What Metric-Dimension Combination Is Not Valid: Exploring The Common Mistakes In Google Analytics

Introduction

If you are using Google Analytics to measure your website’s performance, you must be aware of the importance of choosing the right metric-dimension combination. Google Analytics offers a wide range of metrics and dimensions, and choosing the wrong combination can result in inaccurate data and misleading insights. In this article, we will explore the most common mistakes that website owners make when selecting metric-dimension combinations and how to avoid them.

What are Metrics and Dimensions in Google Analytics?

Before we delve into the common mistakes, let’s first define what metrics and dimensions are in Google Analytics. Metrics are quantitative measurements that indicate the performance of your website. Some examples of metrics are sessions, pageviews, bounce rate, and conversion rate. Dimensions, on the other hand, are qualitative attributes of your website’s traffic. Some examples of dimensions are source/medium, device category, location, and page title.

Common Mistakes in Metric-Dimension Combinations

Mistake #1: Using Incompatible Metrics and Dimensions

One of the most common mistakes website owners make is using incompatible metrics and dimensions. For example, using the “time on page” metric with the “country” dimension is not a valid combination because time on page is a session-level metric while country is a user-level dimension. To avoid this mistake, make sure to check the compatibility of your chosen metric and dimension before using them together.

Mistake #2: Using Too Many Dimensions

Another mistake is using too many dimensions in a single report. Google Analytics has a limit of 7 dimensions per report, and exceeding this limit can result in incomplete or inaccurate data. To avoid this mistake, choose only the most relevant dimensions for your report and use multiple reports if necessary.

Mistake #3: Using the Wrong Scope

Metrics and dimensions in Google Analytics have different scopes, which determine the level at which they are calculated. For example, the “sessions” metric is calculated at the session level, while the “users” metric is calculated at the user level. Using the wrong scope can result in incorrect data. To avoid this mistake, make sure to choose the right scope for your metric and dimension.

Mistake #4: Using Aggregations with Non-Aggregatable Metrics

Some metrics in Google Analytics cannot be aggregated, such as bounce rate and exit rate. Using aggregations with non-aggregatable metrics can result in inaccurate data. To avoid this mistake, use non-aggregatable metrics in their raw form and avoid aggregations.

Mistake #5: Using Metrics and Dimensions Without Context

Metrics and dimensions in Google Analytics are meaningless without context. For example, a bounce rate of 50% may seem high, but it could be normal for a blog post with a long reading time. To avoid this mistake, always provide context for your metrics and dimensions.

Mistake #6: Using Custom Metrics and Dimensions Incorrectly

Google Analytics allows you to create custom metrics and dimensions, but using them incorrectly can result in inaccurate data. For example, if you create a custom metric for “time on page,” make sure to use it only with compatible dimensions and at the right scope.

Conclusion

Choosing the right metric-dimension combination is crucial for getting accurate insights from Google Analytics. By avoiding the common mistakes we’ve discussed in this article, you can ensure that your data is reliable and actionable. Remember to always check the compatibility of your chosen metric and dimension, use only the most relevant dimensions for your report, choose the right scope for your metric and dimension, avoid aggregations with non-aggregatable metrics, provide context for your metrics and dimensions, and use custom metrics and dimensions correctly.