Data science experiments to inform your revenue intelligence journey
Kinetik provides support for micro-projects that enable testing your data quality and accessibility for the most common use cases on the journey to revenue intelligence
Conversion Analysis
Time series analysis of engagement, account, response, lead and opportunity attributes
Buying Center Profiles
Develop a historical time series baseline for digital and guided engagement for targeted buying centers including composition and engagement patterns
Engagement Success Patterns
Analysis of won opportunities to determine the engagement dynamics and buying center compositions that most and least often result in wins and losses
Dynamic Segmentation
Predictive analytics to segment based on prospect behaviors to enable dynamic engagement strategies with personalized content and engagement tactics
Customer Acquisition Costs
Product, channel, or GTM motion, or segment acquisition costs using activity costs specific to marketing, sales and client success resourced employed
Scenario Analysis
Model the go-to-market dynamics and outcomes required to support aggressive growth strategies
Revenue Intelligence
Assessment of maturity of capabilities across marketing, sales, and client success to derive competitive advantage from AI and advanced analytics
MEDDICC Analytics
Predictive analytics across the go-to-market engine of operational outcomes resulting from deployment or improved execution of the MEDDICC method.
Marketing Mix
Analysis of operational outcomes from marketing activities and offers. Predictive analytics for go-to-market outcomes associated with alternative scenarios
