Sales Performance Analytics Apps

Monitors sales performance across regions and business units, at the level a board or leadership review operates.

Combines sales performance with talent impact and regional coverage, which is closer to the shape of an actual quarterly business review agenda than a revenue chart alone.

Analyzes revenue, growth and operational performance at regional level.

Visualizes sales performance by state and city.

Assesses territory performance through an interactive map.

Revenue Overview for business-unit reviews, Regional for a geography-led organization, Geographic and Territory when coverage rather than result is the question. Sales Performance when the review includes people as well as numbers.

Tracks daily sales performance and the key metrics behind it. The default individual view and the usual starting point on this hub.

Shows how an individual's sales moved between periods and attributes the change to its contributing factors.

Compares an individual's sales against the average for their position and breaks down what accounts for the gap.

Compares an individual's sales against the average for their geography and breaks down the gap.

These answer two different objections. A salesperson who says the comparison is unfair because of where they sell is asking for the geography cut. One who says it is unfair because of what they sell is asking for the position cut.

Compares an individual's account activity against their activity target and breaks down the difference.

Tracks year-to-date sales against both quota and prior-year history.

Tracks year-to-date rank against historical data, for organizations where relative standing drives behavior more than absolute attainment.

Tracks deal size and related indicators over rolling periods, which surfaces trends that period-boundary reporting hides.

Separates new accounts from returning ones to show the purchasing behavior of genuinely new business.

Growth that is actually renewal gets reported as acquisition more often than most organizations would like to admit. This application is the one that catches it.

Identifies which products carry the most selling potential for a given salesperson, based on their own book.

Identifies the product and account-type combinations with the most potential for a given salesperson.

Identifies product potential by reference to what comparable peers are selling, rather than to the individual's own history.

Cluster is the one that surfaces something a salesperson did not already suspect, because it compares against peers rather than against their own pattern. It is also the one that needs the most data behind it to be credible.