In the context of on-demand logistics systems, the facility location is becoming even more critical as demand characteristics and customer preferences are changing with respect to the location, time, customer segments etc. Classic facility location models do not take into account customer preferences when the set of facility locations are optimized and therefore the expected profit of the classic facility location models is not an accurate representation of reality. This paper develops a preference-based facility location model which incorporates customer preferences while maximizing the system-wide expected profit in the context of an on-demand logistics provider. The customers are first segmented based on historical data and segment specific preferences are estimated by logit mixture where we take into account heterogeneity within the segment. The performance of the preference-based facility location model is measured by total expected profit and consumer surplus. It is found that, the preference-based facility location model is not only a more accurate representation of reality but also has the potential to increase the expected profit compared to typical facility location models.