Surveys collect comparable responses from a defined group of people. They can estimate how common a need, view or experience is, but unclear questions and the wrong respondents create precise-looking answers to the wrong question. Marketways designs the sample, wording, sequence and measurement scale together and tests how participants understand them. The client receives stated evidence whose population and limits are clear.
The decision this method supports
We use Surveys & Questionnaires to help clients answer: Which questions and response measures will produce evidence that can support the intended analysis?
How the method works
A survey collects structured information from a defined population or sample. Questionnaire design translates the research question into wording and response options that participants can understand consistently. The analysis plan should be established before collection so every question has a purpose.
A business example
A demand survey should distinguish awareness, interest, purchase intent, ability to pay and actual past behaviour. Treating these as one question can produce an optimistic result that does not represent likely demand.
How the client uses the result
Surveys allow a business to collect comparable evidence from more people than interviews alone can reach. A well-designed survey can estimate the prevalence of needs, experiences or intentions and support analysis across relevant customer or employee groups.
What we deliver
We produce structured responses, coded qualitative evidence, observation records or a secondary-evidence base. The result include the population, collection conditions and limits needed for responsible interpretation.
Limits and complementary methods
Surveys provide breadth and comparability, but fixed questions limit depth and results remain exposed to coverage, non-response and response bias.
Selected methods and techniques
We select from these established methods according to the decision, evidence and operating conditions.
- CSAT measurement: Measure customer satisfaction from a stated question or set of questions for a defined transaction, interaction, product or relationship. Record the exact wording, response scale, timing, eligible population, sample, collection mode and scoring rule, including whether the result is a mean, top-box percentage or another calculation. State the valid-response denominator, treatment of missing answers, weights, response distribution and uncertainty so comparisons can be checked. CSAT describes satisfaction in the measured context; different questions or scoring rules are not automatically comparable, and the score is not a universal measure of experience, loyalty, retention or business performance.
- Customer survey design: Design a customer survey so its responses can answer a defined research question for a stated population and period. Translate the objective into clear constructs and questions; choose the sampling frame and method; specify scales, recall period, order, routing, language, collection mode and timing; pilot the instrument; and plan the scoring and analysis before fieldwork. Check coverage, non-response, accessibility, response burden, leading wording, common-method effects, missing data and any weighting needed. Good design reduces avoidable error but does not make a convenience sample representative or turn self-reported attitudes and intentions into observed behaviour.
- Employee survey design: Design the complete employee-survey process around a stated research question. Define the employee population and constructs, write and order questions, choose response scales and routing, plan invitations and sampling, specify anonymity and confidentiality protections, and set response monitoring, analysis and reporting rules before fieldwork. Survey design creates the instrument and collection plan. Questionnaire validation separately tests whether the questions and scores work as intended, while sampling determines which employees provide evidence about the target population.
- NPS measurement: Measure stated recommendation likelihood using the Net Promoter Score convention when that question is relevant to the customer relationship. Ask the defined 0-to-10 recommendation question and specify the population, timing, mode, valid-response denominator and weights. Classify 9-10 as promoters, 7-8 as passives and 0-6 as detractors; calculate the percentage of promoters minus the percentage of detractors, keeping passives in the denominator; and report the full distribution, sample size and uncertainty. NPS is expressed in score points from -100 to +100. It measures stated recommendation, and differences in wording, sampling or context can limit comparison; it does not directly measure actual recommendation, retention or growth.
- Pulse surveys: Run brief surveys at a regular cadence to monitor a small set of employee issues and detect changes that may need investigation. Define the constructs, eligible population, frequency, confidentiality thresholds and response rules, preserve a comparable core of questions and document any rotating items or instrument changes. Pulse describes the short recurring collection programme; longitudinal or repeated measurement describes the time-based research design, and a Pulse Trend Dashboard is an output used to display the results. Frequent measurement does not by itself reveal why a score changed or whether an intervention caused it.
- Questionnaire validation: Check that a questionnaire and its scoring are fit for the population, purpose and constructs they are intended to measure. Before launch, use expert review, cognitive interviews or piloting to test coverage, wording, interpretation, routing and response options. With suitable response data, examine item behaviour, reliability and evidence that the proposed dimensions and scores have the intended meaning. Questionnaire validation tests an instrument created through survey design; reliability is one part of that assessment, and factor analysis addresses specific questions about its underlying structure. A questionnaire can be consistent yet still measure the wrong idea.
- Survey / assessment design: Plan what a survey or assessment will measure, how questions or tasks will capture it, and how answers will be scored consistently.
- Survey research: Collect structured responses from a defined population to answer stated research questions. Specify the target population and sampling frame, probability or non-probability design, questionnaire and pilot, mode, field period and quality checks; then address eligibility, nonresponse, weighting, measurement error and sampling uncertainty before generalising. Question wording, order and response options can change results, and a large response count does not repair a biased frame or sample. Surveys can estimate reported needs, behaviour, attitudes or intentions when the design supports that use. A stated answer is not automatically observed behaviour, realised demand or evidence that one factor caused another.
- 360-degree feedback: Collect structured assessments of a person's observable workplace behaviour from several perspectives, commonly self, manager, peers and direct reports. Define the behaviours, ensure raters had a reasonable opportunity to observe them, keep source groups and disagreement visible, and apply confidentiality and minimum-group rules. The ratings are perceptions shaped by role and context; agreement is useful development evidence but is not proof of demonstrated competence or the cause of a performance result.
- Behaviourally anchored scorecards: Turn service or performance standards into a scoring procedure whose levels are tied to specific observable behaviours. Define when each behaviour has an opportunity to occur, distinguish failure from not observed or not applicable, train assessors and check whether they apply the anchors consistently. Behaviourally Anchored Rating Scales provide the reusable scale format; this method builds and applies a scorecard for a particular setting. Clear anchors improve interpretation but do not by themselves establish validity or reliability.
- Confirmatory factor analysis: Test whether a survey is actually measuring the underlying dimensions it was designed to measure, such as engagement, trust or satisfaction. Instead of letting the data decide the structure, start with a structure already expected and check whether the responses support it. Exploratory factor analysis asks what dimensions seem to exist; confirmatory factor analysis asks whether the dimensions already specified fit the data.
- Customer Effort Score: Measure customers' perceived effort in completing a defined task or interaction using a specified question and response scale. State the task, timing, eligible population, sample, exact wording, scale anchors, direction and scoring rule because common Customer Effort Score instruments differ and a high number can mean either more or less effort. Report the denominator, missing responses, weights, distribution and uncertainty. The reusable CES convention is represented separately as a framework; this method is the measurement procedure, and Customer Effort Score is the populated result. Perceived effort is distinct from counted process steps, satisfaction, loyalty and the causal effect of making a process easier.
Parent method family
Research & Evidence Collection explains how this method connects to adjacent methods and relevant services.
Related service families
These service families contain business questions supported by this method. Service pages link to the wider method family so readers can understand the complete analytical approach.