A CMO's questionnaire + analysis worksheet, adapted from Jenni Romaniuk's CBM template. All example data below is illustrative — not from any real study. Companion material to Lesson 02: How Markets Actually Work.
This is the tool the marketing science community uses to answer one question: when a category buyer thinks about buying, does our brand come to mind — and for which situations? The answer is not "yes" or "no." It is a matrix of associations that maps every brand in the category against every buying situation. That matrix is what you build here.
The kit has three parts. The questionnaire template that you deploy in the market. The analysis workbook logic that turns raw responses into a distinctiveness heatmap. And the interpretation heuristics that translate the heatmap into an investment decision.
Byron Sharp and Jenni Romaniuk built the case that brands grow not by persuading customers to prefer them, but by being mentally available in more buying situations. Two brands with the same market share look identical on the P&L. In the buyer's mind they are not. One is thought of for eight situations. The other is thought of for two. The brand thought of for eight has structural room to grow. The brand thought of for two is at its ceiling.
You cannot see this in Nielsen data. You cannot see this in your own sales data. You can only see it by asking category buyers directly, one Category Entry Point (CEP) at a time, and comparing your brand's associations against the category benchmark.
The questionnaire below is the standard instrument the Ehrenberg-Bass Institute uses. The analysis logic is the same chi-square deviation model the academic literature uses. What is new here is the packaging: a single-file kit any CMO can hand to a market research agency, or run themselves on Prolific for €400.
Fill in your category, your brand list, and your CEP list. The template renders below. Print it. Send it to your research vendor.
The questionnaire produces a big grid of ticks — every respondent, every CEP, every brand. That grid has four canonical outputs. Each answers a different strategic question.
Mental Penetration is the reach figure. Network Size is the depth figure. Mental Market Share is the competitive figure. Share of Mind is the overlap figure. Track all four. Growing brands typically show rising Mental Penetration and Network Size in parallel — one without the other is a red flag.
Once you have the raw response grid, every CEP block becomes three stacked matrices — one tab per CEP block:
| Matrix | What it is | What it tells you |
|---|---|---|
| ACTUAL | Observed number of ticks for each CEP × Brand cell. Row totals = how "popular" a CEP is. Column totals = how "big" a brand is mentally. | The raw scorecard. Big brands win most rows on absolute count — that is not distinctiveness, that is size. |
| EXPECTED | What the counts would be if brand size and CEP size were independent. Calculated by chi-square logic. | The category baseline. Every brand gets its "fair share" of every CEP proportional to its overall mental size. |
| DEVIATION | Actual minus Expected — the mental advantage or disadvantage for each CEP × Brand cell. | The distinctiveness map. Positive = brand over-owns this CEP. Negative = under-owns. Zero = category average. |
This is the standard chi-square "expected under independence" formula. It tells you what each cell would be if there were no brand–CEP association at all — just proportional sharing.
Illustrative numbers built for teaching. Imagine an oat-drink category study with 10 brands and ~1,100 respondents. Read the arithmetic from the top:
| Step | Value | What it means |
|---|---|---|
| Actual ticks: Meadowline × "tastes good" | 195 | 195 respondents said Meadowline tastes good |
| Row total: all brands × "tastes good" | 1,000 | "Tastes good" was a busy CEP — 1,000 total ticks |
| Column total: Meadowline × all attributes | 2,100 | Meadowline is the biggest brand in mental terms |
| Grand total (this CEP block) | 11,000 | All CEP × Brand ticks combined |
| Expected = 1,000 × 2,100 / 11,000 | = 190.9 | If tastiness were split proportional to brand size, Meadowline would get ~191 ticks |
| Raw Deviation = 195 − 190.9 | = +4.1 | Almost exactly at baseline — no distinctiveness signal |
| Deviation Index = 195 / 190.9 × 100 | = 102 | Meadowline is not distinctively tasty. It is category-average, which for the biggest brand is the danger signal. |
| Compare to NordicOat: Column total 1,800 (smaller mental footprint) → Expected on "tastes good" = 1,000 × 1,800 / 11,000 = 163.6. Actual = 177 → Deviation Index = 108. NordicOat over-owns tastiness relative to its size — a distinctive asset worth amplifying. | ||
| And Cloudmilk on a different CEP: Column total 1,500 (small barista-focused brand). On the "For coffee" CEP (row total 850, grand total 10,200), Expected = 850 × 1,500 / 10,200 = 125.0. Actual = 165 → Deviation Index = 132. Cloudmilk over-owns "For coffee" by 32 percentage points. That is the strongest distinctive asset in this fictional dataset — the entire brand strategy should protect it. | ||
Now scale that logic across every CEP × Brand cell in the study. You get a full distinctiveness heatmap. Every green cell is an asset your brand owns. Every red cell is a gap. Every column of mostly-white cells is a brand that is mentally big but distinctively nothing — the most dangerous position in the category.
