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Online Market Research
© 2001 Ann Schlosser, University of Washington Business School
Agenda
• What accounts for differences in actual and forecasted numbers?
– Survey panels vs. server log files
– Response and sampling biases
• Online market research methodologies
– VR/Simulated environments
– E-mail surveys
– ISP’s data warehouse (unobtrusive)
– Quasi-experimental design
• Using the results
Who Has a Reliable Estimate of a Site’s Audience?
Internal Server
Third-Party Ratings FirmsThird-Party Ratings Firms
For pageviews, ratings-firm numbers were anywhere from 85% less than to 300% more than that reported by the site’s server.
Comparing Audience Measurement Firms Using Panel Data
COMPANY U.S PANEL SIZE
RECRUITMENT METHOD
INCENTIVE
Media Metrix
55,000 Random-digit dialing, follow-up mail
$50 annual maximum, giveaways, sweepstakes
Nielsen NetRatings
65,000 Random-digit dialing $50 U.S. savings bonds every six months
PC Data 120,000 Random-digit dialing, advertising
$40 annually, sweepstakes
ComScore 1.4 million
Advertising, partnered with pollsters
Provides faster Internet-page download service
The Trouble With Online Panels
Some Benefits of Panels
• Level of detail– Geography– Unique visitors
(different people accessing the site)
– Captures PC activity
Internal Server Records are Imperfect
• Tallies computer (not human) access– Over counts due to:
• Same user with home and work access
• Spiders and other bots
• ISPs that indiscriminately assign users to IP addresses
– Under counts due to: • Different users of same computer
• Cached pages– Especially problematic if done by ISPs and other content
aggregators
Some Factors Influencing the Reliability of Data
• Response biases
• Sampling biases
• Incentives
Impact of the Internet on Market Research
Kannan et al, 1998
Virtual Shopping Market Research
Comparing Electronic With Mail Surveys
E-mail Mail
Response rate 6%-73% 27%-56%
Response speed 7-8 days 7.5-13 days
Completion Less More
Bad address notification 10 minutes Weeks
Percent of bad addresses 24.5% 2%
Weible & Wallace (1998)
Collecting Data Through ISPs while Protecting Privacy
ISP login/street address Anonymous ID,Geocode,Append Demog.
FoveonCollection (now Plurimus)
login Anonymous ID DataWarehouse
street address
= security key
3rd Party
50 participating ISPs and 3.5 million Web users
Raw Material: Collector Lines
23540 12:04:30 com.egghead.www /store2/ent/eggs_ordstat.browse23540 16:30:57 com.egghead.www /store1/ent/images/space.gif23540 12:04:34 com.egghead.www /media/bnr/B_EggheadSpecials_0823540 12:04:42 com.egghead.www /store2/ent/images/space.gif23540 16:30:57 com.egghead.www /media/images/bdot.gif23540 16:30:11 com.egghead.www /media/images/but_previous.gif23540 16:30:11 com.egghead.www /store1/ent/eggs_shop.additem?s23540 16:30:55 com.egghead.www /store1/ent/eggs_shop.additem?s23540 16:30:32 com.egghead.www /media/images/portal_egg-header23540 16:30:57 com.egghead.www /media/images/recalculate.gif23540 16:30:08 com.egghead.www /store1/ent/eggs_prod.browse?se23540 16:30:07 com.egghead.www /store/ent/eggs_prod.browse?sec23540 16:31:03 com.egghead.www /media/images/but_proceed-order23540 12:04:34 com.egghead.www /media/images/but_nav_auction[323540 12:04:34 com.egghead.www /media/images/but_search.gif25150 12:21:41 com.yahoo.rd /results/a/?http://www.altavist25150 14:41:43 com.yahoo.rd /results/a/?http://www.altavist26004 22:07:53 com.yahoo.rd /search/navbar/top/*http://ink.
FID Date/Time Host URL
Classification of Behavior
23540 OCT16:200012:04:30 com.egghead.www2 /store2/eggs_shop.additem
•Duration•Time of Day•Calendar Day
•www.egghead.com•“Internet Computers”•NAICS Code
•“Shopping Cart”
•Geography (BG ID)•Demography
Geocoding/Appending
CalculationSite Classification
URL Classification
FID Date/Time Host URL
Log File Data
User Start Date/ End Date/ Packets Bytes Host URLID Time Time To/From To/From
GBF vs. GIRF:Reasons for Dot-Com Failures
Poor revenue, cost investment and profit models 61%
No competitive advantage 44%
No consumer benefit 21%
Organization, implementation and execution problems 17%
Channel conflict 10%
Ineffective fulfillment process 7%
Source: BCG
Various Performance Metrics
• 65% abandon shopping carts
• Overall average buyer conversion rate < 4%
• Low customer conversion, upselling and loyalty, even at best sites– At 10 leading e-commerce sites
• 20% converted from visitors to buyers
• 10% upsold
• 5% returned within 6 months
Retention Measures
KEY RESEARCH QUESTIONS
– Are you reaching the right audience?
– Do they remember your website?
– Does it enhance the brand’s image?
– Does it increase sales?
• What is the objective(s) of your website?
Web Site Report
Page Views by Hour
Site Navigation Summary Report
Disentangling the effect of your website
• A quasi-experimental design is the best means of isolating the impact of a website from the numerous external factors which may impact attitudes and opinions
Online Marketing Traditional Marketing
website
Peer influence Press influence
Pre-existing attitudes
Methodology
=Website effect
Experimental Effect
First time users
Experimental Group
- Repeat visitors
Control Group
User accesses website www.your.website
JavaScript sampling procedure
Visitor continuessurfing, unaware of the sampling script
Not Sampled
Survey 1
SampledReturned to
the page
originallyrequested
Survey 2
E-mailinvitation
User accesses website www.your.website
JavaScript sampling procedure
Visitor continuessurfing, unaware of the sampling script
Not Sampled
ONLINE QUESTIONNAIRES
• What should you ask?– Questions relating to your website’s objectives
– Audience profile questions
– Satisfaction questions
– Relationship questions
– Intent questions
– Comparative questions
Type of Information
Available7.65
Type of Information
Available7.65
Detail of Information
Available6.98
Detail of Information
Available6.98
The Layout of
the Site7.84
The Layout of
the Site7.84
Navigation Aides on the Site
6.75
Navigation Aides on the Site
6.75
Speed of Loading Pages7.10
Speed of Loading Pages7.10
Overall Overall SatisfactionSatisfaction
I=.000 I=.533 I=.39 I=.272 I=.000
Customer Satisfaction ModelVisit Again
Visit Again
Recommendto others
Recommendto others
Spend more time
Spend more time
Download Information
Download Information
I=.120I=.120I=.320I=.420
Customer Satisfaction Model
0.00
0.10
0.20
0.30
0.40
0.50
0.60
5.00 6.00 7.00 8.00 9.00 10.00
CRITICAL IMPROVEMENT STRENGTH
LOWER LEVERAGE AREALOWER PRIORITY
Detail of information
available
Navigation aides on the
site
Layout of the site
Type of information available Speed of loading the pages
SATISFACTION WITH FEATURE
IMP
AC
T O
N O
VE
RA
LL
SA
TIS
FA
CT
ION
Strategic Improvement Matrix