I
Is the Price Right? A study of pricing effects in online
grocery shopping
by
Minnie Lau
Submitted to the Department of Electrical Engineering and Computer Science
in partial fulfillment of the requirements for the degree of
Master of Engineering in Electrical Engineering and Computer Science
at the
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
September 2000
@ 2000 Minnie M. Lau. All rights reserved.
The author hereby grants to MIT permission to reproduce and distribute publicly
paper and electronic copies of this thesis document in whole or in part, and to grant
others the right to do so.
A uthor . .
. . ...........
. .........................................
Department of Electrical Engineering and Computer Science
June 7, 2000
Certified by.
John D.C. Little
Institute Professor
Thesis Supervisor
.
Accepted by
.
.
.
. . . .
Arthur C. Smith BARKER
Chairman, Department Committee on Graduate Theses
MASSACHUSETTS INSTITUTE
OF TECHNOLOGY
JUL 2 7 2000
LIBRARIES
Is the Price Right? A study of pricing effects in online
grocery shopping
by
Minnie Lau
Submitted to the Department of Electrical Engineering and Computer Science
on June 7, 2000, in partial fulfillment of the
requirements for the degree of
Master of Engineering in Electrical Engineering and Computer Science
Abstract
This thesis explores the possibility that having a nine as the ending (the right most
digit) of a price may increase or decrease product demand under different circumstances. An experiment simulating an on-line grocery shopping environment was
designed to investigate this effect on grocery products. The findings yield significant
evidence that pricing products with a nine ending will gain a sale advantage in certain
situations, depending on the shoppers' budget limits and the nature of their shopping
trips.
Thesis Supervisor: John D.C. Little
Title: Institute Professor
2
Acknowledgments
Thanks are due to the following people whose assistance I could not have done without:
" Professor John D.C. Little, for everything.
" Robert Zeithammer, for help and guidance.
" LaVerdes Owner and Manager, for providing sales information.
" Friends, for believing and encouraging.
" and of course my parents without whom MIT would not have been possible.
3
Contents
1
8
Introduction
1.1
Motivation for Studying Nine-Endings
. . . . . . . . . .
9
1.2
Literature Review . . . . . . . . . . . . . . . . . . . . . .
10
1.2.1
Underestimation of Actual Price
. . . . . . . . .
10
1.2.2
Association of Meanings to Prices . . . . . . . . .
11
1.3
Current Nine-Ending Theories . . . . . . . . . . . . . . .
12
1.4
Modeling the Effect of Nine-Ending in Consumer Choice
13
15
2 Experimental Design
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
15
. . . . . . . . . . . . . .
15
2.3
Nine-Ending Phenomena to be Studied . . . . . . . . . . . . . . . . .
16
2.4
Overall Description . . . . . . . . . . . . . . . . . . . . . . . . . . . .
18
2.5
Generation of Categories and Products . . . . . . . . . . . . . . . . .
19
2.6
Pricing Adjustment . . . . . . . . . . . . . . . . . . . . . . . . . . . .
22
2.7
Data Collection and Cleaning . . . . . . . . . . . . . . . . . . . . . .
22
2.8
Statistical Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . .
23
Statistical Properties of the Measured Difference in Shares . .
23
2.1
Objective
2.2
Nine-ending Effect Measuring Methodology.
2.8.1
3
25
Result Discussion
3.0.2
Hypothesis Testing . . . . . . . . . . . . . . . . . . . . . . . .
25
3.0.3
Main Nine-Ending Effect . . . . . . . . . . . . . . . . . . . . .
25
3.0.4
Fraction of Nines . . . . . . . . . . . . . . . . . . . . . . . . .
27
4
4
3.0.5
Ordering of Product A within a Choice Set . . . . . . . . . . .
28
3.0.6
Probability of Purchasing of the Two Budget Groups . . . . .
29
3.0.7
Budget Size . . . . . . . . . . . . . . . . . . . . . . . . . . . .
29
3.0.8
Sequence of Choices during the Experiment
. . . . . . . . . .
31
3.0.9
Budget Size and Sequence of Choices . . . . . . . . . . . . . .
32
33
Comments and Summary
4.1
Doing the Online Experiment in the Lab vs. Elsewhere . . . . . . . .
33
4.2
Using Hypothetical Products . . . . . . . . . . . . . . . . . . . . . . .
34
4.3
Future Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
34
4.4
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
34
A Online Survey
36
B Web Experiment
38
C Categories and Products
47
D Figures
52
5
List of Figures
B-i Login Page
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
39
B-2 Scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
40
B-3 Bread Style - First part of a sample aisle . . . . . . . . . . . . . . . .
41
B-4 Bread Choices - Second part of a sample aisle . . . . . . . . . . . . .
42
B-5 Tooth Paste Style - First part of a sample aisle . . . . . . . . . . . . .
43
B-6 Tooth Paste Choices - Second part of a sample aisle . . . . . . . . . .
44
B-7 Questionnaire - Personal Preference Sample Questions . . . . . . . . .
45
B-8 Questionnaire - Shopping Background . . . . . . . . . . . . . . . . . .
46
D-1 Frequency Histograms of 25 Walk-ins . . . . . . . . . . . . . . . . . .
53
D-2 Frequency Histograms of 493 Subjects
54
6
. . . . . . . . . . . . . . . . .
List of Tables
3.1
Main Nine Ending Effect . . . . . . . . . . . . . . . . . . . . . . . . .
26
3.2
Main Nine Ending Share Increase . . . . . . . . . . . . . . . . . . . .
26
3.3
Nine Ending Share Increase vs. Fraction of Nines . . . . . . . . . . .
27
3.4
Nine Ending Share Increase vs. Lagged Fraction of Nines
. . . . . .
28
3.5
Nine Ending Share Increase vs. Fraction of Nines and Lagged Fraction
of N ines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
28
3.6
Probability of Purchase some item vs. High and Low Budget
. . . .
29
3.7
Nine Ending Share Increase vs. Budget Size . . . . . . . . . . . . . .
30
3.8
Nine Ending Share Increase vs. Budget Size and Fraction of Nines
30
3.9
Nine Ending Share Increase vs. Sequence of Choices
. . . . . . . . .
3.10 Nine Ending Share Increase vs. Budget Size and Sequence of Choices
31
32
. . . . . . . . . . . .
37
. . . . . . . . . . .
48
C.2 The Most Popular Products at LaVerdes - Part II . . . . . . . . . . .
49
C.3 The Most Popular Products at LaVerdes - Part III
. . . . . . . . . .
50
. . . . . . . . . . . . . . . . . . .
