京公网安备 11010802034615号
经营许可证编号:京B2-20210330
数据已经成为当今社会的一个组成部分。广泛使用互联网、社交媒体、基于位置的服务和多媒体有助于不断增长的数据,这些数据将产生有关的人、人的喜好等诸多的信息。这种海量的数据给行业更好地了解他们的客户创造了新的机会,并提供基于客户喜好的个性化服务。
正在利用这些海量的数据来寻求更多的东西的产业是酒店业。在过去,酒店和技术从来没有互相补充,因为酒店从业者一直关注有形的东西。他们更愿意花时间和资源在定义业务区域上,如提高一个地方的氛围,拓宽菜单的选择范围,提高服务交付的质量,而不是专注于技术和大数据。其结果是,企业想提供的和客户想要的之间的距离变大了。因此,由于缺乏对客户喜好的了解,酒店业从业者使得企业效率低下并且盈利处于低水平之上。
为了克服这些问题,酒店业开始以一种很显著的方式使用技术,特别是大数据。大数据是关于识别模式和关系的,这些关系存在于可以确定未来趋势的数据和变化的客户喜好之间。有了这些了解,企业可以使得自己的现有产品或添加新的来满足这些客户的期望,这反过来将推动需求,并使得利润增加。
具体地讲,大数据可通过以下方式来提高客户满意度,从而能够提高企业的整体效率和收益。
个性化体验
大数据有充每次给客户提供个性化旅行体验的潜力。当一个企业知道某个特定的客户想要的什么时,它就可以更改其相应的服务。例如,如果一个餐饮企业基于老主顾过去的饮食习惯和他们的社交媒体更新知道老主顾想要什么,那么它就可以提供这样的菜单选项。特别是当客户有饮食禁忌时,如素食主义者或犹太教,这些信息就会派上用场,
这样的策略在许多方面被证明可以为公司带来经济利益。首先,客户对服务很满意,那么他们肯定会再次光顾生意。其次,更重要的是,这个客户很可能会向朋友和家人推荐这个地方。该建议将带来更多的客户,而公司则不用在营销或广告上花费任何金钱。
创造合适的产品和服务
大数据可以给公司对于他们的产品和服务提供更好的方向感。他们会比以前知道哪些产品将成为热点,使他们能相应地规划自己的业务。例如,它是不难预料,在热天人们会喝啤酒或吃冰淇淋,但了解他们喜欢什么啤酒以及什么口味的冰淇淋是很有益的,使企业能够储存足够数量的合适产品。这个信息就是大数据可以给企业的东西。在更广泛的层面上,大数据有助于最大限度地优化品牌的战术决策并给旅游公司提供更好的控制力。
竞争优势
大数据很可能成为帮助企业获得竞争优势的关键因素。在这个意义上说,大数据工具将是主要的差异化要素,因为所有的公司,无论是新的还是老的,都有机会获得相同的数据量。因此,能够创新和捕捉最深的见解的公司将超越其他公司。
在另一个领域,大数据可以帮助定价。公司将能够预见发展趋势,并调整其产品售价,以使他们的服务对客户更具吸引力。一个典型的例子是租金成本。例如,当船租赁公司,知道更多的人将要在夏季前往它所在的城市,大部分旅客可以负担得起的价格,其竞争对手的价格和其产品的预计需求,那么他们就可以定一个能够吸引客户的价格,并且与此同时又使得公司有利可图。这给了企业竞争优势,因为它的定价决策是有相关数据支持的,这种相关数据能够以比以往任何时候都高的精度来预测客户的消费行为。
谨慎的做法
尽管使用大数据能够带来好处,但企业应该注意一些灰色地带。首先,过度个性化可能会适得其反,因为这将被某些人看作是侵犯隐私权。因此,企业应该利用大数据来提供个性化的体验,但不应该过度的这么做。例如,记者登上飞大西洋航线的飞机,很多东西让她大吃一惊,其中她相邻座位的两名记者竟和她前往同一会议。利用大数据,该机设计了座位安排,使得所有的三名乘客有机会在会议之前就知道对方。在另一方面,只要一个老顾客进来,餐厅服务员就会拿出顾客喜欢的饮料。选择也会基于客户的历史订单推出。虽然这些“服务”,一些人是可以理解的,但是对于想在本次计划尝试新鲜事物的顾客来说,这将是非常不愉快的。
其次,大数据本身并没有多大用处,除非企业以创新的方式使用它来提高他们的业务水准。正是这种创新,给了企业竞争优势,使得产品或服务对用户更有吸引力。
最后,企业应该使用正确的大数据工具以最大限度地利用它。实时分析和深刻的洞察力,将提供真正驾驭它的好处必不可少的新模式。
总之,通过提供新的模式和见解,大数据将对对酒店业产生深远的积极影响。有了这个新的信息,企业能够更好地提供个性化的服务,提升客户满意度,提高运营效率,获得竞争优势,所有这一切最终将使企业获得更高的利润。然而,有一些需要小心,特别是在隐私和侵犯客户的方面。当这些问题得到解决,大数据成为企业和旅客的游戏改变者。
Is Big Data a game -changer for businesses and travellers?
