The Consumer Research Behind the QUDAL - Quality Medal

The QUDAL - Quality Medal recognitions are based on consumer surveys conducted through web-based questionnaires at the national level. Respondents evaluate a wide range of product and service categories by naming, in their own words, the brand or provider they personally perceive as offering the highest quality. Example categories include best-quality retail chain, chocolate, mobile phone, and more.

All questions are open-ended – no predefined options are provided – allowing respondents to freely name any brand. Once the survey is completed, ICERTIAS aggregates the responses, and the brand most frequently mentioned in each category is declared the No. 1 in Quality according to consumer opinion and perception. That brand is then awarded the QUDAL - Quality Medal status for the relevant category and country.
 

Recognising "No. 1 in Quality" based on consumer opinions

The ICERTIAS QUDAL - Quality Medal recognises products, services, and institutions that respondents in a given market perceive as delivering the highest level of quality in a clearly defined category, country, and time period. ICERTIAS QUDAL - Quality Medal does not measure, test, verify, or certify objective or absolute quality. It identifies perceived quality leadership, based on the opinions and experiences of consumers (or, where appropriate, screened professionals).

The ICERTIAS QUDAL - Quality Medal program is intentionally focused on quality as perceived by respondents, and is explicitly not a value-for-money program. Respondents are asked to focus on quality only, not on price, not on the price-quality ratio, and not on affordability.

ICERTIAS QUDAL - Quality Medal is also not an environmental, sustainability, climate, or ESG label. The research does not ask respondents to evaluate environmental or social impacts, and ICERTIAS QUDAL - Quality Medal must not be used or presented in a way that implies such performance.

 

Scope of research and categories covered

ICERTIAS QUDAL - Quality Medal studies are conducted at the country level and can cover a broad range of categories (for example, consumer goods, retail, telecom services, banking and insurance, automotive, public services, education, healthcare, and other complex sectors). Categories are typically structured into clear segments (for example, "milk", "family cars", "smartphones"), enabling meaningful comparisons of perceived quality within a defined competitive set.

 

Target populations

At ICERTIAS, every QUDAL - Quality Medal study begins with a clear definition of who is best positioned to answer each question. Target populations are carefully selected for each category to ensure that the individuals responding have the knowledge, experience, and context needed to make credible quality judgments. Whether addressing mass-market products or specialised professional services, this approach ensures that every data point comes from a respondent who truly understands the category being evaluated.

To ensure relevance and credibility, ICERTIAS QUDAL - Quality Medal uses different target populations depending on the category:

• Mass-market categories: samples drawn from the adult general population, designed to be broadly representative for that country.
   
• Specialised or professional categories: screened respondents with relevant experience and exposure (for example, professionals in medicine, law, finance, engineering), ensuring responses reflect informed opinions and lived category experience.

This approach reduces guessing and improves the validity of perceived quality judgements by ensuring respondents are capable of assessing the category they answer about.

 

The DEEPMA approach

ICERTIAS QUDAL - Quality Medal is based on ICERTIAS' DEEPMA (Deep Mind Awareness) methodology, developed in collaboration with expert partners (including GfK and PwC). DEEPMA is designed to move beyond superficial recall by encouraging respondents to pause and reflect on their real experiences, knowledge, and observed performance in the market.

In ICERTIAS QUDAL - Quality Medal, this reflection is directed explicitly toward quality as perceived by respondents, rather than price, promotions, or habit. The intent is to reduce the influence of advertising pressure and simple familiarity, and increase the weight of experience-based evaluation when respondents name the perceived quality leader.

 

Open-ended questioning and unprompted answers

To capture genuine perceptions of quality, ICERTIAS QUDAL - Quality Medal relies on open-ended, unprompted questions rather than closed or predefined answer lists. This approach reduces bias, avoids influence from brand visibility or advertising, and encourages respondents to reflect on their real experiences.

By allowing people to answer freely in their own words, the methodology produces more authentic, experience-based insights into which brands are truly seen as quality leaders.

ICERTIAS QUDAL - Quality Medal uses unprompted questions to capture authentic consumer (or expert) opinion. Respondents do not see predefined brand lists and are not guided toward specific answers.

A typical question format is:

"Based on your personal experience or that of people close to you, which product, service, or institution offers the highest level of quality in this category?"

Because answers are unaided, ICERTIAS QUDAL - Quality Medal results reflect what respondents themselves identify as the perceived quality leader in that category, country, and time period, without list bias.

 

What QUDAL - Quality Medal measures

ICERTIAS QUDAL - Quality Medal measures perceived quality leadership, based exclusively on respondent opinion and experience.