51
A.1
A Survey on Online Grocery Stores - Oct 1999
C.1 The Most Popular Products at LaVerdes - Part I
C.4 30 Categories by Fraction-of-Nines
7
Chapter 1
Introduction
One rapidly developing area on the Internet is on-line grocery shopping. Such services, which usually include home delivery, may be either local or national. In the
Boston area, on-line grocers such as HomeRuns (http://www.homeruns.com), PeaPod
(http://www.peapod.com), Streamline (http://www.streamline.com) and ShopLink
(http://www.shoplink.com) are facing tough competition in the electronic market.
One characteristic of Internet grocery stores is that they provide a shopping environment in which prices frequently end in the digit 9, as is also the case in many
physical grocery stores. Many on-line grocery stores in fact use prices that only end
in 9. However, the effects of this policy are poorly understood.
This thesis reports an experiment that seeks to determine whether prices ending
in nine influence consumer shopping behavior in on-line grocery stores. Chapter one
gives the motivation for the study and a background review of price endings, focusing
on consumer behavior. Chapter two presents the experimental design and hypotheses
along with the methods used for data cleaning and analysis. Chapter three gives
the results and discusses their significance. Chapter four makes several observations
about on-line experiments and summarizes the study's conclusions.
8
1.1
Motivation for Studying Nine-Endings
Nine-Ending Effect
The study of prices that end in nine (nine-endings) has gained
increasing attention due to the high saturation of 9s in the market. A number of previous studies and experiments have already found that nine-endings have a significant
positive effect on product choice. However, most of these studies have examined the
effect only on scanner-panel data for grocery goods, or on sales data from non-grocery
catalogs. Only one study, Ouyang [4], has examined the effect on on-line grocery shopping via a web-based experiment. Even in this experiment, the results require further
testing.
As mentioned earlier, not only do many physical grocery stores use almost all nineendings, but many on-line grocery stores do the same. Such high usage of nine-endings
may not be an optimal strategy in the online market, especially since products are
presented differently online than in the physical store. In addition, pricing strategy
currently varies across online grocery stores.
(see Table A.1) As more and more
commerce is transacted via the Internet, it becomes increasingly important to learn
how nine-endings affect electronic shopping. Such understanding would help retailers
decide on pricing strategies for these environment.
Fraction of Nines Effect
Past studies have suggested that a high fraction of nine-
ending products decreases the positive effects of nine-endings. (Ouyang [4]; Ouyang,
Zeithammer and Little [5]) Similarly, in scanner-panel data, the higher the fraction of
nines, the lower the nine-ending effect appears to be. A similar relationship has been
found in an experiment studying sales of fashion goods in mail catalogs. (Anderson
and Simester [1]) As for on-line grocery products, this effect has yet to be measured
thoroughly.
9
1.2
1.2.1
Literature Review
Underestimation of Actual Price
Frequently, products with a nine-ending have been observed to produce a higher demand than those without it. One popular belief is that nine-endings increase product
appeal, which in turn, increases the likelihood that an individual will buy. This effect has several possible explanations, one of which is the so called underestimation
mechanism. The underlying theory is that consumers underestimate the actual price
of the product when it ends in nine. By ignoring the right-hand digit 9 of the price,
they truncate or round down the actual price. Some evidence has been observed in
a study conducted by Schindler and Kibarian [7]. They find that a 99-price ending
leads to an increase in total consumer sales as compared to the next higher 00-price
ending. Unfortunately, that particular experiment fell short of finding statistically
significant support for the mechanisms involved.
The underestimation mechanism was further studied by Stiving and Unnava [8].
They consider many different price-pairs, including ones that involve nine-endings
and showed that consumers underestimate prices in certain situations. In making
choices between products, consumers may use a rounding down heuristic that ignores
the right hand digits when the difference between two numbers is hard to calculate
mentally. If the prices involve numbers that are easy to subtract, consumers are
likely to subtract them. Otherwise, consumers often estimate the price difference by
ignoring the right hand digits. For example, if the two prices are $3.74 and $3.69,
then subtraction of 74-69 is difficult. Therefore, some people will tend to round down
and hastily conclude that the difference between these two prices is 10 instead of 5.
Their experiments indicate that the underestimation mechanism not only works
in the abstract, but also generates potential market effects when applied to a product choice task. As hypothesized, consumers who are less comfortable manipulating
numbers are more likely to use a rounding down heuristic to evaluate prices. This
study not only verifies that some consumers underestimate certain prices, but also
offers support for just-below pricing, a common practice used by retailers.
10
Underestimation is a well understood mechanism but not the only possible explanation for the nine-ending effect on product demand. Other explanations have been
developed, particularly the "meaning" effect described below.
1.2.2
Association of Meanings to Prices
A discussion of the meaning effect begins with the observation that consumers are
usually not able to remember the exact prices of items they have recently purchased.
Rather than paying close attention to prices, consumers acquire just enough information to make their purchase decisions. They do not consciously remember exact
prices, as would be expected. For example, a study conducted by Monroe and Lee
[3] shows that consumers do not fully process price information but maintain internal
reference prices to evaluate products. Furthermore, Schindler [6] proposes that consumers apply their own intuitive meanings to price endings. People establish special
meanings for price endings through subconscious learning of correlations that occur
in the marketplace. These correlations then serve as a catalyst that connects meanings to price endings during purchase. In particular, Schindler mentions 14 possible
meanings, listed below, that can be associated with the last digit of a price. For
instance, the digit nine has been found to connote discount or sale prices. In general,
empirical evidence has been found to support the effects of some of these meanings
and possible underlying mechanisms have been discussed in literature, but most of
them have not been thoroughly examined in controlled studies.
Price Meanings that may be Stimulated by Price Endings
1. The price is low
2. Price has been reduced
3. Price has not been increased recently
4. Discount or sale price
5. Price results from a careful and precise process
6. Price is negotiable
7. Price is synonymous with even-dollar amount
11
8. Price is the correct price
Meanings Concerning Non-Price Attributes of the Product or Retailer
1. Low quality merchandise
2. Retailer is sneaky, slick, or doesn't play it straight
3. High quality merchandise
4. Classiness, sophistication, or prestige
5. Distinctive signature of retailer
6. Playfulness
1.3
Current Nine-Ending Theories
The association between meanings and prices is used in several current theories to
explain the impact of nine-endings on consumer behaviors. The theories may apply
differently to different people or circumstances. In particular, Zeithammer [10] focuses
on possible mechanisms that would facilitate the association of low prices and nineendings in the minds of consumers. These are described below. Some of them may
help explain the results of the experiment in this study.
Not Aware of Existing Meaning
One theory suggests that consumers have been
conditioned by the high proportion of nine-endings in the current market. People
need to buy products and gain value from doing so. Therefore, they subconsciously
attach a meaning to nine-endings whenever they buy an item with a nine-ending.
The conditioning intensifies as the number of items with nine-endings increases.
Fully Aware of Existing Meaning
A further hypothesis proposes not only that
consumers associate nine-endings with meanings but also that retailers recognize the
situation.
Nine-endings serves two purposes in this case.
