Driving sports conferences by leveraging data About the authors - - PowerPoint PPT Presentation

Driving sports conferences by leveraging data

About the authors

2 Kaustubh is a graduate student pursuing Master of Science in Construction Management from University of Illinois at Urbana Champaign. He has 2 years of professional experience in managing construction projects with 1 year of consulting experience focusing on strategy development. Tanya is a graduate student who is pursuing her Master of Science in the field of Information Management from University of Illinois at Urbana-

• Champaign. She is fond of

extracting unique insights from data and is intrigued by the world of Data Science. Sunanda is a graduate student currently pursuing her master

• f science degree in

Information Management from the University of Illinois at Urbana-Champaign. Prior to her master’s degree, she worked for about 3 years as a Software Development Engineer at Zomato, a fast- growing start up. Veda is a graduate student pursuing Master of Science in Information Management from University of Illinois at Urbana Champaign majorly focusing

• n the Technology Consulting
• pathway. She has professional

experience as an Associate Software Engineer at Accenture Technology.

Kaustubh Kridutta Veda S Bondada Sunanda Dadi Tanya Gupta

Project Manager Consultant Consultant Consultant

About the authors

Patricia is a student at UIUC pursuing her graduate studies in Human Resources Management-PhD track . Her background combines business, healthcare & HR. She has 7 years of experience in research, consultancy, project management, communication & HR. Suin is an undergraduate student pursuing a bachelor’s degree in Sports Management from University of Illinois at Urbana Champaign. She has internship experience as a research intern on sports marketing and sports competition consulting. Minseok is an undergraduate student pursuing a dual bachelor’s degree in Business Marketing and Business Administration at Gies College

• f Business, University of

Illinois at Urbana Champaign. He has internship experience as a research assistant on renewable energy infrastructure consulting.

Patricia Tabarani Minseok Kim Suin Kim

Consultant Consultant Consultant

3

INTRODUCTION

“Information is the oil of the 21st century, and analytics is the combustion engine”

• Peter Sondergaard, Gartner Research

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 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.

Data Collection Data Analysis Data Visualization

4

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 1.1

5

BIG Analysis

Data collection through marketing using MAPs

BIG Analysis | Bizzabo

6

Strength

ASK HELMUT

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

Marketing Automation Platforms (MAPs) track user sessions on a site or event calendar and map out their exposure to event content, and how the audience is discovering it. This provides marketers with the ability to create personalized and adaptive experiences for prospective and existing customers at scale. Updating the content on your website based on the contact’s past behavior Enrolling a contact into a series

• f remarketing ads displayed on
• ne or many different channels.

Assigning a contact to a business development representative or account manager

Hubspot Marketo Salesforce Marketing Cloud Eloqua

Choose the right event management software Develop a marketing automation strategy Designate a marketing automation admin Standardize automation processes Review available integrations to support your event marketing activities  Integrate with collaboration tools  Integrate with CRM

Steps to follow for using MAPs Popular Software

I

How can data be collected through email marketing and Google Analytics

EMAIL MARKETING PLAN IS DEVELOPED RELEVANT USER DATA IS ACQUIRED SEGMENTED USER LISTS ARE CREATED CAMPAIGNS SUCCESS IS MEASURED

 There are various sources of data to consider as well as a variety of extraction methods:

Google Analytics

 It can be used to track people who have shown interest in your ads on Google  Once prospects land on your event website, your website cookies can keep count of how many

• ften these prospects come back before

registering – as well as which pages, they visit the most.  By setting up a tracking pixel in Universal Google Analytics account, you will be able to see what sources are driving traffic and analyze conversions. The usual starting point for data collection is email service provider. This includes data on who opens the email, the time they do it, the links they click on as well as their location Sending out a survey through email or sharing one on social media, can help you find out what customers expect from the event, how much they are willing to pay and how they would rate any previous interactions Internal data can be leveraged by integrating sales CRM system with an email marketing platform. This can help build more detailed customer profiles, to spot behavioral trends across marketing and sales funnels

II

7

BIG Analysis | Eventbrite | Elasticemail

Data Mining of Web Server Logs

View based classification:  Divisions like demographics, organizational type, etc. help in data collection from web server logs into a classified format  Views can visualize this classified data based on what type

• f data is majorly required

Collection of attendee’s geographic region data:  The client IP address is used to obtain data related to an 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

Case Study: IBM enabling data mining of web server logs in 1996 Olympics website

 IBM utilized various advanced algorithms to help in the collection of both quantitative and qualitative data from the web server logs of the Olympics website in 1996  The collaboration of IBM and Olympics fared extremely well as more information related to number of hits based on the sources, sports and country of the client were obtained

III

Collection of relevant conference data through data mining from web server logs

8

BIG Analysis | IBM Data Mining

.

Data collection platforms

 API’s can collect relevant conference data from social media platforms like Facebook, Twitter, etc.  The amount of information retrieved is based on the privacy settings of the platform as well as the individuals using it

Data collection techniques

 API’s follow a hassle-free approach to

• btain data from internet environments

that are almost inaccessible  Primary example of such an internet environment is the back-end of social media platforms in the form of databases

Types of data collected

 API’s are used for collecting quantitative and qualitative behavioral data  Quantitative Data: Hours spent on specific page, number of users with same hashtags, etc.  Qualitative data: Personal details, interests, etc.

Metadata collection

 Apart from the obvious data collection types, API’s are unique in enabling the collection of metadata  Metadata can be defined as data about data and includes date and timestamps, user identifiers and links related to specific messages

IV

Collection of conference data using application programming interfaces (API’s)

9

BIG Analysis | ABI/INFORM Collection

Techniques for data collection during a conference

Social media analytics On-site data collection Registration process and personal scheduling Mobile app and QR code scanning 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.

