Facebook, Instagram, and Twitter are widely recognized as three of the most dominant market giants in digital advertising. TikTok is already competing with these well-established businesses despite the fact that it has been available to consumers for only a few short years. The social network known as TikTok is expanding at a rapid rate, and naturally, the size of its audience makes it appealing to advertisers.

By exporting data from TikTok Ads, marketers have the ability to evaluate the efficacy of advertising on TikTok in comparison to the efficacy of advertising on other channels. This allows them to easily determine which campaigns bring in more revenue and how to distribute their advertising budget.

In this article, you will learn 2 methods to connect TikTok Ads to BigQuery and the key features of both.

What are TikTok Ads?

TikTok Ads provides a platform that is both powerful and user-friendly, and it helps businesses and brands advertise their products and services to millions of users all over the world. This platform helps with targeting, ad creation, insight reports, and ad management tools.

Even though TikTok Ads aren’t as widely used as Facebook or Instagram ads (yet! ), they still present an amazing opportunity for brands that are looking to expand their customer base. Because not a lot of companies and brands have yet recognized the potential of TikTok Ads, now is the ideal time to begin using them.

TikTok Ads provides various one-of-a-kind tools that are designed to assist brands and businesses in reaching their full potential, regardless of the size of their budget or the length of their campaign (for example, 10 days).

TikTok’s advertising platform tools, work similarly to that of Instagram’s Ad Manager. They automate the process of creating, delivering, and optimizing your advertisements.

There are currently two budgeting options available with TikTok Ads: daily and lifetime. You have the ability to make changes to your budget at any time during the course of your campaign if you go with either of these two options.

Key Features of TikTok Ads

  • Superior User Engagement: The high level of user engagement is really what sets TikTok apart from its competitors, despite the fact that many people highlight the platform’s rapidly expanding user base. According to data provided by TikTok as of April 2021, the typical amount of time spent by users on the platform is 87 minutes per day. That is an enormous amount of time that can be utilized by various brands.
  • Ecommerce Capabilities: Although TikTok is best known for its solutions to increase awareness and engagement, the company is determined to offer marketers a suite of full-funnel products and services. TikTok and Shopify initially launched their partnership toward the end of the year previously, and it has since expanded to 15 countries. Shopify merchants can now access the TikTok For Business Ads Manager without having to navigate away from the Shopify dashboard thanks to this newly added functionality.
  • Scalable Creative Tools: TikTok’s powerful creative tools are integrated into the capability, providing merchants with a scalable way to create engaging ads without the need to invest in additional development resources. This enables TikTok to offer merchants a competitive advantage.
  • Brand Effects: Differentiating your advertisements from the competition is easy when you layer in Brand Effects. This augmented reality feature for video overlays functions like lenses on Snapchat. However, it is purposefully crafted to put the spotlight on components that are unique to the brand. The most obvious uses for this feature are in the Consumer Packaged Goods (CPG), retail, and entertainment industries; however, it is highly adaptable to other verticals as well, such as the automotive and travel industries.

What is Google BigQuery?

Google BigQuery is a Data Warehouse hosted on the Google Cloud Platform that helps enterprises with their analytics activities. This Software as a Service (SaaS) platform is serverless and has outstanding data management, access control, and Machine Learning features (Google BigQuery ML). Google BigQuery excels in analyzing enormous amounts of data and quickly meets your Big Data processing needs with capabilities like exabyte-scale storage and petabyte-scale SQL queries.

Google BigQuery’s columnar storage makes data searching more manageable and effective. On the other hand, the Colossus File System of BigQuery processes queries using the Dremel Query Engine via REST. The storage and processing engines rely on Google’s Jupiter Network to quickly transport data from one location to another.

