Abstract: Specific product demand patterns fail to shed light on market characteristics of such a kind of products. For short life cycle experiential products, a lack of sales data and immense demand volatility make it necessary to have a thorough understanding of demand feature of the kind of products in a holistic way. However, the demand feature is difficult to identify. To address the issue, it is imperative to propose a method for mining demand feature patterns suitable for short life cycle experiential products.
Immense demand volatility of a kind of products make it difficult to mine such a kind of products' relationships between product attributes and its total sales volume. After segregating a kind of products into several groups according to their total sales volume, fluctuation of each group's total sales volume becomes relatively small, and thus demand feature of each group with a narrow sales volume interval may be more regular, so it may be easy to mine the demand feature of each group. Based on this, a product demand feature pattern mining method is proposed for short life cycle experiential products by grouping such a kind of products according to their total sales volume.
The method takes updated product introduction set and sales volume of existing short life cycle experiential products as source information. By integrating content analysis and association analysis, the method consists of two processes:(1) product attribute mining process through content analysis,(2) product attribute pattern mining process for each group through association analysis. Through content analysis at the first process, product attribute database is established; relatively comprehensive product attributes are obtained; product attribute table is set up. At the second process, through product attribute association analysis and through visual construction of demand feature resulted from the analysis, product attribute relationship pattern which is possessed by product set grouped in the high sales volume interval but not in the middle and low sales volume interval is mined out, and thus a dynamic demand feature pattern reflecting market demand trend is obtained.
On the basis of data of 65 crime movies and 190 romantic movies shown in China from 2013 to 2016, the demand feature pattern mining method is verified, and demand feature pattern of crime movies and that of romantic movies in recent years are obtained. The patterns may be used to guide creation of these two types of movies.
The demand feature pattern mining method is not only suitable for short life cycle products, but also suitable for long life cycle products with product introduction, because the method only uses product introduction and sales volume as source information. The method can be applied before products get developed, and thus demand feature pattern resulted from the method may be used to guide design of new products and may help to reduce investment risks of new products.

Key words: demandfeature pattern, short life cycle experiential product, content analysis, association analysis, movie demand