10

1.2

BIG Analysis

Leveraging social media to collect data during the conference can mark towards success

87% 77% Social media marketing overview: Social media analytics provides certain features towards the success of the conference:

As of January 2018, there are 4.02 billion internet users around the globe. 3.2 billion, 42% of the world’s total population is reached through social media. With such penetration, it is. Inevitable to use social media for marketing a product /service Atanu Shaw – Forbes council member

Gender , location data: Gender, location provides demographics for customization marketing Customization: There are plenty of customized data providers available Clicks, timing metrics: Clicks & timing provides efficacy

“Social media analytics pays minimal cost, is flexible, accessible, and are effective due to the huge amount of data it provides.”

Social media analytics tools

Competitor: Provides tactical strategies for competency Engagement: Provides real-time interaction with possible customers

 Hootsuite Analytics: combines all features  Brandwatch: 95 million sources, social networks  Talkwalker: Analyzes conversation on social media  Facebook Analytics: Customized for Facebook

I

11

BIG Analysis | Forbes I Hootsuite I Quintly

On-Site data collection using Internet of Things (IoT)

1 3 2 4

Personal device sensors IoT data from personal device data Real-time analysis of the current event Visualization

• f the crowd

using data collected

System of interrelated computing devices, mechanical and digital machines provided with Unique Identifiers (UIDs) have the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction. Mobile-enabled IoT sensors installed locally give a precise view and count of the entire crowd.

It collaborated with service provider Cropland and Belgium city Antwerp to deploy crowd management system for the local events (Tour de France & Tall Ships Races) using IoT.

Orange Belgium

“Orange Belgium is able to provide a real-time data stream of the city of all mobile phones connected to its network within the city”

 The positioning data is derived from an analysis of the connection of phones to masts across 2G, 3G and 4G networks, as well as use of a timestamp to accurately position a device  This dashboard shows the density of people within the given area and monitors the crowd in given time

Case Study:

II

12

BIG Analysis | GSMA

Data driven technologies utilized during the registration process

87% 77% Data collection through registration

 Basic demographics are data that are most often underestimated. Online registration provides a convenient method for both parties

 Google analytics provides a pool of what is the most clicked/searched keyword in the registration process to grab insight of attendee taste

Google Analytics

 Conversion tracking: Identified conversion points can be tracked real time through analytics  Keyword referrals : Keywords searched during online registration is referred as big data  Traffic reporting: Tracks when and how many are registering throughout the day. Heavily influences the marketing method of the conference  Custom dashboards : Data collection can be customized to bring just the essential data upfront  Free to use / custom pricing: Free of usage for general, higher quality version analytics 360 is available for customized pricing

Personal Scheduling

 Traffic control : Conference booths that tracks the most traffics can be located at the center of the conference / venues that generate the most revenue. Traffic can be monitored through personal scheduling platform  Hot cues: Hot venues that draws the most audience can be tracked. Personal scheduling replaces the F2F survey and other terms of time-consuming data collection applications  Keynote speaker: Keynote speaker’s timeslot can be scheduled according to the data collected through the personal scheduling application. Traffic generated during the speech also provides information of future selection of keynote speakers

III

13

BIG Analysis | Google Charts | LevelTen I Guidebook

Data collection using mobile application to improve user experience during the conference

Using mobile app during the conference

1

Real-time event analysis: Information can be used to make adjustments during and after the next event to improve the event experience using commented users experience

3 4 2

Sponsors: They can reach out to target group through mobile app. An app offers more direct channel for sponsors to reach that target audience and for a longer period of time Increase interaction: Attendees are kept up to date, but they can also use it to create a personal schedule, sync this across multiple devices, and get notified when a presentation is about to start Stay connected: Attendees can stay connected to the community and engage in ongoing discussions. With an app attendees can send notifications to all users

 QR code prints the attendees’ name badge that can be easily scanned by other attendees  This allows the organizers to find out who made connection with whom  After the event, attendees can have an access to a list of contacts from the conference

QR code scanning on mobile app

• Technology conference
• 70,000 + attendees

IV

14

BIG Analysis | GEVME | WebSummit | ConferenceCompass

Data collection is a continuous process of gathering and measuring facts and figures on variables of interest. After the conference takes place, it is critical to collect data that measures the success of the conference. Often, customer validation and confirmation data is collected after the conference is held. There are techniques available for collecting post-conference data and attendee feedback which may be applied as part of a continuous feedback loop.

Focus groups Surveys Financial data

Data collection techniques:

• Active and passive data

are involved in data collection techniques after conference

• Active data comes

directly from attendees themselves

• Passive data includes

the indirect insights gathered during the conference

I

Data collection methods for obtaining quantitative and qualitative data after conferences

II III

15

1.3

BIG Analysis | Springer | Billetto

DEFINITION

A focus group is a small group of 4 - 12 people who meet with a trained researcher, facilitator or moderator for 1-2 hours to discuss selected topics in a non-threatening environment to explore attendees' perceptions, attitudes, feelings, ideas and encourage and utilize group interactions.

STRUCTURE & COMPOSITION

A good group mix impacts collected data. A mix

• f ages, sexes and social professional statuses
• f the participants can be used. Focus groups can

benefit when when there are power differences between the participants. Presence of a moderator can help in facilitating group discussions, keeping it focused without leading it.

CRITERIAS TO USE

 For research relating to group norms, meanings and processes  To clarify, extend, qualify or challenge data collected through other methods  To gain specific insights than a generic feedback

BENEFITS

 Multiple explanations of attendees' behavior and attitudes is readily articulated  Allows to collect more information in a shorter duration of time  Provides shared views in which attendees are influenced by the conference

I

Qualitative method of data collection using Focus groups as a tool

16

BIG Analysis | Wiley | Social research| Nature

Collecting data through widespread technique of surveys post conference

Quantitative: Helps conference organizers collect

information by asking concise questions while subjects get to choose from a specific set of answers

Short

“Post-event surveys highlight

the wins and losses and offer an opportunity to re-engage with attendees” -SurveyMonkey

Types Ways of Administration End users

Qualitative: In depth research that aims to gain

audience insights by asking open ended questions

Web based Mobile App Hard copy Email  Audiences: Are they coming back next year?  Speakers: Will they refer the conference?  Reviewers: Would they recommend the event?  Organizing team: How do they evaluate the workflow? Easily understood Nice Design

Consider providing a discount or setting up a $50 drawing to boost the participation rate!

