Overview
You manage relationships with ecommerce and retail companies that use Siena's AI platform to automate customer service interactions. You're making sure they're actually using the product, getting ROI, and expanding into new use cases or higher volumes. You report to the Head of CS and are measured on both retention (NRR) and expansion revenue.
Role Snapshot
| Aspect | Details |
|---|---|
| Role Type | Hybrid CSM/Account Manager - retention + expansion revenue |
| Sales Motion | Customer-led expansion, consultative upsell |
| Deal Complexity | Consultative - requires understanding their CS workflows and AI readiness |
| Sales Cycle | 4-8 weeks for expansions (adding use cases, scaling volume) |
| Deal Size | Likely $30-100K annual expansions depending on usage |
| Quota (est.) | $300-500K expansion ARR annually + 95%+ gross retention |
Company Context
Stage: Early-stage (likely Series A based on 58 employees and product maturity)
Size: 58 employees - small enough that you'll work directly with founders/product team
Growth: Actively hiring for CS infrastructure, suggesting growing customer base needs more coverage
Market Position: Category is crowded (competing with Zendesk AI, Ada, Intercom, etc.) but commerce-specific angle is their wedge. They're trying to prove AI can handle 80% of support tickets without losing the brand voice.
GTM Reality
Pipeline Sources:
- 100% existing customer base - this is pure post-sale CS/expansion
- AE team is bringing in new logos, you inherit them after they sign
- Some accounts may come from PLG/trial motion if they have one
SDR/AE Structure: You don't prospect. AEs close initial deals and hand off. But you own the expansion motion - no AE involvement on upsells unless it's a major strategic deal.
SE Support: Likely minimal - at this stage you're probably doing your own product walkthroughs for expansion use cases. Maybe you can pull in the founding team for complex technical stuff.
Competitive Landscape
Main Competitors: Zendesk AI features, Ada, Intercom's Fin, plus traditional outsourced CS providers (BPOs)
How They Differentiate: Commerce-specific workflows (returns, order tracking, product questions) vs generic chatbot. They claim deeper ecommerce integrations and better understanding of retail customer journeys.
Common Objections: "AI will make our brand sound robotic," "We tried chatbots before and customers hated them," "Our support needs are too complex," "What happens when the AI screws up?"
Win Themes: Speed to resolution, cost savings vs hiring more agents, handles volume spikes (Black Friday), maintains brand voice with their guardrails.
What You'll Actually Do
Time Breakdown
Customer Calls/QBRs (35%) | Adoption Work (25%) | Expansion Hunting (20%) | Internal Stuff (20%)
Key Activities
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Weekly/Bi-weekly Check-ins: You're on Zoom with CS leaders at DTC brands walking through usage dashboards. You're looking at ticket automation rates, customer satisfaction scores, escalation patterns. When the numbers dip, you're troubleshooting - is it a training issue, a workflow problem, or are they just not using it?
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Product Adoption Projects: A lot of your time is spent getting customers to actually use more of the platform. They signed up to automate order status queries, but they're not using the returns workflow or the product recommendation features. You're building business cases, running training sessions, sometimes literally writing their AI prompts for them.
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Spotting Expansion Opportunities: You're in their Shopify or support ticket data looking for signals. If they're hitting volume limits, that's an upsell. If they're manually handling a new category of tickets that Siena could automate, that's an expansion conversation. You need to know their business well enough to see it before they ask.
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QBRs and Renewals: Quarterly business reviews where you're presenting ROI metrics - tickets automated, time saved, CSAT maintained. Renewals are probably annual contracts, so you're managing a renewal pipeline and spotting churn risk 90+ days out. If a customer's usage drops or their executive sponsor leaves, you're in damage control mode.
The Honest Reality
What's Hard
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You're selling AI in a skeptical market: Half your customers are worried about AI screwing up and damaging their brand. You're constantly managing expectations and explaining why the AI did something unexpected. When it goes wrong (and it will), you're the one fielding the angry Slack messages.
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You're at a 58-person company: Things break. Features get delayed. The product roadmap changes based on what the founders decide last week. You'll promise something to a customer and then have to walk it back because priorities shifted. You need to be comfortable with chaos.
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Expansion quota pressure with immature product: You're being measured on expansion revenue, but the product may not have all the use cases customers want yet. You're trying to upsell customers who are still figuring out if the basic features work. It's a delicate balance.
What Success Looks Like
- You're hitting 100%+ net revenue retention across your book - minimal churn, healthy expansion from customers scaling usage or adding workflows
- Your customers are publicly referenceable - they're willing to do case studies, speak at events, because the product is genuinely working for them
- You close $300-500K in expansion ARR annually while keeping gross retention above 95%
Who You're Selling To
Primary Buyers:
- Director/VP of Customer Experience at mid-market ecommerce brands ($10M-100M+ revenue)
- Head of Customer Support at fast-growing DTC companies
What They Care About:
- Cost per ticket and ability to scale support without hiring linearly
- Customer satisfaction scores - they can't let CSAT drop to save money
- Speed during peak seasons (holiday shopping, big sales events)
- Brand voice consistency - they're paranoid about AI sounding generic
- Easy integrations with their existing stack (Shopify, Klaviyo, Gorgias, etc.)
Requirements
- 2-4 years in customer success, account management, or sales at a SaaS company (ideally selling to ecommerce/retail)
- You've carried a revenue number before - this isn't a hand-holding CSM role, you need to close expansion deals
- Comfortable talking to customer experience leaders about metrics (CSAT, ticket volume, cost per interaction, first response time)
- Technical enough to understand how AI/automation works and explain it to non-technical buyers without the hype
- Scrappy self-starter attitude - you'll be building processes, not inheriting a well-oiled CS machine
- Bonus: Experience with ecommerce platforms (Shopify, BigCommerce) or customer service tools (Zendesk, Gorgias, Kustomer)