Same automation. Four completely different workflows.
Tuesday you saw the code. Today you see how real marketing teams actually use it. Each role has different dashboards, different priorities, different wins.
Team Workflows
See how different roles use the same system to transform their daily work.Click each role below
Before Automation
With Automation
Dashboard Metrics
Impact By The Numbers
"I finally have time to think strategically instead of just reporting what happened last week."
— Marketing Manager, 6 years B2B SaaS
How Roles Work Together Through the System
A $50K opportunity stops engaging mid-nurture. Watch how the team collaborates to re-engage without manual coordination.
High-Value Lead Goes Cold
✨ Scroll here to watch the workflow
Team-Wide Impact
| Metric | Before | After | Improvement |
|---|---|---|---|
| Time to Respond to Lead Behavior | 3-5 days (manual monitoring) | Real-time (AI flags instantly) | 99% faster |
| Weekly Reporting Time | 12 hours (4 people × 3 hours each) | 2 hours (review AI reports) | 83% reduction |
| Campaign Launch Speed | 2 weeks (setup, testing, coordination) | 3 days (AI handles execution) | 78% faster |
| Lead Nurture Coverage | 3,000 leads (manual limit) | 8,000 leads (AI scales) | 167% more leads |
Getting Your Team On Board
Specialists worry AI will make their writing generic
Show them the AI draft is a starting point, not the final product. Track open rates before/after: AI-assisted emails perform 32% better because they're personalized at scale.
Specialists become AI advocates when they see higher engagement and less research time.
Managers fear losing control over campaign messaging
Set up approval workflows: AI generates, specialists edit, managers review before send. Nothing goes out without human sign-off.
Managers love having visibility without being a bottleneck. Approval time drops from 2 days to 2 hours.
Analysts worry their job is being automated away
Reframe: AI does data pulling and basic analysis. Analysts now have time for attribution modeling, cohort analysis, predictive scoring—work that was always backlogged.
Analysts get promoted because they're finally doing strategic work that impacts revenue.
Ops teams concerned about integration complexity
Run parallel for 2 weeks: keep manual process, add AI alongside. Compare accuracy, speed, and effort. Let data convince them.
Ops teams become biggest champions after seeing 99.2% deliverability and 5 hours/day saved.
Leadership worried about upfront cost and ROI timeline
Show 30-day payback calculation: $5K/month investment vs $18K/month in time savings = 10-day break-even.
CFO approves when they see it's cheaper than hiring another person.
Investment & ROI
Typical payback in 10-14 days through time savings
Pricing
ROI Calculator
Proven Results
From Demo to Live in 3 Weeks
From demo to production in just 3 weeks
- Connect your CRM, marketing automation, and analytics tools
- Import historical campaign data for baseline metrics
- Configure role-specific dashboards and permissions
- Map your lead stages and scoring model
- Train each role on their workflow (3-hour sessions)
- Run pilot campaign with 500 leads
- Gather feedback from each role, adjust configurations
- Set up approval workflows and notification preferences
- Roll out to all users and full lead database
- Daily check-ins for first week (15 min standups)
- Measure baseline metrics vs new performance
- Optimize based on real usage patterns
Enterprise deployments take 4-6 weeks for multi-brand setups and custom AI model training
2026 Randeep Bhatia. All Rights Reserved.
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