"Quality" is interpreted through the respondent's lens and category context, for example performance, consistency, service experience, taste, expertise, or overall satisfaction, without ICERTIAS imposing a single technical definition across all markets. The output is therefore a structured, research-based indicator of who is perceived as best in quality, not a technical certification of product performance.

What ICERTIAS QUDAL - Quality Medal does not measure:

A key element of ICERTIAS QUDAL - Quality Medal design is what it intentionally does not measure, verify, or claim.

• QUDAL - Quality Medal does not conduct laboratory testing, engineering audits, inspections, or technical benchmarking as the basis for winner determination. The medal reflects quality as perceived by respondents, grounded in their opinions and experiences, not an objective or absolute quality score.
• QUDAL - Quality Medal is not about affordability, price attractiveness, or the price-quality ratio. The program focuses solely on quality from the customer's perspective (consumer or qualified professional), independent of price considerations.
• QUDAL - Quality Medal does not measure or certify environmental impact, climate aspects, circularity, ethical sourcing, labour conditions, human rights, corporate governance, or other sustainability-related dimensions. These topics are intentionally out of scope.

 

Research standards and regulatory context

All ICERTIAS QUDAL - Quality Medal research is designed to follow the ICC/ESOMAR International Code on Market, Opinion and Social Research and Data Analytics, including requirements on legality, transparency, respondent protection, data stewardship, and clear separation of research from marketing.

EU consumer-protection and fair advertising principles

ICERTIAS QUDAL - Quality Medal is positioned as a narrowly defined, evidence-based recognition of consumer-perceived quality in a specific category, country, and time period. This positioning supports compliance with EU consumer-protection principles on clarity, substantiation, and non-misleading presentation, particularly relevant in the context of Directive (EU) 2024/825, which amends key consumer rules to better protect consumers against unfair practices and misleading information in sustainability-related contexts.

 

Technical and statistical foundations

ICERTIAS QUDAL - Quality Medal studies are conducted using Computer-Assisted Web Interviewing (CAWI). This mode supports privacy, reduces interviewer influence, and fits the open-ended, unaided DEEPMA approach by allowing respondents to answer thoughtfully and at their own pace.

Target populations and sampling frames:
 

• General population studies: sampling frames are constructed to reach adult consumers in the country.

• Professional studies: sampling frames are designed to reach screened professionals with relevant category experience and decision influence.

 

Quotas and sample balancing

General population samples are typically managed with quotas aligned to national structural distributions (commonly age, gender, region, and where appropriate additional variables). For professional samples, eligibility screening is mandatory and quotas may be tailored to role, seniority or authority, sector, company size, and years of experience.

Where minor deviations occur, modest weighting may be applied to align achieved samples with benchmarks, while keeping weights within controlled ranges to avoid distorting the dataset.

 

 

Statistical Foundations of QUDAL

 

ICERTIAS QUDAL - Quality Medal uses established quantitative research principles to achieve reliable inference at the national level. Where a general-population base sample of n interviews is used, the approximate margin of error (MoE) for an estimated proportion p at a given confidence level is:

MoE = Z × √( p(1 − p) / n )

For the conservative case (p = 0.5) at 95% confidence (Z ≈ 1.96), a sample size of n = 1,200 yields an MoE of approximately plus or minus 2.8 percentage points at the total-sample level (as in standard national opinion polling practice). Category- and segment-level robustness is additionally protected through coding discipline, data-quality controls, and internal review.

For professional populations, sample sizes are determined with reference to the eligible universe, expected dispersion of opinions, and the minimum precision needed for a robust conclusion.

ICERTIAS QUDAL - Quality Medal studies are designed to produce a nationally reliable view of consumer perceived quality leadership by combining disciplined sampling control with transparent statistical inference. The objective is to quantify consumer opinions and experiences of perceived quality in a defensible way, not to measure objective or absolute quality.

1) Quota design for general population samples

For general population waves, ICERTIAS QUDAL - Quality Medal typically manages fieldwork using quotas aligned to official structural benchmarks, most commonly age, gender, and region, and where appropriate additional variables such as settlement size or other census aligned indicators.

A practical way to express quota control is to define quota cells c = 1..C (for example, Gender × AgeGroup × Region). For each cell:

• Benchmark share in the population: B_c
• Achieved share in the sample: S_c
• Fieldwork is managed so that deviations remain small:

|S_c − B_c| ≤ ε_c for all c

Recruitment is actively monitored during fieldwork so that quota gaps are closed in real time. This reduces the need for heavy post fieldwork correction, improves stability, and is consistent with established professional practice.

2) Eligibility screening and quota balancing for professional samples

For professional or specialist categories, representativeness is defined relative to an eligible universe, not the general population. ICERTIAS QUDAL - Quality Medal therefore applies mandatory screening to confirm that respondents can credibly evaluate the category based on real involvement and experience.

