wix Wix Analytics & Business Insights
Overview
This skill provides comprehensive patterns for calculating business metrics, conversion rates, customer lifetime value, and cross-channel analytics across eCommerce, Events, and Bookings. While Wix doesn't have a direct Analytics REST API, we can calculate powerful insights from available data.
Key Business Metrics
1. Total Business Revenue
Calculate total revenue across all channels:
#!/bin/bash
echo "=== TOTAL BUSINESS REVENUE ==="
echo ""
# 1. eCommerce Revenue
ecom_orders=$(curl -s -X POST "https://www.wixapis.com/stores/v2/orders/query" \
-H "Authorization: ${API_KEY}" \
-H "wix-site-id: ${SITE_ID}" \
-H "Content-Type: application/json" \
-d '{
"query": {
"filter": {"status": "PAID"},
"paging": {"limit": 100}
}
}')
ecom_revenue=$(echo "$ecom_orders" | jq '[.orders[].totals.total | tonumber] | add // 0')
ecom_count=$(echo "$ecom_orders" | jq '.orders | length')
# 2. Events Revenue
events_orders=$(curl -s -X POST "https://www.wixapis.com/events-orders/v1/orders/query" \
-H "Authorization: ${API_KEY}" \
-H "wix-site-id: ${SITE_ID}" \
-H "Content-Type: application/json" \
-d '{
"query": {
"filter": {"status": "PAID"},
"paging": {"limit": 100}
}
}')
events_revenue=$(echo "$events_orders" | jq '[.orders[].netPrice.amount | tonumber] | add // 0')
events_tickets=$(echo "$events_orders" | jq '[.orders[].ticketQuantity] | add // 0')
# 3. Bookings Revenue
bookings=$(curl -s -X POST "https://www.wixapis.com/bookings-reader/v2/bookings/query" \
-H "Authorization: ${API_KEY}" \
-H "wix-site-id: ${SITE_ID}" \
-H "Content-Type: application/json" \
-d '{
"query": {
"filter": {"status": "CONFIRMED"},
"paging": {"limit": 100}
}
}')
bookings_revenue=$(echo "$bookings" | jq '[.bookings[] | select(.payment.status == "PAID") | .payment.price.amount | tonumber] | add // 0')
bookings_count=$(echo "$bookings" | jq '[.bookings[] | select(.payment.status == "PAID")] | length')
# Calculate totals
total_revenue=$(echo "$ecom_revenue + $events_revenue + $bookings_revenue" | bc)
cat <<EOF
ECOMMERCE:
- Orders: $ecom_count
- Revenue: \$$ecom_revenue
EVENTS:
- Tickets Sold: $events_tickets
- Revenue: \$$events_revenue
BOOKINGS:
- Appointments: $bookings_count
- Revenue: \$$bookings_revenue
TOTAL REVENUE: \$$total_revenue
EOF
2. Customer Lifetime Value (CLV)
Calculate average customer value:
#!/bin/bash
# Get all eCommerce orders
orders=$(curl -s -X POST "https://www.wixapis.com/stores/v2/orders/query" \
-H "Authorization: ${API_KEY}" \
-H "wix-site-id: ${SITE_ID}" \
-H "Content-Type: application/json" \
-d '{
"query": {
"filter": {"status": "PAID"},
"paging": {"limit": 100}
}
}')
# Calculate per-customer metrics
echo "$orders" | jq -r '.orders[] | "\(.buyerInfo.email)|\(.totals.total)"' | \
awk -F'|' '{
customer[$1] += $2
orders[$1]++
}
END {
total_customers = 0
total_value = 0
total_orders = 0
for (email in customer) {
total_customers++
total_value += customer[email]
total_orders += orders[email]
}
avg_clv = total_value / total_customers
avg_orders = total_orders / total_customers
avg_order_value = total_value / total_orders
print "=== CUSTOMER LIFETIME VALUE ==="
print ""
print "Total Customers: " total_customers
print "Average CLV: $" sprintf("%.2f", avg_clv)
print "Average Orders per Customer: " sprintf("%.1f", avg_orders)
print "Average Order Value: $" sprintf("%.2f", avg_order_value)
}'
3. Conversion Funnel Analysis
Track customer journey from product views to purchase:
#!/bin/bash
echo "=== CONVERSION FUNNEL ANALYSIS ==="
echo ""
# 1. Total Products (Catalog Size)
products=$(curl -s -X POST "https://www.wixapis.com/stores/v1/products/query" \
-H "Authorization: ${API_KEY}" \
-H "wix-site-id: ${SITE_ID}" \
-H "Content-Type: application/json" \
-d '{"query": {"filter": "{\"visible\": true}", "paging": {"limit": 100}}}')
total_products=$(echo "$products" | jq '.products | length')
# 2. Products with Recent Orders (Conversion)
orders=$(curl -s -X POST "https://www.wixapis.com/stores/v2/orders/query" \
-H "Authorization: ${API_KEY}" \
-H "wix-site-id: ${SITE_ID}" \
-H "Content-Type: application/json" \
-d '{
"query": {
"filter": {"status": "PAID"},
"paging": {"limit": 100}
}
}')
products_sold=$(echo "$orders" | jq '[.orders[].lineItems[].productId] | unique | length')
total_orders=$(echo "$orders" | jq '.orders | length')
# Calculate conversion metrics
product_conversion=$(echo "scale=2; ($products_sold / $total_products) * 100" | bc)
cat <<EOF
CATALOG:
- Total Active Products: $total_products
- Products with Sales: $products_sold
- Product Conversion Rate: ${product_conversion}%
ORDERS:
- Total Orders: $total_orders
- Products per Order: $(echo "scale=1; $products_sold / $total_orders" | bc)
INSIGHTS:
- $(echo "$total_products - $products_sold" | bc) products have no sales
- Focus on promoting low-conversion products
EOF
4. Revenue Trends & Growth
Calculate month-over-month growth:
#!/bin/bash
# Current month
current_start=$(date -u -v1d +"%Y-%m-%dT00:00:00.000Z")
current_end=$(date -u +"%Y-%m-%dT23:59:59.999Z")
# Previous month
prev_start=$(date -u -v-1m -v1d +"%Y-%m-%dT00:00:00.000Z")
prev_end=$(date -u -v-1m -v+1m -v-1d +"%Y-%m-%dT23:59:59.999Z")
# Current month revenue
current_orders=$(curl -s -X POST "https://www.wixapis.com/stores/v2/orders/query" \
-H "Authorization: ${API_KEY}" \
-H "wix-site-id: ${SITE_ID}" \
-H "Content-Type: application/json" \
-d '{
"query": {
"filter": {
"status": "PAID",
"dateCreated": {"$gte": "'"${current_start}"'", "$lte": "'"${current_end}"'"}
},
"paging": {"limit": 100}
}
}')
current_revenue=$(echo "$current_orders" | jq '[.orders[].totals.total | tonumber] | add // 0')
current_count=$(echo "$current_orders" | jq '.orders | length')
# Previous month revenue
prev_orders=$(curl -s -X POST "https://www.wixapis.com/stores/v2/orders/query" \
-H "Authorization: ${API_KEY}" \
-H "wix-site-id: ${SITE_ID}" \
-H "Content-Type: application/json" \
-d '{
"query": {
"filter": {
"status": "PAID",
"dateCreated": {"$gte": "'"${prev_start}"'", "$lte": "'"${prev_end}"'"}
},
"paging": {"limit": 100}
}
}')
prev_revenue=$(echo "$prev_orders" | jq '[.orders[].totals.total | tonumber] | add // 0')
prev_count=$(echo "$prev_orders" | jq '.orders | length')
# Calculate growth
revenue_growth=$(echo "scale=2; (($current_revenue - $prev_revenue) / $prev_revenue) * 100" | bc)
order_growth=$(echo "scale=2; (($current_count - $prev_count) / $prev_count) * 100" | bc)
cat <<EOF
=== REVENUE TRENDS ==='
CURRENT MONTH:
- Orders: $current_count
- Revenue: \$$current_revenue
PREVIOUS MONTH:
- Orders: $prev_count
- Revenue: \$$prev_revenue
GROWTH:
- Revenue Growth: ${revenue_growth}%
- Order Growth: ${order_growth}%
$([ $(echo "$revenue_growth > 0" | bc) -eq 1 ] && echo "✓ Revenue is growing!" || echo "⚠ Revenue declined")
EOF
5. Customer Acquisition Cost (CAC)
Estimate CAC by tracking new vs returning customers:
#!/bin/bash
# Get all orders
all_orders=$(curl -s -X POST "https://www.wixapis.com/stores/v2/orders/query" \
-H "Authorization: ${API_KEY}" \
-H "wix-site-id: ${SITE_ID}" \
-H "Content-Type: application/json" \
-d '{
"query": {
"filter": {"status": "PAID"},
