CallForge – AI Sales Call Processing & Insights Extraction

Automate sales call analysis with AI-powered insights for sales, marketing, and product teams.

Who is This For?

This workflow is designed for:

✅ Sales teams looking to extract structured insights from Gong call transcripts.

✅ Marketing professionals seeking AI-driven customer pain points & content strategy.

✅ Product teams needing feedback from sales calls to prioritize feature development.

What Problem Does This Workflow Solve?

Manually analyzing Gong.io sales call transcripts is slow, inconsistent, and lacks structured insights.

With CallForge, you can:

✔ Extract AI-powered insights about use cases, objections, competitors, and next steps.

✔ Provide structured marketing & product intelligence to enhance strategy.

✔ Automatically store call insights in Notion and Salesforce for easy access.

✔ Ensure resilience with automated reruns on failed workflows (handling Notion API limits).

✔ Improve decision-making with AI-powered competitor and sentiment analysis.

Key Workflow Features

🎤 AI-Powered Transcript Analysis

Uses AI to identify use cases, objections, competitors, and customer pain points. Categorizes insights for sales, marketing, and product teams.

📌 AI Agent Breakdown

🔹 Sales AI Agent – Extracts customer objections, pain points, competitors, and next steps.

🔹 Marketing AI Agent – Identifies recurring topics, keyword trends, and content opportunities.

🔹 Product AI Agent – Captures feature requests and AI/ML-related references.

📊 Structured Output Processing

Sales Data Processor → Stores insights in Notion & Salesforce for sales tracking.

Marketing Data Processor → Extracts SEO & content strategy insights for marketing teams.

Product AI Data Processor → Logs customer feedback to prioritize feature development.

💡 Competitor & Integration Analysis

Tracks competing products mentioned in calls.

Identifies integration needs, flagging workarounds used by prospects.

📢 Real-Time Slack Notifications

Alerts teams on workflow progress and completed call analyses.

🔄 Failure Resilience & Automated Re-Runs

If a Notion API limit is reached, the process resumes automatically.

How This Works

🛠 1. Trigger & Call Data Processing

The workflow retrieves Gong call transcripts and metadata. Normalizes data, correcting common mispronunciations like “n8n.”

🤖 2. AI Agents Analyze the Call

Sales Agent – Extracts actionable insights for sales follow-ups.

Marketing Agent – Identifies recurring themes and keyword trends.

Product Agent – Captures feature requests and AI/ML usage mentions.

📡 3. Data is Stored in Notion & Salesforce

Logs AI-extracted insights in Notion for structured tracking. Pushes sales-related data to Salesforce for team accessibility.

🔔 4. Slack Alerts for Teams

Notifies sales, marketing, and product teams about extracted insights.

Sample Output Data

1️⃣ Sales Insightsjson { “UseCases”: [ { “Summary”: “A manufacturing company wants to automate inventory tracking and reduce manual entry delays.”, “DepartmentTags”: [“Operations”], “IndustryTags”: [“Manufacturing”], “ImplementationStatus”: “Evaluating” } ], “Objection”: { “ObjectionTags”: [“Feature Limitation”], “Nature”: “The prospect wanted a deeper integration with their ERP system, which n8n currently lacks.” }, “CallSummary”: “The call focused on automation for supply chain processes. The prospect expressed interest but wanted confirmation on ERP integration capabilities.”, “NextSteps”: [“Schedule a follow-up demo for ERP integration.”] }

2️⃣ Marketing Insightsjson { “MarketingInsights”: [ { “Tag”: “Workflow Template Request”, “Summary”: “The prospect requested a template for automating CRM lead tracking.” } ], “RecurringTopics”: [ { “Topic”: “CRM Integration”, “Mentions”: 3, “Context”: “Discussed how n8n could sync CRM data automatically.” } ], “ActionableInsights”: [ { “RecommendationType”: “Tutorial”, “Title”: “How to Automate CRM Lead Tracking with n8n”, “Topic”: “CRM Integration”, “Rationale”: “The prospect expressed a need for CRM automation templates.” } ] }

3️⃣ Product Feedbackjson { “ProductFeedback”: [ { “Sentiment”: “Positive”, “Feedback”: “The external speaker praised the simplicity of n8n’s UI, making it easier for non-developers to automate tasks.” }, { “Sentiment”: “Negative”, “Feedback”: “The external speaker mentioned frustration over the lack of a dedicated ERP integration node.” } ], “AI_ML_References”: { “Exist”: true, “Context”: “The external speaker mentioned using AI for automating customer ticket categorization.”, “Details”: { “DevelopmentStatus”: “Building”, “Department”: “Support”, “RequiresAgents”: true, “RequiresRAG”: false, “RequiresChat”: “Yes: External App (e.g., Slack)” } } } How to Customize This Workflow

💡 🔗 Change Data Storage – Swap Notion for Airtable, HubSpot, or another CRM.

💡 📩 Customize Slack Notifications – Send alerts via email, webhook, or another channel.

💡 🛠 Modify AI Processing – Adjust AI models or processing prompts.

💡 📊 Add More Integrations – Sync insights with Pipedrive, HubSpot, or another CRM.

Why Use This Workflow?

✔ Automates Gong call transcript analysis, eliminating manual work.

✔ Improves collaboration by structuring insights for sales, marketing, and product teams.

✔ Boosts sales conversions by identifying objections and next steps.

✔ Enhances marketing and SEO strategy with AI-driven insights.

✔ Optimizes product roadmap decisions based on customer feedback.

This workflow scales AI-powered sales intelligence for better decision-making, content strategy, and sales enablement. 🚀