Advanced Analytics

Gain deep insights into your digital downloads business with comprehensive analytics and reporting.

Analytics Dashboard

Access analytics:

Alva → Analytics → Dashboard

Overview:
• Revenue metrics
• Download statistics
• Customer insights
• Product performance
• Fraud analytics

Revenue Analytics

Sales Metrics

Key metrics:

Total revenue:

Period: Last 30 days
Total: $12,450
vs Previous period: +15% ↑

Breakdown:
Digital products: $11,200 (90%)
Physical + Digital: $1,250 (10%)

Average order value:

AOV: $49.50
Previous: $45.20 (+9.5%)

By product:
Course Bundle: $79.99
Ebook Pack: $29.99
Single Chapter: $9.99

Revenue Trends

Time-series analysis:

Daily revenue:

Chart: Last 30 days
Peak: $650 (Jan 10 - promotion)
Low: $180 (Jan 3 - post-holiday)
Average: $415/day

Seasonality:
Weekends: 20% lower
Mondays: 15% higher
Month-end: 30% spike

Year-over-year comparison:

2024 vs 2023:
Revenue: +45%
Orders: +38%
AOV: +5%

Growth drivers:
• New products (3)
• Better fraud prevention (-2% fraud)
• Improved checkout experience

Download Analytics

Download Statistics

Download metrics:

Total downloads:

Period: Last 30 days
Downloads: 3,456
Unique customers: 1,234
Avg downloads per customer: 2.8

By file type:
PDF: 2,100 (61%)
ZIP: 890 (26%)
Video: 366 (11%)
Other: 100 (2%)

Download Patterns

Usage analysis:

Time of day:

Peak hours:
• 9-11 AM (28%)
• 2-4 PM (24%)
• 8-10 PM (18%)

Lowest:
• 1-5 AM (2%)

Timezone: Shop timezone
Insight: Business hours dominate

Day of week:

Monday: 18%
Tuesday: 16%
Wednesday: 15%
Thursday: 14%
Friday: 13%
Saturday: 12%
Sunday: 12%

Pattern: Weekday-heavy (work/learning)

File Performance

Top files:

Most downloaded:

1. Chapter-1.pdf - 456 downloads
2. Starter-Guide.pdf - 398 downloads
3. Bonus-Pack.zip - 345 downloads
4. Video-Tutorial.mp4 - 289 downloads
5. Workbook.pdf - 256 downloads

Insight: Chapter 1 most popular (product preview?)

Least downloaded:

Files with low downloads:
• Advanced-Topics.pdf - 12 downloads
• Appendix-C.pdf - 8 downloads

Action: Review if needed, consider removal

Customer Analytics

Customer Insights

Customer metrics:

New vs returning:

New customers: 789 (64%)
Returning customers: 445 (36%)

Returning customer value:
AOV: $68 (vs $42 new)
Lifetime value: $145

Insight: Focus on retention = higher revenue

Customer Segmentation

Segment analysis:

By purchase value:

High-value (>$100): 156 customers
• Revenue: $18,900 (45% of total)
• AOV: $121
• Products: Premium bundles

Medium-value ($30-$100): 567 customers
• Revenue: $17,850 (43%)
• AOV: $31.50
• Products: Course packs

Low-value (<$30): 511 customers
• Revenue: $5,100 (12%)
• AOV: $10
• Products: Single items

By engagement:

Power users (5+ downloads): 89 customers
• High engagement
• Low support tickets
• High satisfaction

Regular users (2-4 downloads): 456 customers
• Normal engagement
• Occasional support

One-time users (1 download): 689 customers
• At-risk for churn
• Target for re-engagement

Geographic Analytics

Customer locations:

By country:

United States: 45%
United Kingdom: 18%
Canada: 12%
Australia: 8%
Germany: 5%
Other: 12%

Revenue by country:
US: $18,900 (highest AOV)
UK: $7,200
CA: $4,800

By timezone:

Eastern (US): 35%
Central (US): 20%
Pacific (US): 18%
GMT (UK): 15%
Other: 12%

Optimization: Send emails based on customer timezone

Product Analytics

Product Performance

Product metrics:

Best sellers:

