Skip to content
MapMyStaff
Help Centre · Customer experience

What can you actually conclude from your survey responses?

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.

Immediate answer

Start with what the results actually show

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.

01Scope

Check what the view covers

To review satisfaction or feedback data cautiously, start by describing what the page actually displays before proposing a hypothesis.

Reading

Contextualized reading

Interpret a score, average, or comment from the question asked, period, response count, and filters actually visible.

Levels

Measurement and interpretation

Distinguish information displayed in the interface from the interpretation formulated by the team.

Objective

Describe before explaining

First describe what is observed before proposing a hypothesis, priority, or action.

Limit

A view remains partial

A view may contain missing data, response bias, or differences between customers who respond and those who do not.

02Indicators

Read available elements without making them say more than they do

The following elements describe possible types of reading. Their availability and presentation may vary according to the view used.

Summary

Score or average

Summarizes several responses into one value when such an indicator is displayed. This value may hide differences among individual responses.

Volume

Response count

Indicates the volume included in the view. It guarantees neither representativeness nor the absence of bias.

Context

Proportion, when a denominator is available

When a relevant denominator is genuinely available, a proportion can help place the response count in context.

Change

Distribution or change

When a distribution or change over time is displayed, it can help identify differences or movement. It does not prove their cause.

Qualitative

Comments

Comments add qualitative context, but an individual comment does not automatically represent all respondents.

Aid

Grouping or summary

When an automated grouping or summary is displayed, verify it against original responses and available context.

03Compare

Compare consistent views

A useful comparison seeks to limit methodological differences between views. It does not turn a variation into proof of causation.

  • Same reference: compare the same question or indicator.
  • Comparable scale: check that the scale and choices allow a reasonable comparison.
  • Consistent periods: review durations and contexts that can reasonably be compared.
  • Visible filters: keep comparable selections between views.
  • Known changes: record modifications made to the questionnaire or process.
  • Response count: account for volume and avoid strong conclusions when it is limited.
Remember: a variation between two periods does not prove a single cause, operational improvement, or future financial result.
04Contextualize

Contextualize comments and any groupings

Text responses may explain a perception, but they require cautious reading before qualification.

Comment

Individual experience

A comment describes an experience or perception in a given context. It does not automatically represent all respondents.

Summary

Displayed grouping

When a theme or automated summary is displayed, use it as a reading aid and verify it against available comments.

Limit

Avoid generalization

A word, theme, or small number of comments is not enough to demonstrate a cause or general trend.

Next step

Transition to a signal

A comment or grouping does not automatically become a diagnosis, priority, or case. Qualification is a separate step.

Method

Formulate an observation to verify

Use this six-step method to maintain a clear separation between what is displayed, what is assumed, and what will be decided.

01

Describe the observation

State factually what is visible in the view without immediately adding an explanation.

02

Specify the context

Recall the period, visible filters, and number of responses included.

03

Name the element

Identify the question, indicator, visualization, or group of comments concerned.

04

Record the limits

Note missing data, low volume, or methodological differences that may weaken the interpretation.

05

Define the verification

Indicate which human or operational step will confirm, qualify, or refute the observation.

06

Separate levels

Distinguish the observed fact, explanatory hypothesis, possible signal, and final decision.

Observed fact

What is actually displayed in the period and scope being studied.

Hypothesis

A possible explanation that still requires verification.

Possible decision

An action determined separately after reviewing context and limits.

Support

Document unexpected behaviour

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.

Contact support

Did this page help you interpret survey results cautiously?