They are a purchasing
decision indicator for the consumers and also a price setting regulator for retailers.
Consumers recognize that a certain amount of nine-endings in the market implies low
prices. Based on this recognition, consumers then decide whether or not to buy. In
12
response, the retailers deliberately set the proportion of nine-endings at a level they
have recognized to favor a sale. Thus, nine-endings can generate either a positive or a
negative effect on sales, depending on the proportion of nine-endings and the amount
of information they provide.
Meaning Does Not Exist
Two further theories examine mechanisms that could
cause consumers to believe in nine-ending meanings that do not actually exist. The
consumers' limited ability to process information is one possible cause. Consumers
may erroneously attach meanings to nine-endings by inaccurately inferring an empirical relationship between prices and some property of interest, for example, nineendings and low price, even though the correlation is not actually there. With the
high proportion of nine-ending prices in the market, it would not be surprising for
consumers to find evidence to support a particular belief.
The other theory suggests that consumers do not need all the information contained in the number used to denote price. They may only need a rough idea about
relative cost to make subsequent decision. Therefore, consumers may underestimate
prices (truncate the penny digit) or categorize products simply as relatively "cheap"
or "expensive". Considering the high proportion of nine-endings in the market and the
inclination to reduce mental processing (see section 1.2.1), consumers have incentives
to truncate prices and unavoidably notice the nine-endings. Truncating a nine-ending
leads to a price much less than the original. Thus, the consequence of this behavior
is a perceived association of low prices and nine-endings. (see Zeithammer [10] for
further discussion of this theory)
1.4
Modeling the Effect of Nine-Ending in Consumer Choice
A common technique for testing nine-ending theories is to build a model of product
choice based on an implicit utility function for the consumer. This technique can be
used to predict how consumers behave toward price endings. For example, a logit
13
model by Little and Ginise [2] uncovers significant effects of prices ending in nine.
Using scanner data on pancake syrup, their study discovers that a price ending in
nine increases the probability of purchase.
In addition to the basic logit model, Stiving and Winer [9] incorporate behavioral theories in the utility function. They design models that consider for both the
underestimation effect and the meaning effect, called the "level" and "image" effect
respectively in their study. They find significant image effect in the digits 0 and 9.
The digit 0 suggests a higher quality and the digit 9 signals both lower quality and
good price. Their work underscores the importance of accounting for individual price
digits in consumer choice models.
14
Chapter 2
Experimental Design
2.1
Objective
The objective of the online simulation is 1) to develop a web-based method for measuring the nine-ending effect and 2) to measure the moderating influence of several
shopping conditions on the magnitude of the effect.
2.2
Nine-ending Effect Measuring Methodology
The basic task of a subject in the experiment is to select a market basket of goods
consisting of at most one product from each of 30 categories. Each category contains
five products to choose from plus the option of not choosing anything.
The experiment employs a method that uses simple calculations such as counting
and taking differences to measure the average nine-ending effect across subjects. One
product in each category is designated as "product A" for that category. Only the
price ending of Product A changes during the experiment. The rest of the products'
prices are kept constant and used only to create different shopping environments.
In particular, Product A is assigned either a 9-ending or an 8-ending. The nineending effect is then measured as the difference of product A's share between the two
price-ending conditions. This procedure enhances the validity of the measurement
by keeping everything else (prices and products) constant and varying only the price
15
ending digit of product A between 9 and 8.
2.3
Nine-Ending Phenomena to be Studied
In order to understand the strength of the nine-ending effect more thoroughly, the
study is also designed to examine the influence of the following moderating variables:
Fraction of Nines in the Current Choice Set
The fraction of nines in the choice
set is hypothesized to affect the magnitude of the nine-ending effect. Notice that the
actual fraction of nines seen by a subject depends slightly on whether product A has
a 9 or 8 ending. To resolve this ambiguity, fraction of nines is arbitrarily defined to
be exclusive of Product A. Therefore, the fraction of nines for a specific category is
simply the fraction of the 4 non-A products with a nine-ending. As mentioned in
Chapter 1, fraction of nines have been observed to weaken the strength of the nineending effect with increasing fraction of nines. The measurement of this relationship
in the past online grocery shopping experiment has not been statistically significant.
(Ouyang, Zeithammer and Little [5]) The current study hopes to give a more accurate
picture of this inverse relationship. It is hypothesized that a decreasing fraction of
nines may strengthen the nine-ending effect.
Lagged Fraction of Nines
Similarly, the fraction of nines of the category en-
countered in the period before the present category may also influence the subject's
purchase decision. Notice that, if shoppers skip a category, they do not see its fraction
of nines. Therefore, the relevant lagged fraction of nines corresponds to the category
in which shoppers last made a choice. According to this definition, the strength of
the present nine-ending effect may rise or fall depending on whether the lagged fraction of nines is higher or lower. Most likely, the relationship should resemble the
one for nine-endings in the current choice set. If the shoppers have last seen a high
fraction category, it is hypothesized that they are less likely to buy products with a
nine ending.
16
Interactions of Fraction of Nines and Lagged Fraction of Nines
Both of
these moderating variables, fraction of nines and lagged fraction of nines, may jointly
influence the nine-ending effect.
For example, the combination of having a high
present fraction of nines and a low lagged fraction of nines may weaken the nineending effect. This hypothesis is based on the same rationale as for the fraction of
nine effect. It suggests that the strength of the nine-ending effect decreases as the
subject's exposure to nines increases. In this case, any effect already associated with
a high or low fraction of nines would be intensified. If the present fraction of nines is
high, then it would seem even higher if the prior fraction of nines is low. Similarly,
a high lagged fraction of nines would emphasize the effect of low fraction. Thus,
the nine-ending effect may depend on the polarity between the present and the last
fraction of nines. If shoppers have last seen a high fraction and the current choice set
has a low fraction, then customers are expected to be more likely to make a purchase
of a product that ends in nine.
Order in Sequence of Choices
Another moderating variable that may yield in-
teresting insight is the order in which purchases are made during the experiment.
The nine-ending effect is expected to become stronger in the categories that are encountered later in the experiment. Subjects may become tired as they progress. The
more fatigued they are, the less attention they will pay to prices. As a result, shoppers may be more prone to the nine-ending effects. Therefore, the first 15 categories
encountered are expected have a weaker nine-ending effect than the last 15 categories.
Order of Product A in the Choice Set
In the experiment, each aisle displays
its 5 products in a list. This is how most on-line groceries present their products.
However, the attention that each product receives may vary depending on its position
in the list. People generally look at items from top to bottom. More attention may be
given to the items near the top. Consequently, the nine-ending effect is hypothesized
to be stronger for the products listed near the bottom than the top.
17
Size of the Individual's Budget
The experiment subjects are assigned to either
a large ($80) or a small ($40) budget and are asked to stay within it. Increasing the
budget is expected to decrease the importance of price. As a result, prices matter
less, making the nine-ending effect more likely.