An illustrative eligibility rule can be written as:

Eligible(i) = (Role_i ∈ R) AND (Experience_i ≥ t) AND (DecisionAuthority_i ∈ A)

Only respondents satisfying Eligible(i) proceed. Quotas may then be applied within the eligible universe to avoid over concentration (for example, across sector, company size, seniority, or years of experience bands).

3) Weighting and calibration, applied conservatively

Where minor deviations from quota targets remain after fieldwork, ICERTIAS QUDAL - Quality Medal may apply modest weighting to align the achieved sample with benchmarks while keeping weights within controlled ranges.

Let w_i be the weight for respondent i. For K benchmark variables, calibration targets can be expressed as:

Σ(w_i × x_ik) = X_k for k = 1..K

 

Where:

• x_ik is the respondent value or indicator for benchmark dimension k
• X_k is the known population total or proportion for benchmark dimension k

Raking (iterative proportional fitting) as an illustrative approach

Weights can be adjusted iteratively to match benchmark margins. For a benchmark margin k:

w_i(new) = w_i(old) × [T_k / Σ(w_i(old) × x_ik)]

This is repeated across margins until convergence (within tolerance). The key methodological principle is that weighting is a fine calibration tool, not a substitute for good sampling control.

Weight limits and trimming

To avoid distortion, weights are controlled:

w_min ≤ w_i ≤ w_max

If necessary, trimming is applied and then calibration is repeated. This ensures no small set of interviews carries disproportionate influence.

4) Measuring the impact of weighting

Because weighting increases variance, methodological due care includes quantifying its impact.

Kish effective sample size

A widely used measure is:

n_eff = ( (Σ w_i)² ) / (Σ w_i²)
 

Design effect due to weighting

The design effect can be expressed as:

DEFF_w = n / n_eff

 

A common approximation is:

DEFF_w ≈ 1 + CV(w)²

CV(w) = SD(w) / Mean(w)

These diagnostics make weighting controls measurable and auditable, and they directly connect weighting decisions to statistical precision.
 

5) Statistical precision: confidence intervals and margin of error (MoE)

ICERTIAS QUDAL - Quality Medal uses standard inference for proportions to express uncertainty at the national level.

Standard error for a proportion (simple random sample framework)

For an estimated proportion p_hat based on n interviews:

SE(p_hat) = √( p_hat × (1 − p_hat) / n )

95% confidence interval

With Z = 1.96 at 95% confidence:

CI_95% = p_hat ± 1.96 × SE(p_hat)

MoE = Z × √( p_hat × (1 − p_hat) / n )
 

For the conservative case p_hat = 0.5 (maximum variance) at 95% confidence:

MoE = 1.96 × √( 0.25 / n )

With n = 1,200:

MoE = 1.96 × √(0.00020833...)

MoE = 1.96 × 0.01443...

MoE = 0.0283... = ± 2.83 percentage points

Design adjusted precision (when weights or design effects apply)

When weighting or other design features increase variance, a conservative adjustment is:

SE_design(p_hat) = √( DEFF × p_hat × (1 − p_hat) / n )

MoE_design = Z × SE_design(p_hat)

This avoids understating uncertainty and reflects professional due care.
 

6) Category level robustness in open-ended measurement

ICERTIAS QUDAL - Quality Medal uses open-ended, unaided answers. Category outcomes therefore rely on the number of valid, attributable mentions after coding and cleaning.

Let:

M = total number of valid mentions in a category after coding and cleaning

m_j = valid mentions for brand j

p_hat_j = m_j / M

Then:

p_hat_j = m_j / M

Winner = argmax_j (m_j)

This is a transparent rule aligned with unaided questioning. Robustness is reinforced through coding discipline, data-quality controls, and internal review, ensuring that M and m_j reflect genuine, attributable respondent input rather than noise.

Illustrative close call diagnostic

For two leading brands with shares p_hat_1 and p_hat_2:

• d = p_hat_1 − p_hat_2

• SE(d) = √( [p_hat_1 × (1 − p_hat_1) / M] + [p_hat_2 × (1 − p_hat_2) / M] )

• z = d / SE(d)

This does not replace the counting rule, but it provides an additional statistical lens for internal review in tightly contested categories, alongside re-checks of coding and integrity flags.

7) Sample size logic for general and professional targets

For a target margin of error E at 95% confidence:

• n ≈ (Z² × p × (1 − p)) / E²

• Using p = 0.5 and Z = 1.96:

• n ≈ (1.96² × 0.25) / E²

• n ≈ 0.9604 / E²

Example, if E = 0.03 (3 percentage points):

• n ≈ 0.9604 / 0.0009

• n ≈ 1,067

Finite population correction (when the eligible universe is limited)

If the eligible universe size is N:

n_adj = n / (1 + (n − 1)/N)

This is relevant for specialist universes where the pool of eligible professionals is finite and tightly defined.

