WooCommerce Data Export to Cogny

TL;DR

Export WooCommerce data to BigQuery for AI-powered analytics on customer lifetime value, product performance, and channel attribution—no manual exports required.

What you'll accomplish:

Connect WooCommerce to BigQuery using ETL connector plugin
Automatically sync orders, customers, and products daily
Enable AI analysis identifying which traffic sources bring repeat customers
Discover product combinations predicting high lifetime value
Analyze cart abandonment patterns by traffic source

Time required: 25 minutes | Difficulty: Intermediate | Prerequisites: WordPress site with WooCommerce, admin access, Google Cloud account, Cogny account

Quick Start: Install WooCommerce BigQuery connector plugin (or use Fivetran/Stitch) → Configure authentication → Set daily sync schedule → Connect BigQuery to Cogny.

Related Resources

Essential guides for WooCommerce data analysis:

BigQuery Connection Guide - Connect WooCommerce data in BigQuery to Cogny
CAC Analysis with AI - Calculate true customer acquisition cost using WooCommerce LTV data
Shopify + Cogny Integration - Similar e-commerce integration pattern for Shopify stores

Question

How do I connect WooCommerce to Cogny for AI-powered e-commerce analytics?

Answer

Export WooCommerce data to BigQuery using a connector plugin or ETL tool. Connect BigQuery to Cogny. AI analyzes your orders, customers, and products to find growth opportunities.

No manual exports. No spreadsheets. Just automatic insights.

Quick Tip: Export historical order data first to build baseline metrics before automating ongoing syncs. Starting with 12 months of data gives AI enough signal for seasonal pattern analysis.

Why Connect WooCommerce?

WooCommerce gives you reports. Orders. Revenue. Top products.

But it doesn't tell you:

Which traffic source brings customers who actually come back?
What's your true CAC when you factor in returns and refunds?
Which product combinations predict high lifetime value?
How do abandoned carts differ by traffic source?

Cogny's AI finds these patterns automatically.

What You'll Get

After connecting WooCommerce:

Customer lifetime value analysis Segment customers by LTV and find what high-value customers have in common

Product intelligence Which products drive repeat purchases vs. one-time buys

Channel attribution Multi-touch path analysis across all marketing channels

Cart abandonment insights Why people leave and which abandoned carts to prioritize

Inventory optimization What to stock more, what to discontinue, based on LTV impact

Note: Unlike Shopify, WooCommerce requires a third-party plugin or custom export script. We recommend the BigQuery WordPress plugin for automated syncing or Fivetran for production reliability.

Prerequisites

You need:

WordPress site with WooCommerce (any hosting)
WooCommerce admin access
Google Cloud account (free tier works)
Cogny account (for AI analysis)

Step 1: Choose Your Export Method

Three options:

Option A: Plugin-Based Export (Easiest)

Install WordPress plugin
Configure BigQuery credentials
Automatic sync

Best for: Non-technical users, smaller stores (<10K orders/month)

Option B: ETL Service (Recommended)

Use Fivetran or Airbyte
More reliable
Better for scale

Best for: Growing stores, agencies, multiple sites

Option C: Custom API Export (Advanced)

Use WooCommerce REST API
Build custom sync script
Most control

Best for: Developers, custom requirements

This guide covers Option B (Fivetran) - most reliable for production use.

Time: 1 minute to decide

Step 2: Set Up Google Cloud Project

Go to console.cloud.google.com

Click Select a project → New Project

Name: woocommerce-analytics

Click Create

Google gives you $300 in free credits.

Time: 2 minutes

Step 3: Enable BigQuery API

In Google Cloud Console, search for "BigQuery API"

Click Enable

Wait for activation (usually 30 seconds).

Time: 1 minute

Step 4: Create BigQuery Dataset

Go to console.cloud.google.com/bigquery

Click your project name in Explorer panel.

