Google Search Console
The Qlik Google Search Console connector uses the Search Console APIs to access search-traffic data about your websites, such as clicks per page or clicks per country.
- Qlik Sense Business
- Qlik Sense Enterprise SaaS
- Qlik Sense Enterprise on Windows
- Qlik Sense Desktop
Ways to access your data
To access your Google Search Console data, you need to authenticate the connector with your Google account credentials. After you create a connection and select Google Search Console as your data source, you are redirected to a Google login page. Log into your Google account using your credentials to receive an authentication code. Enter this authentication code into the connector.
Loading data from tables
After you authenticate the connector with your account credentials, use the tables to fetch your data. Some tables are preconfigured to access a specific set of data while others let you create custom queries. The table below outlines some of the use cases for some of the tables that are available.
|ListSites||Data load editor||Use this table to fetch the list of sites that are associated with your Google account.|
|Site||Data load editor||
Use this table to fetch the permission level and status of your sites. This table requires a site URL.
|SearchAnalyticsQuery||Data manager and Data load editor||Use this table to build a custom query. This table requires a site URL, a start date, and an end date for the query.|
To select and load data from a table, enter the required table parameters and click Preview data. Required parameters are marked with an asterisk (*) in the dialog. The table fields are displayed under the Data preview tab. You can select fields individually by selecting the box beside each field name. Select Insert script after you have made your selection.
Building custom queries with the SearchAnalyticsQuery table
The SearchAnalyticsQuery table lets you query the search-traffic data you fetch about your websites. You must specify the site URL and the date range of the query. You can use the Search Type and Aggregation Type menus to limit the query and to aggregate the returned data.
You can group your data by dimension, in the order you supply the dimensions. Valid dimensions are:
You can enter a dimension filter using a JSON statement. The following example is a valid JSON statement that filters the dimension 'country' by the expression 'USA'.
To learn more about building custom queries, see the Search Analytics query documentation.
Working with the Google Search Console API quota limits
The Qlik Web Connectors use the Search Console APIs to extract data from Google Search Console and load it into your Qlik Sense app. While reloading you Google Search Console-based app, you might receive an error message that the connector has reached the Search Console API rate limit and that all subsequent API calls will fail until the connector falls back under the throttling limit. If you receive this error message, then you have exceeded one of the API rate limits.
Reference - Google Search Console developer documentation
You can refer to the Google Search Console APIs documentation to learn more about the requirements and restrictions imposed by the Search Console APIs.
You have exceeded the API limits that are imposed on the Qlik Web Connectors by one of the Google Search Console APIs.
To reduce the impact of reaching the API rate limits, develop your app with the following in mind:
- Extract only the data you need.
- Reload one Search Console-based application at a time.
- Avoid concurrent reloads from different accounts for the same website.
- Ensure that loops in your script that make API calls will not result in infinite loops.
The metrics totals are different between Search Console and connector
When viewing metrics tables in Google, long tables can sometimes become truncated to conserve space.
To understand why you see a difference, refer to the Google Analytics Report.
Data is different when aggregating data by site versus by page
Google uses different accounting methods to aggregate data by site versus by page.
To learn how Google aggregates data, refer to the Google aggregating data documentation.