yigityildiz0 Market Pricing Analysis
Use this for commercial and consumer market analysis, not tradable securities.
Read references/pricing-method.md, references/quality-evidence.md, and references/web-research.md. Use scripts/normalize_prices.py for comparable price and value calculations.
Workflow
- Define the decision: buy, sell, set price, enter a market, compare plans, or evaluate a competitor.
- Resolve the exact product/service variant, geography, date, currency, package size, taxes, shipping, discounts, contract length, renewal and cancellation terms.
- Capture current official pages and independent quality evidence. Treat testimonials, rankings, seller claims and affiliate pages as potentially biased.
- Normalize landed cost and unit price. Do not compare teaser monthly price with full contract cost or different quantities/features.
- Build a feature and quality matrix. Mark unknowns rather than inventing scores.
- Segment competitors into budget, value, premium and specialist positions based on evidence, not branding language alone.
- Explain price gaps through measurable features, service, reliability, brand, distribution, switching cost, or margin—not vague “quality”.
- Test scenarios for FX, discount expiry, shipping, tax, churn, volume and competitor response when relevant.
- Return the best value, best quality, cheapest acceptable, and overpriced/weak-evidence options separately.
Hard rules
- State the page date and country. Prices can vary by account, location and time.
- Include total ownership cost, not sticker price alone.
- Do not convert currencies without a timestamped FX rate supplied or sourced for the same decision date.
- Do not treat review volume as product quality without bias and sample checks.
- Do not scrape or bypass access restrictions; use available public pages and user-provided data.
- Do not recommend a higher price merely because it is premium-branded.
Output
Start with the buying/pricing decision. Show a compact normalized comparison, quality evidence, key trade-offs, competitor positioning, hidden costs, sensitivity and confidence. Identify which missing fact could change the winner.