II

17

BIG Analysis | SurveyMonkey | Getfeedback

Let’s talk money! What financial data is important after the conference is over?

On time performance

Because time is money it is important to check if the schedule went as planned, by making sure the event planner is keeping time for the schedule to happen on time. For example, when the door opens, and when the speakers start and finish.

On time budget

This indicator is important to check if there was any unexpected costs or

• waste. This will help adjust the forecast

for the upcoming year! For example reconcile between the financial projections before the conference and after the conference and dig deeper in the discrepancies.

Number of tickets sold

The more attendees the more tickets were sold! Afterall, the main goal of any conference is to be able to scale. This indicator is a major contributor to the final revenues. Coordinate with the registrations department about the “sales per ticket type” and "sales

• vertime”.

Cost per attendee

The cost per attendee is the breakeven point defined as the minimum number of attendees needed before making profits! Benchmarking against it, is key to determine the event success! It is calculated by dividing the total expenses

• f the event by the total number of

attendees.

III

18

BIG Analysis | Hubilo | Confmanager

Revealing the unknown with data analysis as it’s the cornerstone to launch a successful conference

87% 77%

The roadmap of data analysis

The outcome of data analysis should respond to three main objectives: The roadmap is consistent for different

• domains. First, you find the main research
• questions. Then, you collect data.

Afterwards, comes one crucial part which is making sense of the numbers by analyzing them using different tools. I Answer key research questions Get as much data as possible Compare results to a standard (demographics, history etc.) II III

Analyze your audiences persona and demographics Forecast your finances to avoid falling short Brand the event with an accurate marketing campaign

“Go beyond your competition”

78% of executives acknowledge the power of data in producing better outcomes. Hence, conducting analysis at every stage of the implementation of a sports conference, especially prior to the event date, is key! Main fields to consider prior to the conference

19

BIG Analysis | SurveyMonkey | CIO

2.1

87% 77%

The impact of analyzing audience persona and demographics on event planning before the conference

 Registration data helps in retrieving insights pertaining to the persona and demographics of each prospective attendee  Data Analytics can reflect upon attended expectations from the conference enabling the organizers in planning the event flow of the conference  Analyzing relevant data and using appropriate methods for analysis can lead to efficient event planning and event success

• 1. Attendee

IIICategories

Attendee categories like demographics and organization types are useful in analyzing trends and plan events based on obtained insights.

• 2. Crowd

IIIIDensity

Crowd density estimation helps the

• rganizers plan the shape of the

crowd flow and focus on conference related intricacies like number of check-in lines and proper venue.

• 3. Attendee

IIIIInterests

Predictive analytics interpret the trends pertaining to past and present topics of interest among the attendees to foresee and plan ahead for future conferences.

Case Study: Tamoco creating an edge for its clients with data analytics

Tamoco is an organization responsible for provision of location, profile and demographics based data, trends and insights to its customers. Tamoco’s client base constitutes some renowned names from different sectors like Uber, Unilever, Danone, Vodafone, PepsiCo, etc. and this clientele can be expanded by conferences that would benefit from gathering and analytics of relevant data to stay ahead in the competition.

I

Data analytics for understanding and nurturing the assets of a conference: Audience

20

BIG Analysis | Eventtia | Tamoco

87% 77%

Step 1: Extraction of insights Step 2.1: Strategized digital promotion Step 2.2: Offline promotion Step 3: Performance Evaluation

Some major data sources from which insights can be extracted include registration and social media. Insights like demographics, topics of interest and reasons to attend, online activity times and hashtags can together enable promotion of conference in a way that attracts more audience. Marketing can be done via social media platforms, digital marketing platforms, online advertisements and geo-fencing based on specific insights gained from data analytics. Online presence of prospective audience, popular web pages they visit and demographics are the key insights needed. Past and recent registration data can be used to target potential attendees who do not use popular social media and digital platforms. They can be targeted by email and SMS campaigns which can also be analyzed to understand what content and time attracts the audiences the most and implement it in the future. Analytics has not only made it easier to promote conferences but also analyze the timely performance of the various promotion techniques implemented. PCMA – a renowned organization boasts about its performance and revenue enhancement after utilizing the power of data in the field of sales and marketing.

II

Promotional and marketing campaigns before a conference made easy with data analytics

21

BIG Analysis | Towards Data Science | PCMA

 Performing pricing analytics enable to analyze trends in past audience registration data to come up with good pricing strategies. Metrics like willingness to pay (WTP), feature value, average revenue per user and lifetime value (LTV)/Customer acquisition cost (CAC) ratio help in determining the future pricing strategies.  Weekly analysis of registration data with respect to the number of registrations is crucial for implementation of dynamic pricing strategies aiming towards a trade-off between volume of registrations and the overall profits.  Early-bird discounts and loyalty promotions focus on volume enhancement while after a certain break-even volume, the prices can cater to increasing profits.  Competitor overview using data analytics is equally essential to compare and implement appropriate pricing strategies.

Pricing analytics can yield an ROI

• f 200 to 350

percent in 12 months

• Price Intelligently by

Profitwell, an industry standard software, boasts of determining proper pricing strategies for its clientele (Atlassian, lyft, HubSpot, PluralSight, Autodesk, etc.)

• It promises a growth
• f up to 30 percent to

its client base just by the use of pricing analytics. Case Study: A well of profits by Profitwell

Multiplying power with potential: Enhancing financial gains of a conference with data analytics

III

22

BIG Analysis | Profitwell | Price Intelligently | Phocas | Deloitte

People Counting Networking Event Safety Organized and substantiated planning and the direction given to the orderly progress of events where large groups of people gather together Use of density analysis to measure the number of people at a large gathering. Usage of mobile applications to interact with other attendees develop professional or social contacts.

