โ† Tuesday's Code

How Teams Use Onboarding Automation ๐Ÿ‘ฅ

Different roles, same system, faster activation

October 1, 2025
๐Ÿš€ Product๐Ÿ‘ฅ 4 Rolesโšก Real Workflows

Same automation. Four different workflows.

Tuesday you saw the code. Today you see how Product, Growth, CS, and Design each use it differently. Each role has different metrics, different views, different wins.

Team Workflows

๐ŸŽฏ

Product Manager

4 hours/day โ†’ 30 min/day

88%
Faster

Before

Manually analyze user drop-off points in spreadsheets (90 min)
Write feature specs based on gut feeling (120 min)
Chase teams for activation data updates (45 min)

After

Check AI dashboard for drop-off patterns (5 min)
Review AI-generated improvement suggestions (10 min)
Export data-driven roadmap priorities (15 min)
Activation
68%
โ†‘
Drop-off
Step 3
โ†’
Time to Value
4.2 days
โ†“
Feature Adoption
34%
โ†‘
Volume
Monitor 5,000+ user journeys
Saved
3.5 hours saved daily on analysis
Quality
Data-driven decisions vs gut feeling
Outcome
Focus on strategy, not spreadsheets

"I finally have time to think about what to build, not just what's broken."

โ€” Product Manager, 6 years B2B SaaS

How Roles Collaborate Through the System

Watch how the automation connects four teams to solve one user's problem in real-time.

๐Ÿšจ

User signs up, gets stuck at Step 3 (integrations setup)

๐Ÿค–
AI Agent
8:00 AM
Detects user stuck on integrations for 8 minutes
๐Ÿค
Customer Success
8:01 AM
Receives alert: 'User stuck - integrations confusion'
๐ŸŽจ
Designer
8:15 AM
Reviews session replay, spots unclear CTA button
๐ŸŽฏ
Product Manager
9:00 AM
Sees pattern: 23% of users stuck at same step
๐Ÿ“ˆ
Growth Lead
10:30 AM
Launches A/B test with clearer CTA copy
๐Ÿค–
AI Agent
2 days later
Monitors test, auto-applies winning variant after 48 hours
๐Ÿ’ก

One stuck user triggered four teams to fix a systemic issue. 23% drop-off eliminated in 48 hours.

Practice-Wide Impact

MetricBeforeAfterImprovement
Activation Rate68%84%
+16 pts
Time to First Value6.8 days2.1 days
69% faster
Support Tickets340/month89/month
74% reduction
Team Hours/Week62 hours14 hours
77% saved

Getting Your Team On Board

โš ๏ธ
Fear

Product Managers think AI will replace their judgment

๐Ÿ’ก
Response

Show activation dashboard: 'AI finds patterns, you decide priorities. It's a research assistant, not a decision-maker.'

โœ…
Result

PMs spend 88% less time on analysis, 300% more time on strategy.

โš ๏ธ
Fear

Growth Leads worried AI can't understand user psychology

๐Ÿ’ก
Response

Run parallel test: manual segmentation vs AI segmentation. AI identifies 3 segments you missed.

โœ…
Result

Growth leads use AI for discovery, apply human creativity to solutions.

โš ๏ธ
Fear

Customer Success fears losing personal touch

๐Ÿ’ก
Response

Calculate time saved: 37 min/user ร— 80 users/week = 49 hours. Use for high-touch calls with enterprise accounts.

โœ…
Result

CS handles 3x volume while increasing personalization for key accounts.

โš ๏ธ
Fear

Designers think AI can't understand good UX

๐Ÿ’ก
Response

Show heatmaps and session replays: 'AI shows you what users actually do, not what they say they do.'

โœ…
Result

Designers ship data-informed iterations 10x faster.

โš ๏ธ
Fear

Leadership concerned about upfront cost

๐Ÿ’ก
Response

ROI calculation: 48 hours/week saved ร— $75/hour = $3,600/week = $187K/year. System pays for itself in 6 weeks.

โœ…
Result

Approved after seeing activation rate jump 16 points in pilot.

๐Ÿš€

Want This for Your Product Team?

We'll show each team member exactly how they'll use it. Custom demos for PM, Growth, CS, and Design.