Interpret your analysis, part 2: Advanced features

This article explores some advanced features available as you interpret your event segmentation analyses. For a primer on the basics, refer to part one.

Rolling averages

Rolling averages display the unweighted mean, which smooths out a chart. This option helps when you have cyclical users—for example, people that use your product during the week, but not on weekends.

To apply a rolling average to your chart, click Advanced and select Rolling Average from the drop-down list.

This chart displays the daily event totals without a rolling average. Notice the sharp peaks and valleys in the line.

When you add a rolling average of seven days, those fluctuations disappear. Each data point now represents an average of the previous seven days of data.

Each day's data is included in that day's data point:

• For the current day, Amplitude uses a dotted line to show that data collection for today isn't finished. Use an Offset in the date picker to exclude the current day from your analysis.
• With a seven-day rolling average, the first six days of your selected time period fetch data from outside the selected time period. For example, in an analysis covering the month of February, the result for February 6 averages data over January 31 to February 6.

Rolling windows

A rolling window is another method to smooth your data. It displays the aggregate last N days of information in a single data point. Rolling windows help when you want to view aggregated metrics—such as your 7-day active user count—on a daily basis.

This option differs from the rolling average because a rolling window doesn't average your data over the selected time frame. Instead, it sums the data.

To apply a rolling window to your chart, click Advanced and select Rolling Window from the drop-down list.

This chart displays event totals without a rolling window.

Below, the event totals display with a rolling window of seven days. Each day represents a sum of the previous seven days of events.

As with a rolling average, when you use a seven-day rolling window, the first six days of your selected time frame fetch data from outside the selected time period. For example, in an analysis covering the month of February, the result for February 6 averages data over January 31 to February 6.

Cohort filtering

When you select a rolling window, specify whether aggregation happens before or after Amplitude filters results according to the cohort or cohorts you select.

• before cohort filter: Amplitude aggregates the event data, then applies the cohort and filters the results.
• after cohort filter: Amplitude applies the cohort and filters the results, then aggregates the resulting event data.

Cumulative sum

Cumulative sum displays a running total of events in a single data point. For example, to show a running total of revenue generated by purchase events, use cumulative sum.

To apply a cumulative sum to your chart, click Advanced and select Cumulative from the drop-down list.

This chart shows a running total of purchases that use the Complete Purchase event. The April 19 data point represents a sum of purchases on all the preceding days of the selected time frame. Here, that means April 5 to April 19.

Cumulative sum with uniques generates a count of unique users for each data point, with duplicates removed.

For example:

• On April 5, User A triggered Complete Purchase.
• On April 11, User A and User B triggered Complete Purchase.
• On April 19, User C and User D triggered Complete Purchase.

On the data point for April 19, Amplitude returns a total count of four because four unique users fired this event from April 5 to April 19.

Real-time segmentation

View segmentation data in real time. Note these caveats:

• You can segment only one day of data for real-time.
• Amplitude rounds event times down.
• Amplitude caches charts every five minutes for all users.

Period-over-period comparison

Use period-over-period comparison to compare the results of your current time range against previous time periods. The comparison control appears in the top-right of the chart, near the date picker.

To start a comparison, click Previous Period vs. above the chart. The Compare with panel opens.

Choose a comparison period

Select from the following preset comparison options:

Each preset displays the calculated date range so you can verify the comparison window.

Custom comparison periods

For more control, use the custom period options:

These options let you compare against specific dates, such as a product launch or campaign start.

Both custom options support a Rolling toggle. When you enable Rolling, the comparison period shifts forward automatically as time passes, keeping the same offset from the current date range. When Rolling is off, the comparison period stays fixed to the exact dates you chose, regardless of when you view the chart.

Compare multiple periods

You can compare up to two previous periods at the same time. Click Add Comparison in the Compare with panel to add a second comparison period. Each comparison period can use a different preset or custom date range.

To remove a comparison, click the X next to the period you want to remove.

View comparison results

Toggle between display modes in the Compare with panel:

• Absolute values: displays the raw metric values for each period.
• Percentage change: displays the percentage difference between the current period and each comparison period.

Period-over-period for custom formulas

Use period-over-period comparison with the custom formula metric. For example, compare your current rolling average with that of the previous month.