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 Google Sheets or as BigQuery columns when you choose BigQuery as the destination.
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 |
Trusted by Shopify Store Owners and Marketing Teams
See what founders, ecommerce managers, and agencies say about SyncRange.
Marketing Agency Owner
I was impressed how easily SyncRange could connect our clients Facebook and Google Ads data that I upgraded immediately and I'm implementing it across all our Google Sheets reporting dashboards 😍
Multi-ecommerce business owner
Prior to using SyncRange, I was hiring VA's to copy and past data from my Shopify Stores and multiple Facebook Ad accounts Every day. SyncRange has eliminated the need for VA's and saved me hours managing their work. It's also a lot cheaper than hiring VA's.
Shopify Store Founder
We were manually updating our Google Sheets every day with data from Shopify, Meta Ads, and Google Ads (sales, discounts, returns, ad spend). It was a time consuming mess. SyncRange completely solved that. Now everything updates automatically each morning, and our daily profitability tracker is always accurate and up to date. It’s saved us hours each week and removed all the guesswork. Total game changer
Ecommerce Store Owner
Prior to finding SyncRange, I was looking to hire developers to build custom integrations to Sheets for my store and marketing channels. I was quoted $1300+ to build a custom integration with ongoing maintenance fees. SyncRange is a fraction of the cost and I didn't have to wait for it to be built.
Connect your account, then follow the configuration guide for your first export.
Other data sources you can sync to BigQuery
