CRM and sales tools
Activities, accounts, meetings, opportunities, stages, timing, deal economics, and outcomes.
Sales Throughput is an interactive concept for turning existing sales activity, conversion, stage velocity, and deal economics into a defensible diagnosis—so a team can fix the limiting stage instead of demanding more of everything.
No sign-up. The public demonstration uses synthetic data. Any CSV selected in the mapper stays in your browser.
Salesforce, HubSpot, and other CRMs can capture the activity and report the output. But a missed number may still be caused by volume, targeting, the opening message, qualification, proposal capacity, next-step discipline, or deal selection. The same result can be produced by entirely different failures.
“Work harder” is not a diagnosis.
Activities, conversations, meetings, qualified opportunities, proposals, and wins.
Stage-to-stage rates reveal where targeting, messaging, qualification, and closing weaken.
Time exposes congestion that a conventional funnel report cannot see.
A realistic industrial-sales demonstration with 50,000+ synthetic activities, eight representatives, multiple product families, and a deliberately seeded operating constraint.
A new automation package increased opportunity complexity. The company’s existing proposal process had been designed for simpler products.
Turnaround moved from a 4.8-day historical baseline to roughly 11 days, concentrated in automation opportunities.
Top-of-funnel activity remained healthy while proposal-to-win performance weakened in the constrained product family.
Reserve technical review capacity, hold prospecting constant, and measure whether turnaround and conversion recover together.
The public prototype is designed to be explored, challenged, and explained—not watched passively.
Open the modelSee personal pace, the first underperforming stage, the effort required to compensate, and one controlled experiment—without a public leaderboard.
Inspect team throughput, named representative patterns, segment concentration, systemic capacity, and modeled interventions.
Select any personal stage to inspect the underlying records, exact denominator, benchmark, and reasoning behind the diagnosis.
The demonstrated outbound chain is one model. Inbound, distribution, industrial, and complex technical sales require different stages and benchmarks.
See how a Salesforce-style export can map into a common diagnostic model without uploading the raw file.
Deterministic evidence. Conversion, cycle time, volume, and revenue calculations do not depend on an AI model inventing an answer.
Auditable reasoning. The diagnostic explains which signals support the recommendation and what the evidence does not prove.
Local-first data handling. The prototype reads selected CSV files inside the browser and does not transmit or store them.
Data readiness before false precision. A production system should disclose missing fields, inconsistent stages, and insufficient samples before offering a confident diagnosis.
Honest scope. This is an interactive concept demonstration—not a claim of production CRM integration, category invention, or causal certainty.