Different domains in which data can be utilized for crowd management during the conference

23

BIG Analysis

2.2

Intelligent safety management system to prevent potential danger of the attendees in the event

Wireless sensors Storage module Control module

Detects the walking, step movement, and hand movements of the user to avoid any crushes or stampedes

Movement sensors

Predict dangerous cases before they occur during the event Located in either a watch or bracelet Handling all forms of required data to manage the crowd Personal information & contact information

Collecting data

Captures data from the attendees in the event, and store in designed

• database. The module

analyses collected data from sensors Monitors and evaluates human situations as individuals and as groups in the same area according to their locations. Real-time decision support to prevent crowd incidents Handling all forms of required data to manage the crowd Prevent crushes, fire, stampedes Presents smart diagrams for all data related to individuals and groups of people in the same area

Data visualization Presentation module

Heatmap, pie-charts

Tracking X Control

I

24

BIG Analysis | EEE

i. Knowing how many people attend your event is an important input into event planning and management processes, but it also plays a key role in the evaluation process ii. If the crowd has a consistent density, estimate the size of the event area (usually measured in square meters) and multiply it by the estimated number of people per square meter

Density of crowds from 1 (top left) to 4 people per square meter (clockwise)

iii. You’ll need to estimate the crowd size within each cell using the same logic as above, and then add the cell counts together to get the total crowd size

DIVISION OF EVENT AREA INTO SUB-AREAS

II

How can data analysis help with people counting at a large gathering?

25

BIG Analysis | EventEconomics

25

How can mobile applications be used to get people connecting at events?

Strength

ASK HELMUT

HELP ATTENDEES BOOK MEETINGS BEFORE YOUR EVENT BEGINS OFFER ATTENDEES A SEARCHABLE DIRECTORY CREATE A TAILORED EXPERIENCE WITH ARTIFICIAL INTELLIGENCE BOOST ENGAGEMENT ONLINE WITH A SOCIAL MEDIA WALL CREATE IMMERSIVE EXPERIENCES FOR ATTENDEES

There’s so much an event app can help an organizer do, like collecting important data on what the attendees look forward to and what they loved about the event.

 QR codes can be created for each individual attending the event to make the invites personal  Eventbrite Onsite powered by Entegy, Pathable and Guidebook are three successful event apps used in conferences  Attendify and Whova are popular event apps used for networking and B2B events  FestApp by Aloompa and Eventbase are well appreciated apps for festivals and consumer events

III

26

BIG Analysis | Eventbrite | Marketing Week London

Aftermath of a Conference is critical to increase marketing efficiency and boost attendance at the next conference. Analyzing shortcomings

• f events can help in the development of strategies to plan better for

future events. Tracking Techniques:

I II III

Speaker Engagement Active Community Engagement Social Media Engagement

• Database of past events can

be a goldmine of information

• Tracking attendee and

speaker data along with their engagement on various platforms like conference community and social media can help in analyzing the success of various events in a conference

• Analyzing shortcomings of

events can help in the development of strategies to plan better for future events.

IV

Net Promoter Score

Various domains where data analytics can be leveraged after conference

27

BIG Analysis | Methods and metrics for measuring the success I Bizzabo

2.3

Analyzing speaker engagement using opportunity score (OS)

 Determine how the event will be promoted  How will the invitation reach the audience  Targeted approach to the right audience group  Create separate flyers for different demographic’s group  Exposing the key-note speaker through media is an alternative way to approach the audience. It does not function as an advertisement; therefore it seems more appealing to the audience. Potential key media coverage  Keynote speaker must hold the

• rganization’s key messages

 Surveys function if the message was clearly delivered to the audience.  Successfully raise awareness of the

• rganization

 Opportunity score is an efficient way to measure whether if the audience is engaging with the keynote speeches. By doing so, the conference can market their identity to the audience as well. Potential for key message dissemination  Determine the audience  Sub-categorize the audience  Total number of followers on SNS  Total number of Speaker mentions on social media platforms  Data driven from the audience speaker engagement provides data that can be further utilized in making decision models for the conference. Audience size and composition

Key-note speakers are purposely a medium that engages the audience to the event. Conferences are utilizing this opportunity to draw closer connection with the audience and drawing information and analyzing them. Evaluating the speaker engagement provides data of how effective was the speech and what are the strategic decisions to make on the upcoming

• events. There are several primary data selections that can be collected. Demographics, media coverage, key message

dissemination, raise awareness. Opportunity score is the technique to define the effectiveness of these categories.

I

28

BIG Analysis | Forbes I The Measurement Advisor

Building a community of repeat-customers and maximizing the lifetime value of each and every one of them is a cost-effective way to grow your business than repeatedly finding and marketing to new one-time customers.

RETENTION

Measures community members that return to community space within a specific amount of time

ACTIVE USERS AVERAGE SESSION LENGTH

Measures the average amount of time a member spends in the community space in a single visit

% OF USER GENERATED CONTENT

Measures the total number of posts published by community members or host in a specific timeframe

TOTAL POSTS MARKED INAPPROPRIATE

Provides an estimate on how much moderation is required to ensure a protected troll-free community

• By creating a community, we

encourage an open dialogue with our customers and help them to start conversations with each other.

• A community

gathers loyal customers into a space to talk about your brand, share great customer experiences and encourage further loyalty. Provides snapshot of number of unique visitors who interacted with the product or visited community space in a period

Essential metrics that can be tracked through community engagement

II

29

BIG Analysis | Forbes I Klipfolio

 Metrics:  Total number of followers  Total number of page likes  Facebook: Provides a detailed analysis of page like total gains, total losses over a designated time period  Twitter: Twitter Analytics provides a 28-day summary of followers along with gain/loss trends.

Track Follower Growth

 Metrics:  Date and time of posting  Date and time of comments  Date and time of likes  Date and time of shares  Knowing when your audience is most likely to engage with your content is important. It helps in tailoring your strategy to post your content at the right time (when your audience is most active).  Facebook and Twitter both provide analytic tools to track when audience is most active and the best days of the week.