"paging": {"limit": 100}
}
}')
# Analyze customer behavior
echo "$all_orders" | jq -r '.orders[] | "\(.buyerInfo.email)|\(.dateCreated)|\(.totals.total)"' | \
sort -t'|' -k1,1 -k2,2 | \
awk -F'|' '
{
email = $1
date = $2
value = $3
if (!(email in first_order)) {
first_order[email] = date
first_value[email] = value
new_customers++
new_revenue += value
} else {
returning_customers++
returning_revenue += value
}
}
END {
total_customers = new_customers + returning_customers
total_orders = NR
print "=== CUSTOMER ACQUISITION ==="
print ""
print "NEW CUSTOMERS:"
print "- Count: " new_customers
print "- Revenue: $" sprintf("%.2f", new_revenue)
print "- Avg First Order: $" sprintf("%.2f", new_revenue / new_customers)
print ""
print "RETURNING CUSTOMERS:"
print "- Repeat Orders: " returning_customers
print "- Revenue: $" sprintf("%.2f", returning_revenue)
print ""
print "RETENTION:"
print "- Repeat Purchase Rate: " sprintf("%.1f", (returning_customers / total_orders) * 100) "%"
print "- New vs Returning: " sprintf("%.0f", (new_customers / total_orders) * 100) "% / " sprintf("%.0f", (returning_customers / total_orders) * 100) "%"
}'
6. Churn & Retention Analysis
Identify customer churn patterns:
#!/bin/bash
# Get orders from last 90 days
ninety_days_ago=$(date -u -v-90d +"%Y-%m-%dT00:00:00.000Z")
recent_orders=$(curl -s -X POST "https://www.wixapis.com/stores/v2/orders/query" \
-H "Authorization: ${API_KEY}" \
-H "wix-site-id: ${SITE_ID}" \
-H "Content-Type: application/json" \
-d '{
"query": {
"filter": {
"status": "PAID",
"dateCreated": {"$gte": "'"${ninety_days_ago}"'"}
},
"paging": {"limit": 100}
}
}')
# Analyze customer last purchase date
echo "$recent_orders" | jq -r '.orders[] | "\(.buyerInfo.email)|\(.dateCreated)"' | \
awk -F'|' '
{
email = $1
date = $2
last_purchase[email] = (last_purchase[email] > date) ? last_purchase[email] : date
}
END {
now = systime()
active_30 = 0
active_60 = 0
at_risk = 0
for (email in last_purchase) {
# Convert ISO date to epoch (approximation)
days_since = 30 # Simplified - in real implementation, calculate actual days
if (days_since <= 30) active_30++
else if (days_since <= 60) active_60++
else at_risk++
}
total = active_30 + active_60 + at_risk
print "=== CUSTOMER RETENTION COHORTS ==="
print ""
print "Active (last 30 days): " active_30 " (" int(active_30/total*100) "%)"
print "At Risk (31-60 days): " active_60 " (" int(active_60/total*100) "%)"
print "Churned (60+ days): " at_risk " (" int(at_risk/total*100) "%)"
print ""
print "⚠ " at_risk " customers may be churning - consider re-engagement campaign"
}'
7. Product Performance Matrix
Categorize products by sales volume and revenue:
#!/bin/bash
# Get all products
products=$(curl -s -X POST "https://www.wixapis.com/stores/v1/products/query" \
-H "Authorization: ${API_KEY}" \
-H "wix-site-id: ${SITE_ID}" \
-H "Content-Type: application/json" \
-d '{"query": {"paging": {"limit": 100}}}')
# Get all orders
orders=$(curl -s -X POST "https://www.wixapis.com/stores/v2/orders/query" \
-H "Authorization: ${API_KEY}" \
-H "wix-site-id: ${SITE_ID}" \
-H "Content-Type: application/json" \
-d '{"query": {"filter": {"status": "PAID"}, "paging": {"limit": 100}}}')
# Calculate per-product metrics
echo "$orders" | jq -r '.orders[].lineItems[] | "\(.productId)|\(.quantity)|\(.price.amount)"' | \
awk -F'|' '
{
product = $1
qty = $2
price = $3
sales[product] += qty
revenue[product] += (qty * price)
}
END {
print "=== PRODUCT PERFORMANCE MATRIX ==="
print ""
print "Stars (High Sales, High Revenue):"
for (p in sales) {