1. Complete Course Bundle - $7,900 (158 sales)
2. Ebook Pack - $4,200 (140 sales)
3. Video Series - $3,150 (63 sales)

Conversion rate:
Complete Course: 8.5%
Ebook Pack: 6.2%
Video Series: 4.1%

Product trends:

Growing:
• Video Series (+45% MoM)
• Advanced Pack (+30% MoM)

Declining:
• Starter Bundle (-15% MoM)
• Legacy Course (-25% MoM)

Action: Sunset legacy products, promote video

File-to-Product Mapping

Mapping effectiveness:

Well-mapped products:

Complete Course Bundle:
• 12 files mapped
• Clear structure
• High satisfaction
• Low support tickets

Insight: Comprehensive mapping = better experience

Under-mapped products:

Starter Pack:
• Only 2 files
• Customer confusion
• Higher support tickets

Action: Add more value or clarify offering

Conversion Analytics

Funnel Analysis

Conversion funnel:

Download journey:

1. Order placed: 1,000
2. Email opened: 850 (85%)
3. Download link clicked: 765 (90% of opens)
4. File downloaded: 720 (94% of clicks)

Drop-off points:
• Email: 15% not opened
• Click: 10% opened but didn't click
• Download: 6% clicked but didn't download

Optimization opportunities:
• Improve email subject lines
• Make download button more prominent
• Troubleshoot download issues

Email Performance

Email metrics:

Download notification emails:

Sent: 1,234
Delivered: 1,220 (98.9%)
Opened: 915 (75%)
Clicked: 823 (90% of opens)

Industry benchmark:
• Transactional emails: 65-80% open rate
• Click rate: 20-30%

Performance: Excellent ✓

Email timing:

Best send times:
• 9-10 AM: 82% open rate
• 2-3 PM: 78% open rate
• 8-9 PM: 65% open rate

Worst:
• 1-5 AM: 35% open rate

Insight: Send during business hours

Fraud Analytics

Fraud Detection Metrics

Fraud statistics:

Fraud rate:

Total orders: 1,234
Flagged: 45 (3.6%)
Approved after review: 38 (84%)
Rejected: 7 (16%)

False positive rate: 3.1% (acceptable)
Fraud prevented: $890 (estimated)

Fraud patterns:

Common indicators:
• High-risk countries: 45%
• Mismatched billing: 30%
• Multiple failed payments: 15%
• VPN/proxy usage: 10%

Top fraud countries:
1. Country A: 12 attempts
2. Country B: 8 attempts
3. Country C: 5 attempts

Action: Tighten rules for high-risk regions

Review Time Analytics

Fraud review efficiency:

Average review time: 45 minutes
Fastest: 10 minutes
Slowest: 4 hours

By time of day:
Business hours: 25 min (fastest)
After hours: 2.5 hours

Improvement: Consider 24/7 review or automation

Performance Analytics

Download Speed

Performance metrics:

Download performance:

Average download speed: 25 MB/s
Median: 20 MB/s

By region:
North America: 35 MB/s (fastest CDN edge)
Europe: 28 MB/s
Asia: 22 MB/s
Other: 18 MB/s

95th percentile: 5 MB/s
Action: Investigate slow outliers

Page Load Times

Website performance:

Download page load:
Average: 1.2s
Median: 0.9s
95th percentile: 2.5s

Target: < 2s
Status: ✓ Meeting target

Bottlenecks:
• Large images: 0.3s
• External scripts: 0.2s

Optimization: Compress images, async scripts

Behavioral Analytics

User Behavior

Download behavior:

Download attempts:

Successful (first try): 85%
Retry required: 12%
Abandoned: 3%

Retry reasons:
• Network timeout: 45%
• Browser issue: 30%
• User error: 25%

Improvement: Add resume support, clearer errors

Time to download:

After purchase:
Within 1 hour: 65%
1-24 hours: 25%
1-7 days: 8%
7+ days: 2%

Insight: Most download immediately
Action: Ensure immediate email delivery

Custom Reports

Report Builder

Create custom reports:

Report configuration:

Analytics → Reports → Create Custom Report

Dimensions:
☑ Date
☑ Product
☑ Customer segment
☑ Country
☑ File type

Metrics:
☑ Revenue
☑ Downloads
☑ Customers
☑ Conversion rate

Filters:
• Date range: Last 90 days
• Product: Course Bundle
• Country: US, UK, CA

