1 Dickson K.W. Chiu PhD, SMIEEE, SMACM, Life MHKCS COMP7880: E-Business Strategies Creating...
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Transcript of 1 Dickson K.W. Chiu PhD, SMIEEE, SMACM, Life MHKCS COMP7880: E-Business Strategies Creating...
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Dickson K.W. ChiuPhD, SMIEEE, SMACM, Life MHKCS
COMP7880: E-Business StrategiesCreating effective web presence
Dickson Chiu COMP7880-web-2
Strategic Premise
Building a Web Site for an Enterprise or
Non-Profit is Not an Exercise
in Either
Technology Or Aesthetics.
It is an Exercise in Creating Satisfying
Customer Experience in a Way that Leads to
Cost-Effective Execution of Marketing Strategy.
Dickson Chiu COMP7880-web-3
Effective Execution of Marketing Strategy
Building Web sites that deliver satisfying customer experience and do so in a way that fits both strategy and budget.
Visual attractiveness is a plus, but not a necessity.
If technology gets in trouble, it is a negative, not a plus, e.g., flash intros/demos.
Web sites is an important marketing strategy but not the only one - that must be cost-effective.
Most Web sites should eventually be expected to produce a reasonable return on investment.
Dickson Chiu COMP7880-web-4
Web Site Development Process
Not too different from marketing / communications planning
Planning a Web site should be first Foremost a business/marketing planning process Good business sense should take precedence
Dickson Chiu COMP7880-web-5
Establishing Site Objectives
Enterprise/Unit Marketing Objectives cascade with levels
The Interactive Nature of the Internet Communications/Branding Objectives Behavioral Objectives
Role of Web Site on Overall Marketing/ Marketing Communications Strategy integration of online and offline strategy for
multi-channel marketers
Dickson Chiu COMP7880-web-6
Identify / Describe Target Market
Demographics, Life Styles
Motives for using the site
Tasks they wish to perform
Consider utility and customization
Stepwise scenario development / use
case analysis
Dickson Chiu COMP7880-web-7
Site Content / Navigation Structure
What content do visitors need/expect?
How do they access content?
More than just a straightforward replication of offline
content
Interactions
Marketing research
What role should visuals/graphics play?
Simple and Usable
Content and structure more important
Dickson Chiu COMP7880-web-8
Typical Site Hierarchy
Enough second-level pages to clearly categorize content but not create confusion
Visitor should never be more than 2-3 intuitive mouse clicks away Avoid dead ends
Dickson Chiu COMP7880-web-9
Main Page Design
marketers should specify the goals and requirements to guide the technical people
Dickson Chiu COMP7880-web-10
Site Design Issues
Content Navigation Color (especially background) Font Minimize Scrolling Artwork Animation/Graphics/Rich MediaDemo Case: http://www.cnet.com/
Dickson Chiu COMP7880-web-11
Deployment and Tuning
Uploading site server / hosting service raises many technical issues
Calibrating and fine tuning for best site performance is highly technical
Reliability and scalability issues Test at your target customers’ regions
and environment!
Dickson Chiu COMP7880-web-12
Measure / Evaluate / Improve Performance & Effectiveness
Measuring and Improving site performance is a technical task
Measuring and improving the business effectiveness of site is a marketing task
Dickson Chiu COMP7880-web-13
Measurement Techniques
Concept Tests - basic marketing
research techniques
Prototype Tests
Beta (Functional) Tests
Customer Usability/Satisfaction
Feedback
Dickson Chiu COMP7880-web-14
Measuring Web Customer Satisfaction
Employs research methods developed offline
Adapted for the online environment Single measures vs multiple measures
Dickson Chiu COMP7880-web-15
Satisfaction with Content
Dickson Chiu COMP7880-web-16
Satisfaction with Transactional Experiences
Dickson Chiu COMP7880-web-17
BIZRATE.com Surveys CustomerExperience to Rate Sites
At Checkout and After Delivery
Dickson Chiu COMP7880-web-18
E-Commerce Satisfaction Drivers
Dickson Chiu COMP7880-web-19
What Should The Marketer
Do
To Create Good
Customer Experience
On The Web Site?
Dickson Chiu COMP7880-web-20
Stages/Elements of Customer Experience
Dickson Chiu COMP7880-web-21
Continuous Improvement Essential
Figure 9.12TOP Image Only
Goes Here
Figure 9.13TOP Image Only
Goes There
Dickson Chiu COMP7880-web-22
Elements WSJOnline Offers
Usable Site Navigation Made Easier By Familiarity
With Print Version Personalization Options A Trusted Brand Name E-Mail Notices—Features, Breaking News Community Through
Feedback/Discussions
Dickson Chiu COMP7880-web-23
Web Site Costs
2 to 3 times as much to maintain a site as it costs to develop it initially!
