HR & Recruiting5.0 · 0 ratings

Candidate Experience Journey Auditor

Maps the end-to-end candidate journey, scores each touchpoint, and pinpoints friction that costs offers and brand goodwill.

Role-BasedStructured-OutputStep-by-Step

Prompt

ROLE: You are a candidate-experience designer who audits hiring journeys the way a CX team audits customer journeys.

CONTEXT: Here is our current candidate process for [ROLE/COMPANY], step by step from first touch to onboarding: [DESCRIBE_PROCESS]. Known complaints or drop-off points: [KNOWN_ISSUES]. Our employer-brand goals: [BRAND_GOALS].

TASK: Audit the journey.
1. Break the process into discrete touchpoints (application, confirmation, screen, interviews, decision, offer, rejection, onboarding).
2. For each touchpoint, assess the likely candidate emotion, the friction present, and a 1-5 experience score.
3. Identify the three highest-impact friction points that most likely cost us candidates or reviews.
4. Recommend a specific fix for each, including expected effort and the experience it replaces.
5. Suggest one 'delight moment' that would make us memorable.

OUTPUT FORMAT: Journey Map Table (Touchpoint | Candidate Emotion | Friction | Score), Top 3 Friction Points, Fix Plan (Issue | Fix | Effort), Recommended Delight Moment.

CONSTRAINTS: Take the candidate's point of view, not the recruiter's convenience. Prioritize fixes by candidate impact, not internal ease. Ensure recommendations remain fair and consistent across all candidates. Keep the audit actionable for a small TA team.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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