Gmkt Interview Questions

---
name: gmkt-interview-questions
description: Prepares you for a marketing interview with likely questions drawn from the ad, STAR stories from your real experience, a mock interview where Claude asks and you answer, and feedback on each answer. Use for "run gmkt-interview-questions", "marketing interview questions", "graduate marketing interview", "mock interview for marketing", "STAR answers for marketing", "what campaign do you admire", "how do you use AI interview question", part of the Claude for Marketing Graduates Pack by Polar Bear.
---

# Marketing Interview Questions

## When To Use
The interview is on Thursday and you have never been asked to critique a brand out loud. Use this to work out what they are likely to ask, shape your real stories, and practise answering until it sounds like you.

## When Not To Use
If the next stage is a take-home task or a case presentation, use Marketing Task Prep. This is preparation only: never use it during a live interview.

## Inputs
- The ad, or your Job Ad Decoder output.
- Your CV and, if you have them, your proof project case study and How I Used AI Note.
- Two or three things you have noticed on the brand's public channels.
If you have none of this, I start from the job title and the marketing staples, and mark the output as a first draft.

## Approach
Competency questions are answered with STAR: situation, task, action, result. Prospects extends it to STARR with a final reflection on what you learned, which suits graduates because it turns a small example into evidence of judgment. The action is the core: what you did, "I" not "we". The failure it prevents: a four-minute story about a group project where the interviewer never finds out what you did.

## Workflow
1. Ask up to three questions: the interview format (panel, video, one to one) and length, who is interviewing if the invite says, and which of your experiences you most want to talk about.
2. Build likely questions from the ad's lines plus marketing staples: a campaign you admire and why, a number you would track and why, how you use AI in your work, and a critique of the brand's social, prepared from what you have seen in public.
3. Shape STARR stories from your real experience, in your words. I ask questions until the action is clear and specific; the result goes in only if it is real; the reflection says what you would do differently.
4. Run the mock interview: I ask one question at a time and wait for your answer, then follow up as an interviewer would ("why that channel?", "what would you do next?").
5. Give feedback on each answer: is STAR there, is it specific, is there evidence, is it too long. Feedback is about the answer, never a score of you, and never a script to memorise.
6. Draft three questions for you to ask the interviewer, from the ad and the brand.

## Output Format
```markdown
# Marketing Interview Questions
**Role:** [job title] · **Format:** [panel / video / one to one] · **Date:** [date]
## Likely questions
| Question | Why they might ask | Your story or angle |
|---|---|---|
| [question] | [ad line or staple] | [your story] |
## STARR stories
### [Story name]
- Situation: [your words]
- Task: [your words]
- Action: [what you did, "I"]
- Result: [real result, or "not known"]
- Reflection: [what you learned]
## Mock interview feedback
| Question | STAR present | Specific | Evidence | Length | One change |
|---|---|---|---|---|---|
| [question] | [yes / partly / no] | [note] | [note] | [note] | [note] |
## Questions to ask them
1. [question]
## Decision
[You decide by [day before interview] which three stories you lead with.]
```

## Done When
- Every must-have from the ad has a likely question against it.
- Each STARR story is from your experience, with "I" in the action.
- The mock interview asked one question at a time.
- Feedback covers the answers, not you.

## Quality Bar
- No invented results, follower counts or metrics in any story.
- The brand critique is built from public content you saw, fair and specific.
- The AI answer matches what you really do and what your How I Used AI Note says.
- No promise about the outcome of the interview.
- Claude asks and gives feedback; it never sits the interview for you or invents a story you did not live.

## Next
Run gmkt-job-ad-decoder (Job Ad Decoder) to start the next application.

## About the makers

This pack is made by Polar Bear, a consultancy built by ex-McKinsey founders with a dream to make AI work for People, not instead of them. We help our clients build people systems and AI-first ways of working, and we run our own company on Claude. If your team has outgrown the self-serve version, message Pauline (linkedin.com/in/paulinebertry).