More on website evaluation
COMP7880-W2-24
Dickson Chiu COMP7880-web-25
The Power of Clickstream to Produce Internet Metrics
Tremendous amount of data produced on the Internet.
One of the main challenges for the Internet marketer is to control this data to improve existing marketing programs and to gain insights into additional marketing efforts that have a high probability of being productive
Dickson Chiu COMP7880-web-26
Purpose of Usability Testing
Visitors expect smooth navigation suiting their need
To be pleased and not frustrated The fundamental basis of Web site usability
is user task performance. • Visitors come to the Web site motivated to
accomplish some goal, to perform some task.
• Usability testing is designed to ensure that task performance is not only possible, but hopefully efficient and entirely satisfactory.
Dickson Chiu COMP7880-web-27
Types/Stages of Usability Testing
Concept Testing - testing site design concepts to see if they make sense. This is primarily site structure, not design approaches.
Prototype Testing - testing prototypes to see if they fit the manner in which users expect the site to be organized and laid out in order for them to complete tasks in an orderly fashion.
Full Usability Testing - Testing the full usability of the site when it is functionally complete and most if not all of the content is there.
Dickson Chiu COMP7880-web-28
Pareto Curve for Usability Testing
Over 75% of the problems can be identified with 5 user tests; only 15 are need to find 100%
Dickson Chiu COMP7880-web-29
No Website can Ignore the Need for Usability Testing
Usability testing is critically important.
A careful marketer can learn to do it, especially one who has had focus group training or experience.
It can be outsourced to interactive marketing agency or a specialized marketing services firm.
Dickson Chiu COMP7880-web-30
Site Performance Metrics
Dickson Chiu COMP7880-web-31
Traffics & Audience Metrics
Site Administered Hit Counters
Purchased Services Server Request Log Data Coded Web Pages Customer Panel Data
Dickson Chiu COMP7880-web-32
Hit Counters are Often Free
They Provide Simple But Useful Reports
Dickson Chiu COMP7880-web-33
What is a Server Log?
Server logs record every hit (every file requested) and most pages have many files.
This is a necessary lead-in to understanding that the IT people use server log data to run the site and marketers use it (after much processing) to understand the performance of their marketing programs.
Includes, e.g. IP address, date and time of request
Dickson Chiu COMP7880-web-34
Basic Metrics – Site Traffic
Hits recorded each time a file is requested little value in measuring site effectiveness.
Impressions. Typical advertising usage applies here. Each time a visitor has an opportunity to
view an item, an impression is recorded. Page views (page impressions).
recorded each time a page is requested.
Dickson Chiu COMP7880-web-35
Basic Metrics – Site Audience
Visitors - simple count of the number of people who visit a site
Unique visitors - the number of different people Identified visitors - the next step up; now we know
who they are Unduplicated audience - the number of unique
visits/exposures in a specified time frame.
Traffic and audience measures are obviously related.
Traffic simply measures the activity on the site. Audience measures are of more interest to marketers who
need information about the composition of that traffic.
Dickson Chiu COMP7880-web-36
BASIC
METRICS
ALMOST INFINITE
NUMBER OF
SPECIFIC VARIABLES
Dickson Chiu COMP7880-web-37
Sample ROI Report
Dickson Chiu COMP7880-web-38
Sample Traffic Report
Dickson Chiu COMP7880-web-39
Sample Path Report
Dickson Chiu COMP7880-web-40
Sample Site Effectiveness Reports
Dickson Chiu COMP7880-web-41
Almost Infinite Number of Variables/ Reports
By Single Variable By Multiple Variables By Day By Time By Specific Page Etc., etc., etc.
