Have you ever noticed discrepancies between the real-time reporting numbers in Ezoic's Big Data Analytics and Google Analytics? This article explains why real-time reporting might appear higher in Big Data Analytics compared to Google Analytics real-time. By understanding the differences in how each platform calculates active users, you'll gain insights into why these variations occur and how Ezoic's approach offers a more accurate reflection of user activity on your site. Let's dive into the specifics behind these real-time metrics and clarify the reasons for the contrasting data.

Google calculates this 'right now' number as the number of unique users that have visited the site in the last 5 minutes. Similar to this, Ezoic calculates that number as any user that has some activity in the last five minutes. For the Ezoic definition, this activity could include scrolling down the page while reading, copy/pasting content, filling out information, etc. 

Unfortunately, the Google definition of 'right now' does not accurately reflect active users on the site. Let's say a user comes to your site and they find a great page with a lot of interesting content and they take about 15 minutes to read the entire post. With the Google definition, they would mark that user as inactive after the first 5 minutes. That user would become active again, once they visit another page. 

However, Ezoic's definition of real-time accounts for this! The system knows that the user is being active because the user is scrolling and copy/pasting the content along the way. Because of this difference, you will likely see a different number in Big Data Analytics real-time reports compared to Google Analytics.

To troubleshoot discrepancies between Ezoic's real-time user data and Google's real-time user data, follow these steps:

1. Understand Definitions: Know the differences between Ezoic's and Google's definitions of 'right now' or real-time users. Google calculates it based on unique users who have visited the site in the last 5 minutes, whereas Ezoic counts any user with activity in the previous 5 minutes, including actions like scrolling, copy/pasting, or filling out forms.
2. Identify the Issue: If you notice a discrepancy in the number of real-time users reported by Ezoic and Google Analytics, the first step is to understand that this is due to the different definitions each system uses.
3. Compare Real-Time Reports: Open the real-time reports in both Ezoic's Big Data Analytics and Google Analytics. Document the number of users each system reports.
4. Check User Activity: Assess if users are engaging in activities that Ezoic counts as 'active' but Google does not. For instance, if users are spending more than 5 minutes on a single page, they might not be counted as 'active' by Google after the initial 5 minutes, while Ezoic will continue to count them as active due to ongoing interactions.
5. Verify Implementation: Ensure that both Ezoic and Google Analytics tracking codes are properly implemented on your site. Faulty or missing tracking codes can lead to inaccurate real-time reporting.
6. Cross-Reference with Other Data: Use other metrics and data points, such as session duration and page views, to further understand user behavior and the discrepancies in real-time data.

By following these steps, you can pinpoint the reasons for discrepancies and ensure your site's analytics accurately reflect user engagement.

To maintain an accurate understanding of real-time user activity and avoid discrepancies between different analytics platforms, consider the following tips:

1. Understand Platform Differences: Be aware that different analytics tools have varying definitions of "active users." For example, Google Analytics may mark a user as inactive after 5 minutes of inactivity, while other platforms might have different criteria.
2. Cross-Reference Analytics Data: Regularly compare data from multiple analytics platforms to identify any significant discrepancies. This can help in understanding how each platform calculates user activity and prevent misunderstandings.
3. Educate Your Team: Ensure that everyone involved with website analytics understands the differences in how user activity is measured. This knowledge can improve the accuracy of your data interpretation and decision-making processes.
4. Use Activity Trackers: Employ tools that can track user behavior more granularly, such as heatmaps or session recordings, to get a better sense of user engagement beyond what is shown in standard analytics reports.
5. Regularly Review Definitions: Periodically review the definitions and methodologies used by your analytics tools to stay updated on any changes or improvements. This will help maintain consistency in data interpretation.
6. Optimize Content for Engagement: Create engaging content that encourages users to interact with your site, thereby reducing the chances of being marked as inactive.

If you need further assistance interpreting Big Data Analytics' real-time reporting, please log in via https://support.ezoic.com/ to make use of our dedicated resources for support. We're here to help!