 

 

Data-quality controls and fraud prevention

To ensure results reflect genuine human opinion and experience, ICERTIAS QUDAL - Quality Medal applies layered data-quality controls appropriate to CAWI (for example, duplicate participation protections, speed checks, consistency checks, and technical validation). Only interviews that pass integrity thresholds are included in the final dataset.

Coding and normalisation of open-ended responses

Because the central ICERTIAS QUDAL - Quality Medal question is open-ended, ICERTIAS applies a structured coding and normalisation process to ensure fairness and comparability:

• creation and maintenance of coding frames (brands and providers and common variants)
• consolidation of spelling variants, abbreviations, and colloquial naming under a standard entry
• separation of umbrella corporate names from consumer-facing brands where category context requires it
• exclusion of answers that are too generic to map reliably to a specific market actor.

Coding is performed by trained analysts, supported where appropriate by automated text tools, with documentation and review steps designed to ensure replicability and consistency across categories and waves.

Handling unclear or invalid answers

To protect methodological integrity:

• nonsense, joke, or offensive strings are removed
• answers that cannot be linked reliably to a specific brand or provider are treated as invalid for winner determination
• where a category produces unusually high rates of invalid or non-attributable responses, the category may be withheld for that wave to avoid unstable or misleading outcomes.

 

Determination of winners and ties

Within each country and category, the ICERTIAS QUDAL - Quality Medal recipient is the brand or provider with the highest number of valid mentions after data cleaning, coding, and validation. Only the top-ranked entity in each category may carry ICERTIAS QUDAL - Quality Medal status for that category, country, and period.

Where the lead is narrow or patterns appear atypical, ICERTIAS applies additional internal checks (including coding re-validation and data-integrity review) before confirming results. In the rare event of an exact tie, ICERTIAS may recognise joint outcomes or withhold certification if evidence suggests instability.

 

Governance, independence, and conflicts of interest

ICERTIAS QUDAL - Quality Medal is designed to preserve independence and credibility by maintaining clear governance boundaries between research operations and commercial licensing. Results are determined by respondent answers in the validated dataset under the methodology, and the program is positioned as consumer-driven rather than jury-based or self-nominated.

Treatment of brands with serious regulatory issues

While ICERTIAS QUDAL - Quality Medal reflects perceived quality based on respondent opinion and experience, ICERTIAS recognises that serious, credible regulatory actions (for example, significant safety enforcement or major compliance breaches) can undermine consumer trust. ICERTIAS QUDAL - Quality Medal therefore includes a final screening stage in which brands or institutions that have been legally sanctioned or flagged by competent authorities for serious issues may be excluded, to protect the integrity of the medal and avoid misleading market signals.

 

Licensing and Usage Rules

Licensed companies receive detailed usage rules and communication guidelines. The medal may be used to communicate that, according to an ICERTIAS survey, respondents in a given market perceive the brand or provider as "No. 1 in Quality" in a defined category, country, and period.

 

To remain fair, accurate, and compliant, communications must always:

• specify country, category, and award period or fieldwork period
• clearly indicate that the recognition reflects consumer (or qualified professional) perception, based on opinions and experiences, not objective or absolute quality
• avoid implying broader characteristics not measured (including environmental, sustainability, or social superiority), consistent with EU rules on misleading practices and label implications, including Directive (EU) 2024/825.

 

Oversight and protection against misuse

ICERTIAS monitors market usage of the ICERTIAS QUDAL - Quality Medal mark and reserves the right to suspend or withdraw a licence where the medal is presented in a misleading manner, particularly where communication implies claims outside the program scope (for example, environmental or social performance claims not measured by ICERTIAS QUDAL - Quality Medal).

 

Methodological Integrity and Compliance

The QUDAL - Quality Medal research process is fully aligned with the ICC/ESOMAR International Code on Market, Opinion and Social Research and Data Analytics. This ensures ethical conduct, legal compliance and professional rigour at every stage of data collection and analysis.

Participant rights are protected throughout, while companies receive unbiased, perception-based insights grounded in real experience. QUDAL - Quality Medal does not measure environmental, sustainability or ESG performance; it focuses exclusively on how quality is perceived by respondents.

 

The Seven-Step QUDAL - Quality Medal Certification Process

To preserve accuracy and integrity, ICERTIAS applies a structured seven-step process for QUDAL - Quality Medal, from survey design and sampling through data validation and analysis to the final recognition of brands that people rate as delivering outstanding perceived quality.

 

 

The Seven-Step QUDAL Certification Process: