractions
   - Reduce manual work

2. **Automated Updates:**

   - Script to update documents
   - Automated calculations
   - Validation checks

3. **Automated Alerts:**
   - Data quality issues
   - Anomaly detection
   - Target vs. actual alerts

---

## Reference Documents

- **Methodology:** `03-ANALYSIS/METRICS_METHODOLOGY.md`
- **Actual Metrics:** `03-ANALYSIS/ACTUAL_METRICS_2025.md`
- **Scripts:** `scripts/` directory
- **Data Files:** `06-DATA-ANALYSIS/` directory

---

**Note:** This process is based on the initial metrics update completed on 2025-12-02. Refine as needed based on experience and feedback.