Lifetime vs. Reporting Period

Sprout uses two separate data collection methodologies, Lifetime and  Reporting Period, to provide two different perspectives on the performance of your content. Each widget within Sprout’s Reports uses a distinct methodology, so you might notice that two of your reports or widgets have different values for the same metrics in the same date range. Lifetime is more representative of the work you did, and Reporting Period is more representative of metrics accrued/your audience’s activity.

Note: You can find which methodology is being used by hovering over any metric in the Sprout app.

Understanding the Differences

Let’s establish some basics first.

Posts: Content sent out to your audience (Tweets, posts, Reels, stories, etc.)

Activities: Instances where your audience interacts with a profile or its posts (likes, comments, views, etc.)

Each methodology attributes activities in a different way.

Reporting Period

The Reporting Period methodology displays information about activities that took place during the selected date range. This is a static data set that is based on the date range you have chosen, and can include any posts published to your profiles.


The Lifetime methodology displays information based on posts published during the selected date range and is a rolling total. This reflects the lifetime performance of the post, and includes all activities that occurred during or outside of the selected date range. All metrics related to the post are attributed to the day the post was published. 



Let's say a post is published on Monday. By the end of the week on Sunday, it has 344 reactions.

When using the Reporting Period methodology for that entire week, we would know the incremental distribution of reactions for each day (86 on Monday, 71 on Tuesday, 38 on Wednesday, 60 on Thursday, 36 on Friday, 25 on Saturday and 28 on Sunday). We can add the daily values together to show 344 reactions for the week.

Now, if we were to measure the same post through the lens of the Lifetime methodology, we’d see the lifetime activity of the post attributed to the day it was posted. In this case, 344 reactions were attributed to Monday, and no reactions were attributed to Tuesday through Sunday.

Additionally, if we narrowed the date range to only Monday and Tuesday of that week, the total number of reactions using the Reporting Period methodology would be 157 (86 on Monday + 71 on Tuesday), but the Lifetime value of 344 reactions would remain the same.

Additional Considerations

  • Lifetime data can be filtered in any way a post can be filtered (Reels only, organic only, video posts only, etc.).
  • If a post from a prior date goes viral, and the date that post was published is not included in the date range of subsequent reports, there is no way to discover that spike in activity using the Lifetime methodology.
  • Lifetime allows for average per-post calculations. 
    • To calculate an average per post metric, Sprout takes the total metric value and divides it by the number of posts. We use Lifetime because there is a distinct subset of posts (posts published during the date range) to use as the denominator. If we used Reporting Period instead, we would need to use the number of any posts your profiles have ever published as the denominator, which does not provide a meaningful average.
  • Lifetime values change as more metrics are gained over time. Re-running reports may yield different numbers.
    • For example, let’s say a report for all January posts is run on February 1st and then rerun again on February 5th. The January posts continue to receive likes on the 2nd, 3rd, 4th and 5th of February, so when the report is rerun on the 5th, the number of likes will be higher than the prior January report. Sprout recommends that customers run reports on the same day each month for more accurate month-over-month comparisons.



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