Optimal Times for Engagement

 Likes and reactions on posts: Sentiment analysis on posts can provide an analysis on the interest of current posts, and can inform the type of information that can be shared in the future.  Monitoring mentions: Creating and promoting an official hashtag for the event can help in easily tracking the level of conversation across social channels.  Content being shared: Highly shared posts indicate that it was particularly helpful, or had a strong emotional or psychological connection to it.  Referral traffic: Acquisition data tells the kind

• f traffic received from social to the website

and how that traffic performs once it arrives.

Additional Trackers Social media is now a part of our routine. According to Marketing Science Institute, 46% social network users discuss activities. Social media is a critical tool to analyze audience interests and market the event.

Essential metrics that can be analyzed from social media engagement of audience

III

30

BIG Analysis | Research gate | Socialmediaexaminer

This score asks a simple question: "On a scale of 1-10, how likely is it that you would recommend this event to friends?" This score is an indicator of:  How much value your event brought to attendees  Attendee loyalty score  Attendee satisfaction score Promoters Scores of 9-10 are considered "promoters" who act as loyal enthusiasts for the event brand. Passives Detractors  Simple Survey  Promoters and detractors need individual attention  Can be improved to ask additional feedback from Passives and Detractors Scores of 7-8 are considered "passives" who are satisfied attendees but are still vulnerable to competitive

• fferings.

Scores of 0-6 are considered "detractors" and run the risk of damaging event brand through negative reviews.

IV Analyzing attendees satisfaction using Net

Promoter Score (NPS)

Features:

31

BIG Analysis | Forbes | Bizzabo

A visual treat for your data using visualization tools

Power BI Google charts Tableau D3 QlikView Rawgraphs

32

3

Illustrating the outcomes of data analysis using Power BI makes it easier to set recommendations

87% 77%

• verview:

Power BI has many features that make it indispensable to users:

Power BI helps analysts visualize the data, after collecting and analyzing it in order for the final dashboards to be published. For progressive analysis, experts can employ different dimensions present in Power BI without the involvement of the IT department. Pay minimal cost, Power BI is a subscription based service that does not require buying licenses, support, etc. Flexibility, can be used across multiple devices & platforms Create reports easily, with the “drag and drop” functionality

• Dashboards can only be shared with users with

similar domains or tenants listed with the user Office 365.

• Power BI can only source data from a single

source.

• There are limited data sources that permit to

connect to real time Power BI dashboards.

“By putting this dashboard in Power BI, we can change the mindset of how meetings are run with business users.”

• Karl Kreis, Senior Product Intelligence Manager, Microsoft

Challenges

Capture outliers with the drill down functionality Run report Q&A with artificial intelligence

• Limited size for shared files: up to 250MB &

1GB for created database.

3.1

33

BIG Analysis | crmsearch | encorebusiness

87% 77% Google Charts

 A visualization tool for integrating insights obtained from data analysis with website interfaces, online dashboards and mobile devices  A web service that provides a two-fold solution in the form of varied visualization options and their direct display on your web platform

Notable features

 Variety: Vivid chart choices ranging from simple

• nes to highly complex visualizations

 Real-time analysis: Allows the display of charts

• btained from real-time analysis of data

 Customized dashboards: Create elegant dashboards with required controls and charts  Free of cost: No additional costs for adding visually appealing insights to your website  Portability: Creation and customization of charts from any type and kind of platform

Challenges

 Offline usage: Cannot create charts offline and is dependent on a good internet connection  Collaboration issues: Team members can face issues in collaborating over Google Charts  Interpreting interface: Google Charts interface is difficult to understand for a first-time user  Lack of sophisticated look: The final visualization is robust but looks very basic  Lack of AI capabilities: Google Charts is yet to introduce AI tools and capabilities

Creating and looking at the bigger picture of data with Google Charts

3.2

34

BIG Analysis | Google Charts | wpDataTables | Capterra | TrustRadius

Making data visually appealing using Tableau

Case Study:

Bol.com

“People can easily view multiple insights on a single dashboard, making it easy to spot important outliers and trend.”

Why Tableau? How did it help?

‘Tableau has given more control over business

• perations ( inventory management,

assortment quality and stock levels). This enabled us to improve overall customer service levels, while reducing environmental impact.’

Challenges Notable features

 Screen resolution: The layout of the dashboards gets disturbed if the tableau developer’s screen resolution is different from end user’s screen resolution  Notification of report: Absence of automatic refreshing of the reports requires users to put manual effort when updating the data  Data visualization: It converts unstructured information and data into visually appealing and functional dashboards  Data source connections: It supports connections with data sources like HADOOP, SAP and DB Technologies, improving data analytics quality and creates informative dashboards

A business intelligence tool for analytics visualizing. It showcases data in numerous vivid forms Healthcare Insurance Education

Leading web shop in the Netherlands for books, toys, and electronics

3.3

35

BIG Analysis | Tableau | AbsentData | SamSolutions

How does D3.js bring data to life?

D3 sits right between the data and visual graphics, the perfect place for a library meant for data visualization.

 D3 stands for Data Driven Documents  D3 helps you bring data to life using HTML, SVG, and CSS and is the most widespread BI&A platform that can extend their visualization capabilities using open- source libraries  D3’s emphasis on web standards gives you the full capabilities

• f

modern browsers without tying yourself to a proprietary framework, combining powerful visualization components and a data- driven approach to DOM manipulation 662 companies reportedly use D3.js in their tech stacks including Coursera, Square, and Zalando.

Flexible Simple Beautiful visualizations

All of these features have been timed perfectly to coincide with the rise of new browsers and a push towards documents created using open standards.

Easy connection between data and graphics Slow DOM Manipulation Expensive Notable Features: Challenges: Most compared technologies:

3.4

36

BIG Analysis | D3.js | Gartner | Stackshare

Easily accessible application with multiple case usage Qlikview

QlikView is a data analysis platform that provides self-service for users and organizations. With QlikView you can analyze data and use your data discoveries to support decision making. QlikView lets you to visualize the data collected and cost-effectively provide insights to the industry.

