Intuitively, factors are latent variables that underly the scores in your observed variables. Usually, the interpretation of each of these factors is based on the content of the original variables so that each factor is interpreted as whatever the attributes with high loadings for this particular factor have in common. Ideally, factor scores would therefore represent the score on the underlying latent variable.
By construction, regression factor scores in SPSS are standardized. A score of 0 on a factor therefore means that the ratings of the importance of the relevant attributes is close to the average for your sample. Similarly, a negative score means that the he ratings of the importance of the relevant attributes is lower than average.
DiStefano, C., Zhu, M. & Mîndrilă, D. (2009). Understanding and Using Factor Scores: Considerations for the Applied Researcher. Practical Assesment, Research & Evaluation, 14 (20).