saurabhshuklagrowisto Competitor Teardown Skill
Most competitive analysis is a wall of prose nobody acts on. This skill forces the landscape into a scored matrix and then answers the only three questions that matter: where do we win, where do we lose, and what is the wedge no one else can copy.
When to use
- Before writing positioning or homepage messaging.
- Before a launch, to pick the angle competitors cannot easily counter.
- When deals keep slipping to one competitor and you need to see the pattern.
When NOT to use
- For feature checklists to hand to product — this is about buyer-decision positioning, not a spec sheet.
- With only your own opinion as input — score dimensions from real buyer evidence (reviews, sales-call notes, win/loss), not gut feel.
Method
- Pick the dimensions a buyer actually decides on (not every feature — the 5-8 that move a deal).
- Score every player 0-5 on each dimension, from evidence.
- The engine returns:
- Wins — dimensions where you lead.
- Losses — dimensions where a competitor leads you.
- Whitespace — dimensions the whole category scores low on (own it before anyone does).
- Wedge — the single dimension where you are strong and the field is weak: your sharpest positioning.
Inputs
{
"brand": "YourBrand",
"competitors": ["Rival A", "Rival B"],
"dimensions": [
{"name": "Time to value", "weight": 3, "scores": {"YourBrand": 5, "Rival A": 2, "Rival B": 3}}
]
}
weight (1-3) reflects how much the dimension moves a buyer.
Output (JSON)
ranking[] (weighted total per player), wins[], losses[], whitespace[], and a single recommended wedge with the reason.
Run it
python scripts/teardown_score.py # built-in sample
python scripts/teardown_score.py in.json # your own landscape
Zero dependencies, no API keys. Deterministic scoring in scripts/teardown_score.py.