Revenue Operations Classification
Python
SQL
JavaScript
TypeScript
Analytics
Problem
Revenue performance was inconsistent despite measurable product-market signals. Sales teams lacked alignment, pipeline visibility, and a repeatable enablement system.
Approach
- Analyzed win/loss behavior, segment conversion, and stage iteration friction.
- Identified ideal customer profile signals from account revenue, company size, and competition context.
- Designed CRM scoring recommendations to prioritize higher probability deals.
- Built actionable operating playbooks for sales velocity and pipeline quality control.
Impact Direction
- Clearer GTM focus for high-converting customer segments.
- Better forecast quality through score-based prioritization in CRM.
- Stronger manager intervention on stalled opportunities and iteration-heavy deals.
- City and channel level recommendations for budget and enablement planning.