CRM Pipeline Rebuild & Sales Automation
Audited, rebuilt, and automated a CRM system that had become unusable, transforming it into a reliable pipeline that improved deal close rates by 30%.
The Problem
The client's JobNimbus CRM had accumulated 18 months of dirty data: duplicate records, stale pipeline stages, inconsistent tagging, and no automated follow-through. Sales reps were ignoring it entirely and reverting to ad-hoc tracking methods.
The Solution
Performed a full CRM audit and data cleanup, rebuilt the pipeline stage logic, set up automated status updates and task triggers, and built reporting dashboards to give management real-time visibility into pipeline health and rep activity.
How I approached it
CRM Audit
Exported all records and ran a full audit: identified ~340 duplicate contacts, 60+ stale deals older than 6 months, and 12 inconsistently used pipeline stages. Documented all issues.
Data Cleanup
Merged duplicates, archived stale records, standardized contact and deal fields, and normalized stage names to a clean 6-stage pipeline.
Pipeline Rebuild & Automations
Rebuilt pipeline stages in JobNimbus with clear entry/exit criteria. Configured automated tasks, reminders, and status updates at each stage transition. Set up escalation alerts for deals that stall.
Reporting Dashboard
Built a dashboard showing pipeline volume by stage, conversion rates, average deal age, and rep activity, giving management weekly visibility without manual reporting.
Tools & Platforms
Results
- 30% improvement in deal close rate within 60 days of launch
- Eliminated 340+ duplicate records and rebuilt clean data foundation
- Sales reps re-adopted the CRM with consistent usage within 2 weeks
- Management gained real-time pipeline visibility for the first time
Key Metrics
What I learned
CRM adoption is a people problem as much as a system problem. Rebuilding the data was important, but the biggest win was simplifying the pipeline stages so reps could use it without thinking: fewer stages, clearer criteria.
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