Driving sports conferences by leveraging data
About the authors Kaustubh Kridutta Veda S Bondada Sunanda Dadi Tanya Gupta Consultant Project Manager Consultant Consultant Kaustubh is a graduate student Tanya is a graduate student Veda is a graduate student Sunanda is a graduate student pursuing Master of Science in who is pursuing her Master of pursuing Master of Science in currently pursuing her master Construction Management Information Management from of science degree in Science in the field of from University of Illinois at Information Management from University of Illinois at Urbana Information Management from Urbana Champaign. He has 2 Champaign majorly focusing the University of Illinois at University of Illinois at Urbana- years of professional Champaign. She is fond of on the Technology Consulting Urbana-Champaign. Prior to experience in managing extracting unique insights from pathway. She has professional her master’s degree, she construction projects with 1 experience as an Associate worked for about 3 years as a data and is intrigued by the year of consulting experience world of Data Science. Software Engineer at Software Development focusing on strategy Accenture Technology. Engineer at Zomato, a fast- development. growing start up. 2
About the authors Patricia Tabarani Minseok Kim Suin Kim Consultant Consultant Consultant Suin is an undergraduate Minseok is an undergraduate Patricia is a student at UIUC student pursuing a bachelor’s student pursuing a dual pursuing her graduate studies degree in Sports Management bachelor’s degree in Business in Human Resources from University of Illinois at Marketing and Business Management-PhD track . Her Urbana Champaign. She has Administration at Gies College background combines internship experience as a of Business, University of business, healthcare & HR. research intern on sports Illinois at Urbana Champaign. She has 7 years of experience marketing and sports He has internship experience in research, consultancy, competition consulting. as a research assistant on project management, renewable energy communication & HR. infrastructure consulting. 3
INTRODUCTION Data Collection Big data create a massive uptick in the amount of information organizations collect, manage and analyze. It has the potential to unlock big insights for every industry, large to small. Data-driven conferences provide planners with a deep-dive into understanding the metrics and related best Data Analysis business practices to ensure the success of conferences. Our mission is to share how to leverage data and analytics to plan a more impactful conference strategy. “Information is the oil of the 21st Data Visualization century, and analytics is the combustion engine” -Peter Sondergaard, Gartner Research 4
1.1 Techniques for collection of data before a conference The incorporation of sophisticated data collection techniques that can be implemented before a conference have great potential in contributing towards the success of the conference. They can set the layout for the type and level of analytics to be performed and assist the organizers in taking care of the pre-requisites that can boost the attendance and functioning of the conference. I Marketing Automation Platforms II Email Marketing and Google Analytics III Data Mining from Web Server Logs IV Application Programming Interfaces 5 BIG Analysis
Data collection through marketing using MAPs I Steps to follow for using MAPs Marketing Automation Platforms (MAPs) track user sessions on a ASK HELMUT site or event calendar and map out their exposure to event content, Choose the right event management and how the audience is discovering it. This provides marketers with software the ability to create personalized and adaptive experiences for prospective and existing customers at scale. Develop a marketing automation strategy Strength Updating the content on your Popular Software website based on the contact’s past Designate a marketing automation admin behavior Enrolling a contact into a series Hubspot Marketo Standardize automation processes of remarketing ads displayed on one or many different channels. Review available integrations to support your Salesforce Assigning a contact to a business Marketing Eloqua event marketing activities development representative or Cloud Integrate with collaboration tools account manager Integrate with CRM This simple tracking method can have a large impact on event attendance and provides valuable learning lessons to ensure future events are as optimized as possible 6 BIG Analysis | Bizzabo
How can data be collected through email marketing II and Google Analytics Google Analytics EMAIL MARKETING RELEVANT USER SEGMENTED USER CAMPAIGNS PLAN IS DATA IS LISTS ARE SUCCESS IS DEVELOPED ACQUIRED CREATED MEASURED There are various sources of data to consider as well as a variety of extraction methods: It can be used to track people who have shown The usual starting point for data collection is email service provider . interest in your ads on Google This includes data on who opens the email, the time they do it, the links Once prospects land on your event website, your they click on as well as their location website cookies can keep count of how many often these prospects come back before Sending out a survey through email or sharing one on social media , registering – as well as which pages, they visit can help you find out what customers expect from the event, how much the most. they are willing to pay and how they would rate any previous interactions By setting up a tracking pixel in Universal Google Analytics account , you will be able to Internal data can be leveraged by integrating sales CRM system with see what sources are driving traffic and analyze an email marketing platform. This can help build more detailed customer conversions. profiles, to spot behavioral trends across marketing and sales funnels 7 BIG Analysis | Eventbrite | Elasticemail
Collection of relevant conference data through data III mining from web server logs Case Study: IBM enabling data mining of web Data Mining of Web Server Logs server logs in 1996 Olympics website View based classification: Divisions like demographics, organizational type, etc. help in IBM utilized various advanced algorithms to help in the data collection from web server logs into a classified format collection of both quantitative and qualitative data from the Views can visualize this classified data based on what type web server logs of the Olympics website in 1996 of data is majorly required The collaboration of IBM and Olympics fared extremely well Collection of attendee’s geographic region data: as more information related to number of hits based on the The client IP address is used to obtain data related to an sources , sports and country of the client were obtained attendee’s geographic region The IP addresses that visited a website can be accessed by the host without even proper registration by the clients Association rules for data collection from Big Data: To obtain data in an interpretable form, the association rules algorithm is applied Data in its natural form is accompanied by different associations among them, thus, helping in further analysis 8 BIG Analysis | IBM Data Mining
Collection of conference data using application IV programming interfaces (API’s) Data collection platforms Types of data collected API’s can collect relevant conference API’s are used for collecting quantitative data from social media platforms like and qualitative behavioral data Facebook , Twitter , etc. Quantitative Data : Hours spent on . The amount of information retrieved is specific page, number of users with based on the privacy settings of the same hashtags, etc. platform as well as the individuals Qualitative data : Personal details, using it interests, etc. Data collection techniques Metadata collection Apart from the obvious data collection API’s follow a hassle-free approach to types, API’s are unique in enabling the obtain data from internet environments collection of metadata that are almost inaccessible Metadata can be defined as data about Primary example of such an internet data and includes date and environment is the back-end of social timestamps , user identifiers and links media platforms in the form of related to specific messages databases 9 BIG Analysis | ABI/INFORM Collection
1.2 Techniques for data collection during a conference Data collection during the conference is the most essential part of leveraging data. During the conference, there are numerous data that can be collected. Choosing the right tool and the method will effect the success of a conference. Social media analytics On-site data collection Registration process and personal Mobile app and QR code scanning scheduling 10 BIG Analysis
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