An O2O coupon distribution method and system based on big data analysis
A technology for distributing systems and coupons, applied in data processing applications, commerce, instruments, etc., can solve problems such as high marketing costs for merchants, inaccurate goals, and user interference.
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Embodiment 1
[0099] In this example, based on the real online and offline consumer behavior data provided by the Alibaba platform between January 1, 2016 and June 30, 2016, it is predicted that the user will use the coupon within 15 days after receiving the coupon in July 2016. Explain the situation and give distribution recommendations:
[0100] Step 1: According to figure 1 The steps of the method, first divide the training set 1, the training interval is from January 1, 2016 to April 13, 2016, the verification interval is from April 14, 2016 to May 14, 2016; the training set 2, the training interval From February 1, 2016 to May 14, 2016, the verification interval is from May 15, 2016 to June 15, 2016; the prediction interval is from March 15, 2016 to June 30, 2016, and the forecast The result interval is from July 1, 2016 to July 31, 2016;
[0101] Step 2: read data from online user business and coupon data files, offline user business and coupon data files, and offline user consumpti...
Embodiment 2
[0150] This embodiment combines the attached figure 2 Specifically explain the coupon distribution system. The data of the coupon distribution system is divided into online user merchants and coupon data, offline user merchants and coupon data, and data to be predicted, which are collected by the data collection module. Users pass The upload operation uploads the data file; the data collected by the data collection module is uploaded locally to the server background management module through the network service, and the server background management module passes the absolute paths of the three types of data into the algorithm model, and then managed by the service background The algorithm part of the module reads the data and processes the data, and then sends the processing results to the database, and the database transmits the statistics to the front-end user module; the front-end user module gives distribution suggestions by classifying the prediction results, and at the s...
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