Nandini R. Raha shared the Brevian report showing reps only spend ~28% of their time selling. The rest is burned on manual research and managing "Frankenstein" stacks that cost ~$275k+. The Reality: We are paying high-ticket salaries for smart humans to do data entry. It’s a massive OpEx leak. 💡 The Insight: Relevance > Personalization. Scaling isn't about hiring more SDRs; it's about building a Reasoning Engine. You don't need a human to type every email; you need a system to decide why we are reaching out. 📖 The Playbook (Tech Stack: Clay + GPT-4o + Smartlead): I replaced the fragmented stack with a unified "Waterfall" workflow to reclaim that 72% lost time: Deep Enrichment (Clay): Aggregating 10+ data sources. If there's no valid "trigger," the system doesn't send. Reasoning Layer (GPT-4o): The LLM acts as a Research Analyst, writing 1-to-1 context-based messages. Infrastructure (Smartlead): Routing through a multi-inbox setup to maintain a real 85-95% inbox placement. 🎥 The Proof (Visual Walkthrough): I recorded a raw breakdown of the architecture. (Excuse the audio/mic quality, I recorded this in the flow of building, but the logic is all there): [https://www.loom.com/share/4cb0e981d86043bfabf3281a64903cc1 📈 The Outcome: Automated the grunt work so reps focus purely on closing. Happy to nerd out on the workflow logic if anyone is facing similar stack bloat!
