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Events and Tourism Review Vol. 4 No. 1 (2021), 1-13, DOI: 10.18060/23958                                                                                                  

               Copyright © 2021 Blair Orlando and Yeqiang (Kevin) Lin 

  This work is licensed under a Creative Commons Attribution 4.0 International 

License. 

 

Events and Tourism Review                                     
 
June 2021                                                                                                                                                 Volume 4 No. 1      

   

 

The Application of Data Analytics in the Events Industry 

 

 
Blair Orlando 
 

Yeqiang (Kevin) Lin 
 

California Polytechnic State University, San Luis Obispo 

Correspondence: yklin@calpoly.edu (Y. Lin) 

 

 
 

 

 

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Recommended Citation 

Orlando, B. & Lin. Y. (2021). The Application of Data Analytics in the Events Industry. Events 

and Tourism Review, 4(1), 1-13.  
 

 

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Events and Tourism Review Vol. 4 No. 1 (2021), 1-13, DOI: 10.18060/23958                                                                                                  

               Copyright © 2021 Blair Orlando and Yeqiang (Kevin) Lin 

This work is licensed under a Creative Commons Attribution 4.0 International License. 

 

 

 
 

 

 

Abstract 

 

This research examined the data analytics practices used within the events industry and the value 

of such applications. This study consisted of an interpretive case review of current companies 

within the events industry. The interview process explained the current practices being used to 

collect and analyze data. The common themes revealed data analytics are being used to evaluate, 

redesign, and enhance company performance, marketing strategy, decision guidelines, and 

economics. The study shows data collection and analysis is mostly focused on determining what 

consumers want and are looking for within the industry. The findings of this study support the 

importance of applying data analytics within industry-related companies to be financially 

successful and maintain market-share. Both the results from this study and the literature used 

indicate the significance of data analytics and the tremendous amount of opportunity buried 

beneath the application of data, although there is still room for growth. 

 

Keywords: Data, Analytics, Applications, Events, Technology 
 

 

 

Introduction 

 

The use of data within the events industry is expanding and setting the tone for the 

marketplace’s next big revolution. With data at the forefront of this massive revolution, companies 

today are taking advantage of adopting data practices to significantly improve businesses by 

personalizing customer experience. Monetate Inc. (2019) found 93% of businesses with an advanced 

personalization strategy, either in the development stage or currently being implemented, 

experienced revenue growth. This up-and-coming business trend reaches all industries and 

enormously influences business decisions and actions, both in real time and future thinking. Data 

has emerged as the leading catalyst in changing how companies access information (Freeman, 

2019), and is a key attribute in being classified as a major component in a worldwide panacea for all 

corporate ills. With the ability to provide a wealth of information related to many aspects of the life 

of individuals, organizations, and markets (Mayer-Schönberger & Cukier, 2013), data has given 

companies the tools necessary to answer and understand new insights about previously unreachable 

questions. 

Insights generated from data analytics can provide companies a competitive edge to make 

decisions concerning marketing, sales, and current demands within a market; data can also 

transform how companies shape their business plan. For 2019, more than 2/3 of the top marketing 

companies that have previously invested in the collection and processing of data are increasing their 

investment in marketing data analytics because of the tremendous amount of opportunity data has to 

offer (Freeman, 2019). Data are ultimately changing the way society lives, works, and thinks 

(Mayer-Schönberger & Cukier, 2013) and has the power to revolutionize every aspect of life. The 

value of data influences society in previously immeasurable ways, which is why it is an integral part 

of main business tactics and strategies. 

Technological advancements have greatly enhanced the accessibility of data and have 

allowed for tremendous growth in the business world. Collecting and gathering data today can be 

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Events and Tourism Review Vol. 4 No. 1 (2021), 1-13, DOI: 10.18060/23958                                                                                                  

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done almost instantaneously. The increasing digitization of society through the combination of 

devices, such as smartphones and tablets, virtually allows data to be found anywhere at any time 

(Verhoef, Kooge, & Walk, 2016). Specifically for the events industry, data represents the before, 

during, and after of each event. In 2015, the Center for Exhibition Industry Research (CEIR) 

conducted a study on 307 business-to-business exhibition executives, focused on the use of analytics 

by business-to-business exhibition organizers. This study showed how data can provide exhibition 

organizers with: statistics providing a better picture of the target audience, insights that help guide 

planning and strategizing, and translating analytics into the programming of individual records 

(CEIR, 2015). However, there is a lack of academic research on the applications of data analytics in 

the events industry. Thus, the purpose of this study was to examine common data analytics practices 

within the events industry and determine the value of such practices. This study can contribute to 

marketing research and act as a reference point for using and applying data that can enhance event 

marketing strategies and business tactics, while providing clarity about how data analytics are 

currently being used among top industry-related organizations. It also allows marketing researchers 

to investigate the diversity data can provide in the events industry, primarily about consumer 

interactions within markets and the products they consume. 

 

Review of Literature 

 

The Nature of Data Analytics  

Data are everywhere, and today data are proliferating at an extraordinary rate (Davenport, 

2013). The world relies on data every day, whether it stems from social media channels, registration 

platforms, site clicks, or feedback from surveys (Curran, 2019), data are constantly being collected 

and later reviewed and analyzed. For example, approximately 72,698 Google searches worldwide 

are happening this very second (Internet Live Stats, 2019). Those searches are contributing to the 

2.5 quintillion bytes of data created everyday (Marr, 2019) further explaining how data are 

influencing the world today.  

There are four dimensions to data: volume, velocity, variety, and veracity (Troester, 2012). 

These dimensions acknowledge the scale of data, analysis of streaming data, the different forms of 

data, and the uncertainty of data (Ayisi, 2014). These four dimensions offer a guide for analysts to 

use and follow in trying to accomplish the large task of applying data to a market. Researchers have 

classified the main sources of different types of data as: (1) public data, (2) private data, (3) data 

exhaust, (4) community data, and (5) self-quantification data (George, Haas, & Pentland, 2014). 

Each type of data represents a certain niche that is often combined with other sources to be used in 

providing some type of insight to a particular scenario, commonly known as analytics.  

Data analytics represents specific techniques that examine large amounts of data to uncover 

hidden patterns and other insights. Data analytic techniques are situational and encompass a variety 

of different disciplines (Pantelis & Aija, 2013), most commonly involving statistical analysis and 

categorical analysis (Mariani et al., 2018). Analysis results are useful to all industries and have 

become necessary to produce within the world of business (Scott, 2018). The benefits of analyzing 

data are limitless and act as a key component in improving business decisions and maintaining the 

relevancy of markets (Jewoo & Jongho, 2018).  

Thinking analytically is now seen as necessary for success throughout all industries 

(McGuire & Osborn, 2017). Having an analytical mindset is classified as an individual or group that 

is engrossed and perceptive to their surroundings and demonstrates the ability to think deeply and  

 

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Events and Tourism Review Vol. 4 No. 1 (2021), 1-13, DOI: 10.18060/23958                                                                                                  

               Copyright © 2021 Blair Orlando and Yeqiang (Kevin) Lin 

This work is licensed under a Creative Commons Attribution 4.0 International License. 

 

 

respond flexibly to changing circumstances (Alexander, 2014; Ku, 2009). Data-driven decisions 

within an organization are guiding how businesses are run, both internally and externally. The rapid 

growth of analytical thinking has allowed companies to better understand certainties about trends 

while providing more evidence for identifying areas where data can further inform one’s 

interpretation about why trends occur (Mayer-Schönberger & Cukier, 2013). Regarding how 

companies are thinking and treating data, shifting from simply producing data to instead consuming 

data can be the difference between successful and unsuccessful marketing (Fisher, 2009). Applying 

data analytics within a business can heavily influence marketing strategies and provide clarity about 

the significance in changing such strategies.  

 

Applications of Data Analytics 

Data analytics applications act as the main players in today's data-driven world and 

practically any topic or question can be explored with analytics (Davenport, 2013) and has the 

potential to greatly impact the events industry. Essentially, such applications represent how data 

science gets operationalized, meaning how end-users interact with data, both big and small (Perez, 

2019). There are various types of data applications that serve different purposes for data analysts 

including: artificial intelligence, statistics, forecasting, predictive thinking, data and text mining, 

optimization, and experimental design (Davenport, 2013). The integration of data analysis and 

applications techniques within technology is used throughout multiple sectors of the events industry 

including conventions and meetings, tourism and travel, and sports. 

Various techniques and their accompanying results can be extremely influential in making 

decisions. One popular application of data analytics in the events industry is target marketing. For 

example, social media platforms, such as Facebook, Instagram, Snapchat, and Twitter, have created 

an endless stream of data through impressions, likes, and views (Hu & Zhang, 2018). Platforms like 

these have allowed companies to access valuable data including information about users’ photos and 

location data (Suo & Zhang, 2015). Hence, the information provides companies with the necessary 

data to adjust their marketing strategies and to predict the desires of where the target audience wants 

to be spending their time. Data generated from social media is another key driver in successfully 

measuring business performance. Metrics from various social platforms can provide marketers with 

information that shows how users share, view, or engage with their content or profiles (Barnhart, 

2018). Social media networks have now created platform tools available for content analysis such as 

Facebook Insights, Twitter Analytics, and Google Analytics. These tools allow brands to target 

current and potential customers, drive engagement and conversions, find out what content best 

performs and how to leverage social networks accordingly (Sears, 2019). This information is used to 

assess campaign performance, understand the target audience, develop creative content, report to 

upper management, optimize campaign performance, and measure return on investment (Barnhart, 

2018). The evolution of technology has created a resource to attain endless opportunity for data 

usage.   

Another application currently being used among the events industry, more specifically 

among high budgeted mega-events, is Radio Frequency Identification (RFID) wristbands. RFID 

wristbands have electronic chips inside them that collect and track data. Large events, such as 

festivals, use RFID wristbands to track attendees’ actions regarding location, spending, and interests 

in real time (Hernandez, 2016). By collecting data and understanding the demands and needs of 

consumers, companies can improve business efficiency, finances, and customer satisfaction and 

retention (Eventbrite, 2019). 

 

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Events and Tourism Review Vol. 4 No. 1 (2021), 1-13, DOI: 10.18060/23958                                                                                                  

               Copyright © 2021 Blair Orlando and Yeqiang (Kevin) Lin 

This work is licensed under a Creative Commons Attribution 4.0 International License. 

 

 

Data applications provide event professionals the information necessary to offer more 

personalized experiences, by catering to specific needs. In addition, this information allows event 

companies the ability to better plan and structure their events. For example, data from an annual 

event showing the number of attendees, sales, and costs act as the foundation for predicting the next 

event. Having this prediction informs companies about changes that would be most beneficial to 

implement in the future. 

 

Barriers and Challenges to Data Analytics Adoption 

Data are constantly evolving and always being thought about and processed to develop new 

systems and perspectives on how to tackle the ongoing challenge of applying data effectively and 

efficiently. It is important to understand the complexity and challenges behind data. Data, though 

extremely valuable, represents a mass amount of information that can be difficult to interpret and 

use successfully. Technology has allowed for the digitalization of large amounts of data at an 

incredibly fast rate (Jewoo & Jongho, 2018). Although it is inevitable that technological 

advancements are going to continue to grow rapidly, issues associated with using data are also 

emerging alongside that growth. Data analytics can be intimidating to work with due to the influx of 

opportunity that lies within data. The hierarchical constraints most frequently explained in literature 

are (1) cost and time (Jain, Sharma, & Jayaraman, 2014), (2) correctness in conclusions (Ding & 

Simono, 2010), (3) combining extremely different sources of information (Bedeley & Nemati, 

2014), and (4) information overload (Leeflang et al., 2014).  

 Data, when used correctly and effectively, can strengthen any business, but unfortunately, 

the limitations involved with collecting and analyzing data can be overwhelming. Two of the 

biggest challenges come from a lack of funding and time. It costs and takes a lot of time to find, 

hire, and invest in a team of data analysts that have proper knowledge of the events industry and 

know how to process industry-related data. Although some data comes at little to no cost, the 

problem still lies with finding the right people to be able to examine and highlight key insights about 

that data. Another major contributor in limiting companies from using data analytics to their 

advantage is avoiding falsifying conclusions from data. Today, more than 80% of data is 

unstructured (Grimes, 2018) and refers to data that simply does not fit neatly in traditional relational 

databases, mainly because it represents information related to multiple industries and sectors within 

such industries (MongoDB, 2019). The scale of unstructured data can have some complications 

relating to the missing values within data that can lead to data being misused and can cause false 

interpretations or bias results (Jewoo & Jongho, 2018). Developing a system that can combine big 

and small data is another issue companies face regarding data application (Ayisi, 2014).  

Though valuable, the rapid proliferation of data available today makes it difficult to weed 

through the data and come up with a compelling narrative to share with key stakeholders within a 

company (Berland, 2017). This goes hand in hand with the issue of information overload caused by 

the unstructured nature of large volume data. Managers are faced with the demanding task of 

organizing and determining the best way to strategically use data as an advantage within their 

businesses (Saxena & Lamest, 2018). Information overload is usually characterized by feeling 

overwhelmed (Savolainen, 2007) by the sheer capacity of data and the paucity of time (Ayyagari et 

al., 2011).  

The main connection among all these challenges is simple, finding value in data. To 

overcome these challenges, companies must investigate the purpose behind using and analyzing 

data. Nevertheless, companies must embrace the opportunity within data and develop a system that  

 

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Events and Tourism Review Vol. 4 No. 1 (2021), 1-13, DOI: 10.18060/23958                                                                                                  

               Copyright © 2021 Blair Orlando and Yeqiang (Kevin) Lin 

This work is licensed under a Creative Commons Attribution 4.0 International License. 

 

 

aligns with their business plan and use that as a guide for making decisions and changing business. 

Although several studies have investigated the impact data can have within a business, few have 

investigated this topic in relation to the events industry. This study specifically addresses the 

challenges and benefits of adopting data analytics among top industry performers. 

 

Methods 

 

This research adopted an interpretive case research strategy to examine how data analytics is 

being used within the events industry and determine the value of collecting and analyzing large 

quantities of data. The research was focused on addressing the strategies being used to collect data 

and its impact on business changes and improvements. 

Industry leaders from the events, experiential marketing, tourism, travel, and sports sectors 

were identified to participate in the study. Due to the time-sensitive nature of this study, phone 

interviews allowed greater access to participants. Data collection took place between June 2018 and 

February 2019. An interview technique called “responsive interviewing,” in which the participants’ 

responses throughout the interview created the remaining interview guide was used for the study 

(Rubin & Rubin, 2012). Furthermore, the research focused on event companies that have already 

adopted using data and applying it to their organizations. With the event industry being highly 

exposed to user-generated content through websites among all sectors of the industry, such content 

was heavily utilized to benefit this study. 

Twenty-five companies within the events industry were contacted via email and phone about 

participating. To qualify for this study, participants were required to be working at an industry 

related company currently using data analytics to directly influence their events. All participants 

contacted to be a part of this study are in California, however their respective employers are 

headquartered all over the United States of America, with various clients around the world. 

Participant selection was focused on industry leaders, located in California, throughout all sectors 

(see Table 1) related to the events industry. A total of fifteen interviews were conducted with 

industry leaders, who use data to improve business and make decisions. The companies contacted to 

participate in this study represent multiple sectors of the events industry including tourism, 

corporate, convention and meetings, sales, technology, weddings, wine tourism, travel, recreation, 

and sports (see Table 1).  

 

Table 1. Description of Respondents & Sector Represented in the Events Industry 
 

Title of Interviewee  Participants Sector in the  

Events Industry 

Case 1 Vice President of Marketing  Corporate 

Case 2 Director of Field Marketing Technology and Sales  

Case 3 Senior Program Manager Sports 

Case 4 Senior Manager of Marketing Operations Technology and Sales 

Case 5 Vice President of Communications Travel & Tourism  

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Events and Tourism Review Vol. 4 No. 1 (2021), 1-13, DOI: 10.18060/23958                                                                                                  

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Case 6 Strategic Marketing Research Consultant Travel & Tourism 

Case 7 Executive Vice President of Operations Corporate 

Case 8 President & CEO Travel & Tourism 

Case 9  Assistant General Manager Sports 

Case 10 Sector Analyst Convention, Meetings  

Case 11 Senior Event Director Weddings 

Case 12 Senior Program Director Recreation 

Case 13 Operations Manager Travel & Tourism 

Case 14 Global Director of Media Product 

Marketing & Management 

Travel & Tourism 

Case 15 Senior Account Manager Corporate 

 

Interviews ranged from twenty-five to forty minutes and were either in person or conducted 

over the phone. A series of open-ended interview questions were used as a guide to provide in-depth 

research regarding how data was being produced, assessed, and implemented at the time of this 

study. 

Based on the literature reviewed, three variables were used to measure the use of data 

analytics within the companies involved in the study: applications, insights, and challenges. For 

applications, two questions addressed how companies are gathering and collecting data. For 

insights, four questions lead to a discussion about the value behind data and addressed how the 

results from the data collected was being used. For challenges, participants were asked to explain 

any current or potential barriers their company has faced from incorporating data analytical 

practices into their companies.  

To ensure honesty and comfort, each interview began with an explanation of the research 

project. Additionally, the participants were informed that their responses would remain confidential 

and anonymous. The purpose of these standards was to help increase participation due to the nature 

of sensitive information about the companies involved. Interviews were recorded on a laptop and 

then coded to find patterns that emerged. The goal of coding all responses was to identify key terms, 

recurring themes, and ideas that were later used to build conclusions about the study. 

 

Results 

 

This section presents the major themes that emerged from a thematic analysis. This study 

follows an interpretive research design; therefore, the themes use the language of the study 

participants. Four themes emerged after analyzing the transcription of the interviews: (1) the 

overwhelming feeling about the potential of using data, (2) the marketing benefits and influences 

from using data in enhancing customer experience, (3) data as financial justification for event value  

 

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Events and Tourism Review Vol. 4 No. 1 (2021), 1-13, DOI: 10.18060/23958                                                                                                  

               Copyright © 2021 Blair Orlando and Yeqiang (Kevin) Lin 

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and investment, and (4) the current concerns related to data type and source. 

 

Overwhelming Feeling about the Potential of Using Data  

Relatively early during the interview, participants made frequent references about feeling 

overwhelmed about incorporating data into their organizations. During the interview, these 

references amounted to a significant amount of the participants’ time and were constantly being 

revisited. Another common trend participants spoke about was how limited resources, for example, 

accessibility of data, personnel, and budget, acted as main contributors to feeling overwhelmed: 

The hardest thing about the new ‘data revolution’ … is it’s hard to figure out where to start, 

especially when you don’t have the time or money to put into it. (Case 8, President & CEO) 

This notion of feeling overwhelmed was most noticeably related to the problem of data 

ownership. The study revealed that most of the relevant customer-related information organizations 

want to access and utilize is sourced from outside organizations. This information, unstructured in 

nature, was deemed as the key to truly understanding what customers value and want in an event. 

However, participants continued to share their frustrations about attaining such valuable 

information:  

How do you find the balance between finding data to use and then, in turn, using that data to 

influence decisions and proceed to turn into actions… it is an issue that we are still trying to 

solve? (Case 12, Senior Program Director) 

Despite the overwhelming feelings that participants experience, they still use a wide range of 

data techniques and practices throughout their organizations.  

  

Marketing Benefits and Influences Using Data in Enhancing Customer Experience  

For all the organizations involved in this study, it was clear that data reveals necessary 

insights, about their events and customers, that heavily influence their marketing decisions. To a 

large extent, participants attested to using data as the main source of monitoring their market, 

driving strategy and change, attaining, and retaining customers, improving financial performance, 

and assessing products and services. A common example mentioned was how data can represent 

metrics related to specific marketing campaigns. Metrics such as website page volume, social media 

impressions, and conversions from the event website to the selected ticketing system can be used to 

produce insights about the targeted audience. Essentially, participants explained how data can be 

incorporated into every aspect of their company’s business plan and measure the overall success of 

an event:  

Data is the middle ground between flying blind in understanding your market and having 

deep personal identifiable information that can prove what customers are looking for in 

their experience. (Case 1, Vice President of Marketing)  

Across case studies, participants described a core function of using data as real-time 

analysis. At an educational conference, for example, data is derived from scanning each attendee’s 

badge upon entering a specific educational session. This data provides information to understand 

what attendees are doing in real-time. This information can add value to event planners because it 

can be applied to personalized messages sent to individual attendees, suggesting further sessions that 

relate to their interests. Real-time analysis, explained by multiple participants, allows their 

companies to make decisions before, during, and after their events. This contributes to creating 

memorable and personalized experiences for their customers, which relates to the mission of all the 

participants’ organizations: 

 

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Events and Tourism Review Vol. 4 No. 1 (2021), 1-13, DOI: 10.18060/23958                                                                                                  

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Capturing, reviewing, and processing data is one of our main priorities in order to have a 

successful event. It starts with before the event by looking at how attendees respond to the 

schedule of planned events and what they signed up for. Then during the event, looking at 

whether attendees are sticking to their original plan and making changes based on that 

information to send them updated suggestions. After the event is over, a comparison between 

their original plan and what they did at the event is used to predict their behavior next time. 

(Case 7, Executive Vice President of Operations)  

  

Data as Financial Justification for Event Value and Investment    

Another related theme that emerged from the interviews is that data contributed to the 

rationalization of various financial concerns and questions. Participants revealed that investigating 

quantitative data about event sales, number of attendees, and attendee actions can act as the main 

source for justifying the importance of an event. There was a standard among case companies 

explaining the financial power of data, and its ability to significantly increase companies’ ability to 

measure return on investment. Participants also explained how event planners use data to justify the 

budget for an event and prove the value of having such events. For example, data showing the 

percent of total attendees who attended a particular speaker at a tradeshow provides valuable 

insights about whether investing in that speaker was advantageous: 

We scan a barcode at all our different smaller event sessions (i.e., presentation, activity) to 

view attendance and be able to compare different sessions… then looking at that information 

and determining what sessions are necessary for the next year and what people are 

interested in. (Case 3, Senior Program Manager) 

 

Current Concerns Related to Data Type and Source   

Concerning data type and source, participants expressed the difficulty of managing data, 

allocating resources, and remaining ethical. Participants explained how deciding what type of data 

collection and analysis methods they should use is a harsh reality. This is because of the large 

amount of effort, time, and money it takes to process data effectively and ethically. Furthermore, the 

cryptic nature data possesses and the unfathomable amount of data accessible was explained by 

participants as a difficult task to tackle and use successfully: 

Though there is a lot of data out there, it’s not all focusing on the same thing and depending 

on resources available within your organization you have to choose what data source/s to 

invest in and then try to gain the most value from the/those chosen source/s. (Case 14- 

Global Director of Media Product Marketing and Management)  

 

Connecting and determining whether there is any correlation between different data points 

and insights is not an easy task. We reference this issue as triangulation meaning if you see a 

spike in one data set, but not the other/s and vice versa, it is hard to pinpoint and confidently 

understand what is causing that change or spike. (Case 6- Strategic Marketing Research 

Consultant) 

Another similar topic that was frequently shared among participants was the issue of privacy 

associated with adopting data analytics throughout their organizations. Participants revealed the 

necessary caution associated with and using data legally and ethically: 

No brand wants to be seen as insensitive in invading people’s privacy in general, but 

especially in relation to data. This is something we are extremely careful about because we 

would never want to damage the relationship and trust we have built with our customers. 

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Events and Tourism Review Vol. 4 No. 1 (2021), 1-13, DOI: 10.18060/23958                                                                                                  

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(Case 4, Senior Manager of Marketing Operations) 

Though companies involved in this study revealed that client privacy is an issue on its own, 

participants speaking on behalf of those companies also shared that this issue has majorly 

contributed to some hesitation associated with the overall adoption of data analytics practices. 

Furthermore, participants explained how these issues have led to slow progression in taking 

advantage of this up-and-coming data forward approach to business.  

 

Discussions, Limitations, and Conclusions 

 

This study aimed to extend the existing knowledge about how data can positively impact the 

events industry by investigating what current data analytical practices are being used throughout the 

events industry and determine the value of such practices. Although previous literature has revealed 

the importance of using data to better understand customer expectations and behaviors (Verhoef, 

Kooge, & Walk, 2016), the present study found that the benefits of applying data throughout the 

events industry directly contribute to enhancing customer experience and improving future events. 

This suggests that data analytics can be used as a valuable resource for companies looking to 

provide their customers with memorable experiences in a more precise manner (Mayer-Schönberger 

& Cukier, 2013).  

Data analytics, when used ethically, can directly influence, and improve how event 

companies make decisions and cater to customer needs and expectations (Fisher, 2009). Event 

planners should allocate a portion of their marketing dollars to collecting, processing, and analyzing 

data to act as the main source in continually improving their events. For example, venues used for 

events and vendors associated with events should be evaluating the attractiveness in, the interest of 

and why customers decide to use their venue for specific events. Another example related to vendors 

associated with events, specifically food vendors, is reviewing data about customer satisfaction via 

survey, comments, and reviews. Data produced through observing attendee actions and behaviors, 

such as their decision process, can be used to verify the products consumers want and provide 

insight about what vendors should be offering to match customer needs.  

Additionally, the results of this study show how data can provide the evidence necessary to 

predict the success of future events and justify an event budget. This indicates that the greater 

number of resources devoted to developing and analyzing data, the better financial success of a 

business. At a large music festival, for example, stakeholders can monitor the number of attendees at 

each different performer's show. This information not only shows what attendees are interested in 

and how they are spending their time, but also provides evidence about each specific shows return 

on investment, sales, and other financial measures (Barnhart, 2018). Moreover, the study also 

revealed a few complications associated with adopting data into the participants' organizations, such 

as time, cost and resources needed to collect and process data (Bedeley & Nemati, 2014; Ding & 

Simono, 2010; Jain, Sharma, & Jayaraman, 2014; Leeflang et al., 2014). To overcome these 

obstacles event planners should become more educated on the subject and how other companies are 

successfully incorporating data analytics into everyday business (Fisher, 2009). Other ways event 

planners could overcome the overwhelming feeling of using data could be by attending conferences 

on data analytics and their applications, joining associations related to data practices, and 

participating in workshops showing the benefits and challenges of using data. These solutions could 

act as a defining factor in effectively improving the events industry. The information is out there 

(Davenport, 2013), it is now up to event planners and stakeholders to take advantage of it and turn it  

 

https://creativecommons.org/licenses/by/4.0/


Orlando, B. & Lin. Y. (2021) / Events and Tourism Review, 4(1), 1-13. 
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Events and Tourism Review Vol. 4 No. 1 (2021), 1-13, DOI: 10.18060/23958                                                                                                  

               Copyright © 2021 Blair Orlando and Yeqiang (Kevin) Lin 

This work is licensed under a Creative Commons Attribution 4.0 International License. 

 

 

into useful insights that will benefit their organization. 

Despite the various evaluations and assessments employed in this study, three limitations can 

be identified. Although this study has a diverse representation of sectors within the events industry, 

the size of this study cannot be generalized to a larger population. Unfortunately, the nature and 

scope of the events industry make finding probability samples difficult and costly. The sample size 

for this study must be considered with respect to the recency of this type of research regarding data 

analytics within the events industry. Thus, future studies should continue to examine this new topic 

at a larger scale and reveal the progression of this major revolution. Additionally, revealing the 

benefits and challenges of data analytics for smaller-scale businesses in the events industry 

remained uncovered since the sample of this study was restricted industry leaders. Therefore, further 

research focusing on smaller companies within the events industry, maybe on a state level, would be 

beneficial. Lastly, because of time constraints with this study the specific techniques event 

companies use to collect and analyze data were not explored. This includes addressing the 

development of incorporating data analytics into sector-specific companies and interviewing 

companies that own, gather, and analyze data that is then outsourced and used within hiring event 

companies, in more detail. Another possible research direction would be a longer study looking at 

the specific systems in place among event companies that are solely devoted to data analytics.   

Although what we aim for is a theoretical generalization, we cannot claim for empirical 

generalization, as findings are context specific. Therefore, to achieve empirical generalization, the 

future work researching how data analytics can be applied and used within the events industry may 

engage in investigating case companies from other sectors and countries to explore their practices. 

Despite its limitations, this study discussed the concept of applying data analytics in the 

context of top industry performers within the events industry and shared the findings from fifteen 

case studies. The industry is still learning how to properly define this tactic and is working on 

developing efficient, low-cost ways to gather and collect data to improve company success. The 

results have provided researchers and practitioners with new insight regarding the benefits, 

challenges and applications associated with applying data analytics to the events industry. Overall, 

the events industry is lacking in supporting the application of data analytics and needs to make 

researching this topic a higher priority. 

 

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