Find and Qualify Leads from Social Conversations
Build an AI-powered sales development agent that finds prospects expressing buying intent on social media and qualifies them before your competitors even notice.
The Problem
Your ideal customers are signaling their needs on social media every day. They're complaining about competitors, asking for recommendations, and discussing pain points your product solves. But traditional SDR workflows can't capture this opportunity:
Manual monitoring is impossible at scale
No human can track thousands of relevant conversations across Twitter, Instagram, and Reddit simultaneously
By the time you find a prospect, they've already bought
Social buying signals decay fast—someone asking for CRM recommendations today will have chosen one by next week
Generic outreach gets ignored
Without context from the actual conversation, your cold outreach looks like every other sales email
API complexity creates barriers
Building custom social listening tools requires managing multiple platform APIs, rate limits, and data pipelines
The Workflow
The AI SDR agent follows a sensor-brain-actor pattern that mirrors how your best human SDRs work, but at machine scale.
Example Queries
Ask Claude in natural language. Here are some examples with the underlying API calls:
Find prospects complaining about competitors
>"Find tweets where people are complaining about [Competitor] being too expensive or hard to use. Include their follower count and recent posting history."
Identify people asking for recommendations
>"Search Twitter for people asking for CRM recommendations in the last 7 days. Show me accounts with more than 1000 followers who seem to be business decision makers."
Monitor competitor mentions with sentiment context
>"Find Instagram posts mentioning [Competitor] where people are discussing problems or asking questions. Include the comment threads so I can see the full conversation."
Build a prospect list from industry conversations
>"Find users who have posted about "marketing automation" or "lead generation" challenges in the last month. Rank them by engagement on their relevant posts."
Why XPOZ
No Platform API Keys Needed
Access Twitter and Instagram data without obtaining developer credentials from each platform. XPOZ handles authentication and rate limiting through the MCP server.
Natural Language Queries
Ask questions in plain English instead of writing API calls. The Model Context Protocol translates your intent into the right tool calls automatically.
Rich Qualification Data
Go beyond basic profile info. Access authenticity scores to filter out bots, engagement metrics to identify active accounts, and historical posting patterns to understand prospect behavior.
Conversation Context at Scale
Pull complete discussion threads including replies, quotes, and comments. Your SDRs get the full picture of what prospects are actually saying—not just isolated keywords.
Unified Multi-Platform Access
One interface to query Twitter, Instagram, and Reddit. Build prospect lists that span platforms without juggling multiple tools or data formats.
Frequently Asked Questions
XPOZ provides the raw conversation data—Claude handles the intent classification. Because you control the prompts, you can tune the qualification criteria to your specific ICP and buying signals. The system improves as you refine your intent patterns based on which leads convert.
Yes. The workflow outputs structured data (prospect name, profile URL, conversation context, qualification notes) that can be passed to any CRM via API or exported as CSV. Many teams use Claude Code to build direct integrations with Salesforce, HubSpot, or their existing sales stack.
Particularly well. B2B decision makers often discuss work challenges publicly on Twitter. The profile enrichment features help identify job titles, company affiliations, and professional networks that matter for B2B qualification.
XPOZ maintains intelligent caching with automatic refresh for data older than one week. For time-sensitive prospecting, you can request real-time data using the `forceLatest` parameter, though this increases query latency.
Twitter profiles include authenticity scoring fields (`isInauthentic`, `isInauthenticProbScore`) that help filter out fake accounts. You can incorporate these scores into your qualification logic to focus on genuine prospects.
Get Started
Connect XPOZ to Claude in under two minutes:
Open Claude.ai Settings → Connectors
Add custom connector with URL: `https://mcp.xpoz.ai/mcp`
Authenticate with your account
Start with 100,000 free results per month. No credit card required. Begin by asking Claude to find people discussing problems your product solves—you'll have qualified prospects in your first session.
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