In addition, the budget constraint is expected to affect purchasing behavior. The
people with a high budget will have different shopping objective and strategy than
people with a low budget. This difference may either increase or reduce the nineending effect depending on the situation. For example, the low budget group may
stop buying towards the end of the experiment, while the high budget group may buy
more seeing that they have plenty of money left. In general, the subjects with a high
budget are expected to purchase a larger total amount of products than the subjects
with a low budget even though the shopping task they have been given is the same.
Thus, the high budget constraint may induce a stronger fraction-of-nine effect than
the low budget constraint.
2.4
Overall Description
In a simulated on-line grocery store, respondents are asked to choose a list of goods
from 30 selected categories. A budget constraint of $80 or $40 is assigned randomly
to individual shoppers.
The 30 categories are described as 30 different "aisles". The experiment assigns
the aisles in a random order to each shopper. In each aisle, shoppers are first asked
to pick a "style" that they prefer for the products associated with that aisle. A style
is usually a prominent characteristic associated with products of a particular aisle,
for example, flavor is a style of ice cream.
Shoppers do not have to pick a style, they can choose to skip an aisle completely
and proceed to the next.
If they do pick a style, then they will see a list of 5
products, identified by brand name and price. The shopper can choose to buy any of
the 5 products or not purchase any of them.
After the shoppers have gone through the 30 aisles, they are asked to fill out a
18
two-page questionnaire. The first page inquires about their brand preferences. The
second page asks about the subject's past on-line shopping experiences. On the first
page is a list of the 30 categories with the corresponding 5 product brand names but
no prices. Participants are asked to buy one product from each category as if price
were not a concern. Again, the participant can choose not to buy anything. The
order of the 30 categories and the 5 products in each category are both randomly
generated for every participant.
The experiment was conducted online for one week and also during a two-hour
walk-in session at a computer cluster. I recruited respondents by posters throughout
the MIT campus (including residential halls and computer clusters) and by sending
email messages to several mailing lists. The participants were compensated with a free
movie ticket. An additional ticket was given to participants who took the experiment
during the walk-in session.
Please see Appendix B for the screens of the online experiment.
2.5
Generation of Categories and Products
Considerable care is required in constructing categories and products for the experiment. The guidelines were as follow:
1. Select 30 categories and a set of 5 substitutable products in each category.
Each category must:
(a) Contain 5 different brands, without including any house-brands.
(b) Not be dominated by a single brand (e.g. Coke dominates the soft drink
category).
(c) Be popular among the MIT community. A popular category is defined as
one that receives high volume sales at LaVerdes, the only grocery store on
the MIT campus (see Appendix C for the list of high volume sales).
All individual products within a category must be:
19
(a) Popular among MIT population, defined as having high volume sales at
LaVerdes.
(b) Not house brands.
(c) Substitutes for other products in the same category (e.g. products having
the same size).
2. Keep the prices of the products similar to those found in the local supermarkets
and online grocery stores popular to the MIT community. To do this:
(a) Obtain the real product prices and unit prices from Star Market, LaVerdes
and HomeRuns.
(b) Using the unit prices as a measure of relative price between products,
adjust the original product prices according to the heuristic discussed in
the Price Adjustment section below.
3. For each category, randomly pick one of the five products to be designated as
Product A.
Product A of each category will have one of two possible price endings, either
9 or 8. The prices of the other products stay constant. For each subject and
each Product A, the 8 or 9 is assigned at random with equal probability.
Notice that the position of product A in the list is critical since it may vary the
strength of nine-ending effect. Thus, it is important to make sure that there is
an equal number of Product As (6 in this case) occupying the same position on
the list of 5 products. (6 * 5 possible positions = 30 categories)
4. First randomly assign 6 categories to each of the five levels of fraction of nines.
Then check that the assignment satisfies the following criteria:
Note that there are 5 levels of fraction of nines (0.0 0.25 0.50 0.75 1.0) as defined
in the previous chapter. Since there is a total of 30 categories; therefore, each
level of fraction of nines should be found in 6 different categories.
20
(a) The following categories are distributed evenly among the different levels
of fraction of nines. These particular categories represent products that
are similar in that the 5 products within the category differ by only one
or two features (other than brand names).
"
"
"
"
"
"
"
"
*
"
"
paper towel
shampoo
toothpaste
water
dish-washing soap
pasta
detergent
trash bags
cups
plates
pasta
(b) Categories that are price sensitive are distributed across the different levels
of fraction of nines. According to data from Ouyang [4], the following four
categories are significantly sensitive to price variations: 1) Frozen Dinner,
2) Juices, 3) Cereal, 4) Ice cream.
(Ouyang's experiment data for ice cream
was distorted by subject's misinterpretation, but ice cream is still assumed to be price
sensitive because it is a non-esessential item.)
(c) Ordering of Product As: In a list of five products, the product A can be
placed in one of 5 possible positions (1st(top), 2nd, 3rd, 4th, 5th(bottom)).
The different positions of product A from a specific level of fraction of nines
should span the 5 possibilities.
(d) To avoid biases related to the characteristics of Product A, at least one of
the product As from each fraction of nines levels should be the following:
i. The most popular in the category according to LaVerdes' sales information and the local Star Market sales observations.
ii. The most expensive of the 5 products in the category.
iii. The cheapest in the category.
21
iv. An average item that lacks the first three features.
Please see Table C.4 for a list of the 30 aisles used in the experiment and their
corresponding levels of fraction of nines.
2.6
Pricing Adjustment
In adjusting the prices, we use a heuristic that minimizes the influence of underestimation, as defined by Stiving and Unnava [8]. According to the study, people tend
to round down prices when they compare price pairs that are difficult. Since people
process price information from left to right, they are more likely to round down when
the difference between two prices is difficult to calculate. Individuals who are less
inclined to perform numerical computation round down more frequently. Therefore,
prices in this experiment are adjusted to minimize these situations, eliminating the
possibility of having the underestimation effect as an important explanatory variable.
2.7
Data Collection and Cleaning
Over 500 subjects were recruited during a one week period in which the experiment
operated. An additional 25 people participated during a two-hour walk-in session
conducted at a computer cluster. The walk-in sample formed a control group to
develop norms for screening outliers. Individuals were eliminated for whom
" Average time spent per aisle visited was too long (greater than 25 seconds) or
too short (less than 5 seconds).
" Total number of aisles visited was too few (less than 15).
These two parameters measure the engagement level of our subjects. Time spent
per aisle measures the time subjects take to make a choice in a particular aisle. A
choice could be the act of either buying one of the 5 products or making no purchase.
The time spent in choosing the style of products is excluded, since the subjects have
22
not seen the product list at that point. The total number of aisles visited includes
only the aisles in which a subject bought a product or chose not to buy anything after
examining the 5 products. See Figures D-1 and D-2 for histograms of the walk-in and
on-line subjects used for data analysis.
