Building an all-new data connector is challenging, especially when you are already overloaded with managing & maintaining your existing custom data pipelines. To fulfill an ad-hoc Apple Search Ads to BigQuery connection request from your marketing team, you’ll have to invest a significant portion of your engineering bandwidth.

We know you are short on time & need a quick way out. This can be a walk in the park if you just need to download and upload a couple of CSV files. Or you could directly opt for an automated tool that fully handles complex transformations and frequent data integrations for you.

Either way, with this article’s stepwise guide to connect Apple Search Ads to BigQuery effectively, you can set all your worries aside and quickly deliver time-sensitive campaign data to your data-hungry marketing team in 7 nifty minutes.

How to connect Apple Search Ads to BigQuery?

Your marketers are keenly waiting on you to provide data from campaign reports and search term reports into BigQuery for scalable analysis. Without any further ado, let’s get right on it and replicate data from Apple Search Ads Data to BigQuery using any of the following approaches.

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Downloading & Uploading data as CSV files via custom code

Follow the below steps to integrate Apple Search Ads to Bigquery via CSV files:

Step 1: Download Report

In Apple Search Ads, custom reports can be created by choosing different metrics per requirement. And these custom reports can be downloaded as CSV files by clicking the download icon next to the report in the Actions column of the Custom Reports page.

Step 2: Load CSV file to BigQuery

  • Get the required IAM permissions, to load data into a BigQuery table or partition.
  • CSV data can be uploaded to BigQuery using Python. For a detailed setup of Python for BigQuery, check BigQuery Python API reference documentation.
  • Finally, use the below Python Code to upload CSV data and complete the Apple Search Ads to BigQuery data replication process.
from import bigquery

# Construct a BigQuery client object.
client = bigquery.Client()

# Set table_id to the ID of your project table
table_id = "your-project.your_dataset.your_table_name" #edit accordingly

job_config = bigquery.LoadJobConfig(
        bigquery.SchemaField("name", "STRING"),
        bigquery.SchemaField("post_abbr", "STRING"),
    # The default source format is CSV
filename= "****.csv" #Give CSV filename here

load_job = client.load_table_from_file(
    filename, table_id, job_config=job_config
)  # Make an API request.

load_job.result()  # Waits for the job to be complete.

destination_table = client.get_table(table_id)  # Make an API request.
print("Loaded {} rows.".format(destination_table.num_rows))

By printing the last lines, you get to know how many rows of data are uploaded.

Exporting & importing CSV files to provide data for your marketing & sales teams is an effective option for the following cases:

  • Little to No Transformation Required: Carrying out complex data preparation and standardization tasks are impossible using the above method. Hence, it is an excellent choice if your Ad campaign data is already in an analysis-ready form for your business analysts.
  • One-Time Data Transfer: At times, business teams only need this data quarterly, yearly, or once when looking to migrate all the data completely. For these rare occasions, the manual effort is justified.
  • Few Reports: Downloading and uploading only a few CSV files is fairly simple and can be done quickly.   

A problem occurs when your business teams require fresh data from multiple reports every few hours. It becomes vital to clean and standardize the data for people to make sense of it when it is available in multiple formats. As a result, you soon find yourself devoting a sizable amount of your engineering bandwidth to building new data connectors. To guarantee a transfer with no data loss, you must also keep an eye out for any changes in these connectors and repair data pipelines as needed. These on-priority tasks can easily eat up 40-50 % of the time needed to complete your core engineering duties.

So, is there a simpler yet effective alternative to this? You can…

Automate the Data Replication process using a No-Code Tool

Going all the way to write custom scripts for every new data connector request is not the most efficient and economical solution. Frequent breakages, pipeline errors, and lack of data flow monitoring make scaling such a system a nightmare.

You can streamline the Apple Search Ads to BigQuery data integration process by opting for an automated tool. To name a few benefits, you can check out the following:

  • It allows you to focus on core engineering objectives while your business teams can jump on to reporting without any delays or data dependency on you.
  • Your marketers can effortlessly enrich, filter, aggregate, and segment raw Apple Search Ads data with just a few clicks.
  • The beginner-friendly UI saves the engineering team hours of productive time lost due to tedious data preparation tasks.
  • Without coding knowledge, your analysts can seamlessly standardize timezones or aggregate campaign data from multiple sources for faster analysis.
  • Your business teams get to work with near-real-time data with no compromise on the accuracy & consistency of the analysis.

