Account Manager / Customer Success Manager

Overview

You own retention and expansion for enterprise customers after they've implemented Decagon's AI customer service agents. You're monitoring how the AI is performing (deflection rates, customer satisfaction, escalation patterns), working with customers to optimize agent performance, and identifying opportunities to expand into additional channels or use cases. You're part CSM (keep them happy), part account manager (find expansion revenue), and part product specialist (troubleshoot AI behavior).

Role Snapshot

Company Context

Stage: Series D - $250M raise at $4.5B valuation (Coatue, Index)

Size: 301 employees (grew from 10 people ~18 months ago)

Growth: Hyper-growth - post-sales team is likely being built out rapidly to support new customer influx

Market Position: Early in customer lifecycle - most customers are still in first year of implementation, figuring out what works

GTM Reality

Your Book of Business:

• 10-15 enterprise accounts (given complexity of AI customer service implementation)
• Mix of newly launched customers (still proving value) and mature customers (ready for expansion)
• Likely stratified by ACV or complexity (you might have a few $1M+ customers and several $200-500K customers)

Expansion Opportunities:

• Additional channels (started with chat, expand to voice and email)
• Additional use cases (started with tier 1 support, expand to returns, account inquiries, technical support)
• New business units or geographies
• Higher AI autonomy levels (let AI resolve more complex issues)

Risk Factors:

• AI performance not meeting expectations (deflection rate below target)
• Customer experience issues (bad AI responses hurting CSAT scores)
• Internal resistance from support teams (fear of job replacement)
• Budget cuts or leadership changes

Competitive Landscape

Competitive Pressure: Customers are being pitched by other AI vendors constantly, evaluating build vs buy, or considering switching to integrated helpdesk AI

Your Job: Prove continuous improvement and ROI so they don't churn or switch

What You'll Actually Do

Time Breakdown

Customer Check-ins (30%) | Performance Monitoring (25%) | Expansion Selling (25%) | Firefighting (20%)

Key Activities

• Weekly/bi-weekly business reviews: You're walking customers through AI performance metrics (ticket deflection, resolution time, CSAT scores, cost savings). When numbers are good, you're heroes. When deflection drops or CSAT dips, you're troubleshooting why the AI isn't working as expected.
• Optimization projects: Customers need the AI to get smarter over time. You're working with them to improve training data, refine conversation flows, add new intents, and tune the AI model. This requires understanding their specific use cases and iterating on agent behavior.
• Expansion conversations: When a customer is happy with AI chat, you're pitching voice or email. When they're using AI for basic inquiries, you're selling them on returns processing or account management use cases. This is consultative sales - showing ROI on incremental use cases.
• Damage control: AI agents will mess up - give wrong answers, escalate unnecessarily, frustrate customers. You're the first call when something goes wrong. You need to investigate, coordinate with product/engineering, and keep the customer from churning while it's fixed.

The Honest Reality

What's Hard

• You're managing AI performance expectations - customers expect magic, reality is the AI works great 80% of the time and struggles 20%. You're constantly explaining limitations and managing disappointment.
• Expansion is dependent on adoption success - you can't upsell a customer whose initial AI implementation is underperforming. You spend a lot of time getting the first use case right before you can sell more.
• Product is still maturing - expect bugs, feature gaps, and unexpected AI behavior. You're working with a fast-moving product team, which means things break and change frequently.
• Renewal pressure is high - these are expensive, high-visibility implementations. If a customer churns, it's a big deal. You're carrying quota pressure without full control over outcomes (AI performance, product roadmap, etc.).

What Success Looks Like

• Maintaining 100%+ net revenue retention across your book
• Expanding 50%+ of customers by $50K+ annually
• Proactively catching performance issues before customers escalate to leadership
• Building champions who advocate for Decagon internally and give you visibility into expansion opportunities

Who You're Selling To

Primary Contacts:

• VP/Head of Customer Experience (your executive sponsor, owns renewal and expansion budget)
• Director of Customer Support (day-to-day operator managing the AI agents)
• Operations/Analytics leads (watch the metrics, care about ROI)

What They Care About:

• Is this delivering ROI? They need to justify the investment - cost per ticket going down, agent productivity going up, customer satisfaction stable or improving.
• Is this getting better over time? AI should continuously improve, not stagnate. They want to see progress.
• Can we expand safely? They're cautious about putting AI into more critical use cases without proof it works.

Requirements

• 3-5 years in customer success, account management, or implementation for B2B SaaS (preferably CX tools, AI products, or technical platforms)
• Comfortable with data and metrics - you live in dashboards tracking AI performance
• Technical aptitude - you need to understand how AI agents work, when issues are data problems vs model problems vs product bugs
• Consultative selling skills - expansion is not just "buy more", it's building business cases for incremental use cases
• Strong relationship management - you're managing multiple stakeholders, navigating politics, and building trust in a high-stakes environment