AI SDR Agent (Multi-Channel)
Outbound SDR agent that researches, personalizes, and follows up across email, LinkedIn, and SMS — and classifies replies.
The Problem
A human SDR sends 30-60 personalized emails a day before quality drops. The bottleneck isn't writing, it's research: figuring out who to contact and what hook works. An AI SDR stack (Clay for enrichment + Smartlead for sending + Lindy/n8n for orchestration) can run thousands of personalized sequences with reply classification — escalating only positive responses to a human. The pattern is now table-stakes for B2B agencies and any service firm with a defined ICP.
Best For
Workflow Steps
Define the ICP + qualifying signals
Specifics: industry, company size, role, geography, intent signals (hiring for X, just raised, using competitor tool). The narrower, the better the personalization downstream.
Build the enrichment waterfall in Clay
Source list from Apollo / LinkedIn Sales Navigator. Enrich each row with website summary, latest news, mutual connections, and a 1-line 'why now' hook generated by GPT-4 grounded in the enrichment data.
Generate personalized first-touch emails
Prompt the model with the enrichment payload. Output: 35-55 word email with one specific personalization line, one value prop, one soft CTA. Reject any email that doesn't pass a personalization check (unique line not present in 50%+ of sends).
Multi-channel sequence
Day 0 email → Day 3 LinkedIn connect (no note) → Day 5 follow-up email → Day 10 LinkedIn message → Day 14 break-up email. Throttle to 30 sends/day per inbox to protect deliverability.
Reply classification agent
Every reply gets routed to a classifier: positive (book meeting), question (auto-draft answer for human review), not now (move to nurture), unsubscribe (DNC). Only positives + complex questions hit a human.
Auto-book on positive
When the classifier sees a yes, the agent inserts a Calendly link OR proposes 3 specific times pulled from the rep's calendar. Confirms via reply, drops a calendar invite.
Weekly inbox + deliverability review
Monitor open rates, reply rates, spam-folder placement, sender reputation. Cool an inbox if open rate drops below 30%. Rotate inboxes and warm new ones continuously.
Copy-Paste Templates
Use these templates as-is or customize for your business.
You are writing a first-touch outbound email. Use this enrichment data: {{enrichment_json}}. Constraints: 35-55 words, one specific personalization line drawn from the data (not generic flattery), one value prop tied to a likely pain point for their role, one soft CTA (a question, not a meeting ask). Tone: peer-to-peer, no jargon, no exclamation marks. Output only the email body — no subject line, no signature.Classify this reply into exactly one bucket: POSITIVE (interest, asking to learn more, asking for time), QUESTION (specific question that needs an answer before they'll commit), NOT_NOW (interested but bad timing), NOT_INTERESTED (polite no), UNSUBSCRIBE (asked to be removed), OOO (out of office). Reply text: {{reply_body}}. Output JSON: {"label": "...", "confidence": 0-1, "suggested_action": "..."}Hi {{first_name}} — circling back one last time. If now isn't the right moment for {{value_prop}}, totally understood. I'll close the loop on my end. If anything changes, you have my email. — {{sender_first_name}}Orchestration pattern
Multiple specialized agents collaborate: a router/orchestrator delegates to sub-agents (researcher, writer, classifier). Higher capability, more failure surface — invest in observability before scaling.
Learn the agentic glossary →Failure modes & mitigations
Where this workflow tends to break in production — and what to put in place before you ship it.
Spam folder placement kills the campaign
Mitigation: Daily seed-list deliverability tests; cool inboxes that drop below 90% inbox placement.
Personalization line is generic
Mitigation: Programmatic dedup check against last 100 sends; reject if Jaccard similarity > 0.6.
When NOT to Use This
Do not run multi-channel outbound without monitored deliverability infrastructure (separate domain, warmed inboxes, SPF/DKIM/DMARC). Do not use for industries where cold email is restricted (healthcare, regulated finance to consumers). Skip if you can't handle 30+ inbound conversations/month — the bottleneck moves to your closer.
30-60-90 Day Implementation Plan
A phased approach to get this workflow running and delivering ROI.
Days 1–30
Foundation
- Set up core tools and integrations
- Configure basic workflow automation
- Test with a small set of real scenarios
- Train team on new process
Days 31–60
Optimization
- Review initial results and adjust triggers
- Add edge case handling
- Connect additional data sources
- Measure time saved vs. manual process
Days 61–90
Scale
- Roll out to full team or all locations
- Set up monitoring and alerts
- Document SOPs for the automated workflow
- Identify next workflow to automate
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