To know the comfort of such an effective automated tool, let’s see how a cloud-based platform like Hevo effortlessly connects Apple Search Ads to BigQuery in 3 easy steps:

  • Step 1:  Configure Apple Search Ads as a source by providing your Apple credentials. 
Apple Search Ads to BigQuery: Configure Apple Ads as Source

Note: You must authorize Hevo to access data from your Apple Search Ads account using the API keys. 

  • Step 2: Connect to your Google BigQuery account via a user or service account.
Login using Google Account
  • Step 3: Configure BigQuery as your destination to start the data replication from Apple Search Ads to BigQuery.
Configure BigQuery as Destination

After implementing the 3 simple steps, Hevo will take care of building the pipeline for replicating data from Apple Search Ads to BigQuery based on the inputs given by you while configuring the source and the destination.

The pipeline will automatically replicate new and updated data from Apple Search Ads to BigQuery every 6 hours (by default). However, you can adjust the Apple Search Ads to BigQuery data replication frequency per your requirements.

Data Replication Frequency

Default Pipeline FrequencyMinimum Pipeline FrequencyMaximum Pipeline FrequencyCustom Frequency Range (Hrs)
6 Hrs1 Hr24 Hrs1-24

Hevo is fully-managed and completely automates the process of not only loading data from your 150+ plug and play connectors(including 40+ free sources)but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code. The data is handled securely and consistently with zero data loss with fault-tolerant Hevo’s architecture.

By employing Hevo to simplify your Apple Search Ads to BigQuery data integration needs, you get to leverage its salient features:

  • Reliability at Scale: With Hevo, you get a world-class fault-tolerant architecture that scales with zero data loss and low latency. 
  • Monitoring and Observability: Monitor pipeline health with intuitive dashboards that reveal every stat of pipeline and data flow. Bring real-time visibility into your ELT with Alerts and Activity Logs. 
  • Stay in Total Control: When automation isn’t enough, Hevo offers flexibility – data ingestion modes, ingestion, and load frequency, JSON parsing, destination workbench, custom schema management, and much more – for you to have total control.    
  • Auto-Schema Management: Correcting improper schema after the data is loaded into your warehouse is challenging. Hevo automatically maps the source schema with the destination warehouse so that you don’t face the pain of schema errors.
  • 24×7 Customer Support: With Hevo, you get more than just a platform, you get a partner for your pipelines. Discover peace with round-the-clock “Live Chat” within the platform. What’s more, you get 24×7 support even during the 14-day full-feature free trial.
  • Transparent Pricing: Say goodbye to complex and hidden pricing models. Hevo’s Transparent Pricing brings complete visibility to your ELT spend. Choose a plan based on your business needs. Stay in control with spend alerts and configurable credit limits for unforeseen spikes in the data flow. 
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What can you achieve by migrating data from Apple Search Ads to BigQuery?

Here’s a little something for the data analyst on your team. We’ve mentioned a few core insights you could get by replicating data from Apple Search Ads to BigQuery, does your use case makes the list?

  • Know your customer: Get a unified view of your customer journey by combing data from all your channels and user touchpoints. Easily visualize each stage of your marketing & sales funnel and quickly derive actionable insights.   
  • Supercharge your ROAS: Find your high ROAS creatives on which you should be spending more money, thereby boosting your conversions. Identify the different creatives and copy that work best for your customer segment. 
  • Analyze Customer LTV: Get a competitive edge with near-real-time data from all your marketing channels and understand how different targeting, creatives, or products impact your customer LTV.  

Summing It All Together

Just by importing & exporting CSV files for your marketing team’s rare Apple Search Ads data replication requests, you can easily hit it right out of the ballpark. But what if these data updates need to happen every few hours? Your marketers are always on the hunt to boost their ROI by monitoring real-time campaign performance. Don’t worry! You won’t need to bite the bullet and spend months developing & maintaining custom data pipelines. You can make all hassle go away in minutes by taking a ride with Hevo’s 150+ plug-and-play integrations

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Saving countless hours of manual data cleaning & standardizing, Hevo’s pre-load data transformations get it done in minutes via a simple drag n drop interface or your custom python scripts. No need to go to your data warehouse for post-load transformations. You can simply run complex SQL transformations from the comfort of Hevo’s interface and get your data in the final analysis-ready form. 

Want to take Hevo for a spin? Sign Up for a 14-day free trial and simplify your Apple Search Ads to BigQuery data integration process. Check out the pricing details to understand which plan fulfills all your business needs.

Share your experience of connecting Apple Search Ads to BigQuery! Let us know in the comments section below!

Nidhi B.
Freelance Technical Content Writer, Hevo Data

Nidhi is passionate about carrying out in-depth research on topics related to data integration and analysis, and loves to see the impact by offering informative content to assist individuals in delving deeper into these intricate subjects.

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