US20240137592
2024-04-25
Electricity
H04N21/2542
An information processing method involves utilizing computer processors to receive data related to live sales conducted by a livestreamer through live video streaming. The data is then input into a machine learning model, which generates results that help obtain promotional information beneficial for the livestreamer's sales activities.
Recent advancements in technology have transformed communication methods, shifting from one-way channels like newspapers and television to interactive platforms such as livestreaming. This evolution has been particularly pronounced during the COVID-19 pandemic, leading to a surge in the popularity of livestreaming for online sales, where viewers can engage with sellers in real-time.
In livestream commerce, the effectiveness of sales strategies significantly impacts sales volume. Traditionally, these strategies have been determined subjectively by the livestreamer without optimal data-driven insights, leading to missed opportunities for enhancing sales performance. Addressing this gap is a primary focus of the proposed method.
The information processing device comprises several key components: a receiving unit for capturing live sales data, a processing unit that applies machine learning algorithms, and an advice generation unit that produces actionable insights for the livestreamer based on processed data. This structure facilitates real-time adjustments to sales strategies during live broadcasts.
By leveraging machine learning, the proposed system aims to enhance sales outcomes by predicting product sales based on livestream parameters. This predictive capability allows livestreamers to adapt their selling techniques dynamically, ultimately optimizing both sales volume and profitability during live streams.