Below: fictional deviation indices built to demonstrate the four patterns you should learn to spot. Eight CEPs × six brands. Green = over-indexed (distinctive asset). Red = under-indexed (mental gap). White = category-average.
How to read this heatmap — four patterns to spot:
FarmFirst (the sixth column) has no green cells and multiple red cells. That is a brand with weak mental structure — either it needs multi-year investment to build associations, or the strategy needs to change.
Minimum n = 300 category buyers per market. Below 300, individual cell counts (especially for smaller brands × niche CEPs) become too small to trust the chi-square math. Romaniuk's practical rule: at least 20 expected ticks per brand-CEP cell you actually care about. If your smallest brand of interest has a mental market share of 3%, you need ~700 respondents to get 20 expected ticks in most cells. Target n = 500 for a well-established category. Target n = 1,000 if you want statistically defensible sub-group cuts (heavy vs light buyers, region, demographic).
Three price bands. Prolific (~€3–4 per completed 15-min response, best sample quality, EU + UK + US). Bilendi / Cint / Toluna (~€2–3, larger panels, more targeting depth, DACH strong). Norstat / Respondi (traditional panel providers, best for regulated categories). For a 500-respondent DACH oat-drink study, budget €1,500–2,500 in fielding. Add €800 if you use a fieldwork agency to script the survey.
| Deviation Index | Meaning | What to do |
|---|---|---|
| > 120 | Distinctively over-associated. Your brand owns this CEP in the buyer's mind. | Amplify. Make this CEP a codified distinctive asset — put it in the tagline, the pack, the media. Byron Sharp's mental-availability compounding logic applies most strongly here. |
| 80–120 | Category-average. No distinctiveness — neither an asset nor a gap. | Watch. These CEPs are the middle ground where a small campaign push can create ownership if the category structure allows. Do not spend big to build here unless the CEP is strategically core. |
| < 80 | Under-owned. Buyers do not think of your brand for this CEP. | Decide: ignore (this CEP is off-strategy for your brand) or invest (this CEP is strategic and you accept a 3–5 year build). Do not attempt to close a <80 gap with tactical activity — the memory structure has to be built. |
| Whole CEP row where no brand indexes > 120 | Category white space. No brand owns this CEP. | Land grab — but weigh the potential first. An unowned CEP is only an opportunity if the CEP itself matters. Check the row total (how many respondents ticked any brand for this CEP) and cross-reference against category buying frequency for that occasion. A big-volume CEP with no owner is the single most valuable finding a study produces — a first mover with a consistent multi-year signal can own it. A low-volume CEP with no owner is usually just an irrelevant CEP for the category, not an opportunity. Rank white-space CEPs by row total (potential), then invest in the top two or three. |
| Whole brand column with mostly 100 ± 15 | Mentally big, distinctively nothing. | The Kraft Heinz problem. Big Mental Market Share, low Network Size, no ownable CEP. The brand grows with category tailwind and shrinks the moment a distinctive challenger enters. Fix by picking two CEPs and investing consistently for 24+ months. |
The study produces four deliverables the executive team should see, in this order:
The brand that knows its mental map plans its next three years around a real category picture. The brand that guesses runs the same campaign it ran last year, wonders why it did not work, and blames the media agency. The difference is one questionnaire and one workbook. Now you have both.