Share of Model Measurement Worksheet

This worksheet is the practical companion to Share of Model: The AI-Era Metric Every B2B Team Should Track. It turns the article’s frameworks into a working tool a CMO, CRO, or revenue leader can run in a single session. Use it as-is, or adapt the question set to your category. Download the printable PDF.

What This Worksheet Does

Share of Model is the percentage of relevant buyer questions where AI engines — ChatGPT, Perplexity, Gemini, and Google AI Overviews — cite or recommend you versus competitors. This worksheet measures it honestly: not raw mentions, but recommendation, weighted by buying intent and paired with accuracy. Work through the five assessments, locate your maturity level, and commit to an action plan. Mentions are vanity. Recommendation is pipeline.

1. Recommendation Ladder Assessment

Assessment 01

Score your position, rung by rung

Rung 5 — SelectedThe model names you as the best fit for this buyer. Score 1–5 for how often this is your position on high-intent questions.

Rung 4 — RecommendedYou are put forward as a strong option, with reasons. Rungs 4 and 5 are the pipeline zone.

Rung 3 — ComparedYou appear in a side-by-side with named rivals, but the recommendation may tip elsewhere.

Rung 2 — CitedYour content is quoted or linked as a source. Over-counted by most tools.

Rung 1 — MentionedYour name appears with no endorsement. The vanity zone. Your Ladder score is the sum of Rungs 4 and 5, out of 10.

2. Qualified Share of Model (QSoM) Calculator

Assessment 02

QSoM = (Σ intent weight × ladder multiplier) ÷ (Σ intent weight) × 100

InputsBuild a fixed set of 20–40 real buyer questions from live deals. Score each appearance by ladder position and weight by intent.

Weighting systemIntent weight: High = 3, Medium = 2, Low = 1. Ladder multiplier: Recommended or Selected = 1.0, Compared = 0.5, Cited = 0.3, Mentioned = 0.2, Absent = 0.

Worked exampleOn a ten-question set, raw Share of Model can read 90% while Qualified Share of Model reads 37% — because you are everywhere on low-stakes questions and absent on the high-intent one that decides deals. The PDF includes the full calculation grid.

3. Description Drift Audit

Assessment 03

Visibility without accuracy is a liability

Messaging consistencyThe engines describe your category, product, and ideal customer the way you do. Score 1–5.

AI interpretation consistencyThe engines agree with each other about what you do and who you serve.

Positioning consistencyYour differentiator survives the model’s summary instead of being averaged into the category.

4. Share of Model Measurement Stack Assessment

Assessment 04

Rate each capability, 1 to 5

VisibilityWe know monthly which engines surface us for our top buyer questions.

CitationsWe track when our content is quoted or linked as a source.

ComparisonsWe monitor the head-to-head comparisons the engines generate about us.

RecommendationsWe measure how often we reach Rungs 4–5, not just Rung 1.

Conversion indicatorsWe tie AI-shaped research to assisted pipeline and influenced deals.

5. Maturity Model

Assessment 05

Locate your level — target one level up per quarter

Level 1 — InvisibleThe engines rarely name you. Competitors own the shortlist and you find out by accident.

Level 2 — MentionedYou appear in lists but never with endorsement. High raw share of model, near-zero qualified.

Level 3 — ConsideredYou show up in comparisons on high-intent questions, but the recommendation usually tips elsewhere.

Level 4 — RecommendedThe engines put you forward with reasons on the questions that precede real deals.

Level 5 — PreferredYou are the default answer in your category, described accurately, hard for rivals to dislodge.

6. Executive Action Plan

Assessment 06

Immediate, 30-day, and 90-day moves

Immediate (this week)Assemble 20–40 real buyer questions, run them across four engines, record your baseline, and name one accountable owner.

30-dayRebuild your highest-intent pages as citable substance, fix the worst Description Drift at the source, and publish one original framework only you can offer.

90-dayStand up a corroboration program, re-run the question set, and report the movement in Qualified Share of Model to leadership.

This worksheet sits alongside the AI Visibility Architecture (the supply side) and the AI Buying Committee (the demand side) as the measurement leg of the ERM Advisory AI Operating System. For help running a baseline, work with E.R.M. Advisory directly.

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