if (sales[p] > 10 && revenue[p] > 500) {
printf " Product %s: %d units, $%.2f\n", p, sales[p], revenue[p]
}
}
print "\nWorkhorses (High Sales, Lower Revenue):"
for (p in sales) {
if (sales[p] > 10 && revenue[p] <= 500) {
printf " Product %s: %d units, $%.2f\n", p, sales[p], revenue[p]
}
}
print "\nNiche (Low Sales, High Revenue):"
for (p in sales) {
if (sales[p] <= 10 && revenue[p] > 500) {
printf " Product %s: %d units, $%.2f\n", p, sales[p], revenue[p]
}
}
print "\nUnderperformers (Low Sales, Low Revenue):"
for (p in sales) {
if (sales[p] <= 10 && revenue[p] <= 500) {
printf " Product %s: %d units, $%.2f\n", p, sales[p], revenue[p]
}
}
}'
8. Cross-Channel Customer Journey
Track customers across eCommerce, Events, and Bookings:
#!/bin/bash
echo "=== CROSS-CHANNEL CUSTOMER JOURNEY ==="
echo ""
# Get all customer emails from orders
ecom_customers=$(curl -s -X POST "https://www.wixapis.com/stores/v2/orders/query" \
-H "Authorization: ${API_KEY}" \
-H "wix-site-id: ${SITE_ID}" \
-H "Content-Type: application/json" \
-d '{"query": {"filter": {"status": "PAID"}, "paging": {"limit": 100}}}' | \
jq -r '.orders[].buyerInfo.email' | sort -u)
# Get event customers
event_customers=$(curl -s -X POST "https://www.wixapis.com/events-orders/v1/orders/query" \
-H "Authorization: ${API_KEY}" \
-H "wix-site-id: ${SITE_ID}" \
-H "Content-Type: application/json" \
-d '{"query": {"filter": {"status": "PAID"}, "paging": {"limit": 100}}}' | \
jq -r '.orders[].contact.email' | sort -u)
# Get booking customers
booking_customers=$(curl -s -X POST "https://www.wixapis.com/bookings-reader/v2/bookings/query" \
-H "Authorization: ${API_KEY}" \
-H "wix-site-id: ${SITE_ID}" \
-H "Content-Type: application/json" \
-d '{"query": {"filter": {"status": "CONFIRMED"}, "paging": {"limit": 100}}}' | \
jq -r '.bookings[].contactDetails.email' | sort -u)
# Analyze overlap
total_ecom=$(echo "$ecom_customers" | wc -l | tr -d ' ')
total_events=$(echo "$event_customers" | wc -l | tr -d ' ')
total_bookings=$(echo "$booking_customers" | wc -l | tr -d ' ')
# Cross-channel customers
cross_channel=$(comm -12 <(echo "$ecom_customers") <(echo "$event_customers") | wc -l | tr -d ' ')
cat <<EOF
CUSTOMER DISTRIBUTION:
- eCommerce Only: $total_ecom customers
- Events Only: $total_events customers
- Bookings Only: $total_bookings customers
- Cross-Channel: $cross_channel customers
INSIGHTS:
- Cross-channel customers are more valuable
- Consider bundling products/events/services
- Target single-channel customers with other offerings
EOF
9. Revenue per Channel per Day
Track daily performance across channels:
#!/bin/bash
TODAY=$(date -u +"%Y-%m-%d")
# eCommerce today
ecom_today=$(curl -s -X POST "https://www.wixapis.com/stores/v2/orders/query" \
-H "Authorization: ${API_KEY}" \
-H "wix-site-id: ${SITE_ID}" \
-H "Content-Type: application/json" \
-d '{
"query": {
"filter": {
"status": "PAID",
"dateCreated": {"$gte": "'"${TODAY}T00:00:00.000Z"'"}
},
"paging": {"limit": 100}
}
}')
ecom_rev=$(echo "$ecom_today" | jq '[.orders[].totals.total | tonumber] | add // 0')
ecom_orders=$(echo "$ecom_today" | jq '.orders | length')
echo "=== TODAY'S REVENUE ==="
echo ""
echo "eCommerce: \$$ecom_rev ($ecom_orders orders)"
echo "Events: (query separately)"
echo "Bookings: (query separately)"
10. Conversion Rate Optimization (CRO) Metrics
Key metrics for improving conversion:
#!/bin/bash
# Products viewed (products with inventory tracking)
products=$(curl -s -X POST "https://www.wixapis.com/stores/v1/products/query" \
-H "Authorization: ${API_KEY}" \
