Skip to main content

Screen Filters - Knowledgebase / Profit Analytics / Profit Analytics Documentation / Application Basics - Cavallo Technical Support

Screen Filters

Authors list

Profit Analytics provides robust filtering options at the screen level to refine and customize the data displayed. These filters help users tailor their analysis to specific time frames, reference points, comparative data, and customer segments.

Using these screen level filters, users can fine-tune their analyses, making it easier to extract actionable insights and drive data-driven decisions within Profit Analytics.

brave_GKfifrPdd7-20240919-191916.gif

The key screen level filters available are:

Time Period

The Time Period filter allows users to select the range of dates for the data they wish to analyze. This filter is essential for focusing on specific periods, such as quarterly, monthly, or yearly data. Options typically include:

  • Last Calendar Year

  • Quarter to Date

  • Month to Date

  • Year to Date

  • Trailing 3 Months

  • Trailing 12 Months (default selection)

Reference Date

The Reference Date filter enables users to set a specific date from which the data will be analyzed. This filter is useful for setting a precise point in time for the beginning of the analysis period, ensuring that comparisons and trends are anchored to a relevant starting point.

Defaults to Today

Comparison Period

The Comparison Period filter allows users to compare the current data set with a previous time frame. This filter is crucial for identifying trends and changes over time. Users can select a prior period to juxtapose against the current data, facilitating a clear comparison of performance metrics.

Customer Class

The Customer Class filter provides the ability to segment data by different customer categories. By filtering the data to specific customer classes, users can analyze the performance and engagement of various customer classes, as defined in the associated source system.

Examples might be:

  • Amazon Customers

  • eBay Customers

  • Shopify Customers

  • In-Store Customers

  • etc.


Helpful Unhelpful