Through the Portal, you can generate reports on the top movers that are configured through the Event Manager.
In Experience Analytics, a top mover is a stored calculation of deviations in the values of events, dimensions, or ratios. Using the recorded values and counts of the event or dimension, deviations are calculated based on the configured rolling window. The rolling window is defined by a parameter.
The standard deviations for today are reported based on historical data. The dataset that is used for calculating top movers is based on days of data that are retained and currently available and the mode that is used for calculating them.
Since daily deviations are calculated over a period of multiple weeks, you must create the daily movers and allow them to acquire at least two weeks worth of data before you generate Top Mover reports. Otherwise, the data may not be meaningful.
Top mover report data can be calculated for:
- Events with dimension values
For Top Movers for dimensions, only the values that are displayed in a dimension's whitelist and are marked for Top Mover tracking can be displayed in a Top Movers report. For dimension Top Movers, you must create a whitelist of values and mark a set of values first.
- Ratios of Event Counts Note: The creation and reporting on Hourly, dimension, and ratio movers is an enhancement that is associated with cxView, a separately licensed component of the Experience Analytics CX system.
These values then are aggregated for storage on an hourly or daily basis. Storage of hourly movers requires more space.
The calculated movers can then be displayed in the Top Movers page to graphically show variations in values or counts.
You can also apply dimensions to the Top Mover report to filter the display to show only the Top Mover information within a narrowed context.
By default, Top Movers are not calculated and stored for events and dimensions.
- If you want, you can enable auto-creation of top movers for all currently active events and dimensions.
- If auto-creation is not enabled, you must manually create top movers for each event and dimension you want to track.
You can also create movers that are based on the ratio of two events. To compute the mover of a ratio, the ratio is treated as a single event whose count is the ratio of numerator to denominator.
The creation and reporting on ratio movers is an enhancement that is associated with cxView, a separately licensed component of the Experience Analytics CX system.
If the denominator of a ratio evaluates to zero, a null value is recorded. If there are still sufficient data points within the rolling window, then the mover is calculated.
Report access permissions
In the Report Access Permissions window, you can select the users and groups who can view and edit the current report.
You can configure the administrators of the report by available user group. Report administrators
have all of the permissions available to specified users of the report. Report administrators can
edit and delete the report. Members of the
groups are administrators for all reports in the system.
You can configure the users of the report by available user group. Report users can see the report, change parameters, export it, and save it under a new name. You can also change mover report access permissions through the Report Manager.
Top movers deviation calculations
Experience Analytics computes standard deviations, which are used to populate Top Movers. At a global level, you can configure the days over which Top Movers are calculated. In either mode, Hourly and Daily Top Movers are available.
You can configure consecutive days or same day calculations. Consecutive Days mode is useful for monitoring variation of recent activity. For a longer term perspective, Same Days may be a better choice. Experience Analytics administrators can configure the calculation mode through the Portal Management page. Switching between Top Mover Calculation Modes results in the clearing of the old data from the database. When the mode is changed, data can be back-populated where possible. Avoid changing modes frequently.
When Top Movers are computed over consecutive days, the data set includes the focus day and all days preceding it that have not been trimmed. In this table, F indicates the focus day, and SD indicates the data required to calculate the standard deviation for a 7 consecutive-day Top Mover calculation. The Top Mover calculation requires 8 days of data.
When Top Movers are calculated in Consecutive Days mode, you can see data within a few days, instead of waiting four weeks to see a valid data set in the Same Days mode.
In Same Days mode, top movers are calculated based on the values for the same hour or day from the preceding weeks. For example, deviation values for Wednesday are computed using data from the previous Wednesday. In this table, F indicates the focus data, and SD indicates the data that is used to calculate the standard deviation for the 4 same-day Top Mover calculation. The Top Mover calculation requires 5 weeks of data.
Depending on how much data is available, Same Days mode computes Top Movers over the preceding 4 to 16 weeks of data. If insufficient data is available to complete the minimum number, no data is displayed for the Top Mover in the report.
