Automatic Product Copywriting for E-Commerce

Abstract

Product copywriting is a critical component of e-commerce recommendation platforms. It aims to attract users' interest and improve user experience by highlighting product characteristics with textual descriptions. In this paper, we report our experience deploying the proposed Automatic Product Copywriting Generation (APCG) system into the JD.com ecommerce product recommendation platform. It consists of two main components: 1) natural language generation, which is built from a transformer-pointer network and a pre-trained sequence-to-sequence model based on millions of training data from our in-house platform; and 2) copywriting quality control, which is based on both automatic evaluation and human screening. For selected domains, the models are trained and updated daily with the updated training data. In addition, the model is also used as a real-time writing assistant tool on our live broadcast platform. The APCG system has been deployed in JD.com since Feb 2021. By Sep 2021, it has generated 2.53 million product descriptions, and improved the overall averaged click-through rate (CTR) and the Conversion Rate (CVR) by 4.22% and 3.61%, compared to baselines, respectively on a year-on-year basis. The accumulated Gross Merchandise Volume (GMV) made by our system is improved by 213.42%, compared to the number in Feb 2021.

Automatic Controllable Product Copywriting for E-Commerce

“…Though great efforts have been put into the exploration of controllable text generation, extending them into real-world product copywriting generation still remain large challenges, such as inconsistent attribute information before generated text and product information, and unavailability to the labeled copywriting datasets. Product description generation Previous studies for text description generation in the e-commerce domain focused on statistical frameworks such as [6,27,29,30], which incorporate statistical methods with the template for product descriptions generation. Such methods are limited by the hand-crafted templates.…”

The Ethics of (Non)disclosure: Large Language Models in Professional, Nonacademic Writing Contexts

“…There has also been some discussion of the use of large language models in professional and technical communication settings (Biswas, 2023;Castellanos-Gomez, 2023;Knowles, 2022). Zhang et al (2022) have noted that "automatic product copywriting generation has become an important line of research in e-commerce" (p. 12423), and the range of professional applications for large language models increases seemingly daily. In these contexts, the ethical considerations of using AI language models like GPT-4 are more nuanced, as the line between collaboration and deception-if the use of AI goes undisclosed-becomes increasingly blurred.…”