It is recommended to select the most appropriate industry category, as this will help ensure that your data can be compared with relevant benchmark tests. This setting may be used by Google for performance evaluation and analysis, so choosing the correct industry category can better reflect the characteristics of your business, providing more valuable data references and insights.

We advise aligning your settings with the time zone that best suits your business. This adjustment only affects the data collected after the adjustment and does not impact existing data. This will help ensure that your data analysis and reports are based on the correct time zone, enabling you to more accurately understand and evaluate activities and trends.

We recommend to select based on the primary source region or the country of your traffic. Ensuring the appropriate currency setting can better represent your data, aiding in precise financial analysis and reporting.

Data retention settings define the duration for which the data are stored on Analytics servers. This encompasses user data, including Cookies, User IDs, and Advertising IDs, as well as event data. Its flexibility remains yours and helps you manage your data more effectively. It's important to note that this setting primarily affects exploration and funnel reports within GA4 properties, allowing you to delve deep into data analysis and generate customized charts and graphs. However, this does not impact standard aggregated reports (including primary and secondary dimensions), which can still be accessed to gather essential insights into overall trends and performance.

Google Signals is a feature that allows you to gain a more comprehensive understanding of user behavior across different devices and activities, including their journey from first contact to final conversion. By linking user data, it provides cross-platform reporting, retargeting audience building, and audience interest analysis to help optimize ad performance and report accuracy. However, it should be noted that devices with iOS 14 or above need to use the User-ID feature for cross-device tracking, and at least 500 people must be observed daily to be included in the report.

This assessment ensures that your GA4 account is correctly integrated with your Google Ads account to enable data sharing and more precise ad performance tracking. This integration provides a deeper understanding of how advertising campaigns impact your website or application and optimize your marketing strategies accordingly.

BigQuery Export allows you to export GA4 data to BigQuery in its entirety, allowing for SQL-like queries to be used to easily retrieve large datasets. The export includes raw events and can also be merged with external data. Additionally, BigQuery Sandbox is a free instance to run, but will incur charges when exceeding limits. During the export, you can use BigQuery ACLs to manage project and dataset permissions. The exported data may differ from the features of the GA4 interface. For more information on restrictions and differences, please refer to the documentation.

Conversion refers to valuable interactions such as shopping and subscription. Setting up and tagging events as conversions helps evaluate participation and advertising conversions. You can create reports, adjust ad bids, analyze conversion paths, and even re-market to users who have not completed conversions.

Through GA4 Audience Building, you can more accurately target your ads, provide personalized marketing based on different audiences, find audiences with high conversion potential, effectively control ad budgets, improve ad performance and returns, and better understand and leverage your target audience.

In GA4, data sampling is a feature used to process exploratory or funnel reports that contain a large amount of data. When viewing such reports, the system may sample some of the data, and data sampling is triggered when the number of events exceeds the resource type quota limit. The limit for free GA4 is up to 10 million events, while Google Analytics 360 is 100 million events.

Your GA4 property may encounter junk traffic or your GA4 measurement ID may be hijacked and executed on other domains. These are two examples of what could lead to unwanted traffic/sessions being collected in your GA4 property. *If your implementation spans multiple (sub)domains, you must interpret the numbers differently. This cannot decide for you which domains to include in this check.

"Engagement rate" is an important metric in GA4 for evaluating the user engagement of a website or an application. If extremely high (>95%) or extremely low (<5%) engagement rates appear on landing pages with sufficient traffic, it may indicate tracking issues. This related check is only applicable to landing pages with at least 100 entries to increase the accuracy of the check.

The value assigned to event parameters must not exceed 100 half-width characters; the "page_title" parameter must not exceed 300 half-width characters; the "page_referrer" parameter must not exceed 420 half-width characters; the "page_location" parameter must not exceed 420 half-width characters. *This only checks if the page_location exceeds 420 half-width characters.

Do your domain name appear in the referral sources list in GA4? This could lead to unreliable data and, in turn, lead to less than optimal marketing decisions. At the same time, actual contributing conversion marketing channels may not be properly attributed.

Direct traffic refers to traffic from known users or from marketing activities that are not correctly tagged. A high proportion of direct traffic may indicate measurement issues. When GA4 classifies traffic as direct, the reason could be the inadequate information to attribute it to any channel, such as organic or paid. This can occur when users type a URL directly into the search bar, as tracking code issues, HTTPS-HTTP issues, or that social media have not passed referral data. Resolving incorrect direct traffic classification requires a comprehensive approach, including data reconstruction, data unification, and effective attribution of all traffic. Resolving these issues helps to get a true picture regarding the performance of marketing activities, linking the spend to revenue, evaluating the marketing value, and in turn increasing return on marketing investment.

The higher the percentage of the "unassigned" channel group, the more difficult it is to analyze and optimize traffic channels. This leads to the inaccuracy of data and brings serious challenges when analyzing data.

