根据图片内容，输出用户运营团队用户反馈周汇报视频、有趣不枯燥版本---**Report Title:** 客户运营线 用户反馈数据报告 (Customer Operations Line User Feedback Data Report) **Reporting Period:** 2025年6.21-6.27日 (June 21-27, 2025) **用户反馈 数据总览 (User Feedback Data Overview)** * **有效收集 (Valid collections):** 279条 (items) * 41条人工答疑 (15%) (Manual answering) * 238条AI客服 (85%) (AI Customer Service) * 较上周环比下降30% (Compared to last week, a 30% decrease) * **运营跟进率 (Operation follow-up rate):** 100% * 包含院校社群 (Including college communities), 手动提交 (Manual submission), 自媒体平台渠道 (Self-media platform channels) * **产品优化需求跟进 (Product optimization requirements follow-up):** 13条 (items) * 跟进中13条 (13 items in follow-up) * **缺陷修复跟进 (Defect repair follow-up):** 4条 (items) * 2条已处理 (2 items processed) * 2条跟进中 (2 items in follow-up) * **院校对接 (College对接):** 8次 (times) * 数据支持 (Data support), 课程对接 (Course对接), 问题处理 (Issue handling)等 (etc.) **渠道洞察 (Channel Insight)** * **Main Text:** 85%的用户喜欢直接通过AI客服进行答疑 (85% of users prefer to directly use AI customer service for answering questions). 院校数据小幅降低、小红书逐渐转变为信答疑渠道 (College data slightly decreased, Xiaohongshu gradually transformed into a question answering channel). * **Chart Type:** Bar Chart * **X-axis labels:** 院校社群 (College Community), 手动提交 (Manual Submission), AI客服 (AI Customer Service), 小红书 (Xiaohongshu), 教务沟通 (Academic Affairs Communication), App Store. * **Y-axis label:** (Implicit count) * **Y-axis scale:** 0, 50, 100, 150, 200, 250 * **Data Bars and Values:** * 院校社群: 18 * 手动提交: 9 * AI客服: 238 * 小红书: 5 * 教务沟通: 8 * App Store: 1 **时间趋势 (Time Trend)** * **Main Text:** 本周用户反馈整体保持较低水平 (Overall user feedback remained at a low level this week), 因接近期末放暑假 (Due to approaching end of semester and summer break). (符合用户学习规律) (Consistent with user learning patterns). * **Chart Type:** Line Chart * **X-axis labels:** 6月21日 (June 21st), 6月22日 (June 22nd), 6月23日 (June 23rd), 6月24日 (June 24th), 6月25日 (June 25th), 6月26日 (June 26th), 6月27日 (June 27th). * **Y-axis label:** (Implicit count) * **Y-axis scale:** 0, 10, 20, 30, 40, 50, 60 * **Data Points and Values:** * 6月21日: 27 * 6月22日: 52 * 6月23日: 41 * 6月24日: 46 * 6月25日: 56 * 6月26日: 32 * 6月27日: 31 **问题类型-AI客服 (Problem Type - AI Customer Service)** * **Main Text:** 88%学习者提问集中在与【学习成果】相关的操作类问题为主 (88% of learners' questions are mainly operation-related questions related to [learning outcomes]). * **Chart Type:** Bar Chart * **Chart Title:** 高频TOP5问题 (High-Frequency TOP5 Issues) * **X-axis labels:** 成绩 (Grades), 课程/课表 (Courses/Timetable), 学历银行 (Academic Credit Bank), 教评 (Teaching Evaluation), 作业 (Assignments), 考试 (Exams). * **Y-axis label:** (Implicit count) * **Y-axis scale:** 0, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50 * **Data Bars and Values:** * 成绩: 48 * 课程/课表: 37 * 学历银行: 18 * 教评: 13 * 作业: 13 * 考试: 10 * **TOP5 List:** * TOP1: 22%--成绩 (Grades) * TOP2: 17%--课程/课表 (Courses/Timetable) * TOP3: 8%--学历银行 (Academic Credit Bank) * TOP4: 6%--教评 (Teaching Evaluation) * TOP5: 6%--考试 (Exams) **问题类型-院校社群 (Problem Type - College Community)** * **Main Text:** 教育者提问为主，操作类问题反馈占比88%，已全部跟进，缺陷类问题占比12%，已修复完毕 (Mainly questions from educators, operation-related issues feedback accounts for 88%, all followed up. Defect-related issues account for 12%, all repaired). * **Chart Type:** Pie Chart * **Slices:** 88% (labeled), 12% (labeled) * **Legend:** * █ 操作类 (Operation Type) * █ 缺陷类 (Defect Type) * **Problem Descriptions:** * 【操作类】(Operation Type) * 1. 