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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

Web and Business Analytics for Higher Education

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Page 1: Web and Business Analytics for Higher Education

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

Page 2: Web and Business Analytics for Higher Education

AGENDA

● Introduction: Context and Definitions

● Analytics Tools and Case Studies: Website, Email,

Social

● Data Integration Case Study

● Resources for Further Learning

Page 3: Web and Business Analytics for Higher Education

INTRODUCTION

Page 4: Web and Business Analytics for Higher Education

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

Page 5: Web and Business Analytics for Higher Education

Challenge #1

Page 6: Web and Business Analytics for Higher Education

Challenge #2

• Lack of baseline data

• No concrete online

communication goals

Page 7: Web and Business Analytics for Higher Education

Opportunities

● Website new design

● Accessible online and offline data

● Accessible student pool of expertise

Page 8: Web and Business Analytics for Higher Education

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

Page 9: Web and Business Analytics for Higher Education

Success indicators

● Improved online communication efficiency

● Lower offline communication workload

● Less “emergency” situations

● Happier students, faculty and staff at OGS

Page 10: Web and Business Analytics for Higher Education

Business and Web Analytics

Page 11: Web and Business Analytics for Higher Education

Responsibilities & Projects

Reporting &

Monitoring

Data

Integration

Testing &

OptimizationGoogle Analytics

for baseline data

Web redesign

monitoring

Offline & online

data integration

Email analytics

Social media

competitive analysis

Page 12: Web and Business Analytics for Higher Education

REPORTING & MONITORING

Page 13: Web and Business Analytics for Higher Education

GOOGLE

ANALYTICS

Page 14: Web and Business Analytics for Higher Education

Bounce

RatePercentage of visitors who viewed only one page

then left the site

Visitor People who visit our web pages, identified by

cookie

Time

on PageTime visitors spend browsing each page on our

website

Basic Concepts:

Page 15: Web and Business Analytics for Higher Education

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:

Page 16: Web and Business Analytics for Higher Education

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

Page 17: Web and Business Analytics for Higher Education

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

Page 18: Web and Business Analytics for Higher Education

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

Page 19: Web and Business Analytics for Higher Education

WEBSITE REDESIGN PROJECT

Page 20: Web and Business Analytics for Higher Education

● 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

Page 21: Web and Business Analytics for Higher Education

Analytics for Web Redesign Project

Redesign comparison analysis : Frozen visitor reports saved

for comparison & monitor

Page SegmentationCategorize 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

Page 22: Web and Business Analytics for Higher Education

Link Page

Page 23: Web and Business Analytics for Higher Education

Content Page

Page 24: Web and Business Analytics for Higher Education

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

Page 25: Web and Business Analytics for Higher Education

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:

Page 26: Web and Business Analytics for Higher Education

TESTING & OPTIMIZATION

Page 27: Web and Business Analytics for Higher Education

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.

Page 28: Web and Business Analytics for Higher Education

Open & Click: how many recipients open/click through the email

Click through rate: clicks we gain per open

Email Analytics

Page 29: Web and Business Analytics for Higher Education

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

Page 30: Web and Business Analytics for Higher Education

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

Page 31: Web and Business Analytics for Higher Education

Testing & Experiments

Page 32: Web and Business Analytics for Higher Education

Facebook Competitive Analysis

Posting patternsSocial media awarenessBest practices

Measurement

Competitive analysis

Followers: ‘people talking about’

Posts: Frequency

Engagement: post per engagement

(shares, likes)

Page 33: Web and Business Analytics for Higher Education

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

Enga

gem

ent

per

po

st

Fan Page Comparison: Engagement on Brand Posts

Link Photo Status Video Other

Page 34: Web and Business Analytics for Higher Education

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

Page 35: Web and Business Analytics for Higher Education

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:

Page 36: Web and Business Analytics for Higher Education

DATA INTEGRATION

Page 37: Web and Business Analytics for Higher Education

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

Page 38: Web and Business Analytics for Higher Education

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

Page 39: Web and Business Analytics for Higher Education

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

Page 40: Web and Business Analytics for Higher Education

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:

Page 41: Web and Business Analytics for Higher Education

RESOURCES

Page 42: Web and Business Analytics for Higher Education

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)

Page 43: Web and Business Analytics for Higher Education

Questions?

Thank you for coming today!

Melissa Zuroff

[email protected]

Qianyun (Poppy) Zhang

[email protected]