Click ⋮ (three dots) → Create dataset

Dataset ID: woocommerce

Location: Choose region

US stores: us (multi-region)
EU stores: eu (multi-region)
Other: Select closest region

Click Create Dataset

Time: 2 minutes

Step 5: Set Up Fivetran Connector

Go to fivetran.com

Click + Connector

Search for "WooCommerce"

Click WooCommerce connector.

Time: 2 minutes

Step 6: Configure WooCommerce Connection

Get WooCommerce API credentials:

In WordPress admin:

Go to WooCommerce → Settings → Advanced → REST API

Click Add key

Description: Fivetran BigQuery Sync

User: Select admin user

Permissions: Read

Click Generate API Key

Copy:

Consumer Key: ck_xxxxxxxxxxxxxxx
Consumer Secret: cs_xxxxxxxxxxxxxxx

IMPORTANT: Save these now. They won't be shown again.

Time: 3 minutes

Enter credentials in Fivetran:

Back in Fivetran setup:

Shop URL: https://yourstore.com

Consumer Key: Paste ck_...

Consumer Secret: Paste cs_...

Historical sync: Choose how far back to sync

Recommended: 12 months (for seasonal analysis)
Minimum: 3 months (for basic insights)

Click Save & Test

Fivetran tests connection.

If successful: ✅ "Connection successful"

If failed: Check URL, verify API keys, confirm WooCommerce version is 3.0+

Time: 3 minutes

Step 7: Configure BigQuery Destination

Create service account for Fivetran:

In Google Cloud Console:

Go to IAM & Admin → Service Accounts

Click Create Service Account

Name: fivetran-woocommerce-sync

Description: Fivetran connector for WooCommerce data

Click Create and Continue

Grant role: BigQuery Data Editor

Click Continue → Done

Time: 3 minutes

Create JSON key:

Click the service account you just created.

Go to Keys tab.

Click Add Key → Create new key

Key type: JSON

Click Create

JSON file downloads automatically.

Time: 1 minute

Configure in Fivetran:

In Fivetran destination settings:

Destination type: BigQuery

Project ID: Your Google Cloud project ID (e.g., woocommerce-analytics-123456)

Dataset location: Same region you chose in Step 4

Service account JSON: Upload the downloaded JSON file

Click Save & Test

Time: 2 minutes

Step 8: Start Initial Sync

Click Start Initial Sync in Fivetran.

What gets synced:

Orders: Every order and status
Order items: Line items (products in each order)
Customers: Customer details and history
Products: Full catalog with variations
Coupons: Discount code usage
Refunds: Return and refund data
Order notes: Customer and admin notes
Tax and shipping: Transaction details

Sync duration:

Small store (<1,000 orders): 15-30 minutes
Medium store (1K-10K orders): 1-3 hours
Large store (10K-50K orders): 4-8 hours
Very large (50K+ orders): 8-24 hours

You'll get email notification when complete.

Time: Varies (but you can proceed while syncing)

Step 9: Verify Data in BigQuery

While sync runs, check BigQuery.

Go to console.cloud.google.com/bigquery

Expand your project → woocommerce dataset.

Tables appear as sync progresses:

orders
order_items
customers
products
product_variations
coupons
refunds
order_notes

Click a table → Preview tab → See your data.

Time: 2 minutes

Step 10: Connect BigQuery to Cogny

Follow our BigQuery Connection Guide. Once connected, you can run AI-powered CAC analysis to optimize your acquisition spend.

Quick steps:

Create service account for Cogny
Grant BigQuery Data Viewer role
Download JSON key
In Cogny: Add Data Source → BigQuery
Upload JSON key
Select woocommerce dataset

Time: 5 minutes

Step 11: Let AI Analyze

Cogny's AI immediately:

Maps your schema (5-10 minutes)

Identifies tables and relationships
Connects orders → customers → products
Builds data model

Analyzes historical patterns (1-24 hours)

Customer behavior trends
Product performance
Channel effectiveness
Seasonal patterns

Generates recommendations (ongoing)

Specific optimizations
Product insights
Pricing strategies
Inventory guidance

What's in Your WooCommerce Data?

Orders table:

Every purchase.

