AI voice satisfaction surveys: questions and response review

Feedback interview: research question and episode

Define the experience to investigate, such as a first attempt to use a service. Ask what the person tried and what happened without inserting the cause into the question. State which staff decision each question can inform. Unexpected answers and participation refusals remain valid and should not trigger pressure for a positive rating.

Avoid assuming success or dissatisfaction. Asking what happened leaves room for unexpected answers.

Request examples without pressure

Ask one question at a time and clarify vague reports. Provide simple endings when people prefer to stop.

Identify the assistant and purpose. Do not invent a human researcher or personal experiences to create rapport.

Separate reports from interpretation

Review transcripts and recordings where available. For research-system webhooks, verify selected fields and destination receipt.

Summaries interpret reports. Preserve a route back to evidence rather than generalizing isolated suggestions to every customer.

Consider participation

Record invitation methods and responses. Voluntary participants may differ from nonparticipants.

Test short reports, corrections, unexpected subjects and ending requests. This example assumes no automatic campaigns, native research analysis or existing Tigy outcomes.

Investigate without suggesting causes

For fictional waiting complaints, ask where and what followed without suggesting a cause.

Use consistent rating criteria with optional context.

Test criticism and refusal without turning interviews into selling or debating experiences.

Define the decision the interview will inform

Before writing questions, describe the decision staff need to make. Examples include understanding difficulties in booking or finding missing service guidance. “Measure satisfaction” alone is too broad to guide question selection and interpretation. A useful objective identifies what could change after reviewing responses.

Bound the episode. Recent specific experiences help people recall events. Do not combine booking, service use and overall company relationships in one question; responses may address only one component. Identify the interaction being discussed without suggesting whether it should have been positive or negative.

Explain the conversation's purpose and participation through approved procedures. Agents should respect refusals and requests to end. Useful interviews do not require persistence until ratings appear, and criticism should not become an opportunity to sell. Include these boundaries in tests because an otherwise pleasant agent can still create pressure through repeated requests.

Define what will be recorded and who uses the material. Collection should follow the objective. Do not request additional personal details when episode descriptions support analysis. Agree with staff on handling actual help requests arising during interviews. Research participation and operational support are different processes; a caller describing an unresolved problem needs a truthful explanation of what the interview can do and which available path can provide assistance.

Build neutral questions that are easy to answer

Ask about events before general evaluations. “What happened after you requested the change?” leaves room for different experiences. “Was the change quick?” already selects the dimension respondents should consider and may hide other difficulties. The appropriate question depends on the decision being investigated, not on producing favorable answers.

Use one idea per question and avoid internal terminology. People need not know which team or system participated to describe what they heard. If locating a stage matters, ask intelligibly, such as whether something happened before or after speaking to staff. Double questions can produce answers that analysts incorrectly assign to both parts.

Do not include suggested causes unnecessarily. In a fictional case, someone reports waiting too long. Asking whether this happened because a system failed directs interpretation. First ask where they waited and what followed. If later clarification explores a possibility, keep it distinct from the respondent's initial account.

Test questions aloud. Sentences readable on screens may be too long to hear and retain. Check whether people answer without repetition and whether disagreement is comfortable. Test short replies as well as detailed stories: interview quality should not depend on every participant offering a polished narrative. Revise wording that consistently requires explanation before people can understand what is being asked.

Explore accounts without supplying the answer

Useful follow-up asks about details respondents already mentioned. If someone says they repeated information, ask which information or when. Agents should not complete stories with plausible causes. The task is to understand reported experience, not to produce a tidy explanation by filling gaps with assumptions.

In a fictional example, someone says, “It was resolved eventually, but it was exhausting.” Both parts matter. Record resolution and difficulty, then ask what made the process exhausting. Do not convert the whole statement into a positive evaluation simply because completion occurred. Mixed experiences are meaningful and should remain visible in analysis.

