CPG Demo · Beer Concept Test (n=803)

Non-Response Stress Test

Stress test on the published headlines

This tool does not estimate nonresponse bias. It asks how far the released headline would move under assumptions you choose about a hypothetical group the survey may have missed.

Runs on all five concept-test outcomes — purchase intent, package appeal, brand fit, high-quality perception, and premium perception. This is a sensitivity check on the released score, separate from the explanatory model.

Based on the beer concept-test consumer survey of 803 respondents; the valid-case base can differ by outcome.

How to Use This Tool

Pick an outcome, set the sliders, and click Calculate Scenario. Expand for details.

1. Select an Outcome

Choose which released score to stress-test: top-2 purchase intent, package appeal, brand fit, high-quality perception, or premium perception. Each has its own reported figure (e.g., 54.7% for purchase intent, 49.2% for package appeal). The percentage shown is the baseline used by this demonstration.

2. Set the Sliders

Two sliders define your sensitivity scenario. What share of the target sample never responded? sets the nonresponse share (or type a response rate and the slider follows). What would they have said? sets that group's top-2 rate for the outcome you selected. A live preview updates as you drag. This demonstration survey reports no response rate, so the first slider is an assumption here; a live study would set it from its reported rate.

3. Calculate the Scenario

Click Calculate Scenario. The tool applies the nonresponse assumptions directly and reports the resulting headline and percentage-point shift. The calculation is deterministic: it does not use Monte Carlo simulation or resampling.

4. Read the Verdict

The results section asks: how consequential is this assumption for the headline? It compares the scenario shift with a declared precision benchmark. This demonstration dataset carries no published margin of error, so the benchmark is calculated from the outcome's Kish effective sample size. It is not a survey-reported margin of error and does not estimate nonresponse bias. The page also flags a majority flip when the headline crosses 50 percent.

More options

Save and compare

Each run is saved automatically. Expand the Pinned Scenarios drawer at the bottom to compare previous runs side by side.

Reset and iterate

Click Reset to restore defaults. Try fixing one slider and sweeping the other to map where the headline would change.

Base

—% (benchmark ± —)

Baseline used by this demonstration

Scenario

—% (exact under assumptions)

Exact result under the stated nonresponse assumptions

Scenario replaces — respondents with the hypothetical group (—% of sample)

Could nonresponse have changed the headline?

How big is the shift?

Scenario shift —× the precision benchmark

Direction of change —

Magnitude of change — points

Verdict

Benchmark result —

The headline is — under this scenario.

The difference between the headline number and your scenario —.

Detailed Analysis

Baseline used here: the outcome at —%. Illustrative precision benchmark: ±— points.

Scenario-implied headline: —%. This value follows directly from the stated nonresponse assumptions; no resampling or Monte Carlo simulation is used.

The scenario replaces —% of the sample with a hypothetical group at —% on the outcome (gap: — pts).

Why a precision benchmark? This demonstration dataset carries no published, design-based margin of error to compare against. This demonstration therefore uses an illustrative benchmark derived from the outcome's Kish effective sample size. It is a comparison yardstick, not an estimate of nonresponse bias. A live release should use its reported margin of error or another declared precision threshold.

Baseline vs. scenario

Exact scenario calculation

The scenario result is plain arithmetic, not a simulation: it blends the observed rate, kept for the rest of the sample, with your assumed rate for the replacement group, in proportion to the replacement share. The only uncertainty yardstick on this page is the separately declared precision benchmark used to judge the size of the shift. For readers who want the formula: scenario rate = baseline + replacement share × (replacement-group rate − baseline).

Tipping frontier

Every combination of replacement share and replacement-group rate that would move the headline past — points — the precision benchmark the assessment above already uses. Inside the shaded band the headline holds; outside it, the headline tips. Your current scenario is the indigo dot.

The curves are exact, not simulated: because the scenario result is a plain blend of the two groups, the tipping point works out to the baseline plus or minus the benchmark divided by the replacement share. This reports sensitivity to stated assumptions about a hypothetical replacement group; it does not estimate actual nonresponse bias.

Another way to look at it: people differ in how likely they were to answer

The replacement test above treats the replaced share as one group with one rate. In reality people differ in how likely they were to take part, and the risk is that the people most likely to answer also tend to approve (or disapprove) more than everyone else. Two things decide how far that could push the headline: how strongly willingness to take part goes together with the outcome, and how much willingness varies from person to person. The poll cannot measure either, so you set them and the page shows what would follow.

How strongly does willingness to take part go together with the outcome? 0.10

0 = no link · positive = the people likeliest to answer lean toward the outcome · negative = they lean away

How much does willingness to take part vary across people? 0.50

0.05 = almost everyone equally likely · 2 = a few very likely, most unlikely