A diagnostic layer above the CRM

Your CRM records the work. This model asks what the work means.

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.

PRIMARY CONSTRAINT11.0days to proposal
Activity health106%
Automation win rate15.4%
Historical baseline4.8d
01 / THE PROBLEM

A missed quota does not tell you what to do next.

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.
02 / WHERE IT SITS

Keep the CRM. Add a diagnostic operating layer.

Sales Throughput is not designed to replace the system of record. It demonstrates what can happen when the existing evidence is mapped into a transparent model and delivered differently to the seller and the manager.

01 / RECORD

CRM and sales tools

Activities, accounts, meetings, opportunities, stages, timing, deal economics, and outcomes.

→
02 / CALCULATE

Deterministic model

Volume, stage conversion, velocity, benchmarks, sample size, and data completeness.

→
03 / DIAGNOSE

Constraint layer

The first material deviation, its mathematical consequence, and what the evidence cannot prove.

→
04 / ACT

Controlled experiment

One intervention, held variables, a decision threshold, and an auditable result.

What AI contributes

Faster mapping, normalization, pattern explanation, role-specific guidance, and iteration. It does not get to invent the underlying measurements or declare causation the evidence cannot support.

03 / THE MODEL

Three dimensions reveal the operating constraint.

VOLUMEHow much enters each stage?

Activities, conversations, meetings, qualified opportunities, proposals, and wins.

CONVERSIONHow efficiently does work advance?

Stage-to-stage rates reveal where targeting, messaging, qualification, and closing weaken.

15%19%60%35%
VELOCITYHow long does work wait?

Time exposes congestion that a conventional funnel report cannot see.

11.0 days
04 / SYNTHETIC CASE STUDY

ClearPeak Industrial Systems

A realistic industrial-sales demonstration with 50,000+ synthetic activities, eight representatives, multiple product families, and a deliberately seeded operating constraint.

BEFORE

Demand outpaced technical review

A new automation package increased opportunity complexity. The company’s existing proposal process had been designed for simpler products.

CONSTRAINT

Proposal time more than doubled

Turnaround moved from a 4.8-day historical baseline to roughly 11 days, concentrated in automation opportunities.

EFFECT

Downstream conversion declined

Top-of-funnel activity remained healthy while proposal-to-win performance weakened in the constrained product family.

EXPERIMENT

Fix capacity before adding volume

Reserve technical review capacity, hold prospecting constant, and measure whether turnaround and conversion recover together.

05 / TWO OPERATING VIEWS

The seller and manager should see the same system differently.

The public prototype is designed to be explored, challenged, and explained—not watched passively.

Open the model
01

Sales Professional view

See personal pace, the first underperforming stage, the effort required to compensate, and one controlled experiment—without a public leaderboard.

02

Sales Manager view

Inspect team throughput, named representative patterns, segment concentration, systemic capacity, and modeled interventions.

03

Auditable evidence

Select any personal stage to inspect the underlying records, exact denominator, benchmark, and reasoning behind the diagnosis.

04

Configurable sales motion

The demonstrated outbound chain is one model. Inbound, distribution, industrial, and complex technical sales require different stages and benchmarks.

05

Local CSV mapper

See how a Salesforce-style export can map into a common diagnostic model without uploading the raw file.

Built for credibility

The math should be boring. The explanation should be useful.

01

Deterministic evidence. Conversion, cycle time, volume, and revenue calculations do not depend on an AI model inventing an answer.

02

Auditable reasoning. The diagnostic explains which signals support the recommendation and what the evidence does not prove.

03

Local-first data handling. The prototype reads selected CSV files inside the browser and does not transmit or store them.

04

Data readiness before false precision. A production system should disclose missing fields, inconsistent stages, and insufficient samples before offering a confident diagnosis.

05

Honest scope. This is an interactive concept demonstration—not a claim of production CRM integration, category invention, or causal certainty.

READY TO PRESS ON THE MODEL?

Use the system. Change the assumptions. Challenge the diagnosis.

Launch Sales Throughput