Key fields:

id - Order ID
status - pending, processing, completed, refunded, failed
currency - USD, EUR, etc.
total - Order total
total_tax - Tax amount
shipping_total - Shipping cost
discount_total - Discounts applied
customer_id - Who ordered
billing_email - Customer email
date_created - Order timestamp
date_paid - Payment timestamp
payment_method - Gateway used
transaction_id - Payment transaction ID

Order_items table:

Individual products in each order.

Key fields:

order_id - Which order
product_id - Which product
variation_id - Product variation (size, color, etc.)
quantity - How many
subtotal - Item subtotal
total - Item total (after discount)
tax_total - Tax on item

Customers table:

Everyone who's ordered.

Key fields:

id - Customer ID
email - Email address
first_name, last_name - Name
username - WP username
date_created - First order date
orders_count - Total orders
total_spent - Lifetime value
avatar_url - Profile image

Products table:

Your catalog.

Key fields:

id - Product ID
name - Product name
slug - URL slug
type - simple, variable, grouped, etc.
status - publish, draft, private
price - Current price
regular_price - Non-sale price
sale_price - Sale price
categories - Product categories
tags - Product tags
stock_status - instock, outofstock, onbackorder

Example AI Insights

1. High-LTV Customer Acquisition Sources

AI finds: "Customers from organic search:

Average first order: $67
6-month LTV: $312
Repeat purchase rate: 47%

Customers from Facebook ads:

Average first order: $89
6-month LTV: $148
Repeat purchase rate: 18%

Organic customers are 2.1x more valuable long-term."

Recommendation: "Invest more in SEO and content. Reduce Facebook prospecting budget. Focus Facebook on retargeting."

2. Product Bundle Opportunities

AI finds: "Product A and Product B are purchased together in separate orders by 340 customers within 30 days. Average gap between purchases: 18 days. Combined: $127 revenue per customer.

If bundled with 10% discount:

Estimated take rate: 65%
Revenue per bundle: $114
But single transaction = better experience, lower support, higher satisfaction."

Recommendation: "Create 'A + B Complete Kit' bundle. Expected: 220 bundles/month, +$25K revenue."

3. Abandoned Cart Analysis by Source

AI finds: "Cart abandonment rate by source:

Google Ads: 72% abandonment

High cart value ($142 avg)
Abandon at shipping cost step
Issue: Unexpected shipping fees

Organic: 64% abandonment

Medium cart value ($87 avg)
Abandon at account creation
Issue: Forced registration

Email campaigns: 48% abandonment

Warm traffic, high intent
Abandon at payment step
Issue: Limited payment options"

Recommendation:

Show shipping costs earlier for paid traffic
Enable guest checkout
Add more payment methods (Apple Pay, PayPal)

Expected impact: 8-12% increase in conversions

4. Discount Strategy Impact

AI finds: "Customers who use 25%+ discount on first order:

Higher initial AOV ($98 vs $72)
BUT: 63% lower repeat rate
12-month LTV: $118

Customers with no discount:

Lower first order ($72)
52% make second purchase within 90 days
12-month LTV: $267

Discounts attract bargain hunters, not loyal customers."

Recommendation: "Replace first-order discounts with loyalty program. Offer 10% on second purchase instead. Expected LTV increase: 35%."

Combining WooCommerce with Marketing Data

Connect these for full picture:

WooCommerce (orders, LTV)
Google Ads (acquisition cost, ad performance)
Meta Ads (social creative effectiveness)
GA4 (website behavior, funnel analysis)

What this enables:

True ROI by channel:

"Google Shopping:

Ad spend: $12,400/month
Orders: 187
Revenue: $23,800
But: Returns + refunds: $3,200
True profit: $8,200
ROI: 66%

Facebook Prospecting:

Ad spend: $8,900/month
Orders: 142
Revenue: $18,400
Returns + refunds: $5,100
True profit: $4,400
ROI: 49%"

Recommendation: "Shift budget from Facebook to Google Shopping."

