Spending Money Wisely: Online Electronic Coupon Allocation based on Real-Time User Intent Detection

08/23/2020
by   Liangwei Li, et al.
0

Online electronic coupon (e-coupon) is becoming a primary tool for e-commerce platforms to attract users to place orders. E-coupons are the digital equivalent of traditional paper coupons which provide customers with discounts or gifts. One of the fundamental problems related is how to deliver e-coupons with minimal cost while users' willingness to place an order is maximized. We call this problem the coupon allocation problem. This is a non-trivial problem since the number of regular users on a mature e-platform often reaches hundreds of millions and the types of e-coupons to be allocated are often multiple. The policy space is extremely large and the online allocation has to satisfy a budget constraint. Besides, one can never observe the responses of one user under different policies which increases the uncertainty of the policy making process. Previous work fails to deal with these challenges. In this paper, we decompose the coupon allocation task into two subtasks: the user intent detection task and the allocation task. Accordingly, we propose a two-stage solution: at the first stage (detection stage), we put forward a novel Instantaneous Intent Detection Network (IIDN) which takes the user-coupon features as input and predicts user real-time intents; at the second stage (allocation stage), we model the allocation problem as a Multiple-Choice Knapsack Problem (MCKP) and provide a computational efficient allocation method using the intents predicted at the detection stage. We conduct extensive online and offline experiments and the results show the superiority of our proposed framework, which has brought great profits to the platform and continues to function online.

READ FULL TEXT
research
02/09/2023

An End-to-End Framework for Marketing Effectiveness Optimization under Budget Constraint

Online platforms often incentivize consumers to improve user engagement ...
research
08/05/2020

TPG-DNN: A Method for User Intent Prediction Based on Total Probability Formula and GRU Loss with Multi-task Learning

The E-commerce platform has become the principal battleground where peop...
research
09/20/2021

Grouping Search Results with Product Graphs in E-commerce Platforms

Showing relevant search results to the user is the primary challenge for...
research
02/22/2022

A Framework for Multi-stage Bonus Allocation in meal delivery Platform

Online meal delivery is undergoing explosive growth, as this service is ...
research
09/06/2023

Marketing Budget Allocation with Offline Constrained Deep Reinforcement Learning

We study the budget allocation problem in online marketing campaigns tha...
research
08/11/2021

E-Commerce Promotions Personalization via Online Multiple-Choice Knapsack with Uplift Modeling

Promotions and discounts are essential components of modern e-commerce p...
research
08/20/2020

A Deep Prediction Network for Understanding Advertiser Intent and Satisfaction

For e-commerce platforms such as Taobao and Amazon, advertisers play an ...

Please sign up or login with your details

Forgot password? Click here to reset