About segments

Isolate and examine subsets of your data.
In this article:

 

Introduction

A segment is a subset of your Analytics data. For example, of your entire set of users, one segment might be users from a particular country or city. Another segment might be users who purchase a particular line of products or who visit a specific part of your site.

Segments let you isolate and analyze those subsets of data so you can examine and respond to the component trends in your business. For example, if you find that users from a particular geographic region are no longer purchasing a line of products in the same volume as they normally have, you can see whether a competing business is offering the same types of products at lower prices. If that turned out to be the case, you could respond by offering a loyalty discount to those users that undercuts your competitor's prices.

You can also use segments as the basis for audiences. For example, you might create a segment of users who visit your menswear pages, and then target just those users (your audience) with a remarketing campaign that is focused on the new items that you are adding to those pages. Learn more

 

Segment types

A segment is made up of one or more non-destructive filters that do not alter the underlying data. Those filters isolate subsets of users, sessions, and hits:

  • Subsets of users: for example, users who have previously purchased; users who added items to their shopping carts, but didn’t complete a purchase
  • Subsets of sessions: for example, all sessions originating from Campaign A; all sessions during which a purchase occurred
  • Subsets of hits: for example, all hits in which revenue was greater than $10

You can include filters for users, sessions, and hits in the same segment.

The Analytics user model illustrates how segments map to the Analytics data hierarchy:

  • Users: People interact with your property (e.g., your website or app)
  • Sessions: Interactions by a single user are grouped into sessions.
  • Hits: Interactions during a session are referred to as hits. Hits include interactions like pageviews, events, and transactions.

A single user can have multiple sessions, and each session can have multiple hits, as illustrated below:

USER
session session session
hit hit hit hit hit hit hit hit hit

 

Using Segments

When you apply a segment and navigate through your reports, the segment remains active until you remove it. You can apply up to four segments at a time, and compare the separate data side by side in your reports.

In addition to analyzing data with segments, you can use them to build audiences.

Analytics includes predefined segments (System Segments) that you can use as provided, or that you can copy and edit to create new custom segments. You can also build your own segments from scratch. In addition, you can import segments from the Analytics Solutions Gallery, a free marketplace where Analytics users share segments and other solutions they’ve developed.

 

Segment definition and scope

You base segments on the dimensions and metrics in your Analytics reports; for example:

  • User Type exactly matches “Returning User”
  • Country/Territory exactly matches “United States”
  • Ecommerce Conversion Rate > "0.2%"

In addition to identifying the dimensions and metrics for individual filters in a segment, you can also set the scope of the data for a filter. There are three different scopes you can use:

  • Hit: Behavior confined to a single action, for example, viewing a page or starting a video.
  • Session: Behavior within a single session; for example, the goals that users completed during a session, or the amount of revenue they generated during a session.
  • User: Behavior across all sessions within the date range you’re using, up to 90 days; for example all the goals users completed or all the revenue they generated (across all sessions) during the date range.

You use the segment builder to define the component filters of a segment.

 

Limits on segments

Segments that you create or import are subject to the following limits:

Total segments

  • 1000 per user for segments that can be applied/edited in any view (Segment availability: I can apply/edit Segment in any view).
  • 100 per user per view for segments that can be applied/edited only by that user in that view (Segment availability: I can apply/edit Segment in this view).
  • 100 per view for segments in that can be applied/edited by all users in that view (Segment availability: Collaborators and I can apply/edit Segment in this view).

For example:

A user can have:

  • 1000 segments that can be applied/edited in any view, plus
  • 100 segments that can be applied/edited only by that user in only View A, plus
  • 100 segments that can be applied/edited only by that user in only View B

A view can have:

  • 100 segments per user that can be applied/edited only by that user in that view
  • 100 segments that can be applied/edited by any user in only that view

You cannot create or import additional segments once you reach these limits.

These limits do not apply to system segments.

Segments applied to reports

You can have up to 4 segments applied to your reports at any one time.

Date ranges

With user-based segments, you can apply a maximum date range of 90 days to your reports. If your date range is already set to more than 90 days, then when you create a user-based segment, Analytics resets the date range to 90 days from the start date.

Segments based on the Date of First Session option are limited to maximum range of 31 days.

Data limits on user-based segments

As stated above, user-based segments have a maximum date range of 90 days. For that 90 days, Analytics reports on only the first 1000 sessions for each user. Session counts beyond 1000 in a 90-day period are usually an indication of non-human traffic.

Multi-Channel Funnels

Do not use segments with Multi-Channel Funnel reports. Use Conversion segments instead.

AdWords cost data

AdWords cost data is not compatible with segments. If you apply a segment to an AdWords report that includes cost data, then the cost data all have zero values.

 

Next steps

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