Data has become an integral part of our society today. Widespread use of the Internet, social media, location-based services and multimedia are contributing to the ever-growing data explosion that is generating information about people, their preferences, likes and so much more. Such vast amounts of data have created new opportunities for industries to better understand their customers, and to provide personalized services based on their preferences.
One such industry that is looking to make the most out of these vast amounts of data is the hospitality industry. In the past, hospitality and technology have never complemented each other because the hospitality players have always been concerned about tangible things. They preferred to spend their time and resources on defined areas of operations such as to improve the ambience of a place, widen the choice of menus and enhance the quality of service delivery, instead of focusing on technology and big data. As a result, the gap between what the industry offers and what customers want widened. Hence, players in the hospitality industry were left with inefficient businesses and low profitability levels due to this lack of understanding of customers’ likes and preferences.
To overcome these problems, the hospitality sector began to adopt technology, specifically big data, in a profound way. Big data is all about identifying the patterns and relationships that exist between data to identify future trends and changing preferences of customers. With these insights, companies can customise their existing products or add new ones to meet these customer expectations, that in turn will fuel demand, and will lead to increased profits.
Specifically, Big data can be used in the following ways to enhance customer satisfaction, and to improve the overall efficiency and profitability of businesses.
Personalised Experience
Big data has the potential to give customers a personalized travel experience every time. When a business knows what a particular customer wants, it can make changes to its services accordingly. For example, if a restaurant business knows what a regular customer wants based on his or her past eating patterns and social media updates, then it can provide such menu choices. This information will come handy especially when the customers have diet specifications such as vegan or kosher.
Such a strategy will prove to be economically beneficial for the company in many ways. Firstly, the customer is sure to come back to the business again because he or she was satisfied with the service. Secondly, and more importantly, this customer is likely to recommend this place to friends and family members. This recommendation will bring in more customers without the company spending any money on marketing or advertisement.
Creating the Right Products and Services
Big data can provide a better sense of direction for companies with respect to their products and services. They will be in a better position than before to know which products will be a hit, so that they can plan their operations accordingly. For example, it is not hard to predict that people will drink beer or eat ice-cream on a hot day, but it will help to know what beers and what flavors of ice-cream they would like, so that the business can stock the right kind in adequate quantities. This information is what big data can give to companies. On a broader level, big data helps to maximize tactical brand decisions and gives greater control to tourism companies.
Competitive Advantage
Big data is likely to become a key factor for helping companies to gain a competitive advantage. In this sense, big data tools will be the key differentiators because all companies, whether they are new or experienced, will have access to the same amount of data. Hence, the company that can innovate and capture the deepest insights will score over others.
Another area that big data can help is pricing. Companies will be able to foresee trends and adjust their prices accordingly to make their services more attractive to customers. A case in point is the cost of rentals. When a boat rental company, for example, knows that more people are going to travel to its city in summer, the rate that is affordable for most travelers, the prices of its competitors and the estimated demand for its products, they can set a price that is attractive to customers and at the same time, is profitable for the company. It also gives the business a competitive advantage because its pricing decision is backed by relevant data that can predict consumer behavior with a greater level of accuracy than ever before.
Cautious Approach
Despite the benefits that come with using big data, there continues to be some gray areas that companies should watch over. Firstly, over-personalisation can backfire because it will be seen as an intrusion to privacy by some people. Hence, companies should use big data to offer a personalised experience, but should not over do it. For example, a journalist who boarded a transatlantic aircraft found much to her surprise, two other journalists who were heading to the same conference in her adjacent seats. Using big data, the aircraft engineered the seating arrangements to give all the three passengers an opportunity to know each other before the conference. On the other hand, a restaurant waiter brought in a complementary drink as soon as a regular customer walked in. Menu choices were also suggested based on the customers’ past orders. While these gestures would be appreciated by some, it would be seen as a heavy hand by others, especially by people who had planned to try out new items this time.