Statistical Analysis
2.8
Statistical Properties of the Measured Difference in
2.8.1
Shares
The notations and equations used in the discussion of the various nine-ending effects
are as follows:
" N denotes the number of participants
" K denotes the number of categories of products
" M denotes the number of distinct levels that change the strength of nine-ending
effect (e.g. Each category can appear early or late during the experiment, thus
M = 2 in this case.)
*
Slk,m denotes the share of Product A with a nine-ending in category k and
level m
*
SOk,m denotes the share of Product A without a nine-ending in category k with
m levels
* Slk,m-SOk,m
yields the estimate of the nine-ending effect for category k and level
m.
"
Sk,m is defined as Slk,m-SOk,m
Since the nine and non-nine ending of Product A is randomized, approximately
N/M participants will input an observation in each condition.
To estimate variance, each choice of Product A is modeled as a Bernoulli process
with an underlying probabilities POk,m and Plk,m respectively.
Bernoulli choice implies
E[Slk,m - SOk,m1=Plk,m - POk,m
23
Var[Slk,m
-
SOk,m]=(2M/N)[Plk,m(1 - Plk,m) + POk,m(1 - POk,m)]
Estimates are aggregated across categories to gain precision. Using the assumption
that each m-specific nine-ending effect is a fixed incremental gain in probability of
choosing Product A, the estimate of the average difference across categories is the
precision-weighted average of the differences in share A Sk,m, where precision is the
inverse of the variance:
A Sm = (Totar1Pecision) Zk11 precision(A Sk,m) ASk,m
where precision(ASk,m)
Var[zXSk,m]
(2M/N)
=
N2M
Plk,m(1-Plk,m)+POk,m(1-PI,m)
N12M
zKi-k1Plk,m,(l-Plk,m)+POk,m(1-POk,M)
24
-
Chapter 3
Result Discussion
3.0.2
Hypothesis Testing
The effects proposed in the previous chapter are considered using a null hypothesis
that the phenomena discussed have no effect. Values for averages and standard errors
are computed using the equations defined in the previous chapter.
This chapter
presents the results and discusses the findings.
3.0.3
Main Nine-Ending Effect
The basic measure of the nine-ending effect is the difference in Product A's share with
a nine ending and Product A's share with an eight ending. As shown on Table 3.1,
a little more than half of the categories have positive effects and only four have a
significant positive effect (taken to be a t >= 1.6). With so many categories showing
negative values, the average nine-ending effect is rather small and analysis shows it
not to be statistically significant. See Table 3.2. A possible reason for this is the noise
inherent to the design of the experiment. The budget constraint may have caused the
low budget people to shop quite differently from the high budget group. Since the low
budget group contributes roughly half of the sample, their behavior may introduce
noise that obscures a positive effect in the high budget group. Thus, the nine-ending
effect may be important in online shopping, but experimental noise has made it hard
to detect in aggregate analysis.
25
Table 3.1: Main Nine Ending Effect
Ranking
Category Name
Increase in
Standard Error
t-value
0.063
0.069
0.039
0.031
0.060
0.033
0.054
0.068
0.057
0.038
0.058
0.045
0.027
0.023
0.059
0.018
0.028
0.049
0.055
0.062
0.063
0.058
0.054
0.020
0.035
0.055
0.063
0.050
0.066
0.065
2.031
1.347
2.076
2.290
0.983
1.666
0.907
0.617
0.666
0.973
0.620
0.733
1.148
1.217
0.389
0.333
-0.142
-0.102
-0.127
-0.209
-0.222
-0.344
-0.629
-1.75
-1.114
-0.818
-1.015
-1.48
-1.439
-1.830
Product A Share
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Disposable Plates
Pasta in a Bag
Ice Cream-1 Pint
Paper Towels
Pasta Sauce
Water
Bread
Chocolate Chip Cookies
Pasta in a Box
Toothpaste
Breakfast Cereal
Yogurt
Jam or Jellies
Corn flakes
Orange Juice
Laundry Detergent
Tea Bag
Canned Vegetables
Cranberry Juice
Shampoo
Frozen Entree
Dish Washing Liquid
Trash Bags
Mayonnaise
Soup
Disposable Cups
Potato Chips
Milk
Coffee
Ice Cream-1/2 Gallon
0.128
0.093
0.081
0.071
0.059
0.055
0.049
0.042
0.038
0.037
0.036
0.033
0.031
0.028
0.023
0.006
-0.004
-0.005
-0.007
-0.013
-0.014
-0.020
-0.034
-0.035
-0.039
-0.045
-0.064
-0.074
-0.095
-0.119
Table 3.2: Main Nine Ending Share Increase
Nine-Ending
across 30 categories
Increase in
Product A Share
0.009
26
Standard Error
t-value
0.007
1.285
Table 3.3: Nine Ending Share Increase vs. Fraction of Nines
Frac9 Level
0
0.25
0.5
0.75
1
3.0.4
Increase in
Product A Share
0.023
-0.008
-0.004
0.021
0.040
Standard Error
t-value
0.024
0.012
0.017
0.014
0.019
0.958
-0.666
-0.235
1.5
2.105
Fraction of Nines
Contrary to expectations, the result for the fraction of nines effect, as shown on Table 3.3, does not show a diminishing effect for increasing fraction of nines. If anything,
the results suggest the opposite. High fraction of nines seems to produce a higher
nine-ending effect. The absence of the expected relationship again suggest that the
low budget constraint may be adding noise. Also, the type of categories representing
the different fractions may introduce more variance than originally expected.
Nine Ending Share Increase vs. Lagged Fraction of Nines Effect
Lagged fraction of nines, i.e. nines encountered in the prior period, was expected to
affect the strength of nine-endings in the current period. However, no statistically
significant relationship is apparent between nine-endings and the lagged fraction of
nines, as can be seen in Table 3.4. This may have been affected by the experimental
design. In each aisle, shoppers go through a style page before seeing the list of products, the actual fraction of nines. Consequently, the effect of the nines encountered
in the previous aisle may be attenuated.
Interactions of Fraction of Nines and Lagged Fraction of Nines
Not sur-
prisingly, given the results just discussed, the interaction between fraction of nines
and lagged fraction of nines is found to be insignificant as well. The high and low
fractions shown in Table 3.5 are defined as follows. 1) fraction of nines of zero or
a quarter are considered to be low, 2) high fraction of nines refer to the fraction of
27
Table 3.4: Nine Ending Share Increase vs. Lagged Fraction of Nines
Lagged Frac9 Level
Increase in
Standard Error
t-value
0.023
0.012
0.022
0.025
0.023
0.130
-0.666
1.045
-0.480
1.347
Product A Share
0
0.25
0.5
0.75
1
0.003
-0.008
0.023
-0.012
0.031
Table 3.5: Nine Ending Share Increase vs. Fraction of Nines and Lagged Fraction of
Nines
Fraction of Nines-
Increase in
Lagged Frac9
Product A Share
High-Low
High-High
Low-Low
Low-High
0.035
0.04
0.006
0.032
Standard Error
t-value
0.026
0.028
0.026
0.026
1.346
1.428
0.230
1.230
three quarters or one and 3) fraction of nines of a half is considered as neither high
nor low.
