One of the most overlooked features of Google Analytics 4 is Data Import. Others may have an idea about it and thought that it could be just a tool that allows you to import data, and that’s it. We’d say that’s pretty much it - A feature in GA4 that allows you to include additional information from external sources, providing a more complete view of user behavior. However, in this post, we'll explore how to make the most of GA4 Data Import without getting too technical. And our goal here is to share with you this information on how you can properly leverage on Data Import into your analytics strategy and offer valuable insights to enhance your online performance. Here’s what we’ll cover:
What is GA4 Data Import?
Simply put, GA4 data import is a feature in Google Analytics 4 (GA4) that lets you add data from other sources to your website or app analytics. This helps you see a fuller picture of how users interact with your business, both online and offline.
What data types can you import in GA4?
Here are the data types that you can import in GA4:
Customer data (CRM data): This refers to information about your customers that you store in your Customer Relationship Management (CRM) system. This data might include:
- Contact information (name, email, phone number)
- Acquisition source (how they learned about your business)
- Purchase history
- Customer support interactions
- Loyalty program information (if applicable)
Offline sales data: This includes sales data that happens outside of your website or app, such as in-store purchases or phone orders. What is the best example of this is Salesforce offline data.
Importing offline sales data into GA4 allows you to see the complete customer journey, including both online and offline interactions. This can help you understand the effectiveness of your marketing campaigns across all channels and identify any gaps between online and offline customer behavior.
Cost data (from non-Google advertising platforms): This refers to data about the cost of your advertising campaigns on platforms other than Google Ads, like Facebook Ads, Twitter Ads, or LinkedIn Ads. This data might include:
- Campaign name
- Ad platform
- Clicks
- Impressions
- Cost per click (CPC)
Importing cost data from non-Google platforms allows you to see the return on investment (ROI) for all your advertising efforts in one place. This can help you optimize your marketing budget and allocate resources more effectively.
Product data (e.g., SKUs, brands): This includes detailed information about the products you sell on your website or app. This data might include:
- Stock Keeping Unit (SKU)
- Product name
- Brand
- Category
- Price
- Color
- Size
User metadata (e.g., loyalty rating, lifetime value): This refers to additional information about your users that you might not collect through website or app tracking alone. This data might include:
- Loyalty program tier (if applicable)
- Predicted lifetime value (LTV)
- Customer segmentation (e.g., high-value customer)
How to import data in GA4
- In Admin, under Data collection and modification, click Data import.
- Create a new data source or select an existing data source. (See the following sections.)
Create a new data source
1) Click Create data source.
2)Select the data type:
- Cost data (query-time import only)
- Item data (reporting/query-time import)
- User data by User ID (collection/processing-time import)
- User data by Client ID (collection/processing-time import)
- Offline events data (collection/processing-time import)
3) Click Review terms if prompted. This prompt is displayed if you are importing device or user data.
4) Do one of the following:
5) Select Manual CSV upload, select the CSV file on your computer, then click Open.
6) Or
- Select SFTP.
- SFTP server user name: Enter your user name for your SFTP server.
- SFTP server URL: Enter the URL for your SFTP server.
- Frequency: Choose the upload frequency (Daily, Weekly, Monthly).
- Start time: Select the hour when you want the upload to start.
- After the data source is created, the public key for your SFTP server will be visible in the interface where you're creating the data source, and it will be available in the data-source details (see below).
7) Click Next to proceed to the mapping stage.
8) Select the Analytics fields and imported fields you want to map to one another. Edit the field names as necessary.
Click Import.
What is new with GA4 Data import?
The big news with GA4 data import is the addition of Salesforce as a direct data source! This means you can now import data from Salesforce directly into GA4 as offline event data.
Here are the specifics of this update:
- Previously, you would need to export data from Salesforce and then upload it as a CSV file. Now, you can connect GA4 to Salesforce and directly import the data.
- You can set up automated data imports to happen daily or hourly, ensuring your data is always up-to-date in GA4.
- You can choose which Salesforce milestones and attributes you want to import. Milestones will be imported as GA4 events, and attributes can be brought in as GA4 dimensions.
This update streamlines the process of bringing your Salesforce data into GA4 for a more unified view of your customer journey.