Secondly, big data by itself is of little use unless companies use it in an innovative manner to improve their business offerings. It is this innovation that gives a competitive advantage and makes a product or service more attractive to users.
Lastly, businesses should have the right big data tools to make the most out of it. Real-time analysis and deep insights that will offer new patterns are essential to truly harness its benefits.
In short, Big data is having a profound positive impact on the hospitality industry by offering new patterns and insights that were hitherto not available. With this new information, businesses are in a better position to provide customised service, enhance customer satisfaction, increase operational efficiency and gain competitive advantage, all of which eventually lead to higher profits for businesses. However, there are some areas that need caution, especially in terms of privacy and intrusion to customers. When these areas are addressed, Big data becomes a game -changer for both businesses and travellers.
数据分析咨询请扫描二维码
若不方便扫码,搜微信号:CDAshujufenxi
多层感知机(MLP,Multilayer Perceptron)作为深度学习中最基础、最经典的神经网络模型,其结构设计直接决定了模型的拟合能力、 ...
2026-03-30在TensorFlow深度学习实战中,数据集的加载与预处理是基础且关键的第一步。手动下载、解压、解析数据集不仅耗时费力,还容易出现 ...
2026-03-30在CDA(Certified Data Analyst)数据分析师的日常工作中,“无监督分组、挖掘数据内在聚类规律”是高频核心需求——电商场景中 ...
2026-03-30机器学习的本质,是让模型通过对数据的学习,自主挖掘规律、实现预测与决策,而这一过程的核心驱动力,并非单一参数的独立作用, ...
2026-03-27在SQL Server数据库操作中,日期时间处理是高频核心需求——无论是报表统计中的日期格式化、数据筛选时的日期类型匹配,还是业务 ...
2026-03-27在CDA(Certified Data Analyst)数据分析师的能力体系与职场实操中,高维数据处理是高频且核心的痛点——随着业务场景的复杂化 ...
2026-03-27在机器学习建模与数据分析实战中,特征维度爆炸、冗余信息干扰、模型泛化能力差是高频痛点。面对用户画像、企业经营、医疗检测、 ...
2026-03-26在这个数据无处不在的时代,数据分析能力已不再是数据从业者的专属技能,而是成为了职场人、管理者、创业者乃至个人发展的核心竞 ...
2026-03-26在CDA(Certified Data Analyst)数据分析师的能力体系中,线性回归是连接描述性统计与预测性分析的关键桥梁,也是CDA二级认证的 ...
2026-03-26在数据分析、市场研究、用户画像构建、学术研究等场景中,我们常常会遇到多维度、多指标的数据难题:比如调研用户消费行为时,收 ...
2026-03-25在流量红利见顶、获客成本持续攀升的当下,营销正从“广撒网”的经验主义,转向“精耕细作”的数据驱动主义。数据不再是营销的辅 ...
2026-03-25在CDA(Certified Data Analyst)数据分析师的全流程工作中,无论是前期的数据探索、影响因素排查,还是中期的特征筛选、模型搭 ...
2026-03-25在当下数据驱动决策的职场环境中,A/B测试早已成为互联网产品、运营、营销乃至产品迭代优化的核心手段,小到一个按钮的颜色、文 ...
2026-03-24在统计学数据分析中,尤其是分类数据的分析场景里,卡方检验和显著性检验是两个高频出现的概念,很多初学者甚至有一定统计基础的 ...
2026-03-24在CDA(Certified Data Analyst)数据分析师的日常业务分析与统计建模工作中,多组数据差异对比是高频且核心的分析场景。比如验 ...
2026-03-24日常用Excel做数据管理、台账维护、报表整理时,添加备注列是高频操作——用来标注异常、说明业务背景、记录处理进度、补充关键 ...
2026-03-23作为业内主流的自助式数据可视化工具,Tableau凭借拖拽式操作、强大的数据联动能力、灵活的仪表板搭建,成为数据分析师、业务人 ...
2026-03-23在CDA(Certified Data Analyst)数据分析师的日常工作与认证考核中,分类变量的关联分析是高频核心场景。用户性别是否影响商品 ...
2026-03-23在数据工作的全流程中,数据清洗是最基础、最耗时,同时也是最关键的核心环节,无论后续是做常规数据分析、可视化报表,还是开展 ...
2026-03-20在大数据与数据驱动决策的当下,“数据分析”与“数据挖掘”是高频出现的两个核心概念,也是很多职场人、入门学习者容易混淆的术 ...
2026-03-20