Land Microsoft Advertising metrics in BigQuery for cross-engine PPC analysis. SyncRange mirrors the same tab model as Google Ads so multi-channel teams keep schemas familiar.
Overview: all destinations for Microsoft Advertising (Bing Ads)
Connect, choose columns, schedule refreshes
When spreadsheets are not enough, SyncRange loads Microsoft Advertising (Bing Ads) into Google BigQuery. Tables inherit the column layout from your export tabs, so SQL models and dbt projects can depend on predictable names.
BigQuery becomes the place to join marketing, ecommerce, and finance sources, run large historical queries, and power BI tools that expect a warehouse instead of a sheet.
Send your Microsoft Advertising (Bing Ads) data directly to Google BigQuery for enterprise-grade data warehousing. Build a central analytics repository, run SQL across massive datasets, and power large-scale reporting without managing pipelines or writing ETL code.
What we can export, and how it lands
Each row is a field you can include or omit in the app before export. Column headers match the labels below; SyncRange writes them as the first row in your destination (worksheets in Google Sheets or Excel, or BigQuery columns) when you choose BigQuery.
Microsoft Advertising (Bing) export tab using report type 'campaign'. Dimensions depend on the report; metrics are selected per tab from the shared metric library.
| Columns |
|---|
| Date |
| Device |
| Device OS |
| Network |
| Account ID |
| Account Name |
| Campaign ID |
| Campaign Name |
| Campaign Status |
| Campaign Type |
Microsoft Advertising (Bing) export tab using report type 'ad_group'. Dimensions depend on the report; metrics are selected per tab from the shared metric library.
| Columns |
|---|
| Date |
| Device |
| Device OS |
| Network |
| Account ID |
| Account Name |
| Campaign ID |
| Campaign Name |
| Ad Group ID |
| Ad Group Name |
| Ad Group Status |
Microsoft Advertising (Bing) export tab using report type 'keyword'. Dimensions depend on the report; metrics are selected per tab from the shared metric library.
| Columns |
|---|
| Date |
| Device |
| Device OS |
| Network |
| Campaign ID |
| Campaign Name |
| Ad Group ID |
| Ad Group Name |
| Keyword ID |
| Keyword |
| Keyword Status |
| Bid Match Type |
| Delivered Match Type |
Microsoft Advertising (Bing) export tab using report type 'ad'. Dimensions depend on the report; metrics are selected per tab from the shared metric library.
| Columns |
|---|
| Date |
| Device |
| Device OS |
| Network |
| Campaign ID |
| Campaign Name |
| Ad Group ID |
| Ad Group Name |
| Ad ID |
| Ad Title |
| Ad Type |
| Ad Status |
| Final URL |
| Display URL |
Microsoft Advertising (Bing) export tab using report type 'search_query'. Dimensions depend on the report; metrics are selected per tab from the shared metric library.
| Columns |
|---|
| Date |
| Device |
| Device OS |
| Network |
| Campaign ID |
| Campaign Name |
| Ad Group ID |
| Ad Group Name |
| Search Query |
| Keyword |
| Keyword ID |
| Keyword Status |
Microsoft Advertising (Bing) export tab using report type 'geographic'. Dimensions depend on the report; metrics are selected per tab from the shared metric library.
| Columns |
|---|
| Date |
| Device |
| Device OS |
| Network |
| Country |
| State |
| Metro Area |
| City |
| County |
| Postal Code |
| Neighborhood |
Microsoft Advertising (Bing) export tab using report type 'product_dimension'. Dimensions depend on the report; metrics are selected per tab from the shared metric library.
| Columns |
|---|
| Date |
| Device |
| Device OS |
| Network |
| Product ID |
| Product Title |
| Condition |
| Brand |
| Product Type (Level 1) |
| Product Type (Level 2) |
| Product Type (Level 3) |
| Product Category (Level 1) |
| Product Category (Level 2) |
| Custom Label 0 |
| Custom Label 1 |
| Custom Label 2 |
Metrics available to add to export tabs (subject to compatibility with the dimensions you choose).
| Columns |
|---|
| Impressions |
| Clicks |
| Spend |
| Conversions |
| Revenue |
| CTR |
| Average CPC |
| Average CPM |
| Average Position |
| Conversion Rate |
| Cost per Conversion |
| Return on Ad Spend |
| Revenue per Conversion |
| All Conversions |
| All Revenue |
| All Conversion Rate |
| All Cost per Conversion |
| All Return on Ad Spend |
| All Revenue per Conversion |
| View-Through Conversions |
| View-Through Revenue |
| Date Exported |
Social proof
See how teams export clean ecommerce and marketing data to Google Sheets, Microsoft Excel, or BigQuery without manual work.
Large Online Retailer
We manage high-volume ecommerce data across multiple channels and needed clean exports into BigQuery without custom engineering overhead. SyncRange gave us reliable scheduled pipelines and immediate visibility by brand.
Multi-brand Shopify Plus Operator
We run multiple Shopify stores and needed brand-level exports into BigQuery without custom pipeline maintenance. SyncRange gave us reliable scheduled exports and removed hours of manual QA.
Shopify Store Founder
We were manually updating Google Sheets every morning with Shopify and ad data. It was slow and error-prone. Now everything updates automatically, and our daily profitability tracker is always accurate.
Shopify Store Founder
I almost hired developers to build custom Shopify-to-Sheets exports. Quotes were expensive and came with ongoing maintenance. SyncRange was a fraction of the cost and worked immediately without a long build project.
Connect your account, then follow the configuration guide for your first export.
Other data sources you can sync to BigQuery
