Abstract: The present disclosure herein provides methods and systems for optimizing personalized hospitality offerings to suit based on the customer requirement. The present disclosure employs a bucket of prediction models, namely (i) pre-trained hotel prediction model for predicting one or more hotels present in a destination city, (ii) the pre-trained room prediction model for predicting the one or more vacant rooms from the one or more hotels, and (iii) the pre-trained ancillary services prediction model for the predicting the one or more ancillary services available for the one or more vacant rooms. Each prediction model is separately trained on the features obtained from the unstructured historical training data, using a feature extraction technique. The fluidic pricing mechanism is used to provide personalized hospitality offerings by determining the fluidic pricing and offers to multiple relevant ancillary service bundles which may suit mostly to the diverse customers.