丽水地区课程老师方案生成数量预测数据

课程老师作为在线教育企业课程推广与销售的核心力量，其业务成效直接关系到在线教育企业的发展。围绕丽水地区课程老师上月的6项关键指标 —— 云产品总分享数（次）、云产品总浏览数（次）、云产品有效访问人数（次），云共享总分享数（次）、云共享总浏览数（次）、AI 客服总咨询数（次）来建立本月预测方案生成数量（个）的预测模型。该模型通过深度挖掘在线教育行业企业课程老师的行为数据，精准预测学习课程方案生成量。在线教育行业企业可据此推动课程老师转发、分享课程，优化客服话术、推送高转化课程包，为将互动转化为付费与续费，显著提升转化效率提供数据支持。1、数据通过协议获得。通过分析时间、课程老师ID、地区、数据分析时间段、云产品总分享数（次）、云产品总浏览数（次）、云产品有效访问人数（次），云共享总分享数（次）、云共享总浏览数（次）、AI 客服总咨询数（次）建立方案预测模型，来计算课程老师本月预测方案生成数量（个）。
2、对采集到的数据进行脱敏、清洗、去除异常值。建立本月预测方案生成数量（个）模型。
本月预测方案生成数量（个）=0.791 - 0.053*云产品总分享数（次） + 0.185*云产品总浏览数（次） - 0.131*云产品有效访问人数（次） + 0.176*云共享总分享数（次） + 0.043*云共享总浏览数（次） + 0.258*AI客服总咨询数（次） 。
3、此模型有助于所有在线教育行业企业运营策划。为在线教育行业的稳健发展提供数据支持。

Course instructors are the core driving force for course promotion and sales of online education enterprises, and their business performance directly affects the development of such enterprises. A prediction model for the number of predicted course plan generations this month is developed based on 6 key indicators of course instructors in the Lishui area from last month: total number of cloud product shares, total number of cloud product views, total number of valid cloud product visitors, total number of cloud sharing shares, total number of cloud sharing views, and total number of AI customer service inquiries. This model, by deeply mining the behavioral data of course instructors from online education enterprises, accurately predicts the volume of course plan generations. Online education enterprises can use this model to encourage instructors to forward and share courses, optimize customer service scripts, and push high-conversion course packages, thereby providing data support for converting interactions into payments and renewals, and significantly improving conversion efficiency.

1. Data is obtained through formal agreements. A plan prediction model is established by analyzing factors including time, course instructor ID, region, data analysis time period, total number of cloud product shares, total number of cloud product views, total number of valid cloud product visitors, total number of cloud sharing shares, total number of cloud sharing views, and total number of AI customer service inquiries, to calculate the predicted number of course plan generations for instructors this month.

2. The collected data undergoes desensitization, cleaning, and outlier removal. A prediction model for the number of predicted course plan generations this month is established. The formula is as follows: Predicted Number of Course Plan Generations This Month = 0.791 - 0.053 * Total Cloud Product Shares + 0.185 * Total Cloud Product Views - 0.131 * Total Valid Cloud Product Visitors + 0.176 * Total Cloud Sharing Shares + 0.043 * Total Cloud Sharing Views + 0.258 * Total AI Customer Service Inquiries.

3. This model supports operation planning for all online education enterprises, and provides data support for the steady development of the online education industry.

搜集汇总

背景与挑战

背景概述

该数据集是浙江贝玛教育科技有限公司登记的“丽水地区课程老师方案生成数量预测数据”，属于制造业企业数据，包含551条记录，每月更新。它通过课程老师的6项关键指标（如云产品分享数、AI客服咨询数等）建立预测模型，用于在线教育行业精准预测方案生成数量，以优化课程推广和提升转化效率，并已通过区块链存证确保数据可信。