Key Features of Google BigQuery

  • Fully Managed: An in-house setup is not required since Google BigQuery is a fully managed Data Warehouse. To use Google BigQuery, you only need a web browser to log in to the Google Cloud project. By offering serverless execution, Google BigQuery takes care of complicated setup and maintenance processes, including Server/VM Administration, Server/VM Sizing, Memory Management, etc.
  • Exceptional Performance: Due to the column-based design, Google BigQuery provides several advantages over traditional row-based storage, like higher storage efficiency and quicker ability to scan data. These features minimize slot consumption, querying time, and data use by supporting nested tables for practical data storage and retrieval.
  • Security: Google BigQuery offers Column-level protection, verifies identity and access status, and establishes security policies as all data is encrypted and in transit by default. Since it is a component of the Google Cloud ecosystem, it complies with security standards like HIPAA, FedRAMP, PCI DSS, ISO/IEC, SOC 1, 2, and 3.
  • Partitioning: Google BigQuery’s decoupled Storage and Computation architecture employs column-based segmentation to lower the quantity of data retrieved from discs by slot workers. Once the slot workers have finished reading their data from the disc, Google BigQuery automatically finds the most optimum data sharing method and instantly repartition data using its in-memory shuffle function.

Why Connect TikTok Ads to BigQuery?

It is possible to associate cost data from advertising services with user actions on your website, clicks on links in emails, and purchased orders from the CRM system if you upload the cost data from advertising services to a single data warehouse. You will be able to set up advanced analytics and evaluate the effect of all marketing efforts, both online and offline, on business metrics with the assistance of this.

TikTok Ads Manager and other web analytics systems are able to perform an analysis of the following primary performance metrics related to TikTok advertising: CTR, CPC, CPA, CR, sessions, viewing depth, bounce rate, RPC, and ROAS. This is sufficient for small businesses that have limited access to advertising channels.

If you have many customer touchpoints or offline stores and you want to see the entire customer purchase path, it is worthwhile to think about establishing advanced analytics and creating an automatically updated dashboard with all of the metrics in which you are interested. This will allow you to see the entire customer purchase path.

You will always have up-to-date data available to you, be able to conduct a comprehensive assessment of the effectiveness of your advertising, and be able to make important decisions in a timely manner with TikTok Ads BigQuery Integration.

Explore These Methods to Connect TikTok Ads and BigQuery

TikTok Ads allows marketers to retrieve statistics about their ad account, ads, ad sets, and campaigns running on TikTok. Also, BigQuery is a data warehouse known for ingesting data instantaneously and performing almost real-time analysis. When integrated together, moving data from TikTok Ads to Bigquery could solve some of the biggest data problems for businesses. In this article, we have described two methods to achieve this:

Method 1: Connect TikTok Ads to BigQuery using Hevo

Hevo Data, an Automated Data Pipeline, provides you a hassle-free solution to connect TikTok Ads to BigQuery within minutes with an easy-to-use no-code interface. Hevo is fully managed and completely automates the process of not only loading data from TikTok Ads but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code.


Method 2: Connect TikTok Ads to BigQuery through Google Sheets

This method would be time-consuming and somewhat tedious to implement. Users will have to write custom codes to enable two processes, streaming data from TikTok Ads and ingesting data into BigQuery. This method is suitable for users with a technical background.

Both the methods are explained below.

Methods to Connect TikTok Ads to BigQuery

Many organizations need to load their data from TikTok Ads to BigQuery service to access raw customer data, like shipment types, item checkpoints, etc. Take advantage of Google BigQuery’s capability to efficiently run complex analytical queries across petabytes of data. Connecting TikTok Ads data with BigQuery provides a more comprehensive insight into your customer interaction and company’s performance. 

Furthermore, with the TikTok Ads to BigQuery migration, you can perform effective real-time automated processes, saving you time when working on repetitive tasks. This integration is the ideal value addition for an e-commerce company or business owner who wants to improve operations, increase efficiency, and sync data throughout their workspace.

To connect TikTok Ads to BigQuery, you can use two methods.

