Lead Qualification via DMs
Qualifies social DM prospects against three must-have criteria using Revieo and LLM to filter out unqualified leads before human engagement.
What it does
You save time by automatically filtering unqualified social DMs against three must-have criteria using Revieo and an LLM before you engage. This ensures only serious prospects reach your inbox for further conversation.
Step by step
- Set up a webhook listener in Revieo to capture incoming direct message events from social platforms.
- Define a JSON schema for lead qualification criteria including required fields like budget, timeline, and role.
- Configure the LLM prompt template with strict instructions to output only valid JSON matching the qualification schema.
Where the LLM does the work
- Generate nuanced follow-up questions based on vague prospect responses to clarify intent without sounding robotic.
- Assess tone and sentiment in replies to determine if a lead is genuinely interested or just browsing.
- Summarize key decision-making factors from the conversation history for the human sales team review.
Watch out for
Prospects might share sensitive personal data in chats so ensure the pipeline encrypts or redacts PII immediately upon receipt.
Context windows can fill up quickly during long conversations so implement a sliding window strategy to keep only recent relevant messages.
Tools that fit
Revieo Service Social DM interaction and qualification
The agent brief
Everything your agent needs, including the gotchas. Copy it and go.
You are helping me build the following AI agent workflow. ## Goal Lead Qualification via DMs: Qualifies social DM prospects against three must-have criteria using Revieo and LLM to filter out unqualified leads before human engagement. ## Specification - What it does: You save time by automatically filtering unqualified social DMs against three must-have criteria using Revieo and an LLM before you engage. This ensures only serious prospects reach your inbox for further conversation. - Trigger: Triggered by an event (Event · on new DM) - Autonomy: You approve along the way - Expected setup effort: about an afternoon - Tools/services involved: - Revieo: Social DM interaction and qualification - LLM: Filtering tire kickers based on criteria ## Known pitfalls, handle each one explicitly in your implementation 1. Prospects might share sensitive personal data in chats so ensure the pipeline encrypts or redacts PII immediately upon receipt. 2. Context windows can fill up quickly during long conversations so implement a sliding window strategy to keep only recent relevant messages. ## Reference implementation https://www.youtube.com/watch?v=b3yuAekDS4U (workflow template) Fetch and inspect this before building. If it matches my stack, adapt it; if not, rebuild the pattern with my tools. ## Process requirements 1. Before building: ask me which of the listed tools I actually use and what my platform is (n8n / Make / code / other). Do not assume. 2. Adapt the pattern to my answers; do not force the reference stack. 3. Address every pitfall above; tell me how you handled each. 4. Provide a test plan I can run before letting this touch real data. 5. Ask before any step that sends messages, modifies data, or spends money. Source: https://usecasesforagents.com/use-case/ai-lead-qualification-via-dms/ via usecasesforagents.com
Frequently asked questions
Can I use a different Social Media than Revieo?
Yes. Revieo is only the example social media in this recipe. The same flow works with Blotato, Facebook Graph API, Google Business Profile and Instagram Graph API. Swap the social media connection and keep the rest of the setup as written.
Want this running in your business?
This is what I do. I design and build AI agents like this one, and keep them running. If you want it set up for your team instead of doing it yourself, get in touch.
Who it's for
Built for founders and execs who need sales handled without hiring for it.
Sales teams can plug this into their own CRM and call cadence just as easily.