Conversation Intelligence & Insight Extraction

Introduction

Stop spending hours manually researching leads! This playbook empowers Fay to become your automated research assistant, digging deep to find valuable, personalized information about your prospects. Supercharge your outreach by knowing more about who you're talking to.

This playbook instructs Fay to:

• Take a list of leads (or criteria to find new leads).

• Autonomously search various online sources to gather a comprehensive set of data points for each lead.

• Structure this information into an easily digestible format, ready for your sales or marketing team.

Structure of the Process:

1. Input: Provide Fay with your existing leads or specific criteria to find new ones.

2. Enrichment: Fay systematically searches for predefined data points (e.g., contact details, company information, recent activities, technologies used).

3. Synthesis: Collected data is organized and flagged for key personalization opportunities.

4. Output: Enriched lead data is delivered to your specified location (e.g., updated CRM, new spreadsheet).

Recommended Integrations:

• CRM (e.g., HubSpot, Salesforce): To pull lead lists and update records with enriched data.

• Spreadsheet Tools (e.g., Google Sheets, Microsoft Excel): For importing lead lists and exporting enriched data if a CRM is not used.

The Prompt

Objective: To enrich a list of provided leads (or identify new leads based on criteria) with detailed, hyper-personalized information for targeted outreach.
Process:
1.  **Input Leads/Criteria:**
    *   Option A (Existing Leads): Access the list of leads from [specify source, e.g., connected CRM, Google Sheet file ID]. The list should include at least [minimum required data point, e.g., Company Name, Website, or LinkedIn Profile URL].
    *   Option B (New Lead Criteria): Identify new leads based on the following criteria:
        *   Industry: [Specify desired industry/industries]
        *   Company Size: [Specify range, e.g., 50-200 employees]
        *   Location: [Specify city, state, or country]
        *   Recent News/Events (within last X days): [e.g., "new product launch", "hiring for specific roles"]
2.  **Data Enrichment (Autonomous Execution):**
    *   For each lead, find the following information:
        *   Verified Work Email Address.
        *   Direct Phone Number (if publicly available).
        *   1-2 key pain points or initiatives based on recent company news or job postings.
        *   Technologies used by the company ([specify types, e.g., CRM, Marketing Automation]).
        *   LinkedIn Profile URL for the individual and their company.
        *   Recent relevant social media activity by the individual or company.
3.  **Synthesize and Structure Data:**
    *   Compile all collected information for each lead.
    *   Flag the most relevant data points for personalization.
4.  **Output Enriched Data:**
    *   Update existing lead records in my [specify source, e.g., connected CRM].
    *   Alternatively, create a new file [specify format, e.g., Google Sheet, markdown table] with the enriched data.
Schedule: Run this enrichment process [e.g., daily at 9 AM for new leads, or weekly]

✨ Run on Fay

Customization Suggestions:

• Data Points: Customize the list of information Fay should find. Add items like funding rounds, specific job titles, or competitor mentions.

• Sources: As Fay's web browsing capabilities evolve, you could suggest specific types of websites or databases to prioritize for research.

• Output: Tailor the output format or destination. Have Fay create different views or summaries based on the enriched data.

• Scoring: Add a step for Fay to score leads based on the completeness or quality of enriched data found.

With this playbook, you'll transform raw lead lists into actionable intelligence, paving the way for more meaningful and effective engagement.