OpenClaw AI SDR Workflow

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AI SDR Workflow

Build a complete AI sales development system via OpenClaw Ultra. From defining your ICP and researching target accounts to running multi-channel outreach sequences, classifying replies, qualifying leads, and handing off hot prospects to your closing team, manage your entire SDR operation from a single chat interface.

Core System Overview

💡 INFO
This is a closed-loop AI SDR workflow. OpenClaw Ultra handles lead ingestion, account research, message personalization, sequence execution, reply triage, lead qualification, meeting booking, and CRM handoff, so you can generate qualified pipeline continuously without switching between prospecting tools.

System Layer	Core Function	Final Output
Ingestion Layer	ICP definition, lead source integration, list building	Scored and segmented target account list
Research Layer	Account enrichment, trigger event detection, pain hypothesis	Researched account profiles with hooks
Outreach Layer	Multi-channel message generation, cadence design	Channel-specific outreach sequence
Execution Layer	Cross-channel sending, engagement tracking, adaptive follow-up	Executed campaign with signal capture
Reply Layer	Inbound triage, intent classification, FAQ response	Categorized reply log
Qualification Layer	BANT scoring, fit + intent + timing scoring, disqualification rules	Scored leads with routing decision
Handoff Layer	Meeting booking, CRM sync, handoff documentation	Qualified leads passed to sales with full context
Optimization Layer	Performance analysis, ICP refinement, message iteration	Improved conversion rates next cycle

Prerequisites

Item	Requirement
OpenClaw Ultra	Installed and running
ICP Defined	Industry, company size, role, and geography for your ideal prospect
Lead Source	Database, CSV list, or CRM export of target accounts
CRM Account	(Recommended) Active account with API access for lead handoff
Sending Domains	(Recommended) 1–2 secondary domains with SPF/DKIM/DMARC configured for cold email
Calendar Access	(Recommended) Google Calendar or similar for automated meeting booking

Step 0 — Initialize Your AI SDR System

Set up OpenClaw Ultra as your dedicated AI sales development representative.

Operation Steps

Open OpenClaw Ultra new chat session
Prepare your ICP definition, target account list, and sending domains
Paste the initialization prompt

Ready-to-Use Prompt

Act as my AI sales development representative.

My ICP:
- Industry: [industry]
- Company size: [size range]
- Target roles: [job titles]
- Geography: [regions]
- Ideal customer profile: [brief description]
- Lead source: [database, CSV, or CRM]
- Sending domains: [domain1.com, domain2.com]

Build a complete AI SDR system that covers:
- lead ingestion and account scoring
- account research and trigger event detection
- multi-channel outreach creation (email + LinkedIn)
- sequence execution and engagement tracking
- reply triage and lead qualification
- meeting booking and CRM handoff

Step 1 — Define Your ICP and Ingest Leads

Set the targeting criteria and bring your account list into the system.

1.1 Define Your Ideal Customer Profile

Define my target account criteria for this SDR campaign:

Target parameters:
- Industry: [industry or industries]
- Company size: [employee count or revenue range]
- Departments: [departments to target]
- Job titles: [specific roles]
- Geography: [countries or regions]
- Tech stack: [tools they use, if relevant]
- Buying triggers: [events that signal intent — funding, hiring, product launch]

Return a structured ICP document with:
- Primary targets (best fit)
- Secondary targets (good fit)
- Exclusion criteria (who not to pursue)
- Buying committee map for each target account type
- Trigger event priority list ranked by conversion likelihood

1.2 Ingest and Score Your Lead List

Import and score my target account list against the ICP:

Lead source: [CSV / CRM export / database name]
Columns available: [list of columns in your data]

For each account:
- Score ICP fit from 1-5 based on firmographic match
- Score data completeness from 1-5 (missing contact info, empty fields)
- Flag accounts with buying triggers in the last 90 days
- Assign priority tier: hot (score 9-10), warm (score 6-8), explore (score below 6)

Return a prioritized account table sorted by combined score:
| Account | ICP Fit | Data Quality | Triggers | Priority | Next Action |

Step 1 Output

Prioritized target account list with ICP scores and buying trigger flags.

Step 2 — Research Accounts and Find Angles

Deep research each target account to build personalized outreach angles.

2.1 Research Target Accounts

Research the top-priority accounts from my list:

Accounts to research: [list of account names or domains]

For each account, gather:
- Company description, recent news, and funding history (last 6 months)
- Leadership changes, hiring trends, and org structure
- Tech stack they use and recent technology changes
- Public announcements (earnings, product launches, partnerships)
- Key decision-makers with LinkedIn profiles and role context

Return a research brief for each account with:
- Company snapshot (industry, size, revenue trend)
- Recent trigger events with dates
- Decision-maker table (name, title, tenure, LinkedIn URL)
- Personalization hooks ranked by relevance

2.2 Generate Pain Hypotheses and Outreach Angles

For each researched account, generate outreach angles:

Account research briefs: [paste from 2.1]

For each account:
- Identify 2-3 potential pain points based on their industry, size, and recent events
- Map each pain point to your value proposition
- Generate a personalized hook for the first-touch message
- Rate each angle by likely relevance (high / medium / low)

Return an angle brief per account:
| Account | Pain Hypothesis | Relevant Trigger | Hook Suggestion | Angle Score |

Step 2 Output

Research briefs with trigger events, personalization hooks, and ranked outreach angles per account.

Step 3 — Build Multi-Channel Outreach Sequences

Create personalized sequences that coordinate email, LinkedIn, and optional phone touches.

3.1 Write Channel-Specific First-Touch Messages

Write first-touch messages for my outreach campaign:

Target account: [account name]
Decision maker: [name, title]
Personalization hook: [trigger event or pain hypothesis from step 2]
Value proposition: [what we offer]

Create:
1. Cold email (under 120 words, subject line under 50 characters, one CTA)
2. LinkedIn connection request note (under 200 characters, conversational)
3. LinkedIn message (for after connection accepted, under 80 words)

Requirements:
- Reference the personalization hook in the first sentence of each channel
- No attachments or links in the first message
- CTA should be low-friction ("quick question" or "15-minute call", not a demo request)

Return each message with [bracketed placeholders] for custom fields.

3.2 Build an Adaptive Multi-Channel Cadence

Build a 21-day multi-channel outreach sequence for my target accounts:

Channels: email + LinkedIn (phone optional)

Cadence structure:
- Day 1: Email — personalized intro with hook
- Day 3: LinkedIn — send connection request with personalized note
- Day 7: Email — follow-up with new angle or industry insight
- Day 10: LinkedIn message — after connection accepted, short value-add
- Day 14: Email — case study or social proof angle
- Day 21: Email — breakup message, leave the door open

Adaptive rules:
- If prospect replies at any point, exit sequence and route to reply handling
- If prospect opens email 3+ times without replying, trigger a priority follow-up
- If LinkedIn connection is not accepted within 7 days, skip LinkedIn touches
- If email bounces, remove from sequence and flag for data verification

Return the full sequence with timing, channel, message content, and branching rules.

Step 3 Output

Multi-channel outreach sequence with adaptive branching rules, ready for deployment.

Step 4 — Execute Sequences and Track Engagement

Launch your outreach campaigns and monitor prospect engagement signals.

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