Badger attributes the significant change in your business metrics (e.g. Revenue) to related causal variables (e.g. average order value, conversion rate, sessions etc). It further drills down on every other variable that has contributed towards the overall change.

Badger digs on a particular metric (e.g. Sessions) and uncovers all change variables that affect the metric (e.g. Traffic from Metro/ non-Metro, Mobile device/ Desktop device Users, etc). It pinpoints the variables that need you to take quick actions.

Badger performs a Composition Change Analysis on any particular attribute and provides insights on how the composition mix of the attribute (e.g. E-commerce product category) has changed over time with respect to your business metric contribution (e.g. Revenue).

Badger discovers the strongly associated attributes that have a combined effect on your business metric (e.g. Campaign and City performance in driving App Installs). It also provides the composition mix change analysis on various parameters.

Badger uses Anomaly Detection to report in real time all significant anomalies in your business metric (e.g. deviation in New Users traffic from USA). It diagnoses the actual cause of the deviation and the frequency of occurrence.

Badger analyzes the competitive scenario of your business metrics and delivers a snapshot on how your business has performed with respect to industry benchmarks (e.g. App Store Rankings for the app category).