GA4 is very strict in channel tracking (default channel grouping). It is strongly recommended that you keep UTM and default channel grouping rules consistent to ensure that your channel measurement is in the right place. If your GA4 properties show 30, 50 or even 100 media, it is highly possible that the ad series tracking setting is incorrect.

Check if the User-ID feature is used to link user behavior across devices. The User-ID feature allows merchants to generate a unique identifier associating with the user. The identifier allows the tracking of their behavior across different platforms and provides more accurate user data to evaluate cross-platform activity effectiveness.

Content optimization is of paramount importance for maximizing website benefits. By establishing appropriate content grouping, you can optimize content more effectively than ever before, while improving navigation paths to achieve even more outstanding results.

Check if the URL in GA4 contains relevant parameters (e.g. q, s, search, query, keyword) when searching within the site. If the URL contains relevant parameters, GA4 can help determine the keywords from users who searches within the site.

Check if GA4 has Enhanced Measurement Events enabled, which can help evaluate how users interact with your content.

In addition to automatically collected events, it is important to further send relevant custom events according to your business needs. It is recommended to prioritize using events identified by GA4 as these events will automatically fill in the default dimensions and metrics, and update standard reports. This will help to more comprehensively evaluate and optimize your data analysis.

Values are usually essential elements to achieve meaningful reporting. If you mark an event as a conversion, it is recommended that you set a value to help you evaluate the conversion value and benefits in more depth. This not only provides a more comprehensive data insight, but also ensures that your analysis and decisions are based on concrete quantitative information.

When setting up GA4, please make sure to check if there are similar but slightly different event names, such as "page_view" and "page_View". Even though these events are functionally the same, the system will still collect them as different events. To ensure data consistency and accuracy, it is recommended that you unify the names of related events to ensure the accuracy and comparability of subsequent analysis and reporting.

Checking the settings related to the number of transactions on website or application ensures that the tracking of transactions is correct. These transactions include in_app_purchase, ecommerce_purchase, purchase, app_store_subscription_renew, app_store_subscription_convert, and refund.

Checking the total sum of the revenue brought by the completion of purchases on your website or application. You can calculate this metric by summing up the revenue from the purchase, in_app_purchase, app_store_subscription_renew and app_store_subscription_convert events and subtracting the total from the refund event. This will help you understand the actual purchase revenue and ensure that your transaction data is complete and accurate.

When using GA4, it is recommended to use a unique transaction ID to avoid double counting the same user's conversions. By creating a unique ID for each transaction, such as an order confirmation number, you can ensure that the same conversion is not recorded twice. This helps maintain the accuracy of conversion data, avoids double counting situations, and ensures that your analysis results are more reliable.

A duplicate transaction event occurs when the same user can reload the order confirmation page multiple times without placing a new order. This can trigger the 'purchase' event again, resulting in the same transaction being pushed to GA4 twice or even more times. The more duplicate transaction events, the less reliable your analytics data will be.

A repeated transaction event occurs when the same user can load the refund completion page multiple times without placing any new orders. This may trigger the "refund" event again, causing the same transaction to be pushed to GA4 twice or even more times. The more repeated transaction events, the less reliable your analytics data will be.

A common issue with e-commerce websites is that users are redirected to a third-party payment platform before making a transaction, resulting an incorrect attribution in GA4 where the original source is covered by the payment website, and order attribution is inaccurate. This audit is intended to list some common but possibly overlooked payment-related traffic.

Shopping behavior analysis offers insight into buyers' purchasing preferences and patterns by collecting data on their behaviors in the retail environment. This data collection can help market, sales, and logistics personnel to predict market trends and provide valuable guidance when making purchasing decisions, as well as designing promotional activities and store layouts.

In most cases, it is expected that the number of funnel events in the session will gradually decrease as the user enters the purchase flow. The purpose of this check is to ensure that this trend is reflected in the purchase journey, so as to ensure that the user's behavior is consistent with expectations and optimize the conversion path. Note: This check is based on the number of conversations, not the number of users, to ensure that the performance of funnel events at different stages of the purchase process is in line with expectations.

Checking if your e-commerce tracking settings capture not only the value of "purchase-related" events, but also other important "non-purchase-related" events. This will help assess the impact of different events in the customer journey, increasing the accuracy and comprehensiveness of value attribution analysis. This also help when considering tracking key non-purchase-related events, such as adding items to the shopping cart, registering members, filling out forms, etc.. These potential events reveal key turning points in the customer journey and optimize marketing strategies and user experiences.

Based on the reference of GA4 events, especially for e-commerce related events, the items parameter should include either item_id or item_name in the analysis to ensure the completeness and reliability of the data. This ensures that the events track and evaluate the performance of your products and provide you with deeper insights. Please make sure to follow this requirement when submitting data to maximize the benefits of the GA4 analytics tool.

Quantity and Revenue are key indicators used to evaluate the performance of a product transaction. Normally, when we observe a situation where Quantity is 0 but Revenue is not 0, this may indicate that there is some abnormality or special situation in the data.