3.0.5
Ordering of Product A within a Choice Set
The effect of nine-endings was hypothesized to increase as the item appears lower
on the list of choices. However, the experimental results yield no clear pattern that
would support this prediction. A likely reason is that our list is short. The original
prediction assumes that shoppers become tired from looking at a list, and as a result,
gives less attention to the items on the bottom of the list. This does not seem to
apply to our list of only 5 products. In such a short list, all products in each choice
set may receive an equivalent amount of attention.
28
Table 3.6: Probability of Purchase some item vs. High and Low Budget
Budget Size
High Budget
Low Budget
3.0.6
Probability of Purchase
0.851
0.565
Standard Error
0.006
0.009
Probability of Purchasing of the Two Budget Groups
Before moving into the analysis related to budget sizes, Table 3.6 provides the likelihood of purchasing some item (any item), regardless of its price ending, for the two
budget groups. The people given an $80 budget are much more likely to make a purchase than the people with a $40 budget, almost 30 percent more. Such differences
are to be expected. People with different amount of spending money are expected to
use different shopping strategies. Moreover, this probability difference can be interpreted as an indicator that the experiment participants are behaving as if they were
shopping for real. They shop according to the budget assigned and try to stay within
their spending limits.
3.0.7
Budget Size
Since the budget size is suspected of introducing variance, both the nine-ending and
fraction of nines are evaluated by budget size as shown in Table 3.7 and Table 3.8. The
high budget group shows a positive nine-ending effect of 2.6%, which is significantly
greater than zero. The low budget group shows a non-significant negative effect. The
two effects together, one positive and the other a near zero, indicate that the budget
constraint was an effective control variable, strong enough to turn the nine-ending
effect on and off.
These results also support the contention that the reason the main effect is not
significant is that the low budget group has no effect and is simply adding noise that
dilutes the significant effect of the high group.
It turns out that the fraction of nines effect does not yield the expected pattern
even in the high budget group. See Table 3.8. However, the consistency of having
29
Table 3.7: Nine Ending Share Increase vs. Budget Size
Budget Size
Increase in
Standard Error
t-value
0.01
0.01
-0.600
2.600
Product A Share
Low
High
-0.006
0.026
Table 3.8: Nine Ending Share Increase vs. Budget Size and Fraction of Nines
Budget SizeFraction of Nines
High-Frac9=0
High-Frac9=0.25
High-Frac9=0.5
High-Frac9=0.75
High-Frac9=1
Low-Frac9=0
Low-Frac9=0.25
Low-Frac9=0.5
Low-Frac9=0.75
Low-Frac9=1
Increase in
Product A Share
0.017
0.023
0.007
0.023
0.075
0.041
-0.017
-0.032
0.009
-0.008
Standard Error
t-value
0.031
0.022
0.021
0.020
0.027
0.038
0.017
0.026
0.018
0.028
0.548
1.045
0.333
1.150
2.777
1.078
-1.000
-1.230
0.500
-0.285
positive effect in all the high budget's fractions confirms that the high budget people
indeed are shopping differently than the low budget group.
More importantly, this result supports the initial prediction that people with more
spending money are less concerned with prices and therefore, more easily influenced
by the nine-ending effect.
The high budget people were given more than enough
money to buy every most expensive product in all 30 aisles. With hardly any pressure
from the budget constraint, they not only buy more products but also become more
susceptible to the nine-ending effect. Looking from the retailers point of view, the
result indicates that people pay less attention to prices and become more likely to
buy products with a nine price-ending when money is less of a concern.
On the other hand, there appears to be less advantages for using a nine-ending
when the economy is bad. As seen in the low budget group, people are less attracted
to prices ending in nine when prices become important.
30
Table 3.9: Nine Ending Share Increase vs. Sequence of Choices
3.0.8
Sequence
Increase in
of Choices
Product A Share
Early
Late
0.002
0.017
Standard Error
t-value
0.010
0.010
0.200
1.700
Sequence of Choices during the Experiment
One interesting result has emerged from an examination of the sequence of choices
during the experiment. The entire sample of choices is divided into two sets: choices
that are made in the first half of the shopping trip and choices that are made in the
second half of the trip. These two sets are denoted as "early" and "late" respectively.
The two sets display different results. The late set shows a strong nine-ending effect
of 1.7 share points, which is much higher than the approximately zero effect in the
early set. As can be seen in Table 3.9, this result suggests that shoppers are more
susceptible to nine-ending effect during the latter part of the shopping trip.
The reason may be shopping fatigue, the longer people shop, the less attention
they pay to prices and the more susceptible they become to the nine-ending effect.
Furthermore, it may be possible that time becomes a concern for people towards
the end of the experiment. This may suggest that shoppers with limited amount of
shopping time are more likely to buy products with a nine ending. As most of the
Internet shoppers are pressed for time, this may suggest that Internet grocery stores
should set many price endings to nine, especially at the "express" shopping section
if available. In general, retailers may benefit from implementing this policy if they
know that the majority of their customers are purchasing in a hurry.
In terms of the underlying mechanism, the nine-ending effect may be caused by
the meaning effect as described in Chapter 1. The more tired the shoppers become,
the less they fully process price information and the more they rely on price meanings
in making a purchase decision.
31
Table 3.10: Nine Ending Share Increase vs. Budget Size and Sequence of Choices
Budget SizeSequence of Choices
Low-Early
Low-Late
High-Early
High-Late
3.0.9
Increase in
Product A Share
-0.006
-0.002
0.024
0.029
Standard Error
t-value
0.014
0.016
0.014
0.013
-0.428
-0.125
1.714
2.230
Budget Size and Sequence of Choices
In light of the previous finding, the sample is now separated into the following four
subgroups to examine the combinational effect of budget size and order in sequence
of choices: 1) choices that are made early in the shopping trip by a high budget
person, 2) choices that are made late in the trip by a high budget person, 3) choices
made early in the trip by a low budget person and 4) choices that are made late in
the experiment by a low budget person. The results are tabulated in Figure 3.10
The sequence of choice effect appears in both high budget and low budget groups,
although the reduction in sample size required in sorting observations into more cells
leaves the results short of statistical significant.
32
Chapter 4
Comments and Summary
4.1
Doing the Online Experiment in the Lab vs.
