This page provides you with instructions on how to extract data from Bing Ads and analyze it in Power BI. (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.)
What is Bing Ads?
Bing Ads is a pay-per-click (PPC) advertising platform used to display ads based on the keywords that appear in Bing users' search queries.
What is Power BI?
Power BI is Microsoft’s business intelligence offering. It's a powerful platform that includes capabilities for data modeling, visualization, dashboarding, and collaboration. Many enterprises that use Microsoft's other products can get easy access to Power BI and choose it for its convenience, security, and power.
With high-value use cases across analysts, IT, business users, and developers, Power BI offers a comprehensive set of functionality that has consistently landed Microsoft in Gartner's "Leaders" quadrant for Business Intelligence.
Getting data out of Bing Ads
Microsoft makes Bing Ads data available through a Bing Ads 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 Bing Ads 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 Bing Ads data
The Bing Ads 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 Bing Ads 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 Power BI
You can analyze any data in Power BI, as long as that data exists in a data warehouse that's connected to your Power BI account. The most common data warehouses include Amazon Redshift, Google BigQuery, and Snowflake. Microsoft also has its own data warehousing platform called Azure SQL Data Warehouse.
Connecting these data warehouses to Power BI is relatively simple. The Get Data menu in the Power BI interface allows you to import data from a number of sources, including static files and data warehouses. You'll find each of the warehouses mentioned above among the options in the Database list. The Power BI documentation provides more details on each.
Analyzing data in Power BI
In Power BI, each table in the data warehouse you connect is known as a dataset, and the analyses conducted on these datasets are known as reports. To create a report, use Power BI’s report editor, a visual interface for building and editing reports.
The report editor guides you through several selections in the course of building a report: the visualization type, fields being used in the report, filters being applied, any formatting you wish to apply, and additional analytics you may wish to layer onto your report, such as trendlines or averages. You can explore all of the features related to analyzing and tracking data in the Power BI documentation.
Once you've created a report, Power BI lets you share it with report "consumers" in your organization.
Keeping Bing Ads 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 Bing Ads.
And remember, as with any code, once you write it, you have to maintain it. If Microsoft modifies the Bing Ads 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 Power BI 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 SQL Data Warehouse, 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 from Bing Ads to Power BI automatically. With just a few clicks, Stitch starts extracting your Bing Ads data via the API, structuring it in a way that is optimized for analysis, and inserting that data into a data warehouse that can be easily accessed and analyzed by Power BI.