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Revenue X-Ray

Find the revenue between your best and worst locations.

Two dealers score the same NPS. One sells 160 units a month, the other 68. The gap between them is not luck, it is behavior, and it is the largest pool of revenue most enterprises never measure. Three numbers you already know, and the X-Ray shows yours.

Inputs3, sliders
Timeunder a minute
Email requiredno
Grounded in$107M+ at one OEM

The estimate is calibrated to results, not to the size of the gap: it applies the surfacing rate we have actually delivered in your sector. Nothing leaves your browser.

Your variance X-Ray

01 · Sector

Where you operate

Sets the typical spread between similar locations and the sector surfacing rate.

02 · Locations

1,051

How many units

Products, locations, or services you run. Rough is fine.

505002K8K

03 · Revenue

$15.5M

Average revenue per unit

Annual. This is the base every gap is measured against.

$0.2M$2M$20M$100M

04 · Spread

2.4x

How far apart are similar units?

Your best quartile against your worst, on the same footprint and market.

Why this works: the score you already track (NPS, CSAT) is flat across these units. The revenue is not. Resultid finds the behaviors behind the difference and delivers them weekly.

Revenue Resultid would expect to surface from your network

$65.2M/ yr

Your sector’s realized surfacing rate of 0.40%, applied to $16B across 1,051 units. The behavior-driven share of the gap below.

The pool it comes from

$1.4B

Sits between your bottom half and your own median of $15.0M every year. Most of it is market and footprint. The headline is the share behavior explains.

Lowest-performing unitHighest-performing
Revenue todayRecoverable to medianYour median

$21.3M

Your top-quartile unit, per year. This is what the footprint can do.

$10.8M

Your bottom-quartile unit, same footprint, same market.

$10.6M

The gap per unit. Across 1,051 units, that is the pool. Resultid surfaces a calibrated share of it.

What it would take

Your number, next to the one we already delivered.

The $107M+ at a Fortune 500 OEM came from the same mechanism: dealers with identical scores and very different results. Here is how your network compares.

Fortune 500 OEM3,500+ units$107M+ surfaced
Your network1,051 units$65.2M est.
Per unit$31K$62K
01

Connect what you already have

CRM, surveys, call transcripts, reviews, service records. 500+ source types so far, integration is free. No new collection.

Week 1
02

Find the behaviors behind the gap

The engine compares your top and bottom units on everything they do, not what they score, and isolates the handful of behaviors that separate them.

Weeks 2 to 3
03

Deliver the brief to every unit

Each location gets its own prioritized actions, tied to revenue, every week. Operators act on 92% of them.

Day 30

Take it further

Turn this estimate into a number you can defend.

A 30-day diagnostic on one KPI using the data you already have. We show the variance in your real data, name the behaviors behind it, and put the first weekly brief in front of your operators. If we can’t show you revenue you didn’t know was there, you’ll know in the first meeting.

Keep this X-Ray

Copy a summary for your notes, or send it to a colleague. Nothing is stored; the numbers live only in your browser.

Your inputsAutomotive · 1,051 · $15.5M
Spread assumed2.4x (benchmark)
Rate applied0.40% of revenue

GDPR-compliant · nothing leaves your browser · no list

Methodology. Your units are modeled as a ranked distribution whose top-to-bottom quartile ratio equals the spread you chose (or your sector’s benchmark), scaled so the average matches the revenue you entered. The chart shows the pool: the sum of every unit’s shortfall below your own median. The headline applies your sector’s realized surfacing rate (0.30% to 0.45% of revenue, the rate behind Resultid’s $107M+ at a top-5 global OEM), adjusted up or down by how wide your spread is against the sector benchmark. Most variance is market and footprint; the headline counts only the behavior-driven share we have actually recovered.