USE CASE
AI Customer Success: Replace Gainsight, ChurnZero, and Totango
Build an AI customer success team that monitors health scores, identifies churn risks, and automates outreach—before customers leave.
Customer success platforms promise to reduce churn. But Gainsight at $30,000/year is itself a churn risk—for your budget. And you still need CSMs to actually talk to customers.
What do you actually get? Dashboards showing health scores that nobody checks until a customer is already churning. Playbooks that trigger based on arbitrary rules. NPS surveys that go unanswered.
What if customer success just worked? Health scores calculated from real signals, risks identified before they become emergencies, and proactive outreach that actually prevents churn—all automatically, all intelligently.
The Customer Success Platform Tax
Here's what customer success platforms actually cost (before implementation and the CSMs to run them):
| Tool | Price/Month | Annual Cost |
|---|---|---|
 Gainsight | $2,500+ | $30,000+ |
ChurnZero | $1,250+ | $15,000+ |
Totango | $1,000+ | $12,000+ |
Vitally | $400 | $4,800 |
Prices for mid-market tiers as of December 2025. Enterprise pricing is significantly higher.
You're paying $30,000+/year for dashboards that still require a team to watch. The AI does both.
What Customer Success Platforms Actually Are
Strip away the enterprise sales pitch and what are you left with?
| CS Feature | What It Really Is |
|---|---|
| Health Scores | Weighted average of metrics you configure manually (usage × 0.3 + NPS × 0.2...) |
| Churn Prediction | Rule-based alerts when metrics drop below thresholds you set |
| Playbooks | If/then workflow automation with email templates |
| NPS Tracking | Survey tool + spreadsheet for responses |
| Renewal Management | Calendar with contract end dates and email reminders |
Gainsight is a $30,000/year dashboard that tells you a customer is churning—after they've already decided to leave.
What an AI Customer Success Agent Actually Does
An AI customer success agent isn't a dashboard you check. It's a persistent agent that actively manages your customer relationships—and works alongside your Support and Sales agents for seamless coordination:
Monitors health with real understanding
Predicts churn before it happens
Automates routine but feels personal
Spots expansion opportunities naturally
Coordinates with Support and Sales seamlessly
A Day in the Life: Your Customer Success AI Team
Here's what it looks like when AI agents manage your customer success operations. Watch how they monitor health, prevent churn, and identify expansion opportunities:
Health Score Alert
via Slack - #customer-successAt-Risk Customers Detected
| Customer | Score | Change | Primary Signal |
|---|---|---|---|
| Acme Corp ($48K ARR) | 42 | -31 | Daily active users down 60% over 2 weeks |
| TechStart ($24K ARR) | 58 | -18 | Champion (Sarah Chen) left company |
| GlobalCo ($96K ARR) | 51 | -22 | 3 support tickets marked 'frustrated' this week |
Acme Corp shows signs of internal project deprioritization—usage drop coincides with their Q4 budget cycle. Recommend executive check-in. TechStart needs new champion identification urgently. GlobalCo support issues are onboarding-related for their new team.
Renewal Pipeline Review
Q1 Renewal Pipeline Summary
| Customer | ARR | Renewal | Health | Risk Assessment |
|---|---|---|---|---|
| Enterprise One | $120,000 | Jan 15 | 89 | ✅ Low — strong adoption, expanded 2x last year |
| MidMarket Co | $36,000 | Feb 1 | 71 | ⚠️ Medium — new CFO reviewing all vendors |
| GrowthTech | $48,000 | Feb 28 | 45 | ❌ High — considering competitor, budget cuts |
| StartupXYZ | $18,000 | Mar 15 | 82 | ✅ Low — just added 5 seats, high engagement |
Q1 has $222,000 in renewals. $84,000 (38%) shows medium-to-high risk. GrowthTech needs immediate attention—they've been evaluating ChurnZero for 3 weeks. Recommend competitive positioning call and executive sponsor involvement. MidMarket's new CFO (Jennifer Lee) should receive our ROI analysis before budget review on Jan 20.
Expansion Opportunity Alert
via Slack - #customer-successExpansion Signals Detected
Three customers showing strong expansion signals this week:
| Customer | Current Plan | Signal | Opportunity |
|---|---|---|---|
| FastScale Inc | $36K/year | At 95% seat limit, added 3 projects | Enterprise tier (+$24K) |
| DataCorp | $60K/year | Using API at 10x expected volume | API tier upgrade (+$18K) |
| AgencyHub | $24K/year | Asked about white-label in support | Partner program (+$36K) |
FastScale is the warmest—their CEO mentioned 'explosive growth' on LinkedIn yesterday. Recommend proactive outreach before they hit the hard limit. Draft expansion proposal ready in /customers/fastscale/expansion-proposal.md
Weekly CS Report
Weekly Customer Success Report — Week of Dec 16
| Metric | This Week | vs Last Week |
|---|---|---|
| Average health score | 76 | +2 |
| At-risk accounts | 12 | -3 |
| Expansion pipeline | $127,000 | +$31,000 |
| Customer check-ins completed | 34 | +12 |
| NPS responses | 47 (avg: 52) | +8 |
Key win: Acme Corp moved from at-risk (42) to healthy (71) after executive intervention. Usage up 40% since Monday.
