It could be regarded as an extension to multivariate non-linear regression.
We do the regression on the tangible features such as GLA, Lot Size, room counts, stories, and Y/N values on whether or not it has features like certain heating types, certain kinds of views (without regard to quality), certain kinds of roofs and so on. We leave out those things that require subjective judgment, such as the quality of the view, the condition, quality of construction, aesthetics, etc.. We then predict the value of the home based on these tangilble features. It will fall short of the sale price by an amount that reflects the value of the intangible features we did not model for. The actual sale price minus our estimate is a measure of the total contribution to the value of the house of those intangible features. This is how we get a FIRM (relatively speaking) value estimation for the subjective intangible features.
Note that minor tangible features may be left out of the primary regression model, simply because they are minor and provide no significant contribution to value on their own. However, a large number of such minor features can become a major contributor to value - and thus must be thrown into the pool of "intangibles" that are not measured in the first regression. A kitchen with high quality granite counter tops, the best sinks, two Sub-Zero refrigerators, a $25,000 oven from France, and so on, might be treated in its entirety as an intangible. ... And it is precisely this sort of thing that requires a certain degree of finesse by the appraiser in scoring the subject property.
The sale price is in effect a "grade" for the subjective quality/appeal of a home.
What I am saying is that it is a matter of time before services, perhaps from CoreLogic, will provide up-to-date quality/appeal grades for home sales shortly after they occur. For example, you could go out to a site such as Realist and provided you have paid for the service, see an extra field for properties called something like CQA (Condition/Quality/Appeal) that would range say from 0.0-10.0 or possibly 0-100%. AS SOON AS A HOME SELLS, it can be given this score. BUT, you will also get a detailed regression model for the subject market area, a definition of the subject market area, and a breakdown of the features contributing to the value of the sale. The sum of the value contributions will of course add up to the sale price. From this, you will be able to use the same model for the subject and quickly calculate all adjustments. In fact, you can calculate a value for the subject without even having to look at comps.
But central to your valuation is YOUR score for the subject. If that is off, your value is off. However, note, your inaccuracy is limited to the percent of the total value of the intangible features, as the tangible features are already valued by the model. So if the model has an R2 of 0.80, your score for the subject only accounts for 20% of the value. Thus a 10% error in your scoring is effectively only a 2% error.
Your score for the subject is in relation to the breadth of the properties in the subject market area. If you don't have a good sense of the character of the market area, from worst to best homes is, or of the subject, then you will not do a good job of valuation.
If someone wants a value of +/-5%, they will need to have the subject inspected inside and out by an appraiser experienced in the neighborhood.
If they need a value of +/-10% to +/-15%, they can probably get by with a hybrid.
If they need a value +/-20% they can probably get by with an AVM, - and that is assuming that the home is not at the extremes of quality, low or high. AVMs are of course good at estimating the value of average homes, average that is to say, in relation to recent sales. If you are in a market area where most homes are upgraded before sale, those AVM prices can be far different than the value of a home being refinanced.
And, I'm talking about complex market areas, not tract homes, not relatively homogeneous subdivisions. For example, the SF Bay Area is a network of mostly complex market areas.