Finding Comparable Domain Names

Alex Tajirian
August 12, 2011

Determining which domain names are comparables is an imperative for the market approach to valuation.  The larger the number of comparables, the more accurate the value estimate. The problem is that identifying such domain names is far more complicated than most appraisers— professionals or domainers—realize.

A recent paper by professors Gilbert and Hoegl titled “In Praise of Dissimilarity” and published by the Sloan Management Review generalizes the concept of similar products and markets. The article notes that Intel and McAfee share the theme of security even though, under the traditional taxonomy, the two companies are very different. The shared theme, the professors say, justifies Intel’s $7.7 billion acquisition of McAfee. They also cite the way that Facebook, dissimilar to Google in many ways, still manages to share Google’s search engine role.

When valuing a domain name, appraisers have traditionally relied on the prices of sold domain names whose key words are similar to those of the name being valued. But the number of such sales is often so limited that the analyses don’t have adequate data.

A real estate appraiser can compare a house with recently sold properties that have the same number of rooms, the same square footage, and the same neighborhood. The appraised price of a new house on the market would be the average of the comparable houses. Unlike real estate, however, domain name comparables are not easily identified because there are no obvious yardsticks for measuring how much the different factors contribute to value. Even names that contain the same sort of words may not be comparable. Consider the differences that can crop up with Indian tribes. One tribe may be on the federal list of recognized Indian tribes while the other isn’t. One may run a casino and enjoy the profits of a casino-related Web site while the other doesn’t. Domain names incorporating the names of these tribes could be very far from comparable. Statistical methods are needed to weigh a name’s different factors and what they contribute to its value. After that the appraiser can locate comparable names and take the average of their recent sales prices.

Under statistical methods, domain names are divided into buckets according to characteristics such as the number of Google key word search results, the key word’s pay-per-click (PPC) revenue, and the number of trademarks. (Technically the method is called nonlinear discriminant analysis. One such method is tree regressions, which I have been using since 2004.)

Comparables are more than what meets the eye. Statistical models improve the definition of comparable domain names and thereby turn up a larger number of similar sales. That allows for solid price estimates instead of guesswork.