The report shows the top 10,000 users for the sorting criteria you apply.
The User Explorer report lets you isolate and examine individual rather than aggregate user behavior. Individual user behavior is associated with either Client ID or User ID.
Understanding aggregate behavior is important when you’re managing large efforts, for example, campaigns that target large geographic areas. Understanding individual behavior is important when you want to personalize the user experience, or when you need to gain insight into or troubleshoot a specific user experience: for example if you want to analyze the behavior of a user who has an unusually high average order value or see where a user ran into trouble with placing an order.In this article:
To see User-ID data in the report, you need to enable the User-ID feature in your property settings.
Client IDs appear in the report by default for properties that aren’t enabled for User-ID. Learn more about Client ID and User-ID.
See User Explorer data
To open the User Explorer report:
For each client or user ID, you see the following initial data:
- Avg. Session Duration
- Bounce Rate
- Goal Conversion Rate
When you drill into an ID, you see the acquisition date and channel for the user, along with an activity log that details which actions the user took on your site during each session.
By default, you see data for:
- Sessions (LTV): Total sessions over the user's lifetime
- Session Duration (LTV): Average session duration over the user's lifetime
- Revenue (LTV): Total revenue over the user's lifetime
- Transactions (LTV): Total transactions over the user's lifetime
- Goal Completions (LTV) and Goal Value (LTV)
In the left pane, you also see information about:
- Client ID/User ID
- Date Last Seen (when the user last initiated a session)
- Device Category
- Device Platform
- Acquisition Date
Use the Filter by menu to add and remove data types:
You can expand and collapse individual sessions as necessary.
You can expand individual activities to see more detail.
You can create a segment based on any combination of actions that the user engaged in, and then apply the segment to the entire report to analyze the collective behavior of users who took the same actions on your site.
You can apply only user-based segments to this report, and you can apply only one segment at a time.
To create a segment:
- Select the actions you want as the definition for the segment... ...then click Create Segment to open the segment builder.
- Enter a name for the segment, modify the conditions if necessary, choose whether the segment is available in any view or only the current view, and whether you want to apply the segment to the report after you save it.
- Click Save.
When you apply the segment, then you see the first page of the report with a list of IDs that meet those conditions.
Delete user data
You need to have Edit permission to delete the data for individual users.
When you drill into an ID to see data for an individual user, you also have the option to delete the data for that user from the report and from the Analytics system.
To delete the data for an individual user:
At the bottom of the left panel, click Delete User.
Once deletion is requested, data associated with this user identifier will be removed from the Individual User Report within 72 hours, and then deleted from Analytics servers during the next deletion process. Deletion processes are scheduled to occur approximately every two months. If you have exported this data outside of Google Analytics, we recommend you delete it there first.
Reports based on previously aggregated data (for example, user counts in the Audience Overview report) will not be affected.
Learn more about Google Analytics’ data practices and commitment to protecting the confidentiality and security of data.
Respond to specific behavior within a segment
If other reports indicate noteworthy behavior by a particular segment, you can examine specific users within that segment to get a more detailed understanding of what’s going on. For example, if the Audience > Overview report indicates that the 18-24 segment has an unusually high bounce rate or low average session duration compared to other age groups, you can apply that segment to User Explorer, and then take a look at some individual users to see whether they’re bouncing or exiting from the same page or group of pages.
A closer examination of your content might reveal that while the graphics and copy might work well for other age groups, they’re not especially relevant to the 18-24 segment. For example, you might have different age groups buying the same sneaker that has been in production for 100 years, but for wholly different reasons. The 18-24 segment might be responding to what is suddenly a unique design relative to everything else in the market, while their parents are buying nostalgia. In a case like this, you want to support those different segments with site content that is relevant to their motivations for buying.
In a case like this, you can create each segment in Analytics, apply it to the report, and export the IDs for that segment. You can then personalize the site experience based on ID, and direct each group to the relevant content from your ads.
As you develop ongoing relationships with your customers, you also want to develop opportunities to move them to higher levels of conversion. When you understand how your higher level customers purchase, you have the opportunity to lead the next tier of customers along that same path. For example, if you’re a travel agency that books 8, 10, and 15-day tours, it might require only modest effort to encourage customers who routinely purchase 10-day tours to upgrade to 15 days.
The User Explorer report lets you examine how your more valuable users engage with your site, the paths they follow, where they spend their time, which promotions they click. With that information in hand, you can start to personalize the site experience for your middle-tier customers to include the same content and offers your top-tier customers enjoy most.
In this case, create two segments: one of your middle-tier customers and one of your top-tier customers. Apply the top-tier segment to the User Explorer report, and examine the session behavior to see how those users engage with your site--which content they interact with most, which content leads to conversions. Then apply the segment of middle-tier customers and export their IDs. Use that list of IDs to personalize their site experience to more closely match the experience of your top-tier customers.
You can also use that list of IDs you export to build an audience of those middle-tier customers and serve them ads for those higher-end tour packages.
By examining individual session behavior, you can see when your users fall short of completing goals. For example, you can see when they add items to their carts, but don’t go on to complete the transactions, or when they purchase one item but not the complementary item they also viewed (e.g., they purchased the hat but not the scarf).
In these cases, you have perfect opportunities to remarket to those users with specific information related to their experiences. For example, you can remind users of exactly which items they left in their carts; or if a user has purchased a hat, you can follow up with ads for the matching scarf.
You can create segments based on the relevant behavior you identify in the User Explorer report, and then use those segments as the basis for new remarketing audiences.
Personalize customer service
If your business offers high-touch customer service, the User Explorer report let’s you see a detailed history of each user so your CSRs can understand context and offer informed guidance.
For example, if you handle custom property rentals, then a CSR can see which properties users have rented in the past, and which properties they might have been looking at before they called customer service.
If you develop personas as part of your marketing, investigate the behavior of different segments so that those personas are based on how users engage with your site.
For example, you can create segments of male users 18-34 that each fall into different interest categories (e.g., Avid Investors, Sports Fans, Music Lovers), apply those segments to the report, and then look through the session activity to see things like which products they only view versus which ones they purchase, or which goals they tend to complete more often.
When you segment the User Explorer report, you have a list of all IDs associated with that segment that you can export.
- Apply the segment to the report.
- Use the Export menu to choose a format for the exported data.
You can then merge the exported IDs with your offline data.
Unify the online and offline data about your users
You have two options here: