Revenue intelligence insights for modern sales teams. New episodes weekly.
Win rate, deal size, sales cycle — everyone tracks these individually. But pipeline velocity combines all four dimensions into one number that tells you exactly how much revenue your pipeline generates per day. We break down why two teams with wildly different metrics can have 2x different revenue output, why almost nobody tracks velocity, and how AI-driven velocity monitoring predicts missed quarters before they happen.
Most sales orgs spend 90% of their tech budget on acquisition and almost nothing on retention — even though keeping a customer costs 5-7x less than winning a new one. We break down why account health scoring is the most underinvested metric in revenue operations, how AI pulls 40+ behavioral signals into a single score, and why companies with proactive health monitoring see 20-30% less churn.
Your best manager can deeply coach maybe three reps per week. What about the other fifty? We break down why traditional coaching fails at scale, how AI pattern detection across seven risk signals turns every manager into a 10x coach, and why data-driven coaching shouldn't cost $150/user.
B2B buyers are 70% through their decision before talking to a rep. By then it's too late. We break down how AI detects buying committee signals in real time — engagement velocity, multi-threading depth, sentiment shifts — and why the teams winning right now manage pipeline on data, not rep optimism.
Your pipeline number is based on what reps typed into a picklist — and it's maybe 40% accurate. We break down why AI-scored pipeline is consistently 25-35% lower than CRM data suggests, how behavioral signals expose dead deals nobody's called yet, and why every RevOps leader needs to stop forecasting on fiction.
The last two weeks of every quarter shouldn't be chaos — and if they are, that's not a sales problem, it's a systems failure. We break down why real-time deal scoring, automated pipeline monitoring, and continuous forecasting eliminate the fire drill entirely — and why leaders who still rely on weekly pipeline reviews are flying blind.
Your reps quietly gave up on half their deals three weeks ago — and nobody noticed. We break down why rep disengagement is the #1 pipeline killer, how AI detects activity drops before deals flatline, and why your coaching conversations should start with behavioral signals, not spreadsheets.
The average enterprise sales team spends $200-450/user/month on revenue intelligence tools. Three vendors. Three integrations. Three security reviews. We break down the math, explain why native Salesforce changes everything, and why your CFO will champion the switch to StratoForce AI.
We just shipped something massive: an 11-component Revenue Command Center that runs 100% natively inside Salesforce. Pipeline Inspector, Forecast Grid, Coaching Alerts, Deal Velocity, Conversation Intelligence, and an AI agent you can talk to — all at $10/user/month. We break down why this changes the revenue intelligence market.
The average B2B deal involves 6-10 stakeholders, yet most reps engage one or two. We break down why single-threaded deals die, how AI measures stakeholder engagement automatically, and the one question every sales leader should ask about their top ten deals this week.
MEDDIC and BANT aren't broken — but the way we use them is. We explore how AI transforms sales qualification from a checkbox exercise into continuous, evidence-based deal assessment. Champion validation, realistic timelines, and honest pipeline data.
Conversation intelligence is one of the most underrated capabilities in sales tech. We break down how AI transcript analysis turns your calls into actionable insights — and why you shouldn't be paying $150/user for it.