When it comes to your online presence, your interpretation of your data will determine the ultimate outcome. Whether you’re running an eCommerce business, or a personal blog, tracking and analyzing data is crucial to understanding how your audience interacts with your website. Thanks to Google Analytics 4’s Analytics Intelligence, you can use powerful data visualization and reporting features to gain valuable insights into your website’s traffic and user behavior.
What Are Anomalies in GA 4?
In Google Analytics 4, anomalies are data points that deviate from the expected user behavior pattern. Different factors can cause this, such as changes in user behavior, technical issues with tracking, or any external events such as holidays or other significant events.
Various anomalies can occur in Google Analytics 4 based on the measured metric type and timestamp. GA 4 uses a statistical technique known as the Bayesian state-space time series model on a set of YOUR data recorded over time. As the new data appears, it compares all of these values against your previous ones to see if any values lie outside the expected values.
Identifying these anomalies is essential because they indicate problems or opportunities for optimization. An increase in traffic during a specific period of time can indicate the effectiveness of a marketing campaign, while a sudden decrease can indicate technical issues with your website, among other problems. By addressing these anomalies, website owners can improve the user experience and optimize conversions.
Anomaly Detection Methods in Google Analytics 4
Before we start analyzing data, it’s essential that you have a business account in place. Automatic detection is possible with the demo account, but creating custom insights can not be done with a demo account.
Automatic Anomaly Detection Using GA 4 Insights
- Sign in to your GA 4 account.
- Select the Google Merchandise Store from the Demo Account.
- Go to Insights on the home page.
- Here, you can see both time-series and segment-based anomaly detection.
- Click on any insights to observe them and see what Google says.
- Click ‘Suggested Questions’ to use the ‘Ask Analytics Intelligence’ function.
- Google’s AI will be able to comprehensively understand your data and answer questions like “How many users from organic search in the last 30 days?”
- Feel free to type your own question in the search bar.
Time-series anomalies are shown using a time-series graph, while segment-based anomalies use a bar chart. You can see that “Conversions for users who triggered level_complete were 814% more than predicted.” The reason for this spike in your case could be due to a campaign, and considering its effectiveness, you might want to act accordingly.
All of these insights have a reason, and if you can analyze the data to determine the ‘cause,’ you will be able to invest in your marketing strategies accordingly to scale up efficiently.
Setting Up Custom Insights
If specific metrics are irrelevant to your analytics, you can create custom insights in Google Analytics 4 with 50 custom insight cards per property. However, you will need edit or collaborate permissions to create, edit, and share insights.
Using Suggested Custom Insights
- Sign into your GA 4 account, and select your desired website.
- Click on ‘Reports snapshot’ in the reporting menu.
- Head to ‘View All Insights.’
- Here, you can see the ‘Create’ option.
- Here, you can create custom insights, use ‘Suggested custom insight,’ or just ‘Start from scratch.’
- For suggested insights, simply click on ‘Review and create.’
Creating from Scratch
- Considering you’re looking to start from scratch, you can set your own evaluation frequency, segment, metric, and conditions.
- Choose a time period by which you’d like to evaluate, this can be either daily, hourly, weekly, or monthly, depending on how you’d like to analyze.
- Click ‘CHange’ under the segment option to monitor a metric for a specific segment.
- You can build the segment by adding up to 5 dimensions from the drop-down box.
- Select a metric value to monitor.
- Pick a name for your insight which will be shown in the management panel and displayed in your notification alerts.
- Hit ‘Create’ once you’re done to create your custom insight.
Note: You can manage these insights by clicking on ‘Manage’ on the insights page at ‘Reports snapshot.’ Here, you can modify or delete any previously defined parameters using the three vertical dots next to the insight.
Best Practices for Using Anomaly Detection in Google Analytics 4
Define Your Goals
Before you set up your anomaly detection in GA 4, defining your KPIs and business goals is essential. These will help you identify the metrics most important for your business and ensure that you monitor the right data points for the best results.
Set Up Automated Alerts
Using GA 4 and the methods we described above, you can set up automated alerts for anomalies, which will help you quickly identify problems. These alerts can be set up for specific metrics with thresholds.
Use Multiple Detection Methods
You can use a variety of different detection methods. Set up various custom insights based on different metrics. Using multiple detection methods can help you identify a wider range of anomalies and improve the accuracy of your detections.
Understand Your Data
Congratulations, you have successfully extracted the data from GA 4. Now, the important part is analyzing the data to understand the changes in user behavior, technical issues, and any underlying causes that may be affecting your bottom line.
Anomaly detection is an ongoing process, and to achieve the best results, it’s important to monitor your data regularly and respond to any oddities as quickly as possible. Set up regular check-ins to review your data and adjust your strategy as needed.
Data provided by GA 4 are valuable insights that allow you to optimize your online presence continuously. Use these insights to make data-driven decisions that improve your user experience and drive positive results.
You Better Adapt Quick
Digital branding folds itself into more complexity as the days pass. Understanding and utilizing new tools with as much expertise as possible becomes paramount to achieving the best results. By implementing anomaly detection, you can identify opportunities for your business. Using machine learning, you can identify outliers that can save you a lot of time. You can customize the detection to fit your business goals and identify traffic patterns, engagement patterns, and more!