These two methods are explained below:

Method 1: Connect TikTok Ads to BigQuery using Hevo

Hevo provides Google Bigquery as a Destination for loading/transferring data from any Source system, which also includes TikTok Ads . You can refer to Hevo’s documentation for Permissions, User Authentication, and Prerequisites for Google BigQuery as a destination here

Configure TikTok Ads as a Source

Carry out the procedures listed below in order to configure TikTok Ads as the Source in your Pipeline for TikTok Ads to BigQuery Integration:

  • Step 1: In the Asset Palette, select the PIPELINES option.
  • Step 2: In the Pipelines List View, select the +CREATE button.
  • Step 3: Choose TikTok Ads from the drop-down menu on the Select Source Type page.
  • Step 4: Click the + ADD TikTok Ads ACCOUNT button on the page that allows you to configure your TikTok Ads account to TikTok Ads to BigQuery Connection.
TikTok Ads to BigQuery: config tiktok
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  • Step 5: Sign in with the TikTok Business account you normally use.
  • Step 6: To give Hevo permission to access the data from your TikTok Ads account, click the Continue button.
  • Step 7: On the page where you configure your TikTok Ads source, enter the following information to connect TikTok Ads to BigQuery:
    • Name of Pipeline: A one-of-a-kind name for the Pipeline, with a maximum of 255 characters.
    • Select Accounts: Choose the TikTok Ads account (or accounts) whose data you want to import into your account. There is support for selecting multiple Ad accounts.
    • Historical Sync Duration: The amount of time over which the historical data must be ingested. Also known as “duration.” Default value: 6 Months.
  • Step 8: Just hit the TEST & CONTINUE button.
  • Step 9: Move on to the next step, which is to configure the data ingestion and set up the Destination.

Configure BigQuery as a Destination

To configure BigQuery as a Destination in TikTok Ads to BigQuery Integration, follow these steps:

  • Step 1: In the Asset Palette, choose DESTINATIONS.
  • Step 2: In the Destinations List View, click + CREATE.
  • Step 3: Select Google BigQuery as the Destination type on the Add Destination page to connect TikTok Ads to BigQuery.
  • Step 4: Select the authentication method for connecting to BigQuery on the Configure your Google BigQuery Account page.
  • Step 5: Perform one of the following:
    • To connect with a Service Account, follow these steps:
      • Attach the Service Account Key file.
    • To join using a User Account, follow these steps:
    • Sign in as a user with BigQuery Admin and Storage Admin permissions.
    • Provide Hevo access to your data by clicking Allow.
  • Step 6:Configure your Google BigQuery Warehouse page with the following information to connect TikTok Ads to BigQuery:
    • Destination Name: Give your Destination a distinctive name.
    • Project ID: The BigQuery instance’s Project ID.
    • Dataset ID: The dataset’s name.
    • GCS Bucket: A cloud storage bucket where files must be staged before being transferred to BigQuery.
    • Sanitize Table/Column Names: Select this option to replace any non-alphanumeric characters and spaces in table and column names with an underscore (_).
    • Populate Loaded Timestamp: Enabling this option adds the __hevo_loaded_at_ column to the Destination Database, indicating the time when the Event was loaded to the Destination.
  • Step 7: To test the connection, click TEST CONNECTION and then SAVE DESTINATION to finish the setup.

Method 2: Connect TikTok Ads to BigQuery through Google Sheets

TikTok Ads data can’t be imported into Google BigQuery because that database doesn’t have a built-in tool to do so. This issue to connect TikTok Ads to BigQuery can be remedied in a number of ways, including the manual uploading of data, the creation of one’s own scripts, or through Google Sheets as a medium:

Transfer Data from TikTok Ads to Google Sheets

To connect TikTok Ads to BigQuery, the first step is to follow this link to the Google Marketplace to download and install the API Connector add-on.

Make a TikTok app and obtain your Auth code and access token from the app’s settings. You can refer to this link for detailed steps. Then transfer TikTok data into Google Sheets to connect TikTok Ads to BigQuery:

Include your full request URL in the field labeled “request URL“, and include your access token in the section of the “Headers” where Key = Access-Token and Value = your token. Doing so will allow you to create a request.