Confirm meanings when ambiguity persists. Asking whether someone means the wait before staff answered can be appropriate when context supports that distinction. Confirmation should allow correction, and final records must reflect actual replies. Avoid repeatedly asking the same interpretation until participants agree because that can replace clarification with pressure.

Set limits on probing. Short interviews should not explore every comment indefinitely. Prioritize details informing the decision and allow conversations to end. If operational needs emerge, explain available support paths rather than promising action the research agent cannot perform. Evaluate this transition separately so participants do not mistake listening to their complaint for confirmation that a ticket, booking change or other service request has been created.

Use scales without erasing comments and refusals

If research uses ratings, present scales consistently across interviews. Explain endpoints according to the defined instrument. Do not change meanings to make conversation easier or select scores from vague adjectives. Spoken presentation should be understandable without participants seeing a visual scale.

Responses such as “so-so” need not become numbers. Agents can request ratings where scripts require them, but should accept missing answers. Record refusals, uncertainty and questions not asked separately where relevant. These categories reflect different situations and should not all be treated as dissatisfied respondents or quietly removed without explanation.

After ratings, offer room for comments when objectives require understanding reasons. Low evaluations may reflect waiting, incorrect information or different expectations. Scores alone do not establish causes, and agents should not infer them without accounts. Preserve comments that qualify high scores too: someone may be broadly satisfied while identifying an important improvement.

During analysis, keep response bases clear. Do not merge participants providing ratings with those offering comments only. State periods and service types so comparisons do not hide sample changes. If one period includes mostly straightforward requests and another includes difficult exceptions, a score difference cannot automatically be attributed to the agent. Retain missing-response counts and explain how each measure was calculated before drawing operational conclusions.

Validate records and delivery to staff

Separate what participants stated from later interpretation. Labels such as “delay” can organize analysis but do not replace accounts. Preserve unresolved ambiguity instead of assigning themes with artificial certainty. Reviewers should be able to distinguish reported events from hypotheses about their causes.

Where external integrations store responses, define fields, states and episode identification according to need. Tools and webhooks require configuration, and delivery must be tested. Completed conversations do not establish that records reached analysis systems. Test missing responses, delivery failures and repeated events so records remain interpretable without duplicates or unsupported completion claims.

Check samples against material available through approved processes. Verify scores, negations and corrected answers. Recording “I did not like it” as praise changes conclusions even when the interview sounded natural. Include mixed statements and late corrections because these can expose errors hidden by short unambiguous answers.

Limit data exposure and assign access owners. Reports should provide enough evidence to understand findings without distributing unnecessary personal information. Define how staff review and correct misinterpreted records. A corrected record should preserve the basis for the decision rather than silently replacing participant meaning with an analyst's preferred summary. Distinguish interview completion, usable response collection and successful record delivery when evaluating operation.

Turn accounts into testable improvement hypotheses

People accepting interviews may have different experiences from those refusing or ending early. Describe invitations, participation and evaluated service types. Do not present limited samples as portraits of every customer. Participation conditions belong beside findings because they affect how broadly those findings can be applied.

Group themes using clear criteria and review examples that do not fit. Isolated criticism may reveal important risks without representing high frequency. Frequent themes may require investigation to distinguish similar causes. Keep counts tied to actual responses rather than treating multiple comments from one episode as independent participants.

In a fictional case, several accounts mention repeated information after transfer. One hypothesis is failed continuity. Before changing instructions, inspect transfer processes, information available to receiving staff and genuine need for reconfirmation. Reported repetition may have different explanations, and interviews alone do not establish which technical component caused it.

Choose an improvement and a test verifying its expected effect. Compare equivalent episodes afterward and preserve sample limitations. Feedback describes perceived experience and needs; operational evidence complements it when deciding changes and checking whether they helped. Keep unexpected outcomes visible as well. If a shorter opening reduces interview detail or a routing change shifts the participating population, acknowledge that effect rather than attributing every score difference to better service.