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10 Types of Domain Name Appraisers

Alex Tajirian
October 20, 2007


There are two types of domain name appraisers, designated here as type “1” and type “0,” with the former being appraisers who rely on a scientific approach. A large number of domain owners use the services of type “0”—the nonscientific—or do the appraisal themselves. Approaches used by scientific appraisers include regression-type statistical modeling, discounted cash-flow analysis, and reliance on the Law of Large Numbers.

This essay looks at some of the typical erroneous arguments against taking a statistical approach and provides an example from law to shed light on some success stories with statistical models that have changed people’s minds. For a concrete example, we use a study on predicting Supreme Court decision-making.

Appraisal vs. Valuation

“Appraisal” and “valuation” are typically used interchangeably. Although they are both based on opinion, whether that of an individual or group, a valuation is different in that other researchers can replicate it. Nevertheless, this does not necessarily imply that appraisals cannot provide verifiable predictive accuracy or are inferior to valuation models.

Supreme Court Decision Making Study

The stud[1] compares the predictive accuracy of legal experts to statistical regression. The selected experts for the study include scholars (five of whom had been law school deans), practitioners, and pundits. The regression model used only six factors: (1) the circuit court of origin; (2) the issue area of the case; (3) the type of petitioner; (4) the ideological direction of the lower court ruling; (5) the type of respondent; and (6) whether the petitioner argued that a law or practice is unconstitutional. The model’s dataset was composed of 628 cases previously decided by the nine justices.

The regression model predicted 75% of the affirm/reverse results correctly, while the legal experts collectively got 59.1% right. The model also predicted Justice O’Connor’s vote (a swing vote) correctly 70% of the time, while the experts’ success rate was only 61%.

Common Criticism of Statistical Models

Unjustifiable skepticism over the use of statistical models for prediction is not confined to domain name valuation. Other fields include law, wine rating, sports, and medicine, to name a few.[2]

Common themes voiced by the skeptics include too many variables, only “experts” can do it, not enough data, and confusing statistical results. Below I address each of these issues separately.

  1. Too many variables. This criticism does not refer to situations where there are too many variables to estimate compared to observations. Rather, the argument maintains that there are too many hard-to-quantify variables and that not all variables have an impact on all domain names—i.e., there is a large number of domain name–specific factors. To counter this argument, the Supreme Court case above demonstrates that six predictors, a relatively small number, perform better than the experts.

  2. Only “experts” who have buying and selling experience can appraise. The Supreme Court study also provides a counterexample using regressions. Moreover, in general, by aggregating opinions, irrespective of expertise, one can come up with a robust value estimate. The latter approach is based on the Law of Large Numbers[3] instead of regressions.

  3. Not enough data. A significant amount of data on sale prices is publicly available, although the publicly available data does becomes thinner for domains sold for greater than $250,000. Nevertheless, there are sources of data, other than sales prices, that can shed even more information on domain name values.[4]

  4. Statistical results are confusing. The group voicing this particular complaint does believe in the power of statistics, but they hear contradictory messages and are left to wonder who is right and who is wrong. “Coffee is good for you,” “Coffee is bad for you,” “Domain guru says appraisals are useless,” “Domain guru says statistical appraisals are, in general, the most robust.” Who should you believe?

Unfortunately, there is no easy way to decide, especially when you are not an expert in the field. One solution is what Andy Grove, the chairman of Intel, did when he had to decide on the method of treatment for his cancer. He dug into the relevant literature to better understand it. Obviously, not everyone has the learning ability, time, or desire to follow such an approach. Although a domain name’s appraisal is not a matter of life and death, you want to make sure that you are not taken for a ride. Thus, at a minimum, you need to be aware of some common sale pitches and their weaknesses:

a.       “We have more stats and data.” Ask them how do they know that they have more stats than their competitors and how much difference in value precision does their additional data lead to?

b.       If they believe that the length of the domain name is a strong predictor of value, ask them why their belief contradicts other statistical studies.[5]

c.       When someone tells you “I believe company X is the best appraiser,” ask them why. Would that be based on statistical prediction accuracy or the closeness of the appraisals to the recommender’s estimates?

Is Domain Appraisal Worth It?

Standard appraisal fees range from zero to about $40 per domain name. If you have a domain name that is a non-dictionary key word, then statistical models might not be the right approach. On the other hand, for a domain that is a combination of dictionary key words, a fast check of the frequency of the occurrence of the key words and the corresponding number of Ad Sponsors on Google (in addition to checking the domain’s extension and traffic volume) can give you an idea of whether it is worth spending the money on an appraisal and whether a more accurate appraisal is worth the extra cost.


For additional references on domain name appraisal, click here.

[1] For a condensed version of the study, see Andrew D. Martin, et al., “Competing Approaches to Predicting Supreme Court Decision Making,” Perspectives on Politics, 2, vol. 4, 2004, pp. 761–767; available at <>.

[2] Ian Ayres, Super Crunchers: Why Thinking-by-Numbers Is the New Way to Be Smart, Bantam, 2007.

[3] Such an approach has been adopted by

[4] See Alex Tajirian, “Food for Thought: Appraisal Dataset,” DomainMart.

[5] See, for example, Alex Tajirian, “Length of Domain Name Is Irrelevant!,” DomainMart.