Contextualized reading
Interpret a score, average, or comment from the question asked, period, response count, and filters actually visible.
Start by checking the period, filters, number of responses, and comments actually displayed. You can then spot a trend or something worth reviewing without turning a few responses into a certainty.
A survey result should be read in light of the covered period, selected scope, and visible filters. Response count provides important context. When a relevant denominator is genuinely available, the corresponding proportion may also help contextualize results. The question type and scale used influence interpretation. A mean, distribution, or change over time, when displayed, describes only part of the situation. A variation or comment does not prove a single cause. Interpretation produces an observation for the team to verify, not automatically a priority, recovery case, or prediction.
To review satisfaction or feedback data cautiously, start by describing what the page actually displays before proposing a hypothesis.
Interpret a score, average, or comment from the question asked, period, response count, and filters actually visible.
Distinguish information displayed in the interface from the interpretation formulated by the team.
First describe what is observed before proposing a hypothesis, priority, or action.
A view may contain missing data, response bias, or differences between customers who respond and those who do not.
The following elements describe possible types of reading. Their availability and presentation may vary according to the view used.
Summarizes several responses into one value when such an indicator is displayed. This value may hide differences among individual responses.
Indicates the volume included in the view. It guarantees neither representativeness nor the absence of bias.
When a relevant denominator is genuinely available, a proportion can help place the response count in context.
When a distribution or change over time is displayed, it can help identify differences or movement. It does not prove their cause.
Comments add qualitative context, but an individual comment does not automatically represent all respondents.
When an automated grouping or summary is displayed, verify it against original responses and available context.
A useful comparison seeks to limit methodological differences between views. It does not turn a variation into proof of causation.
Text responses may explain a perception, but they require cautious reading before qualification.
A comment describes an experience or perception in a given context. It does not automatically represent all respondents.
When a theme or automated summary is displayed, use it as a reading aid and verify it against available comments.
A word, theme, or small number of comments is not enough to demonstrate a cause or general trend.
A comment or grouping does not automatically become a diagnosis, priority, or case. Qualification is a separate step.
Use this six-step method to maintain a clear separation between what is displayed, what is assumed, and what will be decided.
State factually what is visible in the view without immediately adding an explanation.
Recall the period, visible filters, and number of responses included.
Identify the question, indicator, visualization, or group of comments concerned.
Note missing data, low volume, or methodological differences that may weaken the interpretation.
Indicate which human or operational step will confirm, qualify, or refute the observation.
Distinguish the observed fact, explanatory hypothesis, possible signal, and final decision.
What is actually displayed in the period and scope being studied.
A possible explanation that still requires verification.
An action determined separately after reviewing context and limits.
Review the guide corresponding to configuration, sending, qualification, or support.
Learn about documented features for preparing surveys, collecting responses, and reviewing available results.
View the page →Learn how to prepare and review questionnaire sections, response formats, and language variants.
Read the article →Learn which elements to review to understand the sending options available in your journey.
Read the article →Learn how to review a response in context before treating it as a signal to qualify.
Read the article →If you observe unexpected behaviour in the results display, specify the page and journey used, visible filters at the time, the element, indicator, or visualization concerned, observed result, exact message, approximate date and time, and a sanitized screenshot if useful. Never send a password, authentication code, key, token, technical secret, or unnecessary personal information.