What is a Slice in Analytics? Definition & Examples

Slice

A slice is a subset of your analytics data filtered by dimensions or criteria, enabling focused, segment-specific insights.

Overview of Slices

• Definition

  A slice is a subset of data defined by filters on dimensions and metrics, enabling focused analysis of specific user groups or events.

  • Example: country slice:

    Select ‘Country = United States’ to view metrics for U.S. users only.

  • Example: device slice:

    Filter ‘Device Category = Mobile’ to analyze mobile traffic.

Key Components of a Slice

• Dimensions

  Qualitative attributes used to categorize data, such as geographic region, device type, or traffic source.

  • Geography:

    E.g., Country, City.

  • Device:

    E.g., Desktop, Mobile, Tablet.

• Metrics

  Quantitative measurements like pageviews, sessions, and conversions analyzed within a slice.

  • Engagement metrics:

    Examples include pageviews and session duration.

  • Conversion metrics:

    Examples include goal completions and transactions.

• Filters

  Logical conditions that restrict data to meet slice criteria, such as including or excluding certain values.

  • Inclusion filters:

    E.g., ‘Device == Mobile’ includes only mobile sessions.

  • Exclusion filters:

    E.g., ‘Country != Canada’ excludes Canadian traffic.

Use Cases for Slices

• Audience segmentation

  Analyze behavior and performance for specific user groups such as new vs. returning visitors.

  • New vs returning:

    Compare metrics for first-time and repeat visitors.

  • Paid vs organic traffic:

    Slice by traffic source to assess channel performance.

• Funnel analysis

  Examine how users progress through conversion steps within a particular segment.

  • Checkout funnel:

    Filter users who visited the product page, added to cart, but did not purchase.

  • Sign-up funnel:

    Analyze where users drop off during the sign-up process.

• Geographic performance

  Compare key metrics across different regions to identify high-value markets.

  • City-level analysis:

    Identify metro areas with the highest engagement.

  • Country comparison:

    Rank countries by revenue per visitor.

Implementing Slices in SaaS Tools

• Plainsignal example

  Insert the PlainSignal script into your HTML to start tracking. Then use the dashboard filters to slice by page path.

  • Tracking code:

    <link rel="preconnect" href="//eu.plainsignal.com/" crossorigin />
    <script defer data-do="yourwebsitedomain.com" data-id="0GQV1xmtzQQ" data-api="//eu.plainsignal.com" src="//cdn.plainsignal.com/PlainSignal-min.js"></script>
    

  • Dashboard slicing:

    In PlainSignal’s UI, apply a ‘Page Path’ filter to view metrics for a specific URL.

• Ga4 example

  Use GA4 Explorations to create slices by adding dimension filters.

  • Enable ga4 tag:

    <script async src="https://www.googletagmanager.com/gtag/js?id=GA_MEASUREMENT_ID"></script>
    <script>
      window.dataLayer = window.dataLayer || [];
      function gtag(){dataLayer.push(arguments);}
      gtag('js', new Date());
      gtag('config', 'GA_MEASUREMENT_ID');
    </script>
    

  • Create an exploration:

    In GA4, navigate to Explore > Blank, add ‘Device category’ as a dimension, and set a filter for ‘mobile’.

Best Practices and Pitfalls

• Define clear objectives

  Start with specific questions or hypotheses to guide which slices you create.

• Limit number of slices

  Avoid over-segmentation; too many slices can lead to small sample sizes and confusing results.

• Ensure data quality

  Validate that dimensions and metrics are accurately collected and filter out bot or internal traffic.

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