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Intelligent Event Data: Hospitality, Travel & Tourism Data - Eiffel Tower, Paris Sample

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Snowflake2024-01-12 更新2024-05-01 收录
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Free sample dataset of attended, non-attended and unscheduled events around the Eiffel Tower in Paris, France. These categories play a crucial role in generating domestic, inbound, and outbound tourism activity - which drives transportation, accommodation, retail, restaurants, and other demand. Events such as concerts, school holidays or conferences are powerful tourism attractions. Used by hospitality, travel, and tourism industry providers, PredictHQ’s data can help quickly identify key events that impact locations and behaviors to enhance targeted event-based marketing or foster local tourism partnerships. By better understanding which types of events attract the most tourists, you’re able to easily adjust your strategy to maximize demand and improve forecasting. Data also includes Predicted Event Spend, a dollar figure that reflects the predicted amount of retail, accommodation, and transportation spending in a specific area as a result of a major event. At the core of this figure sits our market leading global event coverage, predicted event attendance, local accommodation demand, aviation demand, third party data and more to give you greater geographical context of the scale of the economic impact an event will have. Categories: community, concerts, conferences, expos, festivals, performing arts, sports, academic, daylight savings, observances, politics, public holidays, school holidays, airport delays, disasters, health warnings, severe weather, terror (attended, non-attended, unscheduled) Location: Eiffel Tower, Paris, France Duration: 6 months Time: January 2023 - June 2023 Fields include: - Title - Category - Labels - Description - Start date and time - End date and time - Predicted end time - Country - Lat / Lon - Venue Name - Venue Address - Rank (PHQ Rank, Local Rank, and) - PHQ Attendance - Event status - Place Hierarchy - Created/updated timestamps - Predicted event spend PredictHQ's data quality is one of its key strengths: 1) We have developed a set of Quality Standards for Processing Demand Causal Factors (QSPD), which are used to define the criteria for high-quality event data. By following these standards, PredictHQ ensures that their data meets the highest levels of quality. 2) We use more than 450 data sources to collect event data, including public records, social media, and ticketing websites. 3) We have built thousands of machine learning models that standardize, verify, enrich, and rank every single event. 4) On average we process 28 million events and 422,000 entities every day 5) We track the quality of our data over time and make improvements as needed. About PredictHQ: PredictHQ is the world’s first and only company that provides the missing context for the biggest external factor that impacts businesses demand – events. PredictHQ’s intelligent data of verified global events enables businesses to forecast shifts in demand from events to be able to adjust their inventory, make changes to labor, dynamically price and operate more efficiently. Think conferences, sports games, college graduations, floods, and more. PredictHQ brings all events into one place, combines it with world-first tools and intelligence to allow organizations to better predict and respond to changing customer demand created by events in an easy, reliable, and scalable way. We meet customers exactly where they are, ensuring they can access our data the way that suits them best. For additional information, contact us at snowflakemarketplace@predicthq.com
提供机构:
PredictHQ
创建时间:
2023-09-05
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该样本数据集涵盖2023年上半年巴黎埃菲尔铁塔周边的各类活动事件,包含事件类型、预测消费等关键字段,旨在帮助旅游相关行业分析事件对经济的影响并优化策略。数据集通过多源采集和机器学习确保高质量,适用于需求预测和营销决策。
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