HOW KINETIK HELPS

Scenario Analysis

Assess the revenue potential of your growth strategy with the power of simulation and a foundation that reflects the reality of your current G2M performance

Kinetik Intelligence

Kinetik Intelligence combines the deep understanding of cause and effect with G2M expertise to identify strategies and tactics to address constraining factors limiting revenue growth

GTM Discovery

Data science based insights illuminate tactical performance within the end-to-end G2M perspective through cluster analysis, attribution, and lifecycle insights.

Growth Blueprints

Design the blueprint for aggressive revenue growth by defining resources, actions, and outcomes for the scenarios you are evaluating.  Kinetik will convert those outcomes into statistical profiles used to simulate the revenue impact.  

Foundation for AI

Role based insights for executives with operational responsibility across the G2M model; from sales to marketing to strategy to channels.  Make functional decisions with an understanding of the end-to-end revenue impact.

CXO Insights

Role based insights for executives with operational responsibility across the G2M model; from sales to marketing to strategy to channels.  Make functional decisions with an understanding of the end-to-end revenue impact.

Secure, automated data ingestion

CRM, marketing, revenue, and cost data securely ingested through file uploads, REST APIs, or run on your data lake.  

How It Works

Kinetik foundational models automate marketing and CRM data through an ingestion engine including metrics from across the go-to market model including lead conversion, progression, and yield statistics to simulate go-to-market performance with direct connections to the tactics and resources required to deliver.  
 Kinetik’s AI Recommendation Engine suggests tactics to address constraining factors identified through AI analysis of your marketing and sales data and a continuous scan of methods, tactics, and productivity drivers with the greatest impact.

Schedule time with our data sciences team to explore options for building a proof of concept model?