Conceptual explanation/prediction of utility function. Extraction of utility function from Big Data
I believe what you are looking for are hedonic regressions:


  In economics, hedonic regression or hedonic demand theory is a
  revealed preference method of estimating demand or value. It
  decomposes the item being researched into its constituent
  characteristics, and obtains estimates of the contributory value of
  each characteristic. This requires that the composite good being
  valued can be reduced to its constituent parts and that the market
  values those constituent parts. Hedonic models are most commonly
  estimated using regression analysis, although more generalized models,
  such as sales adjustment grids, are special cases of hedonic models.
  
  An attribute vector, which may be a dummy or panel variable, is
  assigned to each characteristic or group of characteristics. Hedonic
  models can accommodate non-linearity, variable interaction, or other
  complex valuation situations.
  
  Hedonic models are commonly used in real estate appraisal, real estate
  economics, and Consumer Price Index (CPI) calculations. In CPI
  calculations hedonic regression is used to control the effect of
  changes in product quality. Price changes that are due to substitution
  effects are subject to hedonic quality adjustments.


Hedonic regression on Wikipedia 

The BLS has a nice fully worked example about using this method to price changes in the quality of camcorders. They explore how brand, storage format, image stabilization, weight, and other features influence the price in order to capture how changes in the value of camcorders influences substitution in consumption decisions.