What is a “secondary dimension” in Google Analytics?

In Google Analytics, a secondary dimension is an additional layer of information you can add to your reports to analyze your website or app data with more detail. It acts like a filter within a filter, providing a breakdown of the data you’re already looking at.

Here’s a breakdown of what it is and how it works:

• Primary dimension: This is the main category you’re analyzing your data by, like “City,” “Country,” or “Landing Page.“
• Secondary dimension: This adds another layer of detail to your primary dimension. For example, if your primary dimension is “City,” you could add “Source” as a secondary dimension to see which traffic sources are sending the most users to each city.

Benefits of using Secondary Dimensions

Using secondary dimensions in Google Analytics offers several valuable benefits for analyzing your website or app data

1. Deeper Insights

• Uncover hidden trends: By slicing your data into smaller segments, you can identify patterns and trends that might not be apparent when looking at the overall picture. For example, analyzing user engagement by landing page and device type can reveal which pages perform better on mobile compared to desktop.
• Identify correlations: Explore relationships between different data points. For instance, analyzing user acquisition by source (Organic, Paid) and city can show if specific traffic sources are more effective in certain locations.

2. Efficient Data Segmentation

• Minimize report clutter: Instead of generating multiple reports for each combination of dimensions, you can see everything in a single report, streamlining your analysis process.
• Focus analysis: Narrow down your focus to specific subsets of data. For example, you can analyze user behavior on specific product pages for users from a particular demographic to understand their specific needs and preferences.

3. Tailored Strategies

• Personalize your marketing: Understand how different user segments interact with your website, such as new vs. returning visitors, mobile users vs. desktop users, or users from different regions. This allows you to tailor your marketing messaging and content to cater to their unique needs and preferences.
• Optimize website experience: Identify areas for improvement based on user behavior within specific segments. This can inform content strategy, website design, and user experience improvements for different segments of your audience.

4. Improved Decision Making

• Data-driven decisions: With deeper insights and understanding of your audience, you can make informed decisions about your marketing campaigns, website content, and overall user experience.
• Identify opportunities: Uncover hidden potential within your target audience or website performance, leading to opportunities for growth and improvement.

Using secondary dimensions effectively helps you paint a more complete picture of your website or app’s performance and user behavior, ultimately allowing you to make data-driven decisions that benefit your business goals.

Example Scenario: Understanding user engagement for different product categories across devices

Here’s an example of how using secondary dimensions in Google Analytics can reveal valuable insights:

• Primary Dimension: Product Category (e.g., clothing, electronics, books)
• Secondary Dimension: Device Type (e.g., desktop, mobile, tablet)
• Metric: Average Session Duration

Analysis

By adding “Device Type” as a secondary dimension to “Product Category,” you can see the average session duration for different product categories on various devices. This allows you to:

• Identify which product categories perform best on each device: For example, you might find that users browse clothing for longer on their mobile phones while spending more time researching electronics on desktops.
• Optimize user experience: Knowing which devices users typically use for different categories can inform website design and content optimization for each device type. This can involve tailoring product information, images, and checkout processes for a smooth experience on specific devices.
• Refine marketing strategies: Knowing which device types are most effective for specific categories can help you focus your marketing efforts accordingly. For example, you might prioritize mobile ads for clothing and run display ads on desktops for electronics.

These insights can further be applied to:

• Develop targeted content and promotions: Create content and promotions specific to device type and user behaviour.
• Improve mobile app functionality: Focus on features and functionalities that cater to user behavior on mobile devices.
• Optimize product page layouts: Adjust page layouts to be user-friendly and visually appealing on different devices.

Conclusion

Overall, using secondary dimensions helps you understand user behavior within specific segments, leading to data-driven decisions that improve user engagement and ultimately drive business success.