The latest update, as of April 25, 2024 GA4 announced an improvement on user data import and GA4 audiences. So when data is imported through user data import, and linked using either user ID or client ID, it becomes instantly usable as criteria to determine if a user qualifies for an existing GA4 audience. This happens without needing any additional action from the user. In other words, users who are imported into Analytics and meet the criteria for an existing GA4 audience are promptly included in that audience.
Best practices when performing Data import in GA4
Data Preparation:
- Ensure your data is clean and accurate before import. Inaccurate data can lead to misleading insights in your GA4 reports. Validate your data for errors and inconsistencies before uploading.
- Prepare your data file according to GA4's specifications. This typically involves using a CSV format with specific headers for each data field. Double-check the required format for your chosen data type.
- Map the data fields in your import file to the corresponding fields in GA4. This ensures your data is imported correctly and populates the relevant dimensions and metrics within GA4.
Import Process:
- If you're new to data import, start with a small dataset to test the process and ensure everything works as expected before importing large files.
- Consider scheduling regular imports for ongoing data sources like CRM data. This ensures your GA4 data stays up-to-date.
- Keep an eye on the import process for any errors or warnings. Address any issues promptly to avoid data inconsistencies.
Data Management:
- By default, GA4 user event data is retained for only 14 months. Here’s more information about data retention.
- Exclude internal traffic (your own visits) from your GA4 data to ensure accurate reporting. You can define internal traffic sources within the GA4 settings. Check out our blog post about internal traffic exclusion.
- If your data includes unique fields not natively supported by GA4, consider creating custom dimensions or metrics to capture and analyze that data.
What are the limitations of GA4 Data import?
While GA4 data import offers flexibility in incorporating data from external sources, there are some limitations to keep in mind:
Data Source Size
Each individual data source you import cannot exceed 1 GB in size. This might be a limitation if you're working with very large datasets from external sources.
Total Storage
There's a limit on the total amount of data you can import across all your data sources. The limit depends on your Google Analytics account type:
- Standard properties: 10 GB total storage
- 360 properties: 1 TB total storage
Daily Uploads
There's a cap on the number of data imports you can perform per day for a property. The exact limit is 120 uploads per property per day.
Data Refresh
After importing data, it can take up to 24 hours for it to be reflected in your GA4 reports. This means there might be a delay in seeing the impact of your imported data on your analysis.
Limited Data Types
Not all data types from external sources can be imported into GA4. For example, you cannot import custom variables, time-based dimensions (hour, minute, etc.), or geo-dimensions (specific city, country code, etc.) directly.
Cost Data
There's a separate 90 MB per date limit for cost data imports. This means you cannot upload more than 90 MB of cost data for a specific date within a single data set.
Frequently Asked Questions About GA4 Data Import
What format should my data be in for import?
GA4 supports data imports in CSV, TSV, and JSON formats. Each format has specific requirements for how data is structured and separated.
Can I import custom dimensions or metrics?
No, you cannot directly import custom dimensions or metrics from external sources. However, you can potentially map your data to existing GA4 dimensions and metrics or create custom dimensions based on imported data after it's uploaded.
What about privacy considerations for user data?
It's crucial to comply with all relevant privacy regulations (like GDPR, CCPA) when importing user data. Make sure that you are not importing PII data. For more information read our blog post regarding GA4 Understanding Personally Identifiable Information (PII).
I'm encountering errors during data import. What should I do?
GA4 should provide specific error messages during the upload process. These messages will indicate formatting issues or data inconsistencies in your import file.
- Carefully review the error messages and identify the problematic data points.
- Fix the errors in your source data file (e.g., correcting typos, adjusting data format).
- Re-upload the data file after making the necessary corrections.
Can I delete imported data after it's uploaded?
Yes, you can delete imported data sets from within GA4. However, this will not affect the data that has already been processed and reflected in your reports.
Final Word
In summary, Data Import might seem like a basic tool in Google Analytics 4, but it's actually much more than that. It's like a door that opens up to include extra information from outside sources, helping you understand how users behave even better. This enriches your existing data, making it stronger and enabling you to better understand your audience, clients, leads, and more. Ultimately, it empowers you to make smarter decisions and devise more effective strategies.
Thank you for reading!
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