Overview
You're booking meetings for Account Executives by cold calling and emailing customer support VPs, operations leaders, and CX directors at mid-market and enterprise companies. You're selling them on taking a demo of Giga's AI voice agent platform - essentially pitching AI that handles customer support calls at scale. Most of your day is outbound prospecting into companies that handle high call volumes (telecom, insurance, retail, SaaS).
Role Snapshot
| Aspect | Details |
|---|---|
| Role Type | Pure SDR - booking meetings only |
| Sales Motion | Outbound-heavy (95%+) |
| Deal Complexity | Transactional (your job is to book the meeting) |
| Sales Cycle | Your part: 1-3 weeks to book a qualified demo |
| Deal Size | N/A (you don't close deals) |
| Quota (est.) | 12-20 qualified meetings booked/month |
Company Context
Stage: Series A ($61M raised in Nov 2024, $65M total)
Size: ~70 employees
Growth: Actively hiring sales team, fresh capital to deploy
Market Position: Challenger in a rapidly crowding space - competing against Intercom, Ada, Sierra, Decagon, Poly.ai, and dozens of other voice AI/agent platforms. Category is hot but noisy.
GTM Reality
Pipeline Sources:
- 95% Outbound - you're building lists, cold calling, running email sequences
- 5% Inbound - occasional demo requests from website, but minimal inbound engine at this stage
- No PLG motion - this is enterprise software, not self-serve
SDR/AE Structure: You book meetings, hand off to AEs. Standard outbound SDR setup.
Support: Leadership is focused on training and development (per the post), but you're expected to be self-sufficient on prospecting activity.
Competitive Landscape
Main Competitors: Intercom, Ada, Sierra, Decagon, Poly.ai, Leaping AI, plus legacy providers like Five9/Genesys adding AI features
How They Differentiate: Agent Canvas platform with 90%+ resolution accuracy claim, multi-modal support (chat/voice), enterprise governance features
Common Objections:
- "We're already piloting AI agents with [competitor]"
- "Our support is too complex for AI to handle"
- "We just implemented [CCaaS platform] last year"
- "What's different about you vs. the other 15 AI vendors who called this month?"
Win Themes: Enterprise-grade governance, high resolution rates, handles complex workflows (not just simple FAQ bots)
What You'll Actually Do
Time Breakdown
Cold Calling/Emails (60%) | Research/List Building (20%) | Follow-ups/Nurture (15%) | Internal (5%)
Key Activities
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Cold Calling: 50-70 dials per day to VP Customer Support, Head of CX, Customer Service Directors. You're trying to get past executive assistants and office managers at mid-market and enterprise companies. Most calls go to voicemail. When you get someone live, you have 20 seconds to pitch why AI voice agents are worth a 30-minute demo.
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List Building: 1-2 hours/day researching companies with large support teams. You're looking at job postings (are they hiring support agents?), LinkedIn employee counts, press releases about customer growth. Ideal targets: companies with 50+ support agents, high call volumes, growing fast.
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Email Sequencing: Writing and sending personalized outbound emails (8-12 touchpoints per prospect). You're referencing their tech stack, recent company news, support job postings. Response rates are probably 1-3% if your targeting is good.
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Demo Qualification: When someone agrees to meet, you're running a 10-15 minute discovery call to confirm they're legit (do they have budget authority? actual pain? timeline?). You need to hand qualified opportunities to AEs, not tire-kickers.
The Honest Reality
What's Hard
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Cutting through the noise: Every support leader is getting pitched AI solutions constantly. "We're different" is not a compelling hook anymore. You need very tight, specific value props.
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Gatekeepers: Getting to VP-level buyers means going through EAs, office managers, and "just send me an email" blockers. Direct dials are hard to find for these roles.
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Long consideration cycles: Even when you book a meeting, deals take 4-6 months to close (for the AE). You won't see immediate impact from your work. Some of your best meetings won't close for quarters.
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Skepticism about AI: You're selling during peak AI hype, which means buyers are skeptical. They've been burned by AI vendors promising magic and delivering underperforming bots.
What Success Looks Like
- Booking 12-20 qualified demos per month that convert to opportunities for AEs
- 50-70+ dials per day with personalized, researched outreach
- Response rate of 2-4% on email sequences
- AEs accept 80%+ of your meetings as truly qualified (not tire-kickers)
Who You're Selling To
Primary Buyers:
- VP Customer Support / Head of Customer Experience (enterprise)
- Director of Customer Operations (mid-market)
- Sometimes CCOs or COOs at smaller companies
What They Care About:
- Reducing cost per contact / cost per resolution
- Handling volume spikes without hiring more agents
- Improving CSAT while deflecting simple inquiries
- Agent burnout and retention issues
- Speed to implement (they've been burned by 9-month implementations before)
- Security/compliance for regulated industries
Requirements
- Thick skin - you'll hear "no" or get hung up on 50+ times per day
- Discipline to make high call volume even when it feels futile
- Research skills to find the right targets and personalize outreach
- Willingness to learn enterprise software sales (complex buying committees, long cycles)
- Coachable attitude - this is an "invest in you" culture per the post, but that means taking feedback and iterating
- No prior experience required, but any B2B prospecting experience is helpful