Customer Experience  Provides optimizing data warehouse creation  Automatic designing data warehouse, generating ETL code and applying updates  Reduces time, cost and risk for user to deliver Scalability

 Scales uniformly, allowing IT professional to effectively capacity plan for future system  Able to handle thousands of concurrent users and extreme amount of data, end user performance is high  System administration follows standard approaches

Cost efficiency

 Open source application, for personal usage, it is a free tool with all complete features  Price ranges for corporations are customized. Each company get their best pricing on product

Challenges

 No Online analytical processing  Users cannot predict the profitability of projects  Without Extensions downloading user need to create custom extensions  Maintain the coding standards, else the audit team won't allow to move application in production line

3.5

37

BIG Analysis | Selecthub I Businessqlik I Qlik

RAWGraphs is an open source web application for the creation of static data visualizations. It provides simple ways to map data dimensions onto visual variables. It aims at providing a missing link between spreadsheet applications like Microsoft Excel, Apple Numbers, Google Docs, etc. and vector graphics editors like Adobe Illustrator, Inkscape, etc. Typical customers include Startups, SMEs, Agencies, Enterprises.

Customer Experience

Customer experience is a measure of Product

• usability. RAWGraphs provides easy

visulaizations in 4 steps:  Insert data by uploading or pasting  Select Visualization model  Customize  Export visulaizations

Integration

 Allows downloads as vector SVG or PNG images  Easy to embed into web page  Supports further edits through any vector graphics editor.

Safety & Cost

 Data inserted in the web application is processed only by web browser. No one can see, touch or copy the data.  Being an open source application, it is a free tool with all complete features.

Challenges

 No offline stand-alone version  No support for dynamic visualizations: The visualizations do not automatically update.  No Reusability of new models: To be able to build on existing models.

3.6

Bridging the gap between spreadsheet applications and graphic editors using RAWGraphs

38

BIG Analysis | Rawgraphs

About Thought Leadership

The Thought Leadership Project is an initiative to inspire the strategic use of thought leadership in ways that unlock commercial advantage. This project has the simple aim of sharing best practice, interesting research, and the latest thinking amongst communication professionals to champion best practice in the effective marketing of thought leadership. It involves great ideas that leaders and think about and respond to the issues that face their business and society. Member of this project are informed opinion leaders and the go-to people in their field of expertise. They are trusted sources who move and inspire people with innovative ideas; turn ideas into reality and know and show how to replicate their success. A thought leader is, “an individual or firm that prospects, clients, referral sources, intermediaries and even competitors recognize as one of the foremost authorities in selected areas of specialization, resulting in its being the go-to individual or organization for said expertise.” The second part of their definition claims that a thought leader is, “an individual or firm that significantly profits from being recognized as such.” Russ Alan Prince & Bruce Rogers Forbes Contributors

39

BIG Analysis | Ischool I BCG I Thoughleadershipproject

About Business Intelligence Group (BIG)

The Business Intelligence Group (BIG) at the School of Information Sciences at the University of Illinois at Urbana-Champaign (UIUC) started in 2014 as an experiential learning platform for the students interested in pursuing careers in business and technology management consulting. BIG is a student consulting organizations primarily specializing in formulating strategies in knowledge management, information management, data analytics, business research, and technology-based business development. The School of Information Science at UIUC had consistently been offering business-related courses such as Information Consulting, Competitive Intelligence, and Business Information. However, rapidly changing requirements from industry necessitated engaging students with real-world experiences, linking their knowledge learned in classroom to solving complex problems which many organizations now face with the emergence of new technologies and opportunities.

BIG’s objectives

• Clients must receive high quality services that have actual and practical impact on their

businesses.

• BIG seeks to create an experiential learning environment where students are immersed in real

world projects.

• Students gain professional experiences utilizing their classroom knowledge and training to solve

complex business and technology management problems.

40

BIG Analysis | Ischool I BCG I Thoughleadershipproject

• Herrmann, N. (n.d.). Top 10 Social Media Analytics Features. Retrieved March

28, 2020, from https://www.quintly.com/blog/top-10-social-media-analytics- features

• Newberry, C. (2020, April 2). 11 of the Best Social Media Analytics Tools (Free

and Paid). Retrieved April 5, 2020, from https://blog.hootsuite.com/social- media-analytics/

• Lomborg, S. (2014, July 8). Using APIs for Data Collection on Social Media.

Retrieved March 28, 2020, from https://www-tandfonline- com.proxy2.library.illinois.edu/doi/full/10.1080/01972243.2014.915276

• Elo-Dean, S. (1997). Data mining the IBM official 1996 Olympics Web site.
• How to Get Started with Data-Driven Email Marketing. (2019, December 18).

Retrieved March 28, 2020, from https://elasticemail.com/blog/marketing_tips/how-to-get-started-with-data- driven-email-marketing

• How to Capture More Data for Your Event. (2017, October 9). Retrieved March

28, 2020, from https://www.eventbrite.ie/blog/capture-data-event-ds0c/

• Epstein, D. (n.d.). Event Marketing Automation: The 2020 Guide. Retrieved

March 28, 2020, from https://blog.bizzabo.com/event-marketing-automation

• Crowd monitoring: an interview with Peter Rakers about this technology. (2020,

February 24). Retrieved March 28, 2020, from https://business.orange.be/en/discover/testimonials/crowd-monitoring- interview-peter-rakers-about-technology

• Shaw, A. (2018, May 11). Council Post: How Social Media Can Move Your

Business Forward. Retrieved March 28, 2020, from https://www.forbes.com/sites/forbescommunicationscouncil/2018/05/11/how- social-media-can-move-your-business-forward/#5726a8954cf2

• Gill, P., Stewart, K., Treasure, E., & Chadwick, B. (2008, March 22). Methods of

data collection in qualitative research: interviews and focus groups. Retrieved March 28, 2020, from https://www.nature.com/articles/bdj.2008.192

• Fabijan, A., Olsson, H. H., & Bosch, J. (2015, June 10). Customer Feedback

and Data Collection Techniques in Software R&D: A Literature Review. Retrieved March 28, 2020, from https://link.springer.com/chapter/10.1007/978- 3-319-19593-3_12

• 8 Approaches to Passive Data Collection for Events. (2020, January 28).

