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Operations & ContentCompetitor & Market Research#competitor#matrix#strategy

Competitor Snapshot · 5-Dimension Quick Sweep

Compare 3-5 competitors across 5 axes; first sendable matrix in 15 minutes.

Pain addressed · Pain #2: ops gets asked to 'look at the competition' without an analysis framework — you scroll their site and end up more confused than before.

Competitor Snapshot · 5-Dimension Quick Sweep

Prompt·Advanced
Also available in 中文 →
You are an operations strategy analyst. I'm building a competitor sweep but haven't nailed the dimensions. First recommend 5 axes based on my product and purpose, then fill in the matrix.

# My product
{my_product_description}

# Competitors
{competitor_list}

# Purpose of analysis
{analysis_purpose}

# Task
## Step 1: Recommend 5 axes
Pick the 5 most informative axes. Each gets a one-line "why this".
NOT vague ones like "feature richness". Pick verifiable & comparable ones (e.g. "published auto-classification accuracy", "starter pricing for SMB").

## Step 2: Output the matrix
| Axis | Competitor A | Competitor B | Competitor C | My product |
- Concrete numbers/examples per cell, not "strong"/"comprehensive"
- Cite public sources below the table
- Mark "Not disclosed" / "TBD" where uncertain — don't fabricate

## Step 3: Give me 3 insights
1. My product's most obvious weakness
2. The "white space" no competitor has filled
3. If I can only push in one direction, your recommendation (with one concrete next step)

# Hard rules
- Don't fabricate numbers; mark "Not disclosed"
- Don't praise my product to flatter me
- Tag time-sensitive data with "as of {today}"
Saves ~90 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

    Pin down three things before opening the model: what your product is, the 3-5 competitors you actually compete with, and the real reason your boss asked (not 'comprehensive scan').

  2. 2

    Fill in the placeholders and run it. Read the 5 recommended axes critically — kill any that read as generic.

  3. 3

    Add one axis the model missed (it always misses one — usually pricing tier or onboarding flow) and rerun.

  4. 4

    Pick one or two highest-stakes cells per row and verify them directly on the competitor site or their G2 page — 15 minutes max.

  5. 5

    Lead the report with the three insights; the matrix is the appendix, not the headline.

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 Operations & Content 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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