Candidate Experience

A candidate experience survey you can send this afternoon.

Fifteen questions covering the application, the communication gap, the interviews, interviewer conduct, fairness, and the decision. Copy them as written — or run them here and let an AI follow-up ask what actually happened behind a low score.

Free to start · No credit card · 20 free responses every month
Candidate experience surveyAnonymous
Question 11 of 15 · Fairness

How fair did the overall process feel to you?

12345
Very unfairVery fair
Follow-up

Which stage did that happen at, and what did you expect instead?

The third round was added after I’d already been told the second was final. Nobody explained why.

Under 5 minutesCoded by stage
The survey

Candidate feedback on your recruitment process, question by question.

Fifteen questions, grouped by the stage they ask about, so a low score points at something you can fix. Replace the bracketed placeholders with your company and role names, and route the two decision questions with display logic so nobody is asked the wrong one.

Group · 01

Applying

The part of your process candidates hit before they ever meet a person.

  1. 1How easy was it to find clear information about the role before you applied? (1 = Very difficult, 5 = Very easy)
  2. 2How long did the application itself take you to complete?
  3. 3Did the job description match the role as it was described in your interviews? (Yes / Mostly / No)
Group · 02

Communication

The most common reason candidate experience scores fall, by some distance.

  1. 4How well were you kept informed about where you were in the process? (1 = Very poorly, 5 = Very well)
  2. 5Were the next steps and the timeline explained clearly at each stage? (1 = Not at all, 5 = Completely)
Group · 03

The interviews

Ask about the sessions themselves, separately from the people who ran them.

  1. 6How well did the interviews give you a realistic picture of the job? (1 = Not at all, 5 = Extremely well)
  2. 7Were the questions you were asked relevant to the role? (1 = Not at all, 5 = Extremely)
  3. 8Did you get enough opportunity to ask your own questions? (Yes / Somewhat / No)
Group · 04

Interviewer conduct

Keep it behavioral. "Were they nice?" produces an answer nobody can act on.

  1. 9How prepared did your interviewers seem? (1 = Not at all prepared, 5 = Very prepared)
  2. 10How respectfully were you treated throughout the process? (1 = Not at all, 5 = Extremely)
Group · 05

Fairness

Ask it plainly, then give people room to say what happened.

  1. 11How fair did the overall process feel to you? (1 = Very unfair, 5 = Very fair)
  2. 12Was there any point where you felt you were not evaluated on your ability to do the job? If so, tell us what happened.
Group · 06

The decision

Two branches, one per outcome. Route them so each candidate sees one.

  1. 13If you accepted the offer: what made the difference in your decision? If you declined, withdrew, or were not selected: what one change would most have improved the experience?
Group · 07

Would you recommend applying

The pair worth trending. Everything above explains a move in this number.

  1. 14How likely are you to recommend applying to [Company] to a friend or colleague? (0 = Not at all likely, 10 = Extremely likely)
  2. 15What is the main reason for your score?

When to send it, and who to send it to

Send within a week of the decision, while the detail is still recoverable. A month later you get a mood rather than a memory.

Include the candidates you rejected. They are most of your sample and all of your reputational exposure, and theirs are the scores that end up on review sites.

Keep it anonymous and say so in the first line. A candidate who thinks a bad score gets back to their interviewer will not give you one.

The last two questions are the trendable pair: a 0–10 recommendation score and the reason behind it. Track that score by quarter and by hiring manager.

The sampling problem

Most candidate feedback is collected from the people who got the job.

Onboarding surveys are easy to run and comfortable to read, because they ask the one group whose experience ended well. The candidate who withdrew after the third unscheduled round, and the one who never heard back at all, are not in that sample — and they are the ones writing about you in public.

A candidate experience survey earns its place by asking the whole funnel, close to the decision, about specific stages rather than overall impressions. That turns a bad number into a fixable thing: not "our process is poor" but "four days pass between the second and third round and nobody tells them".

The candidates you rejected are the ones writing your reviews.
How it works

Send it. Probe it. Read it by stage.

The questions above are the whole instrument. What the platform adds is the follow-up and the coding.

1Step 1

Send

One link, everyone who interviewed.

Accepted, declined, and rejected candidates get the same survey within a week of the decision. Anonymous by default.

2Step 2

Probe

The follow-up does the digging.

When someone rates fairness a 2, the AI follow-up asks what happened — in the same sitting, while the detail is still there.

3Step 3

Read

Themes by stage, not one average.

Open-ended answers are coded automatically, so "communication" resolves into the specific gap people keep describing.

The other half

Structured interviewer feedback about candidates.

Candidate experience is one side of the ledger. The other is what your interviewers write down about candidates — and free-text notes typed up an hour after the debrief are where inconsistent hiring decisions come from.

Run the scorecard as its own short survey, sent to each interviewer immediately after their session and submitted before the debrief. Same platform, same analysis, and you can finally see where the candidate’s account and the interviewer’s account disagree.

  • A fixed scorecard per role, so everyone rates the same competencies
  • An evidence field beside each rating — the example, not just the number
  • Submitted before the debrief, so the room doesn’t anchor on whoever talks first
  • Stored alongside the candidate-side responses for the same requisition
The follow-up

What an AI follow-up adds to a feedback form.

A rating of 2 on fairness is a flag, not a finding. On a normal form you either let it sit there or you email the candidate a week later and hear nothing back.

Here the follow-up happens in the same sitting: it asks which stage, which moment, and what they expected instead. Most candidates answer, because they are already in the form and it takes another thirty seconds.

  • Probes a low rating immediately, not in a follow-up email
  • Asks for the specific stage and the specific moment
  • Runs as text, which is what most candidates will actually do
  • Open-ended answers coded into themes automatically
What you get back

Something to bring to the hiring review.

A
B
C
Output · 01

A score you can trend

The 0–10 recommendation question, tracked by quarter, by role, and by hiring manager.

Output · 02

Themes by stage

Application, communication, interview, decision — each with the volume of comments behind it.

Output · 03

Verbatims you can quote

The exact sentences, anonymized, ready to paste into the review deck where a summary would get argued with.

Ask the candidates you didn’t hire.Your first survey is free.

Copy the fifteen questions above, or run them here with follow-ups attached. Twenty free responses every month, no credit card, no sales call unless you ask for one.

GDPR-compliantNo credit card2-minute setup