Retrieved March 28, 2020, from https://billetto.co.uk/blog/passive-data- collection-for-events/

• How to Run Onsite Check-in & Registration for Small Conferences. (n.d.).

Retrieved March 28, 2020, from https://www.gevme.com/l/project/onsite-check- in-registration-for-small-conferences/

• 7 Reasons Why an Event App is a Must-have for Your Next Event. (2017,

September 11). Retrieved March 28, 2020, from https://www.conferencecompass.com/7-reasons/

• Five Essential Features of Google Analytics. (2017, August 14). Retrieved

March 28, 2020, from https://getlevelten.com/blog/colin/five-essential-features- google-analytics

• Meeting Schedule Apps Keep Attendees Organized. (2018, October 15).

Retrieved March 28, 2020, from https://guidebook.com/mobile-guides/meeting- schedule-app/

• GSMA Sma rt Cities Guide: Crowd Manag ement. (n.d.). Retrieved March 28,

2020, from https://www.gsma.com/iot/wp-content/uploads/2016/10/GSMA- Crowd-management-case-study-web/ 41

Bibliography

• Wilson, V. (2013, January 2). Focus Groups: a useful qualitative method for

educational research? Retrieved March 28, 2020, from https://onlinelibrary.wiley.com/doi/epdf/10.1080/0141192970230207

• Focus Groups. (n.d.). Retrieved March 28, 2020, from

http://sru.soc.surrey.ac.uk/SRU19.html

• Hazelton, J. (n.d.). How to use data and analytics to plan a more impactful
• event. Retrieved April 5, 2020, from https://www.eventtia.com/blog/how-to-use-

data-and-analytics-to-plan-a-more-impactful-event

• Tamco. (2019, August 29). About Tamoco - Connecting Online To Offline With

Location Intelligence. Retrieved April 5, 2020, from https://www.tamoco.com/about/

• Qualitative Survey Types & Examples. (n.d.). Retrieved 2020, from

https://www.surveymonkey.com/mp/conducting-qualitative- research/?program=7013A000000mweBQAQ&utm_bu=CR&utm_campaign=7 1700000059189232&utm_adgroup=58700005410222818&utm_content=39700 049736551245&utm_medium=cpc&utm_source=adwords&utm_term=p497365 51245&utm_kxconfid=s4bvpi0ju&gclid=CjwKCAjwp- X0BRAFEiwAheRui8PqHzW01tpId10mQ7yuCO5MFTh0t5iNkVOHA0N486BO VDYVrjmV8xoCmz0QAvD_BwE

• Barrett, J. (2020, January 2). The Ultimate Guide to Conference and Event
• Surveys. Retrieved March 28, 2020, from

https://www.getfeedback.com/resources/online-surveys/ultimate-guide- conference-event-surveys/

• Higgins, R. (2018, August 27). Using Real-Time Event Data to Power Your
• Conference. Retrieved April 5, 2020, from

https://www.eventbrite.com/blog/real-time-event-data-ds0c/

• Tools to create your dream conference. (n.d.). Retrieved April 5, 2020, from

https://www.confmanager.com/main.cfm?cid=1&nid=3337

• How to Measure your Event ROI? (2019, December 12). Retrieved April 5,

2020, from https://blog.hubilo.com/how-to-measure-event-roi/

• Pearl, M. (2017, April 14). Why CEOs believe problem solving through data is

the future of business. Retrieved April 5, 2020, from https://www.cio.com/article/3189984/why-ceos-believe-problem-solving- through-data-is-the-future-of-business.html

• Using Data to Improve Your Event-Marketing Strategy. (2018, November 10).

Retrieved April 5, 2020, from https://www.pcma.org/using-data-to-improve-your- event-marketing-strategy/

• Agrawal, A. J. (2016, October 7). Is Community-Based Marketing Trending?

Retrieved April 5, 2020, from https://www.forbes.com/sites/ajagrawal/2016/09/30/is-community-based- marketing-trending/#56fda4352128

• Software, P. (n.d.). How pricing strategies work better with data analytics.

Retrieved April 5, 2020, from https://www.phocassoftware.com/business- intelligence-blog/how-pricing-strategies-work-better-with-data-analytics

• Pricing Strategy Driven by Data. (n.d.). Retrieved April 5, 2020, from

https://www.priceintelligently.com/?__hstc=174954301.77b7b49613488e1215d0 d39630598a9b.1586165299474.1586165299474.1586165299474.1&__hssc=1 74954301.68569.1586165299475&__hsfp=2279255242&_gl=1*1u1vvdn*_gcl_a w*R0NMLjE1ODYxNjc0NTkuRUFJYUlRb2JDaE1JX0pldm5NYlQ2QUlWZ2JiSU NoMmY5QTJtRUFBWUFpQUFFZ0lNM2ZEX0J3RQ..

• Campbell, P. (2020, April 20). What are Pricing Analytics? Use Pricing Analytics

to Increase Profits. Retrieved April 22, 2020, from https://www.profitwell.com/blog/pricing-analytics 42

Bibliography

• Norkus, J., & Singh, R. (n.d.). Pricing Analytics The three-minute guide.

Retrieved April 5, 2020, from https://www2.deloitte.com/content/dam/Deloitte/global/Documents/Deloitte- Analytics/

• What is crowd management? (n.d.). Retrieved April 5, 2020, from

https://www.heras-mobile.com/crowdmanagement/wat-is-crowd-management

• N. Farooqi, "Intelligent safety management system for crowds using

sensors," 2017 12th International Conference for Internet Technology and Secured Transactions (ICITST), Cambridge, 2017, pp. 144-147.

