E-commerce trial evaluation and recommendation system based on user demands

Abstract

The invention discloses an e-commerce trial evaluation and recommendation system based on user demands. The system comprises a data extraction module which comprises a user inquiry interface and a user screening extraction unit; the trial article processing module comprises a user consumption type recognition unit, a trial article online unit and a trial article and user distribution unit; a trial user logs in the mobile platform terminal, the mobile platform terminal pre-charges the trial article purchase gold coins and puts on-line trial articles of the trial article on-line unit, the trial user can purchase the corresponding trial articles through the trial article purchase gold coins to complete normal shopping experience, and the user completes trial evaluation at the mobile platform terminal. The mobile platform end returns a certain proportion of trial article purchase gold coins for actively purchasing other trial articles; and the trial evaluation integration module is used for manually recording the trial evaluation of the unevaluated trial user in a manual telephone inquiry mode, combining the manually recorded trial evaluation data with the trial evaluation data of the mobile platform end, analyzing and outputting a trial report.

Description

technical field [0001] The invention relates to the technical field of e-commerce service platforms, in particular to an e-commerce trial evaluation and recommendation system based on user needs. Background technique [0002] Before a new product is developed or introduced to the market, it is generally necessary to conduct a trial. Through the trial, user evaluations are obtained to assist in improving the product so that it can better meet the actual needs of consumers. At present, most new products are promoted through e-commerce, and a major feature of e-commerce is the need for traffic, especially user trials and evaluations, which can directly affect the amount of product promotion. [0003] At present, product trial users are mainly selected through the Internet, and then the product is mailed to the trial users. The trial users fill in the trial report according to the pre-set answer sheets, so as to obtain product trial data. There are uncertainties in the whole pro...

AI Technical Summary

Problems solved by technology

[0003] At present, product trial users are mainly selected through the Internet, and then the product is mailed to the trial users. The trial users fill in the trial report according to the pre-set answer sheets, so as to obtain product trial data. There are uncertainties in the whole process, and the output evaluation The results will be inconsistent with the actual situation. For example, the selection of product trial personnel, the selected group of people is relatively broad, and there is great uncertainty in whether the product trial personnel can evaluate or make a fair evaluation. There will be more useless data in the early stage. The results are incorrect, and the effect of product trial and evaluation completion feedback cannot be achieved; there is also the current single answer sheet to fill in the trial report method. To achieve efficient evaluation, the quality requirements of product trial personnel are high, and no effective questionnaire has been formed. Closed loop, the reliability of the final trial data is not high, which leads to low effectiveness of the current trial and recommended related systems, and the platform data is not effectively used