Connect Facebook Ads to Google BigQuery with Windsor.ai
Stream all your marketing data from Facebook Ads to Google BigQuery
There are very few marketing companies, or let’s rephrase that – companies that do marketing that don’t do Facebook Ads. Here we are going to explain how to connect Facebook Ads to Google BigQuery with the Windsor.ai connector, but we will also have a look at the importance of Facebook Ads data and how you and your business can make the most of it.
Unless you are completely off the grid you are surely aware how Facebook has become a huge part of our social lives. We use it to connect and communicate primarily, but it has so many other functions and uses. For marketing companies, Facebook is an obvious choice – all of their customers and potential customers are there.
People that matter are on FB
What do we mean when we say that all the customers are on Facebook? Well, the number of active accounts is about 3 billion. Bear in mind that Facebook reached 2 billion in 2017 and it is pretty evident that the next billion will come even faster. And not all customers are equally important. More than 85% of all people who earn over $100K per year are on Facebook.
Everybody is pretty much hooked up
Moreover, more than two thirds of the US population is currently on Facebook. And most Facebook users log in to their accounts pretty often, so you can be certain that you will reach them there. More than 70% of all users log in on a daily basis, in fact, most of them probably don’t even log out, whereas almost 95% log in at least once a week.
Big numbers – lots of marketing spend
Now, if we have a look at the marketing numbers, the results would be even more astonishing. Facebook’s advertising revenue exceeds $20 billion per year. But this doesn’t mean that advertising on Facebook is expensive, on the contrary. The average cost per mile (CPM) on FB barely exceeds $5.30 whereas the cost per click (CPC) is about $0.43, whereas the average clickthrough rate (CTR) is 3.90%.
And while you do need to have some insight and a fair amount of data to be able to start advertising on Facebook in the first place, the data that you collect from your Facebook ads definitely can help you optimize your campaigns and get even better results in the future.
The metrics that matter
The metrics that are available and can be exported from Facebook Ads Manager include not only strictly campaign related metrics like CPM, CPC and CTR, but also information on different events and actions that customers or potential customers can complete after clicking on the ad, as well as data on their age, gender, location etc, of course without disclosing their identity.
BigQuery comes in
All of that data can be chaotic and sometimes it can be difficult to separate the metrics that are vital to the success of your campaign and the ones that aren’t. On top of that, the metrics and parameters as presented within Facebook Ads Manager, even if you download them in an Excel format can be difficult to follow and present. That’s where BigQuery comes in.
What is BigQuery?!
BigQuery is offered as a platform as a service (PaaS) and it is serverless, which means your data isn’t dependent on a single server or a set of servers and their functioning. It supports querying using SQL and you can manage data, query it, you can integrate it and even use it for machine learning.
If you want to make the best use of your Facebook Ads data, it is a very good decision to add it to BigQuery. There are two ways to integrate your Facebook data into BigQuery, you can do it manually and you can go through Windsor.ai.
It is definitely possible to integrate Facebook Ads data into BigQuery manually, but it is a pretty long and complex process.
Set up Google Cloud Project first
First, you will need a Google Cloud Project which is available as a free trial. Then, you will set up a new project and name it. You will be able to edit it later. Next you need to go to Facebook Ads Manager and select the data you wish to upload to BigQuery and then download the reports. Save the files as .csv files and then go back to BigQuery, enter your project and click “+Create Dataset”. After that you will need to name your dataset, ensure it’s encrypted and then proceed to click “+Create Table”.
In the source section you will need to create table form, select file and the file format. Then you will need to navigate the destination and the schema sections and select the right options.
Partition and cluster settings
But it doesn’t end there. You will need to go to ‘Partition and cluster settings’ and then choose the most viable option for you, either ‘No partitioning’ or ‘Partition by ingestion time’ and then go to Advanced options where you’ll need to set field delimiter.
The following step is to create a table, after which the data warehouse will start becoming populated with the data that was pulled from Facebook Ads Manager.
Start using SQL
After all of that you can go into BigQuery, start writing SQL queries, or export your Facebook data to other tools and software where you can conduct additional analysis.
If you want to add more data you can simply repeat the process and do it. But you will also need to repeat the process whenever you wish to ensure that the data is fresh and uptodate.
Quite a lot of steps
If we put a number on these steps it would’ve been about 20 before you can get your FB Ads data in BigQuery.
Windsor.ai connector Integration
Now let’s see how easy it is to get Facebook Ads to Google BigQuery with Windsor.ai.
- Select FB Ads as a data source
2. Select BigQuery as destination
3. Copy the connector URL
4. After you grant access to the user: email@example.com you should paste the connector URL in BigQuery and the data will start being populated.
And if you don’t know enough about BigQuery, have a look at this Google Cloud resource.
Windsor.ai: Easily connect Facebook Ads to Google BigQuery
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