门店内顾客商品停留时间统计数据

通过自主研发的摄像头以及AI模型算法，精确采集每天三个时间段的顾客在商品的停留时间与总停留时间的占比，来评价商品的销售情况，并用于指导本单位在下月各商品的生产量以及定价等行为。

间的占比，来评价商品的销售情况，并用于指导本单位在下月各商品的生产量以及定价等行为。1数据采集：通过自主研发的摄像头以及AI模型算法，精确采集每天三个时间段的顾客在商品的停留时间，并把每天的三个时间段内的停留时间进行汇总整理。2数据处理：汇总后得到总停留时间Y，按照商品分类，算出每个商品的停留时间X，再算出每个商品的停留时间X在总停留时间Y，得到每个商品的占比情况。3数据应用：根据第二步得到的占比，可以来评价商品的销售情况，并用于指导本单位在下月各商品的生产量以及定价等行为。

## Dataset Description
This dataset evaluates product sales performance and guides the enterprise's production volume and pricing decisions for each product in the next month by accurately collecting and analyzing customers' dwell time on products across three daily time periods via independently developed cameras and AI model algorithms. The specific implementation steps are as follows:
1. Data Collection: Accurately collect customers' dwell time on products during three daily time periods using independently developed cameras and AI model algorithms, then aggregate and organize the dwell time data from the three time periods each day.
2. Data Processing: Obtain the total dwell time Y after aggregation. Categorize the data by product to calculate the dwell time X of each product, then compute the proportion of each product's dwell time X relative to the total dwell time Y to get the proportion distribution of each product.
3. Data Application: Use the proportions obtained in the second step to evaluate the sales performance of products, and guide the enterprise's decisions such as production volume and pricing for each product in the following month.

搜集汇总

数据集介绍

特点

该数据集记录了门店内顾客对不同类别商品的停留时间及其占比，数据规模为169条，每月更新。通过AI算法采集和处理数据，用于评估商品销售情况并指导生产和定价决策。