Analyze data impacted by events
Sometimes an event can impact data quality in your organization. Examples include:
- A bot sending outlier data, such as millions of dollars in revenue
- Your organization pushed an update to your website that negatively impacted your Analytics implementation
- Other issues that affect data quality or completeness
If your site experienced data quality issues, implementation issues, or other gaps in data, you might want to exclude it from reporting to prevent making decisions on partial data. Use these sections to gauge the impact of the event on your data, and determine how you want to proceed.
Analyze and exclude data using segmentation
Adobe Analytics offers a simple and robust way to focus on or exclude data using segmentation. You can use date range dimensions within segments to filter out or focus on those specific dates. See Exclude specific dates in analysis .
Compare an event to previous date ranges
If you want to learn more about how much impact an event made on your data over time, you can use date comparison in Analysis Workspace. This feature lets you compare data day-by-day, week-by-week, or month-by-month to see how it compares with previous ranges. You can then use this comparison to determine how much an event affects trends. See Compare dates impacted by an event to previous ranges .
Derive data using calculated metrics
Once you create segments and use date comparison, you can combine both of these concepts to correct trended data using calculated metrics. Include the segments within a calculated metric, then multiply the affected days by the offset found when comparing dates. See Derive data impacted by events .
Communicate impact to users in your organization
Once you are prepared with how you intend to handle an event, you can communicate to users in your organization . Adobe offers several places within Analytics where you can place text to communicate to users what happened and what components they can use.
This video walks through each of the above steps.
- 0:27 : Exclude data using segmentation
- 2:55 : Compare an event to previous ranges
- 8:42 : Derive data using calculated metrics
- 11:46 : Communicate impact to users