Elsewhere
The web is a good medium for collecting a large set of diverse data in a short period
of time. However, it also allows room for many sources of distractions. Capturing the
full attention of the subjects becomes more challenging since many other activities can
be done at the same time as the experiment, for example, playing computer games.
Thus, an interesting aspect of the experiment is to try to compare the engagement
level of our subjects, in lab versus anywhere else. The walk-in session provided a traditional lab environment that is considered to provide the control needed for running
an experiment. The experimenter found that the walk-ins were more engaged in their
tasks than the subjects who performed the experiment in unsupervised locations.
The walk-in session also proved to be useful for getting direct feedback about specific
concerns of the subjects. Some of these issues had been uncovered in pilot testing,
but the larger walk-in sample provided further insights. As has been seen in the previous chapter, the walk-in samples provided parameters for reliably cleaning the rest
of the samples. For future web-based experiments, it would be beneficial to conduct
a controlled session in parallel, in addition to the pilot testing done in advance.
33
4.2
Using Hypothetical Products
The use of hypothetical products did not generate distraction for the subjects. The
subjects were warned in advance that some hypothetical products would be used and
were comfortable shopping with them. Ideally, hypothetical products would not have
been used, but they were required to implement the design structure. Comments
from the walk-ins and other subjects actually reported that they found the grocery
store realistic.
4.3
Future Research
The experiment was designed so that a first level of analysis could be performed by
simple counts and averages, and those are the results reported here. However, the
data collected will be further explored using various models. One example would
be a logit model where the loyalty preference from the subjects will be considered
in the measurement of the nine-ending effect. Further investigation of other possible
moderating variables on the nine-ending effect may yield further insights into shopping
behavior of the high and low budget groups. Possible moderating variables are the
relative price and popularity of product A as compared to the other products in the
same category. Future measurements of the nine-ending effect should consider and
try to eliminate any biases detected in the design of this experiment. As for future
testing, one particular area of interest would be to examine how the choice of online
stores is related to the number of nine-ending products carried by the store. Another
area would involve further investigation of the various possible meanings associated
with nine endings under different circumstances.
4.4
Conclusion
Two clear pictures emerge from the discussion in the previous chapters. The nineending effect is most influential when it is seen towards the end of a shopping trip.
Perhaps all the products near the check out counter should be priced with a nine
34
ending! The second picture suggests that nine endings will be most effective whenever
the economy is good.
People with more spending money are more likely to buy
products with a nine price ending. This also suggests that gourmet food stores,
tailoring to expensive shoppers, might gain an advantage from pricing many of their
products with a nine ending.
35
Appendix A
Online Survey
36
Table A.1: A Survey on Online Grocery Stores - Oct 1999
OnLine Grocers
Price
Ending
Unit
Price
Product
Description
Homeruns
Mostly 9
Yes
Text
optional
Detailed
Price
Info
Yes
Size
Info
Yes
On
Sale
Icon
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
No
Yes
Yes
No
No
Yes
Yes
No
No
No
Yes
No
No
No
Yes
No
No
No
Yes
No
No
No
No
Yes
Yes
No
No
Yes
Yes
No
Yes
Yes
Yes
No
No
No
Yes
Yes
Yes
Yes
Yes
Personal
List
images
Peapod
9 only
Yes
Text
optional
images
Yourgrocer
9 only
No
Netgrocer
Mostly 9
Yes
Grocexp
Mostly 9
No
Harryanddavid
All in 5
No
Northwestgrocer
Mostly 9
No
Latingrocer
All Digits
No
Text and
images
Text only,
extra images
for featured
items
Text and
Peachtreenetwork
Webvan
Mostly 9
Many 7
No
No
Text
Text and
Gourmet-grocer
Groceronline
Mostly 0 or 5
All Digits
Streamline
Mostly 9
Text,
optional
images
Text and
images
Text and
images
images
images
No
Yes
Text
Text and
images
No
Text,
optional
images
37
Appendix B
Web Experiment
38
Figure B-1: Login Page
The ART of Shopping
Mini Mart is an online shopping research project at MIT. Our goal is to understand how
shopping in the future will be done and to find ways to improve the experience for both the
customer and the seller. In particular, we wish to understand the customers' tradeoff among
price and quality characteristics in an online setting so that customers' needs can best be met
by the seller's offerings.
In the current experiment, we invite participation from the MIT community only. It involves
choosing groceries from available products in several categories and answering three
questions at the end of the study. No groceries are actually purchased.
Participation is entirely voluntary. The time required is about 15 minutes. You can stop at
any time by clicking the QUIT button. Responses will be anonymous. You will be
recognized with a random number only. You may skip any question, although if you skip
very many, your response may be unusable.
For your participation in the simulated shopping trip, you will be offered a reward of SONY
movie ticket. Even though early withdrawal from the study is discouraged, you will be
compensated with a movie ticket regardless.
If you have any questions or problems, please contact Minnie Lau (scarb@mit.edu,
617-441-3569) or Professor John D. C. Little (jlittle@mit.edu, ext. 3-3738).
I understandthat I may contact the Chairmanof the Committee on the Use of Humans as Experimental
Subjects, MIT 253-6787, if Ifeel I have been treatedunfairly as a subject.
* I've read the above and would like to participate
* No, I do not wish to participate at this time
39
Figure B-2: Scenario
Scenario
It's only the middle of the week and your fridge is already running out of food. You've also
realized how busy your schedule will be, so you decide to order your next week's groceries
from your favorite online grocer, Mini Mart.
Mini Mart is an on-line grocery store that offers all the products you want with FREE
delivery. However, it is currently undergoing restructuring to test a new "electronic-aisle"
concept, designed to ease your shopping experience. The new structure will guide you
through the store and present the store "aisles" one by one. There are a total of 30 aisles,
each containing one category of product.
Please select one item per aisle. If you never purchase in that aisle, you may skip it
altogether by selecting this tag:
. If you do not wish to purchase any of the
items offered, indicate "no purchase". Also note that a few products are hypothetical for the
purpose of this experiment and may not exist in the real world. Please stay within your
budget limit!
95% of the experiment consist of the shopping simulation above and the remaining 5%
involve a short survey.
PLEASE:
* DO NOT participate more than once in the experiment, but feel free to ask others to participate.
* Make your choices carefully, your input is valuable to our research.
* Have fun. Thank you very much for your time and participation.
Enter Here!
40
Figure B-3: Bread Style - First part of a sample aisle
'Maft
What kind of bread do you prefer?
0 Oat & Oatmeal
0 Pumpernickel
0 Raisin & Cinnamon
Rye
0 SourDough
0 White
0 12, 9 or 7 Grain
Please make your choices carefully!O Whole Wheat
Your input is important to our research.
