Connect Data from Facebook Ads to Looker

You can get your Facebook Ads data into Looker to make more informed business decisions. This simple and quick guide gives you easy instructions on how you can extract your data from Facebook Ads and then analyze it in Looker. Our Facebook Ads to Looker connector allows you to access your Facebook 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 Facebook Ads with Looker to turn your Facebook Ads data into actionable insights.

Facebook is the world's most popular social network, equipped with a powerful advertising network where billions of dollars are spent each year. Marketers love using Facebook Ads ads to reach their target audience at scale.

Looker is a popular analytics tool that helps bring data and business teams together by making it quick and easy for everyone to explore and comprehend the data which drives business. Looker Analytics can integrate with any SQL database and data warehouse, like Greenplum and Amazon Redshift. From agile startups to large corporations, savvy companies can easily leverage Looker's amazing analysis capabilities to monitor the overall health of their businesses and also make more data-driven and sound decisions. Looker is great as it lets companies access, describe, control, explore, and visualize all their data across any web browser, on any device. Looker can help companies of all sizes use data to drive their business activities and decisions in the right direction.

Extracting data

Before loading your data into Looker, 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. Facebook 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

You have three options for extracting data from Facebook. 1- You can retrieve data programmatically through the Facebook Ads Insights API. It is available to all users who use the platform. Follow the API documentation, and you will enjoy access to endpoints, like impressions, CTRs, and CPC. You can access the API through the SDKs which Facebook offers. Officially, the platforms support SDKs for PHP and Python, while there’re also a number of SDKs (community supported) for languages such as R, Ruby, and JavaScript. Data will be returned in either CSV or XLS format, and when your report is ready based on the request you may access it from a URL. 2- You can export a report that you have created and saved. All you have to do is navigate to Ads reporting from the Facebook Ads Manager navigation and click on the report and then click Export. 3- You can use a tool like Improvado. By leveraging Improvado, you can easily and quickly integrate, connect, and see all your Facebook Ads Insights data flow seamlessly into your desired visualization tool or database. Improvado does not require any technical skills to operate. You can sync your data over with just a few clicks.

Loading data

Looker will connect to your company's data warehouse or database in order to perform its analyses. This is where the data you would like to analyze is stored and maintained. Some of the popular and commonly used data warehouses are Google BigQuery, Amazon Redshift, and Snowflake. Looker's documentation is helpful in this regard as it offers instructions on how you can configure and connect your database or data warehouse. Note that in a majority of cases, it simply involves creating and copying your access credentials, such as a password, username, and server information. Then you can easily move your data into your data warehouse from your various data sources for Looker to use. As soon as you connect your data warehouse to Looker, you may build constructs called explores, and each is a comprehensive SQL view that contains a certain set of data for more analysis. An example can be "customers" or "orders."

Keeping data up to date

If you've made it this far, congrats! You probably have written a program or script to extract your data and move it into Looker. 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, Facebook’s API results include fields like "date" 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.

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 Facebook to Looker automatically. Using Improvado, you can easily combine the most crucial and relevant data from your social media ad campaign into a dashboard. You can then connect this data to Looker.