This is a presentation I gave with Qianyun (Poppy) Zhang on using web and business analytics in a higher education setting at New York University's Student Affairs Conference, February 2015.

1. WEB AND BUSINESS ANALYTICS
FOR HIGHER EDUCATION
Melissa Zuroff, Communications Manager, Office of Global Services,
New York University
Qianyun (Poppy) Zhang, Web and Business Analyst, Office of Global
Services, New York University

2. AGENDA
● Introduction: Context and Definitions
● Analytics Tools and Case Studies: Website, Email,
Social
● Data Integration Case Study
● Resources for Further Learning

3. INTRODUCTION

4. Who we are, our goals
Office of Global Services:
Keep international students, faculty, and
researchers who are in the U.S., and those in the
NYU community going abroad in legal
immigration compliance
Communications:
Provide our audiences with information they can
easily find, act on, and understand

5. Challenge #1

6. Challenge #2
• Lack of baseline data
• No concrete online
communication goals

7. Opportunities
● Website new design
● Accessible online and offline data
● Accessible student pool of expertise

8. Tackling the challenges
● Create student position for web and business
analytics
● Build and establish analytics procedures and
baselines
● Optimize digital channels and distribute
resources to students
● Integrate offline database with online data
to monitor trends and shifts

9. Success indicators
● Improved online communication efficiency
● Lower offline communication workload
● Less “emergency” situations
● Happier students, faculty and staff at OGS

10. Business and Web Analytics

11. Responsibilities & Projects
Reporting &
Monitoring
Data
Integration
Testing &
Optimization
Google Analytics
for baseline data
Web redesign
monitoring
Offline & online
data integration
Email analytics
Social media
competitive analysis

12. REPORTING & MONITORING

13. GOOGLE
ANALYTICS

14. Bounce
Rate
Percentage of visitors who viewed only one page
then left the site
Visitor People who visit our web pages, identified by
cookie
Time
on Page
Time visitors spend browsing each page on our
website
Basic Concepts:

15. PAGES EXITENTRANCE
From, how,
landing page,
time,
geographic
location, demo
IP, interest
Pages, content,
layers,
video,
download,
transaction
Exit point,
return, where,
page,
action,
device
How Google Analytics Tracks You:

16. WEB PAGES
Google Analytics provides
codes to be implemented
User info, page
data, logins, etc.,
Google server
Gather raw data
Prepare for reports
Basic reports such as hot
content, resources, visitor’s
behavior
Customization is available

17. Real-time can show the current events
happening on site
Dashboards provide aggregation of
basic reports to share with key
shareholders
Each of these four tabs include multiple
reports on visitor activity, channel
performance, visitor behavior and
revenue/goal

18. Customization Example
Business objective:
gain more workshop
sign-ups
Customize a goal
in Google
Analytics and
specify what you
want to see
when people
submit sign-up
forms
Report on:
Sign-up
Goal completeness
How many clicks
When clicked
People clicked come
from where
Viewed but not clicked
Strategize to promote
and optimize!
WEB PAGES

19. WEBSITE REDESIGN PROJECT

20. ● Supported by NYU Digital Communication Team
and based on previous user testing results
● Analytics needs: set up standards to monitor
page performances before and after the
redesign to make sure we gained traffic increase

21. Analytics for Web Redesign Project
Redesign comparison analysis : Frozen visitor reports saved
for comparison & monitor
Page Segmentation
Categorize page and assign
performance indicators accordingly
Content page
Link page Page that embed links that we want
visitors to click through
Pages that provide mostly
content, less links

22. Link Page

23. Content Page

24. Link Page
Page that links to other
pages
We want visitors to follow
our lead
We want visitors to find
information they need in
seconds
Measurement:
Bounce Rate
Time on page
Visitor
Content Page
Final page of each
subject
We want visitors to read
our content
We expect visitors to leave
after reading the content
they looked for
Measurement:
Time on page
Bounce Rate
Visitor

25. Web elements are not created equal so
segmentation is an essential part of analytics.
Do not be afraid to measure your progress
and success because this is how we learn.
TAKEAWAY:

26. TESTING & OPTIMIZATION

27. Email Analytics
We want students to have some resources before they walk in for our offline
services and MailChimp helps measure how efficient we are on this.

28. Open & Click: how many recipients open/click through the email
Click through rate: clicks we gain per open
Email Analytics

29. Targeted Communication
We want to send students the information they want the most so,
depending on the message, we segment our mail list based on:
Program progress
Enrollment type
Degree level
Nationality
Visa type & needs

30. Testing & Experiments
A/B testing allows us to find the key differentiators that can improve
our email communication. Elements to test:
Subject line
Content
Timing
(day of the week and time of day sent)
Recipient group

31. Testing & Experiments

32. Facebook Competitive Analysis
Posting patterns
Social media awareness
Best practices
Measurement
Competitive analysis
Followers: ‘people talking about’
Posts: Frequency
Engagement: post per engagement
(shares, likes)

33. FACEBOOK ANALYSIS
We make sure that our post type composition looks similar to our peers
doing the best. We also want to know which type of post could bring
us the most engagement (likes, shares).
Source: simplymeasured
-10
-5
0
5
10
15
20
25
30
35
Engagementperpost
Fan Page Comparison: Engagement on Brand Posts
Link Photo Status Video Other

34. Facebook Competitive Analysis
Peer’s best
performance &
patterns
- Use human face & contribution
from fans
- Work with on-campus publishers
- Offline engagement
- Catch all aspects of student life
Success indicators

35. Analysis is not a one time thing. Optimizing
and analyzing is an on-going cycle and a
good content writer is a must to
optimization.
TAKEAWAY:

36. DATA INTEGRATION

37. Front desk kiosk:
Student ID
Questions/issues
Time
School/program
Advisor seen
Service length
Results
Offline data
Analyze:
Work-load across time
Advisor service length
Patterns/trends in issues student
come in for
Specific topics lagging down the
service time

38. Phone calls & emails:
Student ID
Questions/issues
Time
Advisor
Service length
Results
Analyze:
Patterns/trends in issues
Reasons students call
Whether information online
Offline data

39. Integrated Trend Analysis
Managers can monitor and oversee all channels through one single dashboard.
Opportunities for improvement can be identified through comparison.
Web Call&Email Walk-in
Visa status
*internship, enrollment, visa status and study abroad are types of information that OGS advises on
Enrollment
Study abroad
Internship
Web Call&Email Walk-in
Web Call&Email Walk-in Web Call&Email Walk-in

40. Start with data that is accessible to you and
implement the strategies according to the
data. Always keep the business objective
clear to all team members.
TAKEAWAY:

41. RESOURCES

42. Websites
Books & training
Google analytics forum: https://productforums.google.com/forum/#!forum/analytics
Online behavior blog: http://online-behavior.com/
Web structure knowledge: http://searchenginewatch.com/category/analytics
Analytics Guru-Avinash Kaushik: http://www.kaushik.net
Test your business analytics atmosphere: http://myanalyticsscore.com/
<Web Analytics 2.0> by Avinash Kaushik
<Optimal Database Marketing> by Ronald Drozdenko and
& Perry Drake
<Web Analytics Fundamentals> with Matt Bailey, lynda.com training
<Certificate in Digital Analytics> NYU School of Professional Studies
<Digital Marketing 10 week course> General Assembly
(https://generalassemb.ly/education/digital-marketing)

43. Questions?
Thank you for coming today!
Melissa Zuroff
melissa.zuroff@nyu.edu
Qianyun (Poppy) Zhang
qianyunzhang@nyu.edu