大禹陵景区智能打卡活动分析数据

大禹陵景区智能打卡活动分析数据能够为绍兴市旅游管理和市场营销提供决策支持。该数据有助于预测大禹陵景区及其6大主题展区的受欢迎程度和未来旅游趋势，优化旅游活动策划和资源配置，丰富游客旅游体验，增进游客对大禹治水这一华夏治水文明的了解。通过分析游客在各个打卡点完成打卡的用时情况、平均打卡点用时、有效打卡率、智能票根卡购买率，旅游管理者可以了解游客对6个主题展区的偏好、关卡难易程度，从而策划更具吸引力的大禹陵景区活动和旅游产品，以吸引更多游客，推动区域旅游经济效益增长。1、数据来源与收集：从学院开发的“泥巴世界小程序”后台数据中提取大禹陵景区“禹迹寻踪·千年治水智能打卡活动”的打卡数据集，包括景区名称、活动名称、活动时间、游客名称、智能票根卡编号、智能票根卡购买/租赁、打卡点1至打卡点6的分别用时、完成打卡点数量。
2、数据处理与分析：（1）检查数据的一致性和完整性，剔除缺失、错误或异常的数据。（2）计算平均打卡点用时。平均打卡点用时=完成打卡点1至打卡点6的总用时/完成打卡点数量*100%。其中，未完成打卡的打卡点用时记为0秒。（3）计算有效打卡率。有效打卡率=完成打卡点数量在4个（含）以上的游客人数/游客总人数。（4）计算智能票根卡购买率。智能票根卡购买率=智能票根卡购买人数/游客总人数。
3、数据运用：（1）智能票根卡购买率达到85%以上（含）表示游客对于付费游戏工具的接受程度极高；85%（不含）-55%（含）表示游客对于付费游戏工具的接受程度较高；55%以下（不含）表示游客对于付费游戏工具的接受程度一般。智能票根卡购买率可以用于指导旅游管理者调整景区打卡活动的形式、付费游戏工具的介质和定价。（2）平均打卡点用时可以反映打卡点（关卡）的难易程度，平均打卡点用时在景区活动策划时预期的60秒以内的，表示完成打卡较为容易。平均打卡点用时可用于指导旅游管理者策划更合理的打卡活动形式。（3）有效打卡率在50%以上（含）表示景区本次打卡活动较受欢迎，50%以下表示本次打卡活动的受欢迎程度一般。有效打卡率可帮助旅游管理者预测未来旅游趋势，策划更具吸引力的大禹陵景区活动和旅游产品，以吸引更多游客。

Analysis data of the smart check-in activity at Dayu Mausoleum Scenic Area can provide decision-making support for Shaoxing's tourism management and marketing. This data helps predict the popularity and future tourism trends of Dayu Mausoleum Scenic Area and its 6 themed exhibition areas, optimize tourism event planning and resource allocation, enrich tourists' travel experience, and enhance tourists' understanding of Dayu's Flood Control, a core part of Chinese flood control civilization. By analyzing tourists' check-in time at each check-in point, average check-in time per point, effective check-in rate, and purchase rate of smart ticket stub cards, tourism managers can understand tourists' preferences for the 6 themed exhibition areas and the difficulty level of check-in levels, thereby planning more attractive activities and tourism products for Dayu Mausoleum Scenic Area to attract more tourists and promote the growth of regional tourism economic benefits.

1. Data Source and Collection:
The check-in dataset for the 'Trail of Yu: Millennium Flood Control Smart Check-in Activity' at Dayu Mausoleum Scenic Area was extracted from the backend data of the 'Mud World Mini Program' developed by the college. The dataset includes scenic area name, activity name, activity time, tourist name, smart ticket stub card number, purchase/lease status of smart ticket stub cards, time spent on each of check-in points 1 to 6, and the number of completed check-in points.

2. Data Processing and Analysis:
(1) Check the consistency and integrity of the data, and eliminate missing, incorrect or abnormal data.
(2) Calculate the average check-in time per check-in point. The formula is: Average check-in time per point = (Total time spent on check-in points 1 to 6) / (Number of completed check-in points) * 100%. The time spent on unfinished check-in points is recorded as 0 seconds.
(3) Calculate the effective check-in rate. The formula is: Effective check-in rate = (Number of tourists who completed 4 or more check-in points) / Total number of tourists * 100%.
(4) Calculate the purchase rate of smart ticket stub cards. The formula is: Purchase rate of smart ticket stub cards = (Number of tourists who purchased smart ticket stub cards) / Total number of tourists * 100%.

3. Data Application:
(1) A purchase rate of smart ticket stub cards of 85% or higher indicates that tourists have an extremely high acceptance of paid game tools; a rate between 55% (inclusive) and 85% (exclusive) indicates a relatively high acceptance; a rate below 55% (exclusive) indicates a general acceptance. The purchase rate of smart ticket stub cards can be used to guide tourism managers to adjust the form of scenic area check-in activities, the medium and pricing of paid game tools.
(2) The average check-in time per point can reflect the difficulty level of check-in points (levels). An average check-in time within the expected 60 seconds for the scenic area's event planning indicates that check-in is relatively easy. The average check-in time per point can be used to guide tourism managers to plan more reasonable check-in activity formats.
(3) An effective check-in rate of 50% or higher indicates that the current check-in activity at the scenic area is relatively popular, while a rate below 50% indicates a general popularity. The effective check-in rate can help tourism managers predict future tourism trends and plan more attractive activities and tourism products for Dayu Mausoleum Scenic Area to attract more tourists.

搜集汇总

背景与挑战

背景概述

该数据集聚焦于大禹陵景区的'禹迹寻踪·千年治水智能打卡活动'，包含649条游客打卡记录，涵盖智能票根卡购买情况、各打卡点用时及完成数量等关键字段。数据通过计算平均打卡点用时、有效打卡率和智能票根卡购买率等指标，旨在分析游客对景区活动的偏好和参与度，为旅游管理者提供决策支持，以优化活动策划、提升游客体验并推动区域旅游经济效益。