Multi-touch attribution:

"Customer journey for high-LTV customers:

See Facebook ad (awareness)
Google search → organic result (research)
Leave, return via email (nurture)
Google search → ad click (intent)
Purchase

Average touchpoints before purchase: 4.7 Time from first touch to purchase: 12 days"

Insight: All channels contribute. Stop over-crediting last click.

Common Issues

"API connection failed"

Check:

WooCommerce REST API enabled?
API keys copied correctly (no extra spaces)?
WordPress site accessible publicly (not localhost or staging with IP restrictions)?
SSL certificate valid (https://)?

"Some orders missing"

Check order status filter in Fivetran:

By default syncs: completed, processing, on-hold
Doesn't sync: draft, pending, failed

Adjust filter if you need pending orders.

"Customer data looks incomplete"

WooCommerce guest checkout creates orders without full customer records. This is normal. Cogny can still analyze by email address.

"Product variations not showing up"

Check:

Products are "Variable" type in WooCommerce
Variations are published (not draft)
Fivetran sync includes product_variations table

"Data sync stopped"

Check Fivetran connector status:

Quota limits (free tier: 500K rows/month)
API rate limits (WooCommerce default: 50 requests/minute)
WordPress site downtime

Fivetran shows detailed error logs.

Pro Tips

1. Use UTM parameters in marketing campaigns

WooCommerce doesn't track UTM parameters by default.

Add this to your theme's functions.php:

// Save UTM parameters to order meta
add_action('woocommerce_checkout_create_order', function($order, $data) {
    if (isset($_COOKIE['utm_source'])) {
        $order->update_meta_data('_utm_source', sanitize_text_field($_COOKIE['utm_source']));
    }
    if (isset($_COOKIE['utm_medium'])) {
        $order->update_meta_data('_utm_medium', sanitize_text_field($_COOKIE['utm_medium']));
    }
    if (isset($_COOKIE['utm_campaign'])) {
        $order->update_meta_data('_utm_campaign', sanitize_text_field($_COOKIE['utm_campaign']));
    }
}, 10, 2);

Then save UTM to cookies on landing:

// Save UTM to cookies
(function() {
    const params = new URLSearchParams(window.location.search);
    ['utm_source', 'utm_medium', 'utm_campaign', 'utm_content', 'utm_term'].forEach(param => {
        if (params.has(param)) {
            document.cookie = param + '=' + params.get(param) + '; path=/; max-age=2592000'; // 30 days
        }
    });
})();

Now AI can attribute orders to specific campaigns.

2. Track abandoned carts

Install plugin like "WooCommerce Cart Abandonment Recovery"

Captures abandoned cart data. Syncs to BigQuery via Fivetran. AI analyzes why carts are abandoned.

3. Use customer tags

Tag customers in WooCommerce:

"VIP"
"Wholesale"
"Influencer"

These tags sync to BigQuery. AI segments analysis by tag.

4. Enable detailed logging

WooCommerce → Settings → Advanced → Logging

Set log level to "Info" or "Debug"

Helps troubleshoot sync issues.

5. Sync product categories and tags

Make sure Fivetran includes these tables:

product_categories
product_tags

AI uses these for product performance analysis.

6. Track refund reasons

Use plugin to capture refund reasons. Or add custom order notes.

AI identifies patterns:

"Wrong size" → Size guide problem
"Quality issue" → Product quality
"Late delivery" → Shipping optimization

What You Can Do Now

Immediate actions:

Identify best customers
- Segment by LTV
- Find common characteristics
- Target lookalike audiences
Optimize product catalog
- Best sellers by cohort
- Products that drive repeat purchases
- Dead inventory to clear
Fix conversion leaks
- See where carts are abandoned
- Get specific fix recommendations
- Measure impact
Improve retention
- Identify churn signals
- Find what drives repeat purchases
- Build automated re-engagement

Alternative: WooCommerce Plugin Method

If you prefer a plugin instead of Fivetran:

Option: WooCommerce Google BigQuery Plugin

Some plugins available on WordPress.org or GitHub:

"WooCommerce BigQuery Export"
Custom plugins by hosting providers

Pros:

No third-party service (Fivetran)
Potentially free

Cons:

Less reliable
Harder to troubleshoot
May not sync all tables
Performance impact on your site

Recommendation: Use Fivetran for production. Plugins for testing/POC only.