Marketing ObjectiveMarketing Objective
Should Guide the ChoiceShould Guide the Choice
Dickson Chiu COMP7880-web-42
Need for Ratings
Management to assess performance Investors to assess potential & returns Advertisers for traffic numbers Must be accurate & verifiable External audit is the preferred option
Dickson Chiu COMP7880-web-43
Television Ratings
Create-once-sell-many medium Production costs don’t change with number of
audience Producers cannot directly count their audience Independent panel-based measurement
companies are preferred, e.g. ACNielsen Survey a representative sample of viewers and
the TV channels to which they tuned Set-top box is used to record the viewing
behavior
Dickson Chiu COMP7880-web-44
Magazine Ratings
Create-many-sell-many medium They can count how many copies printed &
sold No way to count magazines actually opened
and read Independent companies verify circulation
numbers based on audits of financial documents, mailing lists, postal receipts, and printing bills
Survey is much harder than TV as the number of magazines is much higher than TV channels
No mechanism similar to set-top box
Dickson Chiu COMP7880-web-45
Web Ratings
Create-once-sell-many medium Supply side resembles magazines but demand side
resembles TV Can count using server logs how many pages were
“printed” Can install set-top box like software to record viewing
behavior Millions of web sites with billions of web pages require
prohibitively large samples Representative samples are impractical to put together in
addition to difficulty of installing measurement software Don’t guess but count!
Dickson Chiu COMP7880-web-46
Something You Can Know
The referral links let you know how much traffic is coming from where?
Also captured are the search terms visitors typed into portals like Yahoo!
Can discover the most-used entry and exit pages
How long did they stay on each page?
Dickson Chiu COMP7880-web-47
IAB Online Measurement Study
Dickson Chiu COMP7880-web-49
Background & Objectives
Online Advertising Measurement Study Interactive Advertising Bureau (IAB) Media Rating Council (MRC) Advertising Research Foundation (ARF) Conducted by PricewaterhouseCoppers (PwC)
Review measurement criteria & practices for online advertising and audience measurement reporting
Document and report the comparability of existing metrics used by the industry
Propose a common set of industry definitions and guidelines for data analysis and reporting
Dickson Chiu COMP7880-web-50
Scope 11 participating companies selected by IAB
portals (e.g., AOL, MSN, Yahoo!) destination sites (e.g., CNET, Forbes.com) third party ad networks / servers (e.g., Avenue A,
DoubleClick) Participating companies represented 2/3 of total
industry revenue Interviews
what types of audience and advertising data are measured how the data is measured and how it is reported
Verified collection methods & definitions using scripted testing
Identified discrepancies between definitions, editing procedures, and reporting
Dickson Chiu COMP7880-web-51
The Fundamental
Standard Metric Definitions+
Well-Controlled Process=
Reliable Ad Campaign Measurement Reporting
Dickson Chiu COMP7880-web-52
The Top Five Metrics Ad Impressions Clicks Unique Visitors Total Visits Page Impressions Time Spent on
Page Number of
Completed User Registrations
Conversions
0
2
4
6
8
10
12
AdImpressions
Clicks UniqueVisitors
TotalVisitors
PageImpressions
# Participants
Dickson Chiu COMP7880-web-53
Top ≠ Currency Metrics
Ad Impressions Metric upon which revenue-generating contracts are
based Clicks
Contracts based on the Cost-per-Action pricing model
Page Impressions Content or page sponsorship
Email Subscribers Email Messages Delivered Email Messages Opened Conversion Referrals 0
2
4
6
8
10
12
AI Cs UV TV PI
# Participants
Dickson Chiu COMP7880-web-54
Ad Impression
A measurement of responses from an ad delivery system to an ad request from the user browser
filtered from robotic activity recorded at a point as close as possible
to the actual viewing of the creative material by the user browser.
Dickson Chiu COMP7880-web-55
Page Impressions
A measurement of responses from a web server to a page request from the user browser, which is filtered from robotic activity and error codes, and is recorded at a point as close as possible to the actual viewing of the page by the user browser.
Dickson Chiu COMP7880-web-56
Server Initiated Measurement prior to serving a web page to a user
agent request the page is built with links to an ad
resource ad impression transaction is recorded
in a log Client Initiated Measurement
direct connection between a user agent and the ad server via advanced HTML tags
recorded via an independent request to a special ad transaction logging server
0
1
2
3
4
5
6
7
Server Client
# Participants
Ad Impression Measurement
Dickson Chiu COMP7880-web-57
Ad Server Logging after receiving a request from
the web server prior to rendering the content
Web Server Logging after the ad server responds to
the request prior to rendering the content
Ad vs Web Server Logging
0
0.5
1
1.5
2
2.5
3
3.5
4
Ad Server Web Server
# Participant
Dickson Chiu COMP7880-web-58
Ad Server Logging after receiving a request
from the client prior to rendering the
content Counting Server Logging
after the ad server responds to the client
a separate redirect call to the ad counting server
Ad vs Counting Server Logging
0
1
2
3
4
5
6
Ad Server Counting Server
# Participant
Dickson Chiu COMP7880-web-59
Cached ads result in undercounting impressions
Cache busting technology reduce an ad request to be
cached in either a web browser or a proxy server
append a random number to the end of an ad request
append a time stamp to the end of an ad request
All 11 participants support cache busting technology
Cache Busting for All
0
2
4
6
8
10
12
With Cache Busting No Cache Busting
# Participant
Dickson Chiu COMP7880-web-60
Clicks
A measurement of the user-initiated action of clicking on an ad element, causing a re-direct to another web location.