To complete calculation of a Mover, this table indicates the default required number of data points for the calculation:
|Calculation Mode||Default Minimum Number of Data Points||Default Maximum Number of Data Points|
|Consecutive Days||4 days||16 days|
|Same Days||4 weeks||16 weeks|
Calculations are made by looking backward from the current date to the date indicated by the Maximum Number of Data Points.
- To complete a valid calculation, the Minimum Number of Data Points must be present. If the minimum number of data points is present, then the standard deviation and average calculations can be completed.
- For event-based Movers, the count of data points does not include any tabulations for null values, which can occur during periods when the event was inactive or data was not available.
- For ratio-based Movers, the count of data points does include any tabulations during periods when the event was inactive or data was not available. The standard deviation and average calculations ignore the null value data point.
Configuring the data volume of the rolling window
The minimum number and maximum number of days of data that is required for a valid Top Mover calculation are defined by parameter:
Top Movers - Minimum data points for calculations
Top Movers - Maximum data points for calculations
Depending the type of Top Mover, data is recalculated on an hourly or daily basis.
Hourly movers are calculated on the first Data Collection run that occurs 30 minutes after the hour. Any newly available data is applied to the calculations up through the preceding complete hour. For example, if the calculation is done at 10:40 am, it includes any new data that is timestamped before 10:00 am. In this example, data with a timestamp between 10:00 am and 10:40 am is not applied to the calculations during the current run.
Daily movers are calculated at 4:30 am each morning. Any newly available data is applied to the calculations up through the preceding complete day. For example, if the calculation is done at 4:30am on April 26, it includes any new data that is timestamped before 12:00 am April 26. In this example, data with a timestamp between 12:00 am and 4:30 am April 26 is not applied to the calculations during the current run. You can change the time when calculations are done for daily top movers.
In some cases, a Top Mover update gathers new data that had been spooled during an earlier period. If spooled data is processed, then when the Top Mover calculation run next runs, the spooled data is included as part of the Top Mover data set. All relevant calculations are done to include the newly captured data in the Top Mover values.
In environments where data is spooling, Top Movers can be retroactively recalculated when the spooled data is later processed.
Movers are calculated by using a simple standard deviation formula.
|Average of captured values|
|Number of captured values|
The standard deviation is calculated by:
- Summing the square of the difference between each value and the average
- Dividing that value by the number of values - 1
- Calculating the square root of that value
When a mover is calculated and the count is zero, if at least one interval for that mover exists with data before this interval, then the zero count is written as the value for the current interval.
Example: STD Calculation for Top Mover
Experience Analytics implements the Top Mover calculations that are based on extracting the data points over the rolling window, depending on the several factors.
The calculations are based on:
- Type of mover
- Configured required dataset for valid rolling window. If the data set includes fewer than four
data points, the standard deviation is not computed and is reported as
- Calculation mode.
This example shows the differences between daily and hourly movers. These configuration options are assumed:
- Type of mover: Daily and Hourly
- Configured required dataset for valid rolling window: The following are the default minimum and
Top Movers - Minimum data points for calculations- 4
Top Movers - Maximum data points for calculations- 16
- Calculation mode: Same Days
For calculating a valid Daily or Hourly top mover with the preceding configuration options, a minimum of four weeks of data is required.
Suppose that you are calculating a mover of counts for Event A. The counts are summed in the following manner for Daily or Hourly movers in this example:
|one week ago||sum1|
|two weeks ago||sum2|
|three weeks ago||sum3|
|four weeks ago||sum4|
For a Daily mover, the counts are summed over 24-hour periods in the rolling window, while Hourly movers use hourly counts during the rolling window.
STDev_SameDays is computed by using the following formula:
StDev_SameDays = std of (sum1, sum2, sum3, sum4)
The average of those four sums is computed this way:
avg_SameDays = avg of (sum1, sum2, sum3, sum4)
The count mover is then computed with this formula:
countDev_AvgSameDays = (sum0 - avg_SameDays)/StDev_SameDays