🎯 Today's Sales Pulse
Alpharun Rolls Out AI Coaching Agents, Boosting Inside‑Sales Conversions 15‑30%
Alpharun introduced autonomous AI coaching agents for its inside‑sales platform, targeting high‑volume regulated B2C call centers. The agents listen to every call, score it against a model built from the company’s own winning conversations, and deliver real‑time feedback to reps. Early customer data show conversion rates climbing 15‑30% within weeks of deployment.
🚀 Top Sales Headlines
Why Your Pipeline Problem Is a Measurement Problem
Something consistent is showing up across B2B SaaS right now: companies missing bookings targets are missing them by roughly the same percentage as their pipeline coverage is short.
RevOps Impact Newsletter
Alpharun Launches AI Agents for Inside Sales Coaching Software That Lift Conversion Rates 15-30%
Alpharun, an inside sales coaching software platform built for high-volume regulated B2C call centers, has launched autonomous AI coaching agents that monitor every customer call across a sales team, identify the behaviors driving conversions among top-performing reps, and train mid-pack reps to adopt those behaviors in real time. Alpharun’s coaching agents listen to every conversation […] The post Alpharun Launches AI Agents for Inside Sales Coaching Software That Lift Conversion Rates 15-30% appeared first on SalesTech Star.
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💬 Top Sales Social Posts
Tweet by @BrianLaManna_
70% of deals lost before stage 3. One prospect was bleeding early-stage pipeline. CRM data was trash. Reps all blamed different things. Nothing was backed by actual evidence. Here's how Gong's AI Theme Spotter fixed it in a single analysis. Filtered calls to only stage 1 and stage 2 closed-lost deals, ran a query across their entire conversation dataset, and surfaced the exact objections killing early pipeline - ranked by percent of deals involved and total $ amount. Then they used AI Builder to flip the script. Filtered to those same deal stages but closed-won, ran a prompt asking for a playbook on handling the objections, and got back a structured document with real examples and discovery questions. Each one linked to an actual call snippet so reps could hear how top performers handled it live. No more guessing. Just real, hard data and a playbook to fix it. Full video on YouTube: https://t.co/HdmItB05FX Other use cases?
Thread by @Askdrbrown
Revenue is a rearview mirror. By the time it drops, the problem is already months old. Track pipeline velocity, NPS trend direction, product usage depth, and sales cycle length. These move before revenue does. Stop managing by the lagging indicator. @AskDrBrown
