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Product ManagerCompetitor & Market Research#JTBD#competitor#PM

Competitor Feature Teardown · JTBD Lens

Through JTBD lens teardown 3-5 competitor features; see jobs being hired for and white-space to enter.

Pain addressed · Pain #2: PMs fall into the 'feature compare' trap — the real value is figuring out what job a user hires that competitor for.

Competitor Feature Teardown · JTBD Lens

Prompt·Advanced
Also available in 中文 →
You're a product strategist skilled at JTBD (Jobs-To-Be-Done). Teardown 3-5 competitor features through JTBD lens.

# My product + target users
{my_product_and_users}

# Competitor features to teardown
{paste_competitor_features}

## Per feature {n}: {one-line description}

### Job Statement ("When ... I want to ... so I can ...")
- When: specific situation
- I want to: action user wants done
- So I can: end result (emotional / social / functional gain)

### Key insights
- **Core struggle**: user's tension in one sentence
- **Old way vs this feature**: where the feature wins
- **Ignored job**: related job this feature doesn't solve

### Imitation vs disruption
Score: Imitation (70%) / Incremental (20%) / Disruption (10%) with reasoning.

## Global JTBD Map
| Job | Competitors competing | User satisfaction with the job |
- Satisfaction ≤ 6/10 = white-space
- No-one or all-bad = 🎯 your opportunity

## Strategic recs
1. One job to catch up on (high-sat but you must follow)
2. One job to flank (no-one or all-bad — you can own)
3. One job to ignore (competitors do it but it's a distraction)

# Rules
- Jobs ≠ feature names — job is user-side
- Satisfaction scores need evidence (reviews / NPS / interviews)
- One rec per category — force the strongest signal
Saves ~120 min per use

Open directly on your favourite AI

One click copies the prompt and opens the platform in a new tab — just paste (⌘/Ctrl + V).

Workflow · 5 steps

  1. 1

    Pick 3-5 competitor features. Describe each not just by name but by use case and observed user reaction (pull from G2 / App Store / Reddit threads / user forums).

  2. 2

    Write 'my product + users' specifically — not 'for everyone'.

  3. 3

    Fill the two placeholders and run it.

  4. 4

    The Job Statements are the load-bearing piece. If the model writes vague 'When' clauses ('when wanting to be productive'), push back for specific situations ('Monday 9am, 10 minutes before the weekly review').

  5. 5

    The 'flank' job in the strategic recs is the gold output — bring it to your next product planning session as the headline proposal.

Verify before you ship

AI's "almost right" is the #1 pain. Tick these off so reviewers can't find the obvious holes. (Checkbox state stays local — we don't track it.)

Done 0 / 5 checks

Why this prompt works

This prompt isn't a generic “write me a Competitor & Market Research”. It folds in the concrete context a Product Manager actually faces (target reader, info density, deliverable format). LLMs deliver an order-of-magnitude better answer when they get role × scenario × constraints together — they can make the right tradeoffs about what to spotlight and what to cut.

When to use

Best moment: you know roughly that you need to do a Competitor & Market Research, but you're stuck on “how do I even ask the AI?” Muscle memory has no template. Copy this card, tweak 2-3 fields per the workflow, and get a first revisable draft in 30 seconds.

Common pitfalls

  • Send without tweaking placeholders · the draft reads as default-GPT and your reviewer spots it in 3 seconds.
  • Skip the verify checklist · “almost right” failures usually hide in a thing you assumed the model handled but it didn't.
  • Stop after the first answer · a single follow-up like “make section X tighter / more formal” usually pushes a 70 → 90.

Variants & extensions

Want to use this card more aggressively? Three extensions:

  • Swap languages: both EN/ZH prompts ship in the card — use the EN version when shipping to a Western audience.
  • Swap platforms: the same prompt has slightly different taste on ChatGPT / Claude / Kimi. The recommended-platform pill marks the best fit.
  • Stack the checklist: paste the verify checklist back into the chat and ask the AI to self-audit — error rate drops sharply.
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