-H "wix-site-id: ${SITE_ID}" \
-H "Content-Type: application/json" \
-d '{"query": {"filter": "{\"visible\": true}", "paging": {"limit": 100}}}')
visible_products=$(echo "$products" | jq '.products | length')
# Products purchased
orders=$(curl -s -X POST "https://www.wixapis.com/stores/v2/orders/query" \
-H "Authorization: ${API_KEY}" \
-H "wix-site-id: ${SITE_ID}" \
-H "Content-Type: application/json" \
-d '{"query": {"filter": {"status": "PAID"}, "paging": {"limit": 100}}}')
unique_products_sold=$(echo "$orders" | jq '[.orders[].lineItems[].productId] | unique | length')
total_orders=$(echo "$orders" | jq '.orders | length')
total_items=$(echo "$orders" | jq '[.orders[].lineItems[].quantity] | add // 0')
# Calculate metrics
catalog_conversion=$(echo "scale=2; ($unique_products_sold / $visible_products) * 100" | bc)
items_per_order=$(echo "scale=1; $total_items / $total_orders" | bc)
cat <<EOF
=== CONVERSION RATE OPTIMIZATION ==='
CATALOG PERFORMANCE:
- Visible Products: $visible_products
- Products with Sales: $unique_products_sold
- Catalog Conversion: ${catalog_conversion}%
ORDER METRICS:
- Total Orders: $total_orders
- Items per Order: $items_per_order
- Cart Size Opportunity: $([ $(echo "$items_per_order < 2" | bc) -eq 1 ] && echo "Increase cross-sells" || echo "Good")
RECOMMENDATIONS:
- $([ $(echo "$catalog_conversion < 50" | bc) -eq 1 ] && echo "50% of catalog not selling - review and optimize" || echo "Catalog performing well")
- $([ $(echo "$items_per_order < 2" | bc) -eq 1 ] && echo "Add product bundles and upsells" || echo "Strong multi-item purchases")
EOF
Important Notes
Data Freshness
- All metrics calculated in real-time from API data
- No historical analytics stored by Wix APIs
- For time-series analysis, query multiple date ranges
Calculation Accuracy
- Always use pagination to get complete datasets
- Filter by
status == "PAID"for revenue calculations - Handle edge cases (zero division, null values)
Performance
- Combine multiple API calls for comprehensive reports
- Cache results for dashboards (refresh every 5-15 minutes)
- Use date filters to limit data volume
Marketing Attribution
- Wix supports UTM parameters in URLs
- Track campaign performance via order metadata
- Integrate with Meta Pixel/Google Analytics for traffic data
Integration Opportunities
Google Analytics
- Connect via Wix dashboard for traffic data
- Track page views, sessions, bounce rate
- Combine with revenue data for ROI
Meta Pixel
- Track conversions and retargeting
- Measure ad campaign effectiveness
- Calculate ROAS (Return on Ad Spend)
Email Marketing
- Track campaign performance via UTM codes
- Measure email-to-purchase conversion
- Calculate email marketing ROI
Business Intelligence Formulas
# Customer Lifetime Value
CLV = (Average Order Value) × (Purchase Frequency) × (Customer Lifespan)
# Customer Acquisition Cost
CAC = (Total Marketing Spend) / (New Customers Acquired)
# Return on Ad Spend
ROAS = (Revenue from Ads) / (Ad Spend)
# Gross Margin
Margin = ((Revenue - Cost of Goods) / Revenue) × 100
# Churn Rate
Churn = (Customers Lost) / (Total Customers at Start) × 100
# Net Promoter Score (requires survey data)
NPS = (% Promoters) - (% Detractors)
API References
- Wix Analytics Help: https://support.wix.com/en/wix-analytics
- Marketing Integrations: https://support.wix.com/en/marketing-integrations-and-tracking
- Conversion Tracking: https://support.wix.com/en/article/about-conversion-tracking
- UTM Parameters: https://support.wix.com/en/article/tracking-campaigns-and-traffic-sources-in-wix-analytics