The Lifetime Value report lets you understand how valuable different users are to your business based on lifetime performance across multiple sessions. For example, you can see lifetime value for users you acquired through email or paid search. With that information in hand, you can determine a profitable allocation of marketing resources to the acquisition of those users.
You can also compare the lifetime values of users acquired through different methods. For example, you can compare users acquired through organic search and users acquired through social, or compare social to email, to see which method brings the higher-value users.In this article:
See Lifetime Value data
To open the Lifetime Value report:
Lifetime Value data is available in all Analytics accounts. No changes to the tracking code are necessary.
There are two time elements in the Lifetime Value report.
Acquisition date range: Set this date range to identify the date range during which you acquired users. For example, you might want to examine data for users who were acquired while you were running a single-day campaign on Black Friday, or a week-long campaign from December 18 to December 24. This setting establishes the cohort that you’ll examine in the report.
X-axis in the graph: Lifetime value is currently a maximum of 90 days. The X-axis of the graph is divided into increments (Day, Week, Month) of that 90-day period, starting with the date of acquisition, which can be any time during the Acquisition Date Range. The graph illustrates how cumulative metric values change over the user lifetime.
How metrics are calculated
This report presents the data as the cumulative average value per user per the time increment you are using (day, week, month). For example, if you are evaluating Sessions per User on a daily basis, then the report shows you one value per day that represents the average number of sessions per user.
Lifetime value is calculated using the cumulative sum of the metric value divided by the total number of users acquired during the acquisition date range. For example, if you acquired 100 users during the acquisition date range, then Sessions Per User is calculated as follows:
|Header||Day 0||Day 1||Day 2|
|Cumulative sessions per day||100||200||300|
|Sessions Per User||100 sessions /100 users =
1 session per user
|200 sessions /100 users =
2 sessions per user
|300 sessions /100 users =
3 sessions per user
You can examine conversions (transactions, goal completions), revenue, and behavior (sessions, session duration, app views).
Use the Metric menus to select which metrics you want to compare in the report.
The following metrics are available in the report:
- Appviews Per User (LTV)
- Goal Completions Per User (LTV)
- Revenue Per User (LTV)
- Session Duration Per User (LTV)
- Sessions Per User (LTV)
- Transactions Per User (LTV)
Understanding metrics in the graphs and tables
The graph illustrates the lifetime value per user for the metrics over a period of 90 days, in increments of days, weeks, or months. For example, if you’re working with the App Views per User (LTV) metric, during Week 1, the average number of views might be 16; during Week 3, it might be 22; and by Week 10, it might reach 35.
Metrics in the table are distributed by the dimension you choose (Acquisition Channel in the example below).
The table includes the number of Users you acquired during the Acquisition Date Range, along with two additional aspects of the metric you selected for the report, for example:
- Appviews per User (LTV): Average Appviews per user over lifetime
- Appviews (LTV): Total Appviews for all users over lifetime
Use the Dimensions menu to select the context in which you want to examine your metric values.
For example, if you’re looking at Sessions Per User (LTV), you might want to know which channel delivered the highest number of sessions per user.
(This report uses Analytics’ default channel definitions, and associates users with their channels of acquisition.)
If you’re looking at Revenue Per User (LTV), you might want to understand which medium is responsible for acquiring users with the highest average revenue.