• Irisys. (n.d.). People Counting - Discover The Benefits. Retrieved April 5, 2020,

from https://www.irisys.net/people-counting

• Crowd counting. (n.d.). Retrieved April 5, 2020, from

https://www.eventhosts.org/resources/

• Torres, A. (2020, March 4). The Best Event App for Every Type of Event:
• Eventbrite. Retrieved April 5, 2020, from https://www.eventbrite.com/blog/best-

event-apps-ds00/

• Sawyer, K. (2019, December 5). 5 Ways to Use Apps to Get People

Networking at Your Event - Eventbrite. Retrieved April 5, 2020, from https://www.eventbrite.com/blog/networking-apps-ds00/

• Event apps raise the bar. (2011). Marketing Week, , 14. Retrieved from

https://search-proquest- com.proxy2.library.illinois.edu/docview/898493342?accountid=14553

• Herzog, C. (2013, June 8). Methods and metrics for measuring the success of

enterprise social software - what we can learn from practice and vice versa. Retrieved April 5, 2020, from https://www.zora.uzh.ch/id/eprint/89258/1/METHODS_AND_METRICS/

• Kim, S. (n.d.). 20 Important KPI's for Measuring Event Success. Retrieved April

5, 2020, from https://blog.bizzabo.com/20-kpis-to-measure-event-success

• Paine, K. (2016, August 19). How to Evaluate Speaker Opportunities and

Measure Thought Leadership Programs. Retrieved April 5, 2020, from http://painepublishing.com/measurementadvisor/evaluate-speaker-

• pportunities-measure-thought-leadership-programs/
• Solomon, M. (2017, July 23). How A Keynote Speaker Can (And Can't)

Transform Your Event. Retrieved April 5, 2020, from https://www.forbes.com/sites/micahsolomon/2013/10/16/what-a-keynote- speaker-can-and-cant-do-for-your-event-your-company-and-for-your-corporate- goals/#2b6882a95902

• Court, L., & Dupuis, M. (2018, November 6). The 5 essential metrics for

community engagement. Retrieved April 5, 2020, from https://www.klipfolio.com/blog/5-essential-metrics-for-community-engagement

• Agrawal, A. J. (2016, October 7). Is Community-Based Marketing Trending?

Retrieved April 5, 2020, from https://www.forbes.com/sites/ajagrawal/2016/09/30/is-community-based- marketing-trending/#56fda4352128

• Agius, A. (2016, November 8). 10 Metrics to Track for Social Media Success.

Retrieved April 5, 2020, from https://www.socialmediaexaminer.com/10-metrics- to-track-for-social-media-success/

• Kim, S. (n.d.). 20 Important KPI's for Measuring Event Success. Retrieved April

5, 2020, from https://blog.bizzabo.com/20-kpis-to-measure-event-success

• Hyken, S. (2016, December 5). How Effective Is Net Promoter Score (NPS)?

Retrieved April 5, 2020, from https://www.forbes.com/sites/shephyken/2016/12/03/how-effective-is-net- promoter-score-nps/#40a4ed2323e4 43

Bibliography

• Greenhill, M. (2018, March 6). Top 10 Benefits of Power BI: Encore Blog.

Retrieved April 12, 2020, from https://www.encorebusiness.com/blog/power-bi- top-10-benefits/

• Microsoft Power BI Review. (n.d.). Retrieved April 12, 2020, from

http://www.crmsearch.com/powerbireview.php

• Google Charts Reviews & Ratings 2020. (2019, December 13). Retrieved April

12, 2020, from https://www.trustradius.com/products/google-charts/reviews

• Google Charts Reviews and Pricing - 2020. (n.d.). Retrieved April 12, 2020,

from https://www.capterra.com/p/176573/Google-Charts/

• Google Charts - wpDataTables - Tables and Charts WordPress Plugin. (n.d.).

Retrieved April 12, 2020, from https://wpdatatables.com/documentation/wpdatacharts/google-charts/

• Charts | Google Developers. (n.d.). Retrieved April 12, 2020, from

https://developers.google.com/chart

• Shivangi, Alves, C., & Khanna, T. (2020, March 25). Pros and Cons of Tableau

Software for Data Visualization [Review]. Retrieved April 12, 2020, from https://www.sam-solutions.com/blog/tableau-software-review-pros-and-cons-

• f-a-bi-solution-for-data-visualization/
• Advantages and Disadvantages of Tableau. (n.d.). Retrieved April 12, 2020,

from https://www.absentdata.com/advantages-and-disadvantages-of-tableau/

• Bostock, M. (n.d.). Data-Driven Documents. Retrieved April 12, 2020, from

https://d3js.org/

• Why developers like D3.js. (n.d.). Retrieved April 12, 2020, from

https://stackshare.io/d3

• Why D3.js is So Great for Data Visualization: Visually Blog. (n.d.). Retrieved

April 12, 2020, from https://visual.ly/blog/why-d3-js-is-so-great-for-data- visualization/

• Data Analytics Platform: Qlik Sense. (n.d.). Retrieved April 12, 2020, from

https://www.qlik.com/us/products/qlik-sense?ga-link=bjp-hp-tab

• QlikView Software. (n.d.). Retrieved April 12, 2020, from

https://www.selecthub.com/big-data-analytics-tools/qlikview/

• Dipartimento, M. M., Mauri, M., Dipartimento, T. E., Elli, T., Caviglia, G., Calibro,
• G. U., … Azzi, M. (2017, September 1). RAWGraphs: A Visualisation Platform

to Create Open Outputs. Retrieved April 12, 2020, from https://dl.acm.org/doi/10.1145/3125571.3125585

• The Thought Leadership Project. (n.d.). Retrieved April 19, 2020, from

https://www.thoughtleadershipproject.org/

• Thought Leadership Publications & Business Insights: BCG. (n.d.). Retrieved

April 19, 2020, from https://www.bcg.com/en-us/featured-insights/thought- leadership-ideas.aspx

• Song, Y.-S. (n.d.). The Business Intelligence Group at the University of Illinois at

UrbanaChampaign: A Case Study . Retrieved April 19, 2020, from https://ischools.org/resources/ 44

Bibliograhy