Direct to BigQuery

Sync Google Analytics to BigQuery in Under 5 Minutes

Sync Google Analytics to BigQuery in Under 5 Minutes

Automatically sync sessions, events, channel performance, landing pages, and campaign attribution data from Google Analytics directly into your own BigQuery project — purpose-built for marketing agencies and large marketing teams.

Automatically sync sessions, events, channel performance, landing pages, and campaign attribution data from Google Analytics directly into your own BigQuery project — purpose-built for marketing agencies and large marketing teams.

Trusted by 1,000+ ad accounts • $700M+ managed spend • 99.9% uptime

Trusted by 1,000+ ad accounts • $700M+ managed spend • 99.9% uptime

DATA PIPELINE

Google Analytics

Weavely

BigQuery

Looker Studio

Sheets

Own your data

Your Google Analytics data lands directly in your BigQuery project — not ours.

Data ownership

You own your data

Warehouse-native setup

Connect to any BI tool

Historical backfills

Automatically included

Save time on reporting

Automated reporting

Client grouping

Organized by default

Data ownership

You own your data

Historical backfills

Automatically included

Client grouping

Organized by default

Warehouse-native setup

Connect to any BI tool

Save time on reporting

Automated reporting

Explore what you can export

Clean, structured exports designed for scalable agency reporting and data warehousing.

This is just a preview — explore the full dataset by creating a free account or booking a demo.

Campaigns

DIMENSIONS

Date
Property ID
Property Name
Session Campaign Name
Session Default Channel Group
Session Source Medium
Timestamp

METRICS

Active Users
Conversions
Engaged Sessions
Event Count
New Users
Sessions
Total Users
User Engagement Duration

Events

DIMENSIONS

Date
Event Name
Property ID
Property Name
Session Default Channel Group

METRICS

Event Count
Event Value
Key Events
New Users
Purchase Revenue
Sessions
Timestamp
Total Purchasers
Total Revenue
Total Users
Transactions

Items

DIMENSIONS

Date
Property Name
Property ID
Item Brand
Item Category
Item ID
Item Name
Item Variant
Transaction ID
Timestamp

METRICS

Gross Item Revenue
Item Discount Amount
Item Revenue
Items Added To Cart
Items Checked Out
Items Purchased
Items Viewed

Source/Medium

DIMENSIONS

Date
New Vs Returning
Property ID
Property Name
Session Campaign ID
Session Campaign Name
Session Default Channel Group
Session Medium
Session Source

METRICS

Active Users
Engaged Sessions
Event Count
New Users
Purchase Revenue
Sessions
Total Users

From account to warehouse in minutes

Step 1

Connect Google Analytics

Secure OAuth authentication

Step 2

Link BigQuery

Select your GCP project

Step 3

Enable exports

Choose your tables

Step 4

Data flows

Automated syncs

Built differently from the start

Feature

Weavely

Typical Connector

Data Storage

Your BigQuery

Vendor-owned

Pricing Model

Flat per ad account

Confusing & expensive

Historical Data

Included

Often add-on

Setup Time

Under 1 hour

Days or weeks

Multi-Client Management

Under 1 hour

Built for single brands

Weavely vs Supermetrics

Supermetrics is powerful for spreadsheet exports and dashboard connectors. Weavely is built for warehouse-native agencies.

Weavely

Direct BigQuery export

Flat per-account pricing

Agency-native architecture

No row-based billing traps

Multi-client structure built-in

Supermetrics

Often per-destination pricing

Volume-based billing

Primarily dashboard-focused

Data often routed through vendor infrastructure

If you're building a scalable agency data warehouse, Weavely is purpose-built for that workflow.

Weavely vs Funnel

Funnel is powerful for centralized reporting and managed transformations. Weavely is built for agencies that want direct control of their data inside BigQuery.

Weavely is

Purpose-built for marketing data

Built for BigQuery from day one

Optimized for agency client structures

Predictable, usage-based pricing

Fast to deploy and scale

Funnel often:

Acts as a reporting layer, not a warehouse

Charges per data volume or workspace

Stores data outside your own BigQuery project

Adds unnecessary transformation layers

Becomes expensive as agencies grow

If you're building a scalable agency data warehouse — not just a reporting layer — Weavely is purpose-built for that workflow.

Technical FAQs

How often does data sync?

Data syncs automatically on a scheduled basis. Most agency accounts sync multiple times per day. Sync frequency can be configured depending on reporting needs.

Does the data land in Weavely's warehouse?

No. Data is exported directly into your BigQuery project. Weavely does not act as a long-term storage layer for your reporting data.

Is historical backfill included?

Yes. On setup, Weavely pulls historical Meta Ads data so you can start with a complete performance dataset.

Do you support attribution windows?

Yes. Because data is structured inside your BigQuery project, you can join it with GA4, CRM, Shopify, or custom datasets for full-funnel analysis.

How do you handle schema changes?

Weavely monitors platform API changes and updates export schemas automatically to ensure continuity and minimal disruption.

Ready to scale without reporting chaos?

Stop losing time to broken connectors. Build infrastructure that scales with your agency.

Ready to scale without reporting chaos?

Stop losing time to broken connectors. Build infrastructure that scales with your agency.

Ready to scale without reporting chaos?

Stop losing time to broken connectors. Build infrastructure that scales with your agency.