Business and supermarket intelligent shopping guide method and system based on big data

Abstract

The invention discloses a business supermarket intelligent shopping guide method based on big data. The method comprises: a user information database and a business supermarket information database are created and updated based on the big data; receiving a shopping guide request sent by a user; Obtaining a starting point and a terminating point of the shopping guide map; Creating a shopping guidedatabase; Calculating a consumption intention score of the commodity in the shopping guide database; And sorting the commodities in the shopping guide database according to the order of the consumption intention scores from high to low, selecting commodity positions corresponding to N commodities with highest consumption intention scores as passing points of the shopping guide map, and connectingthe starting point, the ending point and the passing points according to a route optimization principle by combining with the supermarket map to generate a current shopping route. A user can be helpedto purchase psychological commodities quickly, the searching time is shortened, and the shopping experience of the user is improved; Meanwhile, the merchant accurately masters the user consumption tendency by accumulating the user consumption data, and data support is provided for the sales work of the merchant.

Description

technical field [0001] The invention relates to the technical field of indoor positioning and navigation, in particular to a big data-based smart shopping guide method and system for supermarkets. Background technique [0002] At present, when users go to shopping malls or supermarkets for consumption, they usually need to spend a lot of time looking for the products they want. On the one hand, the shopping time is prolonged and the user experience is poor. On the other hand, users spend a lot of time aimlessly Looking for products, although some unplanned consumption is stimulated, on the whole, the potential consumption lost because the merchant cannot accurately understand the user's needs and the user does not have enough time is far greater than this part of the unplanned consumption. [0003] In addition, a large amount of consumption information data accumulated by users in past consumption is stored in the database and cannot be effectively utilized. Contents of th...

AI Technical Summary

Problems solved by technology

[0002] At present, when users go to shopping malls or supermarkets for consumption, they usually need to spend a lot of time looking for the products they want. On the one hand, the shopping time is prolonged and the user experience is poor. On the other hand, users spend a lot of time aimlessly Looking for goods, although some unplanned consumption is stimulated, overall, the potential consumption lost by merchants because they cannot accurately understand the needs of users and users do not have enough time is far greater than this part of unplanned consumption.

[0003] In addition, a large amount of consumption information data accumulated by users in past consumption is stored in the database and cannot be effectively utilized

Images