Connect Data from Google Ads to Sisense

You can get your Google Ads data into Sisense to make more informed business decisions. This simple and quick guide gives you easy instructions on how you can extract your data from Google Ads and then analyze it in Sisense. Our Google Ads to Sisense connector allows you to access your Google Ads data so you can easily manage various media objects, view metadata, and comments, and get reliable insights and metrics, such as reach, impressions, follower-like ratio, and likes. Integrate your Google Ads with Sisense to turn your Google Ads data into actionable insights.

Google Ads is Google’s own advertising service. The service allows you to easily place search results for your website(s) on a SERP (search engine results page) by paying for them. Advertisers usually bid on specific keywords in order to make sure their clickable adverts appear in Google's search results. As advertisers need to pay for these clicks, it is how Google earns money from search. Google Ads also collects data about various campaigns that businesses can use in order to measure their success or effectiveness.

Sisense is an amazing business intelligence platform which lets you join, picture out and analyze information you need to make more intelligent and better business decisions. With Sisense, you may easily unify all your Google Ads data into visually appealing dashboards through a user-friendly drag and drop interface. Its intuitive business intelligence reporting component is an important element of a software stack which also includes incredible tools to prep, connect, and govern data use.

Extracting data

Before loading your data into Sisense, you will have to prep it first. 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. Google Ads's 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. In these cases you'll likely have to create additional tables to capture the unpredictable cardinality in each record.

Preparing data

For Google Ads, Google offers users a SOAP API. You can get your data into the data warehouse by pulling your data off of Google's servers easily by using the amazing AdWords API's Reporting features. Note that this is an important subset of this API's functionality, which includes the ability to easily manage ads as well. You may also link your Google Ads and Google Analytics accounts in order to allow your data to cross-pollinate. This is great as it provides richer reporting because of the breadth of data and knowledge that exist in Google Analytics about the individuals who might have viewed or clicked on your ads.

Loading data

Sisense is great as it enables quick and easy access to tables within your CSV files. You can upload data in two ways. The first option is to upload your data file to the Sisense Server. As soon as the file is uploaded, your data would be imported into the web-based ElastiCube as it was at the time you uploaded the file. The other option is to define your file location on the Sisense Server. You can import your data from the CSV files by following these steps: Create a new ElastiCube in the Data page of the ElastiCube Manager. Click in the ElastiCube.  You will see the Add Data dialog box. To open the CSV settings, click CSV. Click on File Upload. To upload your data file, click Browse, and then navigate to the file that you need to upload. Now select the CSV files you want to upload and click on Next.  You will see the Select Table list. You have to click on to select preview the relevant columns and then display the Settings. These settings provide more options to customize your data. You can define the following settings in the Settings area:• Culture: This defines various settings, like the format of your date.• First Row has Field Names: This enables you to easily specify column names in the table depending on the first-row header of the spreadsheet.• Delimiter: This allows you to select the character which separates different values within your CSV file. After selecting all the required tables, click Done. Your tables will be added to the schema in Sisense.

Keeping data up to date

If you've made it this far, congrats! You probably have a written a program or script to extract your data and move it into Sisense. Now it's time to think about how you will keep this data up-to-date by loading updated or new data. Of course, you can just replicate all your data every time you have updated your records, but that would be extremely manual and time-consuming. Luckily there is a better way. The key is building your script so that it can sense incremental updates made to the data. Thankfully, Google Ads API results include fields so that you can identify those records which are new since the last update you made (or since the most recent record you have copied). Once you have taken new data into consideration, you can easily set your script either as a continuous loop or cron job to pull down new data as soon as it appears. And keep in mind that, as with most codes, once you write it, you will need to maintain it. In case Google Ads changes its API, or if the API sends a field containing a data type that your code does not recognize, you might have to change the script.

The Easiest And Fastest Way To Do It

If all this sounds a bit overwhelming, don't worry -- there is an easier way to get this done! Thankfully, products like Improvado were developed to move data from Google Ads to Sisense automatically. Using Improvado, you can easily combine the most crucial and relevant data from your ad campaign into a dashboard. You can then connect this data to Sisense.