学生视频学习/作业记录未同步 (Student video learning/assignment records not synchronized) * 2. 教学空间操作问题 (Teaching space operation issues) (学生成绩查询、补考发布、数据导出等) ((Student grade query, make-up exam release, data export, etc.)) * 【缺陷类】(Defect Type) * 1. 作业批改列表有误【已处理】(Assignment grading list has errors [Processed]) * 2. 作业数据有误【已处理】(Assignment data has errors [Processed]) **产品优化推进 (Product Optimization Promotion)** * **Title:** 通过AI客服、院校社群对用户高频问题的洞察，推进产研进行如下产品优化 (Through the insight into high-frequency user issues via AI customer service and college communities, promote the following product optimizations in R&D). * **Section Title:** 【推进中项目15个】重点需求如下：([15 projects in progress] Key requirements are as follows:) * 01 AI批改未完全覆盖 (AI grading not completely covered) * **Description:** 通过和产研讨论会议，探讨扩容方式解决AI批改未完全覆盖问题，提升老师批改效率和产品体验。(Through discussions with R&D, explore expansion methods to solve the issue of AI grading not being completely covered, improving teacher grading efficiency and product experience.) * 02 特殊字符限制、无法保存且识别 (Special character restriction, unable to save and recognize) * **Description:** 通过功能优化来达到支持特殊字符的输入、保存和AI识别批改，提高学生和老师的体验性，以及提高老师们的批改效率和准确性。(Through functional optimization to support the input, saving, and AI recognition and grading of special characters, improve the experience for students and teachers, and enhance teachers' grading efficiency and accuracy.) * 03 AI用户数据分析后台 (AI user data analysis backend) * **Description:** 构筑有据可依的决策基础，聚焦用户意图识别与AI交互行为分析；新增核心数据埋点、AI答案质量评估机制及人工标注复核流程，助力智能能力持续优化。(Build a data-driven decision-making basis, focus on analyzing user intent recognition and AI interaction behavior; add core data points, AI answer quality evaluation mechanism, and manual annotation review process to continuously optimize intelligent capabilities.) * 04 智能舆情监控系统 (Intelligent public sentiment monitoring system) * **Description:** 构筑智能化舆情监控系统，通过实时抓取、分析平台内容，识别负面敏感信息，助力运营团队快速响应，维护品牌声誉。(Build an intelligent public sentiment monitoring system to identify negative and sensitive information by real-time capturing and analyzing platform content, assisting the operations team in quick response and maintaining brand reputation.) * 05 数据埋点体系 (Data point system) * **Description:** 搭建产品数据驱动决策和优化，通过搭建精确数据埋点体系，可以帮助从用户行为中挖掘洞察、驱动增长、优化产品体验。(Build product data-driven decision-making and optimization. By establishing a precise data point system, it can help gain insights from user behavior, drive growth, and optimize product experience.) **技术缺陷修复推进 (Technical Defect Repair Promotion)** * **Section Title:** 【已处理2个】([2 Processed]) * 01 AI批改异常 (AI grading exception) * 02 数据异常 (Data exception) * **Section Title:** 【跟进中2个】([2 In Follow-up]) * 01 AI后台数据走错工 (AI backend data flow error) 作流分类 (Work flow classification) * 02 系统异常(作业提交 (System exception (assignment submission) 提示) (prompt)) **Logo:** 芯位教育 XINWEI EDUCATION