Valuation Methodology
Last updated: May 25, 2026
Real Site Worth publishes an automated value range with a confidence score. We avoid single-number precision because websites, domains, and creator assets trade in markets with uncertainty, negotiation, and incomplete public data.
1. What the methodology is for
The methodology is designed to give owners and buyers a conservative starting point for diligence. It is not a certified appraisal, broker opinion, investment recommendation, tax opinion, or legal conclusion. For the formal limits, see the Valuation Disclaimer.
2. Asset classification
Different assets need different paths. A revenue-generating content site is not valued the same way as a bare domain, a newsletter, an ecommerce store, a SaaS project, or a social account. The first step is to classify the asset type and decide which signals are relevant.
- Operating sites: traffic, monetization, authority, content quality, and business risk.
- Domains: name quality, age, search demand, authority, history, and sale-comparison context.
- Creator and social assets: audience quality, monetization mode, platform risk, transferability, and comparable-market context.
3. Signal collection
A report may use public records, submitted URLs or handles, analytics estimates, authority signals, archive/history signals, market comparables, owner-entered figures, and other non-identifying data. Not every signal is available for every asset. Missing or weak data lowers confidence rather than being silently filled with guesses.
4. Range and confidence
Real Site Worth outputs a range because a real buyer would diligence the asset, negotiate terms, and apply their own risk tolerance. The range generally widens when data is thin, signals conflict, the market is volatile, revenue quality is unknown, or platform risk is high.
The confidence score reflects how much reliable evidence supports the estimate. It is not a promise that the asset will sell inside the band. It is a transparency marker for uncertainty.
5. Conservative posture
We intentionally avoid inflated values. Where model inputs or comps point in different directions, the public estimate leans conservative. A conservative estimate is still imperfect, but it is more useful than a promotional number that cannot survive diligence.
6. Risk adjustments
The model considers downside signals where available. Examples include traffic concentration, monetization fragility, stale content, weak transferability, platform dependency, suspicious history, thin source evidence, extreme niche volatility, or claims that cannot be verified. These risks may reduce the range or lower confidence.
7. AI's role
AI helps explain and organize the report. It does not receive your personal information, and it is forbidden from inventing facts, fabricating sources, or presenting an automated estimate as professional advice.
AI may assist with classification and report narration using the domain or handle plus non-identifying report context. The explanation is still subject to the limits of the underlying data. See How we use AI.
8. What we do not publish
We keep private sourcing, proprietary calibration, internal field names, formulas, and implementation details private. Paid reports may explain more about the finished result, but they still do not expose private operating details.
9. What a report cannot replace
A report cannot replace verified revenue records, analytics access, contract review, account-transfer review, tax analysis, broker diligence, platform-term review, or buyer-specific negotiation. Before a meaningful transaction, verify the asset independently.
10. Corrections and feedback
If a report appears materially wrong, contact us with the domain or handle, the report date, and the issue. We may correct errors, improve a model, or explain why a public signal led to a particular result.