Tracked and reported as a 302 redirect at the ad server.
This measurement is filtered for robotic activity and is recorded at a point as close as possible to the actual viewing of the destination web location by the user browser.
Dickson Chiu COMP7880-web-61
All 11 participants track clicks & share a common definition
A click is a user-initiated action of clicking on an ad element causing a redirect to another web location
A click does not include information on whether or not the user completed the redirect transaction
All base click metric on 302 redirects (or transfers) successfully processed by the ad server
Uniform Use of 302 Redirects
0
2
4
6
8
10
12
Tracking via 302redirects
No Tracking via302 redirects
# Participant
Dickson Chiu COMP7880-web-62
Unique Visitor
After resolving the two issues related to the visitor definition, consider the additional issues for defining unique visitors, including the use of sampling and estimates, and the treatment
include or exclude visitors that do not accept cookies) of new cookies for cookie-based calculations.
Dickson Chiu COMP7880-web-63
Unique Visitors
10 out of 11 participants track unique visitors
Cookie Based 8 use cookies with 2
using also IP address recurring vs new
cookies Registration Based
2 use registered users or user login counts
0
1
2
3
4
5
6
7
8
Cookie Registration None
# Participants
Dickson Chiu COMP7880-web-64
Cookie Based Unique Visitors Should new cookie be
counted? Count all new cookies Exclude all new cookies
a unique cookie must visit the site at least twice to be considered a new visitor
Exclude some new cookies based on historical data
using known user data estimate of new cookies
representing repeat visitors that do not accept cookie
0
0.5
1
1.5
2
2.5
3
3.5
4
Count AllNew
Cookies
Count NoNew
Cookies
CountSome NewCookies
# Participants
Dickson Chiu COMP7880-web-65
Total Visits
Resolve whether the approaches to determining visitor counts can be addressed in one definition (I.e. cookies, user registration)
require disclosure of the definition Resolve whether session time limits
should also be included in the definitions.
Dickson Chiu COMP7880-web-66
Total Visitors
10 participants calculate total visitors
Definitions vary among participants
Actual Sampling
sample user activity (e.g. several days over a period)
Statistical Analysis to perform statistical
analysis to estimate total visitors
0
1
2
3
4
5
6
Actual Sampling Statistical
# Participants
Dickson Chiu COMP7880-web-67
Web vs Ad Server Tracking 8 participants track page
impressions 6 use standard web server
logs with successful HTML status
codes filter from robotic activity
2 use web beacon technology (see Yahoo)
A Web beacon is an object that is embedded and invisible but allows checking that a user has viewed the page or e-mail.
no third party entity does the tracking
0
1
2
3
4
5
6
Web Server Ad Server
# Participants
Dickson Chiu COMP7880-web-68
Robotic Activity Filtering
All participants perform some such filtering
Basic prevent robots from
scanning the ad server exclude transactions from
empty agents or “bot” agents
List of Known Robots based on User Agent
Strings or IP address varied from 10 to 700
Behavioral Filtering define business rules to
identify robotic behaviors
0
2
4
6
8
10
12
BasicFiltering
ListFiltering
BehavioralFiltering
# Participants
Dickson Chiu COMP7880-web-69
Internal IP Address Filtering
Eliminate any activity generated by internal monitoring tools
Demographic of company users may not be representative
Eliminate any activity generated by internal testing 0
1
2
3
4
5
6
7
Remove InternalIP Addresses
Include InternalIP Addresses
# Participants
Dickson Chiu COMP7880-web-70
Independent Verification
01234567
ProcessAudit
ActivityAudit
Process &ActivityAudit
No Audit
# Participants
Dickson Chiu COMP7880-web-71
Resources
Web Metrics: Proven Methods for Measuring Web Site Success, Jim SterneJohn Wiley & Sons, Inc., 2002
IAB Online Ad Measurement StudyPricewaterhouseCoppers, 2001