Concern: Enterprise segment showing 5% decline in average health. Recommend segment-level QBR analysis.
Full report saved to /customer-success/reports/weekly-2025-12-16.md
The Killer Feature: A Connected Customer Success Workspace
Here's what makes this fundamentally different from any customer success platform you've used. In Lazarus, your AI agents share a persistent workspace—the same customer data, the same engagement history, the same health signals.
When your health monitoring agent detects a risk, it writes to the shared customer database. Your outreach agent sees the context and personalizes accordingly. Your renewal agent knows the full history when contract time comes. No sync issues, no data silos—just agents collaborating in real time.
/customer-success
├── customers/
│ ├── all-customers.csv
│ ├── health-scores.csv
│ └── at-risk-customers.csv
├── renewals/
│ ├── upcoming-renewals.csv
│ ├── renewal-playbook.md
│ └── renewal-forecast.md
├── expansion/
│ ├── opportunities.csv
│ └── upsell-signals.md
├── engagement/
│ ├── check-in-schedule.csv
│ ├── qbr-templates/
│ └── onboarding-sequences/
└── reports/
├── weekly-health.md
├── churn-analysis.md
└── nrr-report.mdNo per-customer pricing
Full customer history ownership
Sales and Support alignment built in
Intelligence compounds over time
This isn't a dashboard that shows you customer health. It's a customer success team that manages customer health.
Build Your Customer Success AI Team in 15 Minutes
Here's how to build your first customer success agent—and set up the foundation for proactive customer management:
Step 1: Create the agent and write instructions
Open Lazarus and create a new agent. Name it 'Customer Success Agent' or 'Health Monitor.' Then describe what you want:
"You are my customer success agent. Monitor all customers in /customers/. Calculate health scores weekly based on usage, support tickets, and engagement. Alert me if any score drops below 60 or changes by more than 15 points. Send check-in emails based on playbooks in /playbooks/. Identify expansion opportunities and coordinate with Sales Agent."
Step 2: Connect your customer data
Product usage, support tickets, billing history, NPS responses—the signals that indicate customer health. The agent synthesizes them all.
Step 3: Define your health model
What does healthy look like for your customers? At-risk? The agent starts with sensible defaults and calibrates based on actual outcomes.
Step 4: Build your playbooks
What happens when health drops? When renewal approaches? When expansion signals appear? The agent follows your playbooks automatically.
Step 5: Let it run
The agent handles routine monitoring and outreach. You focus on the high-touch relationships that actually need human attention.
That's it. You've built customer success that runs automatically while you focus on the customers who need you most.
The Full Picture: Your Customer Success AI Team
Build a team of specialized agents that share the same workspace—each focusing on what they do best, all working together:
| Agent | Role | Workspace Access |
|---|---|---|
| Health Monitor Agent | Tracks and scores all customer health signals | Reads /customers/*, writes /customers/health-scores.csv |
| Outreach Agent | Manages check-ins, onboarding, and engagement | Reads /customers/*, /playbooks/*, writes /engagement/ |
| Renewal Agent | Manages renewal pipeline and risk mitigation | Reads /customers/*, writes /renewals/ |
| Expansion Agent | Identifies and coordinates upsell opportunities | Reads /customers/*, writes /expansion/, notifies Sales Agent |
How They Work Together
Customer data flows in → Health Monitor Agent calculates scores and detects changes → writes to /customers/health-scores.csv and alerts on risks
Health drops trigger Outreach Agent → runs appropriate playbook → personalizes based on customer context → tracks engagement
Renewal date approaching → Renewal Agent prepares review → assesses risk based on health trends → coordinates with you on strategy
Expansion signals detected → Expansion Agent packages opportunity → notifies Sales Agent with full context → tracks outcome
No manual monitoring. No 'how is this customer doing?' Every agent sees the full picture, and so do you.
Four agents. One workspace. Zero customers falling through the cracks. Complete visibility.
Stop paying $30,000/year for dashboards that tell you a customer is churning after they've already decided to leave.
Gainsight + CSM team costs $200,000+/year. Your customer success AI team costs a fraction—and actually prevents churn before it happens.
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