This page provides you with instructions on how to extract data from Bing Ads and analyze it in Google Data Studio. (If the mechanics of extracting data from Bing Ads seem too complex or difficult to maintain, check out Stitch, which can do all the heavy lifting for you in just a few clicks.)
Bing Ads is now Microsoft Advertising
What is Google Data Studio?
Google Data Studio is a simple dashboard and reporting tool. It's free and easy to use, but it lacks the sophisticated features of higher-end reporting software. Many of the connectors it supports are for Google products, but third parties have written partner connectors to a wide variety of data sources. Its drag-and-drop report editor lets users create about 15 types of charts.
Getting data out of Microsoft Advertising
Microsoft makes Advertising data available through a Microsoft Advertising API, which offers data on things like ad insights, estimated bids, estimated positions, and many other kinds of data. Because it’s a SOAP API, scripts must call data objects by making SOAP request messages.
For example, to get data about bid opportunities, you could use the Microsoft Advertising API GetBidOpportunities service. The service’s syntax includes four header elements and three body elements, two of which are optional. Once you decided exactly what information you wanted, you could code a SOAP request that might look like this:
<s:Envelope xmlns:i="http://www.w3.org/2001/XMLSchema-instance" xmlns:s="http://schemas.xmlsoap.org/soap/envelope/"> <s:Header xmlns="Microsoft.Advertiser.AdInsight.Api.Service.V11"> <Action mustUnderstand="1">GetBidOpportunities</Action> <ApplicationToken i:nil="false">ValueHere</ApplicationToken> <AuthenticationToken i:nil="false">ValueHere</AuthenticationToken> <CustomerAccountId i:nil="false">ValueHere</CustomerAccountId> <CustomerId i:nil="false">ValueHere</CustomerId> <DeveloperToken i:nil="false">ValueHere</DeveloperToken> <Password i:nil="false">ValueHere</Password> <UserName i:nil="false">ValueHere</UserName> </s:Header> <s:Body> <GetBidOpportunitiesRequest xmlns="Microsoft.Advertiser.AdInsight.Api.Service.V11"> <AdGroupId i:nil="false">ValueHere</AdGroupId> <CampaignId i:nil="false">ValueHere</CampaignId> <OpportunityType>ValueHere</OpportunityType> </GetBidOpportunitiesRequest> </s:Body> </s:Envelope>
Sample Microsoft Advertising data
The Microsoft Advertising API returns XML objects. In response to a bid opportunities request, for example, the service would provide a SOAP response that might look like this:
<s:Envelope xmlns:s="http://schemas.xmlsoap.org/soap/envelope/"> <s:Header xmlns="Microsoft.Advertiser.AdInsight.Api.Service.V11"> <TrackingId d3p1:nil="false" xmlns:d3p1="http://www.w3.org/2001/XMLSchema-instance">ValueHere</TrackingId> </s:Header> <s:Body> <GetBidOpportunitiesResponse xmlns="Microsoft.Advertiser.AdInsight.Api.Service.V11"> <Opportunities xmlns:e63="http://schemas.datacontract.org/2004/07/Microsoft.BingAds.Advertiser.AdInsight.Api.DataContract.V11.Entity" d4p1:nil="false" xmlns:d4p1="http://www.w3.org/2001/XMLSchema-instance"> <e63:BidOpportunity> <e63:AdGroupId>ValueHere</e63:AdGroupId> <e63:CampaignId>ValueHere</e63:CampaignId> <e63:CurrentBid>ValueHere</e63:CurrentBid> <e63:EstimatedIncreaseInClicks>ValueHere</e63:EstimatedIncreaseInClicks> <e63:EstimatedIncreaseInCost>ValueHere</e63:EstimatedIncreaseInCost> <e63:EstimatedIncreaseInImpressions>ValueHere</e63:EstimatedIncreaseInImpressions> <e63:KeywordId>ValueHere</e63:KeywordId> <e63:MatchType d4p1:nil="false">ValueHere</e63:MatchType> <e63:SuggestedBid>ValueHere</e63:SuggestedBid> </e63:BidOpportunity> </Opportunities> </GetBidOpportunitiesResponse> </s:Body> </s:Envelope>
Preparing Microsoft Advertising data
If you don’t already have a data structure in which to store the data you retrieve, you’ll have to create a schema for your data tables. Then, for each value in the response, you’ll need to identify a predefined datatype (INTEGER, DATETIME, etc.) and build a table that can receive them. The source API documentation should tell you what fields are provided by each endpoint, along with their corresponding datatypes.
Complicating things is the fact that the records retrieved from the source may not always be "flat" – some of the objects may actually be lists. This means you’ll likely have to create additional tables to capture the unpredictable cardinality in each record.
Loading data into Google Data Studio
Google Data Studio uses what it calls "connectors" to gain access to data. Data Studio comes bundled with 17 connectors, mostly to pull in data from other Google products. It also supports connectors to MySQL and PostgreSQL databases, and offers 200 connectors to other data sources built and supported by partners.
Using data in Google Data Studio
Google Data Studio provides a graphical canvas onto which users drag and drop datasets. Users can set dimensions and metrics, specify sorting and filtering, and tailor the way reports and charts are displayed.
Keeping Microsoft Advertising data up to date
At this point you’ve coded up a script or written a program to get the data you want and successfully moved it into your data warehouse. But how will you load new or updated data? It's not a good idea to replicate all of your data each time you have updated records. That process would be painfully slow and resource-intensive.
Instead, identify key fields that your script can use to bookmark its progression through the data and use to pick up where it left off as it looks for updated data. Auto-incrementing fields such as updated_at or created_at work best for this. When you've built in this functionality, you can set up your script as a cron job or continuous loop to get new data as it appears in Microsoft Advertising.
And remember, as with any code, once you write it, you have to maintain it. If Microsoft modifies the Microsoft Advertising API, or if the API sends a field with a datatype your code doesn't recognize, you may have to modify the script. If your users want slightly different information, you definitely will have to.
From Bing Ads to your data warehouse: An easier solution
As mentioned earlier, the best practice for analyzing Bing Ads data in Google Data Studio is to store that data inside a data warehousing platform alongside data from your other databases and third-party sources. You can find instructions for doing these extractions for leading warehouses on our sister sites Bing Ads to Redshift, Bing Ads to BigQuery, Bing Ads to Azure Synapse Analytics, Bing Ads to PostgreSQL, Bing Ads to Panoply, and Bing Ads to Snowflake.
Easier yet, however, is using a solution that does all that work for you. Products like Stitch were built to move data automatically, making it easy to integrate Bing Ads with Google Data Studio. With just a few clicks, Stitch starts extracting your Bing Ads data, structuring it in a way that's optimized for analysis, and inserting that data into a data warehouse that can be easily accessed and analyzed by Google Data Studio.