[Generate Report]

Scheduled Reports

Automate reporting:

Schedule setup:

Analytics → Reports → Schedule

Report: Weekly Performance Summary
Frequency: Every Monday, 9 AM
Recipients:
• owner@yourshop.com
• manager@yourshop.com

Format: PDF + CSV attachment
Include:
• Revenue vs target
• Top products
• Customer acquisition
• Key metrics vs last week

[Create Schedule]

Export and Integration

Data Export

Export analytics data:

Export options:

Analytics → Export

Format:
○ CSV (spreadsheet)
● Excel (formatted)
○ JSON (API integration)
○ PDF (report)

Data:
☑ All orders
☑ All downloads
☑ Customer data
☑ Product performance

Date range: Last 90 days

[Export Data]

Google Analytics Integration

Enhanced tracking:

Setup Google Analytics:

Settings → Integrations → Google Analytics
Tracking ID: UA-XXXXXXXXX-X or G-XXXXXXXXXX

Enhanced ecommerce:
☑ Enable enhanced ecommerce
☑ Track product views
☑ Track add to cart
☑ Track purchases
☑ Track downloads

Custom dimensions:
• cd1: File type
• cd2: Customer segment
• cd3: Product category

Custom events:
• file_download
• download_limit_reached
• link_expired

API Access

Programmatic analytics:

Analytics API:

GET /api/analytics/revenue
Authorization: Bearer {api_key}

Query parameters:
?start_date=2024-01-01
&end_date=2024-01-31
&group_by=day
&product_id=prod_123

Response:
{
  "total_revenue": 12450.00,
  "data": [
    {"date": "2024-01-01", "revenue": 380.00},
    {"date": "2024-01-02", "revenue": 425.00},
    ...
  ]
}

Benchmarking

Industry Benchmarks

Compare performance:

Digital downloads benchmarks:

Your shop vs Industry average:

Conversion rate:
You: 5.2% | Industry: 3.5% ✓ 49% better

Download completion:
You: 94% | Industry: 85% ✓ 11% better

Email open rate:
You: 75% | Industry: 70% ✓ 7% better

Support tickets per order:
You: 0.08 | Industry: 0.15 ✓ 47% fewer

Overall: Above average performance

Insights and Recommendations

AI-Powered Insights

Automated insights:

Smart recommendations:

💡 Revenue opportunity identified:
Customers who bought "Chapter 1" have 78% likelihood
to buy "Complete Course" within 30 days.

Recommendation:
• Create upsell email campaign
• Offer bundle discount
• Estimated revenue: +$2,400/month

[Create Campaign]

Trend detection:

📊 Trend alert:
Video downloads increased 45% this month.
Customers prefer video over PDF (2:1 ratio).

Recommendation:
• Create more video content
• Bundle videos with PDFs
• Increase video product pricing (+15%)

Estimated impact: +$1,800/month

Best Practices

1. Check Analytics Weekly

Regular review:

Weekly routine:
☐ Review revenue vs target
☐ Check top products
☐ Monitor fraud rate
☐ Review customer feedback
☐ Identify trends

Action: Adjust strategy based on data

2. Track Key Metrics

Focus on what matters:

Critical metrics:
✓ Revenue
✓ Conversion rate
✓ Customer satisfaction
✓ Download success rate
✓ Support ticket rate

Nice to have:
○ Page views
○ Time on site
○ Bounce rate

3. Use Data for Decisions

Data-driven approach:

Before launching new product:
1. Analyze similar product performance
2. Review customer demand signals
3. Test pricing with small segment
4. Monitor initial response
5. Scale or pivot based on data

Result: Higher success rate

4. Segment Your Customers

Targeted actions:

High-value customers:
• Exclusive offers
• Priority support
• Beta access

At-risk customers:
• Re-engagement campaigns
• Discount offers
• Feedback requests

Result: Better retention, higher LTV

5. Set Up Alerts

Proactive monitoring:

Alert when:
• Revenue drops >20% vs last week
• Fraud rate >5%
• Download failure rate >10%
• Support tickets spike
• SSL certificate expiring

Benefit: Catch issues early

Next Steps

File Watermarking - Protect content
API Webhooks and Automation - Automate workflows
Custom Domain Setup - Brand experience
Understanding Dashboard Metrics - Metrics guide