Automatic Product Copywriting for E-commerce


  • Xueying Zhang JD.COM Silicon Valley Research Center
  • Yanyan Zou JD.COM
  • Hainan Zhang JD.COM
  • Jing Zhou JD.COM
  • Shiliang Diao JD.COM
  • Jiajia Chen JD.COM
  • Zhuoye Ding JD.COM
  • Zhen He JD.COM
  • Xueqi He JD.COM
  • Yun Xiao JD.COM Silicon Valley Research Center
  • Bo Long JD.COM
  • Han Yu Nanyang Technological University
  • Lingfei Wu JD.COM Silicon Valley Research Center



Product Copywriting, Product Description, Text Generation, Recommendation, E-Commence


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 e-commerce 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 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.




How to Cite

Zhang, X., Zou, Y., Zhang, H., Zhou, J., Diao, S., Chen, J., Ding, Z., He, Z., He, X., Xiao, Y., Long, B., Yu, H., & Wu, L. (2022). Automatic Product Copywriting for E-commerce. Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 12423-12431.