Amanda Wilson
These are 3 AI-automated workflows ideas we can help you implement:
1
CRM Data Enrichment & Hygiene Automation
Continuously enrich and deduplicate Salesforce and HubSpot records by syncing multi-source data (Gong, spreadsheets, campaign platforms) and applying AI-driven deduplication and normalization. Triggered daily or on data ingestion, this system keeps CRM and analytics platforms clean and attribution-ready for reliable pipeline and revenue insights.
Reduces manual data cleaning by 80%—saving ~10+ hrs/week for RevOps/marketing teams—while increasing attribution accuracy and enabling faster campaign analysis, which supports up to 15% more pipeline-qualified leads from cleaner targeting and reporting.
2
AI-Driven Lead Handoff & Lifecycle Workflow
Automates lead transitions and status updates across marketing, sales, and customer success using integrated triggers in Salesforce, Slack, and email. Ensures no leads get lost, with automated notifications, status enrichment, and attribution syncing as prospects move through the funnel.
Cuts lead handoff lag by 50% (from days to hours), improving conversion at each stage; conservatively +10% increase in closed-won rates via reduced drop-off and better lifecycle visibility—especially impactful for complex sales typical in pharma and financial services.
3
AE Pre-Sales Call AI-Automated Reporting System
Generates pre-call briefs for AEs by aggregating the latest structured (Salesforce pipeline, campaign data) and unstructured (Gong call notes, Slack threads) insights. Delivered to the rep before each meeting, these contextual reports highlight deal risks, prior objections, and next-best-action recommendations.
Saves 30–60 minutes per call prep; with 20–30 calls/week per AE, this recovers 10–15 hours/week and boosts meeting effectiveness—translating to +5–10% lift in progression rates and more predictable pipeline movement.