To illustrate, enter a request like this as an example:


In the URL, you will notice a few different kinds of parameters:

  • The “dimensions” parameter gives information about how the data should be grouped (the example above groups by day and ad ID)
  • The “metrics” parameter specifies the fields that you want to be included in the report.
  • The “data level” parameter indicates the degree of granularity that you desire for your data (by account, campaign, adgroup, or ad)
  • The “order field” parameter specifies the field that should be used to order the results.
  • The “page size” parameter displays the number of records to return; for more information regarding this topic, refer to the section of the manual titled “Handle Pagination.”

The documentation includes a comprehensive listing of all the metrics that are currently available (and other parameters).

Transfer Data from Google Sheets to BigQuery

The next step in connecting TikTok Ads to BigQuery is by transfering data to Google BigQuery. Using the data connector that comes with BigQuery, you can quickly and easily import your data from sheets into the database. The following steps demonstrate how to:

  • Step 1: Sign in to your Google Cloud Platform console, and then use the hamburger menu to navigate to the BigQuery user interface.
TikTok Ads to BigQuery: Connecting to GCP
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  • Step 2: Choose the option to Create Data set within BigQuery.
  • Step 3: After the dataset has been created, the following step is to create a BigQuery table that will store the data that is imported from sheets.
  • Step 4: You start by clicking the “Create Table” button. On the tab labelled “Create a Table”, choose “Drive” to connect TikTok Ads to BigQuery.
  • Step 5: Under the source window, select Google Drive as your source and then copy the URL from our Google Sheet into the Select Drive URL tab of the window that appears. As the format, you have the option of choosing either CSV or sheets. Both formats give you the ability to choose the auto-detect schema, and you can also choose the column names and data types that you want to use.
  • Step 6: After giving the table a name, select the option to create a table. Because your sheets are linked to your BigQuery instance, any time you commit changes to your sheet, those changes will immediately be reflected in BigQuery in the TikTok Ads to BigQuery Integration.
  • Step 7: Now that your data is stored in BigQuery, you can perform run SQL queries on the data that you have ingested.

With this, you have successfully connected TikTok Ads to BigQuery.


In this article, you understood the main features of TikTok Ads and Google BigQuery. And learned two methods to integrate TikTok Ads to BigQuery. TikTok Ads is TikTok’s advertising platform for Business Accounts. It enables users to retrieve statistics about their ads, ad accounts, ad groups, and campaigns running on TikTok. Google BigQuery allows you to analyze this data to find meaningful insights to improve user experience.

However, as a Developer, extracting complex data from a diverse set of data sources like Databases, CRMs, Project management Tools, Streaming Services, and Marketing Platforms to your Database can seem to be quite challenging. If you are from non-technical background or are new in the game of data warehouse and analytics, Hevo Data can help!

Visit our Website to Explore Hevo

Hevo Data will automate your data transfer process, hence allowing you to focus on other aspects of your business like Analytics, Customer Management, etc. Hevo provides a wide range of sources – 150+ Data Sources (including 40+ Free Sources) – that connect with over 15+ Destinations. It will provide you with a seamless experience and make your work life much easier.

Want to take Hevo for a spin? Sign Up for a 14-day free trial and experience the feature-rich Hevo suite first hand.

You can also have a look at our unbeatable Hevo pricing that will help you choose the right plan for your business needs!

Sharon Rithika
Content Writer, Hevo Data

Sharon is a data science enthusiast with a hands-on approach to data integration and infrastructure. She leverages her technical background in computer science and her experience as a Marketing Content Analyst at Hevo Data to create informative content that bridges the gap between technical concepts and practical applications. Sharon's passion lies in using data to solve real-world problems and empower others with data literacy.

No-Code Data Pipeline for Google BigQuery