Next Steps

Immediate actions:

Export at least 3 months of historical data for baseline analysis
Segment customers by LTV to find high-value acquisition sources

Advanced implementation:

CAC Analysis with AI - Calculate true cost per customer across all channels
Shopify + Cogny Integration - Similar process for Shopify stores

Need help? Contact support

FAQ

Q: Will this slow down my WooCommerce site?

Minimal impact.

Fivetran uses WooCommerce REST API. Queries are rate-limited and throttled.

For extra safety:

Sync during off-peak hours
Use caching plugin (WP Rocket, W3 Total Cache)

Q: What about GDPR compliance?

You're the data controller. Data stays in YOUR BigQuery.

For GDPR:

Update privacy policy to mention analytics
Provide data deletion on request
Consider anonymizing customer data in BigQuery

Q: Can I connect multiple WooCommerce sites?

Yes.

Each site becomes a separate dataset. Cogny analyzes together or separately.

Great for:

Multi-brand stores
International sites
Separate B2B and B2C

Q: What's the cost?

Fivetran:

Free tier: 500K rows/month
Paid: $60-120/month for most stores

BigQuery:

Storage: ~$2-10/month
Queries: Usually free (within Google Cloud free tier)

Total: ~$5-130/month

Q: How often does data sync?

Fivetran free: Daily Fivetran paid: Hourly, or real-time

Most stores don't need real-time. Daily is fine for AI insights.

Q: What if I'm on WooCommerce.com hosted?

Same process works.

WooCommerce.com = WordPress.com with WooCommerce. REST API available on Business plan and higher.

Q: Can I use this with WooCommerce Subscriptions?

Yes.

Subscription data syncs through:

subscriptions table (subscription details)
orders table (renewal orders)

AI analyzes:

Subscription churn patterns
Lifetime value with subscriptions
Upgrade/downgrade trends

Q: What happens to historical data if I disconnect?

Data already in BigQuery stays there. You keep it forever (unless you delete).

Future syncs stop. Historical analysis still works.

Ready to Unlock WooCommerce Insights?

Most WooCommerce stores don't know:

Which 20% of customers drive 80% of profit (and where they come from)
Why 70% of first-time buyers never return
Which products predict high lifetime value
How much money is lost to preventable cart abandonment

You can't find this in WooCommerce reports. Too much data. Too many dimensions.

AI finds it automatically.

Not set up yet?

Schedule a demo and we'll show you what's hiding in your WooCommerce data.

About This Guide

Written by the Cogny team—built by the founders who created AI optimization systems for Netflix, Zalando, and Momondo at Campanja, and scaled growth for Kry, Epidemic Sound, and Yubico through GrowthHackers.se.

We've integrated WooCommerce for hundreds of stores. This is the battle-tested process.

Last Updated: December 31, 2024

WooCommerce Data Export to Cogny

WooCommerce Data Export to Cogny

TL;DR

Related Resources

Question

Answer

Why Connect WooCommerce?

What You'll Get

Prerequisites

Step 1: Choose Your Export Method

Step 2: Set Up Google Cloud Project

Step 3: Enable BigQuery API

Step 4: Create BigQuery Dataset

Step 5: Set Up Fivetran Connector

Step 6: Configure WooCommerce Connection

Step 7: Configure BigQuery Destination

Step 8: Start Initial Sync

Step 9: Verify Data in BigQuery

Step 10: Connect BigQuery to Cogny

Step 11: Let AI Analyze

What's in Your WooCommerce Data?

Example AI Insights

Combining WooCommerce with Marketing Data

Common Issues

Pro Tips

What You Can Do Now

Alternative: WooCommerce Plugin Method

Next Steps

FAQ

Ready to Unlock WooCommerce Insights?

See Cogny in Action