Google Campaign Manager to Grafana

This page provides you with instructions on how to extract data from Google Campaign Manager and analyze it in Grafana. (If the mechanics of extracting data from Google Campaign Manager 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 Campaign Manager?

Campaign Manager (formerly DoubleClick Campaign Manager) is a web-based ad management system that advertisers and agencies use to manage creative assets and run ad campaigns.

What is Grafana?

Grafana is an open source platform for time series analytics. It can run on-premises on all major operating systems or be hosted by Grafana Labs via GrafanaCloud. Grafana allows users to create, explore, and share dashboards to query, visualize, and alert on data.

Getting data out of Campaign Manager

Campaign Manager has an API that you can use to get information about advertisers, campaigns, creative assets, and more. For example, to get information about a campaign for a given profile, you would call GET /userprofiles/{profileId}/campaigns/{id}.

Sample Campaign Manager data

Here's an example of the kind of response you might see with a query like the one above.

{
  "kind": "dfareporting#campaign",
  "id": long,
  "idDimensionValue": dimensionValues Resource,
  "accountId": long,
  "subaccountId": long,
  "advertiserId": long,
  "advertiserIdDimensionValue": dimensionValues Resource,
  "advertiserGroupId": long,
  "name": string,
  "archived": boolean,
  "startDate": date,
  "endDate": date,
  "comment": string,
  "billingInvoiceCode": string,
  "audienceSegmentGroups": [
    {
      "id": long,
      "name": string,
      "audienceSegments": [
        {
          "id": long,
          "name": string,
          "allocation": integer
        }
      ]
    }
  ],
  "eventTagOverrides": [
    {
      "id": long,
      "enabled": boolean
    }
  ],
  "clickThroughUrlSuffixProperties": {
    "overrideInheritedSuffix": boolean,
    "clickThroughUrlSuffix": string
  },
  "defaultClickThroughEventTagProperties": {
    "overrideInheritedEventTag": boolean,
    "defaultClickThroughEventTagId": long
  },
  "creativeGroupIds": [
    long
  ],
  "creativeOptimizationConfiguration": {
    "optimizationModel": string,
    "optimizationActivitys": [
      {
        "floodlightActivityId": long,
        "floodlightActivityIdDimensionValue": dimensionValues Resource,
        "weight": integer
      }
    ],
    "id": long,
    "name": string
  },
  "additionalCreativeOptimizationConfigurations": [
    {
      "optimizationModel": string,
      "optimizationActivitys": [
        {
          "floodlightActivityId": long,
          "floodlightActivityIdDimensionValue": dimensionValues Resource,
          "weight": integer
        }
      ],
      "id": long,
      "name": string
    }
  ],
  "lookbackConfiguration": {
    "clickDuration": integer,
    "postImpressionActivitiesDuration": integer
  },
  "createInfo": {
    "time": long
  },
  "lastModifiedInfo": {
    "time": long
  },
  "traffickerEmails": [
    string
  ],
  "externalId": string,
  "nielsenOcrEnabled": boolean,
  "adBlockingConfiguration": {
    "enabled": boolean,
    "overrideClickThroughUrl": boolean,
    "clickThroughUrl": string,
    "creativeBundleId": long
  },
  "defaultLandingPageId": long
}

Loading data into Grafana

Analyzing data in Grafana requires putting it into a format that Grafana can read. Grafana natively supports nine data sources, and offers plugins that provide access to more than 50 more. Generally, it's a good idea to move all your data into a data warehouse for analysis. MySQL, Microsoft SQL Server, and PostgreSQL are among the supported data sources, and because Amazon Redshift is built on PostgreSQL and Panoply is built on Redshift, those popular data warehouses are also supported. However, Snowflake and Google BigQuery are not currently supported.

Analyzing data in Grafana

Grafana provides a getting started guide that walks new users through the process of creating panels and dashboards. Panel data is powered by queries you build in Grafana's Query Editor. You can create graphs with as many metrics and series as you want. You can use variable strings within panel configuration to create template dashboards. Time ranges generally apply to an entire dashboard, but you can override them for individual panels.

Keeping Campaign Manager data up to date

Now what? You've built a script that pulls data from the Campaign Manager API and loads it into your data warehouse, but what happens tomorrow when you have new data?

The key is to build your script in such a way that it can identify incremental updates to your data. Thankfully, many of the API results include fields like createInfo that allow you to identify records that are new since your last update (or since the newest record you've copied). Once you've take new data into account, you can set your script up as a cron job or continuous loop to keep pulling down new data as it appears.

From Google Campaign Manager to your data warehouse: An easier solution

As mentioned earlier, the best practice for analyzing Google Campaign Manager data in Grafana 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 Google Campaign Manager to Redshift, Google Campaign Manager to BigQuery, Google Campaign Manager to Azure SQL Data Warehouse, Google Campaign Manager to PostgreSQL, Google Campaign Manager to Panoply, and Google Campaign Manager 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 Google Campaign Manager to Grafana automatically. With just a few clicks, Stitch starts extracting your Google Campaign Manager data via the API, 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 Grafana.