05b ths categbry
41
Figure B-4: Bread Choices - Second part of a sample aisle
Your Current Cart Total : $8.21
You have 22 aisles left to visit. Please plan ahead to stay within your BUDGET: $ 80
Rye Bread - 16oz packaged
Price Choice
Brand
$1.79
0
Bouyea Fassetts $1.99
0
Country Kitchen $1.89
0
J.J.Nissen
$1.49
Wonder
$1.58
0
0
Arnold's
0
no purchase
Next]
42
Please make your choices carefully.
You input is important to our
research.
Figure B-5: Tooth Paste Style - First part of a sample aisle
)Mart
Please pick your favorite kind of toothpaste:
o Regular
0With Baking Soda
Please make your choicesOWith Tartar Control
carefully!
Your input is important to our 0 Extra Whitening
research.
43
Figure B-6: Tooth Paste Choices - Second part of a sample aisle
Your Current Cart Total: $10.10
You have 21 aisles left to visit. Please plan ahead to stay within your BUDGET: $ 80
With Tartar Control
Toothpaste - 6oz regular
tube
-
e.
Brand
urn
Price Choice
Aim
$2.09
0
Aquafresh
$2.79
0
Colgate
$2.58
@
Crest
$2.69
Q
Dental Care $2.89
0
no purchase
0
Please make your choices carefully.
You input is important to our
research.
44
Figure B-7: Questionnaire - Personal Preference Sample Questions
Free Shopping
For the following 30 categories, shop as if price were not a consideration.
1. 1/2 Gallon Milk:
O Hood 0 Beatrice 0 Sealtest183 0 Garelick Natural 0 West Lynn Creamery 0 none
2. l6oz Box of Pasta:
O Barilla 0 Prince 0 President's Choice 0 Ronzoni 0 Mueller's 0 none
3. Toothpaste - 6oz regular tube:
O Aquafresh 0 Colgate 0 Aim 4 Dental Care Q Crest 0 none
4. 100 Regular Tea Bags:
O Lipton 0 Red Rose 0 Salada ® Twinings 0 Tetley 0 none
5. Packaged Bread (16 oz packaged):
O Country Kitchen Cl Arnold's 0 Bouyea Fassetts 0 J.J.Nissen C Wonder ()none
6. Paper Towels - I Roll:
o Scott 0 TopCrest 0 Kleenex 0 Bounty 0 Cottonelle ) none
7. 26oz Pasta Sauce Jar/Can:
O Prego C Classico ( Hunt's 0 Healthy Choice of Ragu 0 none
8. Chocolate Chip Cookies (- 8oz):
O Chips Ahoy-Nabisco 0 Chips Deluxe-Keebler 0 Pepperidge Farm 0 Famous Amos
o President's Choice 0 none
9. Detergents - Liquid or Powder(-50oz):
o All 0 Xtra 0 Tide 0 Cheer 0 Wisk 0 none
10. Disposable Cups (20ct):
o Dixie C Dart 0 Royal Chinet C)Top Crest 0 Solo () none
11. Flavored Chips - Large Bag(~ Ooz):
O Lays Chips 0 Wise Potato Chips C) Sun Chips * Doritos 0 Ruffles Chips 0 none
12. Orange Juice (-64oz):
0 Veryfine C Minute Maid 0 Tropicana C Dole 0 Floridas Natural 0 none
27. Coffee (~12 oz can):
C Chock Full of Nuts 0 Hills Brothers Colombian C Maxwell House 0 Eight O'Clock
0 Folgers 0 none
28. Cranberry Juice (-48oz):
0 President's Choice * NorthLand 0 Ocean Spray 0 Seneca 0 V8 Splash 0 none
29. Yogurt (-8oz):
C Dannon C Stonyfield Farm 0 Columbo 0 Breyers 0 Yoplait C none
30. Mayonnaise (~16oz):
o Kraft 0 Hellmann's 0 Bright Day * Cain's 0 Master Choice 0 none
45
Figure B-8: Questionnaire - Shopping Background
Questionnaire
1. Do you regularly shop for groceries online? Yes No
Approximate number per year: E
2. Do you regularly shop for other non-grocery products online? Yes No
Approximate number per month: (~]
3. Have you participated in any on-line experiment before? Yes No
If so, approximately how many? >= 5 3 to 5 =< 2
4. Other comments:
Methods of receiving your rewards:Pick up in personInterdepartmental mailNone, I am voluntary
Please provide your name and address for interdepartmental mailing:
46
Appendix C
Categories and Products
47
Table C.1: The Most Popular Products at LaVerdes - Part I
Categories
Candy
Canned Vegetables
Cereals
Chips and Snacks
Coffee and Tea
Cookies and Crackers
Condiments
Popular Products
Snickers
Milky Way Snack
3 Musketeers Snack
Reese's Peanut Butter Cups
M+M Plain Candy
M+M Peanuts Candy
Del Monte Corn
Del Monte Green Beans
Del Monte Peas
Green Giant Niblets Corn
Size
13 oz
13 oz
13 oz
13 oz
16 oz
16 oz
15 oz
15 oz
15 oz
11 oz
Cheerios - General Mills
15 oz
Kellogg's Corn Flakes
Kellogg's Raisin Bran
Kellogg's Frosted Flakes
Kellogg's Rice Krispies
Pringles Chips
Lays Chips
Ruffles Chips
Doritos
Wise Potato Chips
Maxwell House Instant Coffee
Maxwell House Instant Coffee
Maxwell House Coffee
Chock Full 0 Nuts coffee
Salada Tea Bags
Chips Ahoy
Oreo
Triscuts Crackers
Wheat Thins Crackers
Ritz Crackers
Fig Newtons
Heinz Ketchup
French's Mustard
Hellmann's Mayo
Cains Mayo
Daily Pickle Spears
18 oz
20 oz
20 oz
13.5 oz
7 oz
7 oz
7 oz
7 oz
7 oz
8 oz
4 oz
13 oz
13 oz
100 ct
18 oz
20 oz
8.5 oz
10 oz
16 oz
16 oz
36 oz
16 oz
16 oz
16 oz
24 oz
48
Table C.2: The Most Popular Products at LaVerdes - Part II
Dairy
Milk
1/2 Gallons
Land-o-Lakes Butter
Detergents
Philadelphia Cream Cheese
Colombo Yogurt
Tide Liquid
Tide Powder
All Liquid
Cheer Liquid
Clorox Bleach
Joy Dish Liquid
Ivory Dish Liquid
Irish Spring
Ivory Soap
Ivory Liquid Hand Soap
Stouffer's Entrees
Stouffer's Entrees
Healthy Choice Dinners
Celeste Cheese Pizza
Eggo Waffles
Lender's Bagels
8 oz
8 oz
50 oz
33 oz
50 oz
50 oz
64 oz
40 cf
14.7 oz
14.7 oz
5 oz
4 pack
7.5 oz
10 oz
11 oz
11 oz
6 oz
12.3 oz
12 oz
Green Giant Veggies
16 oz
Mott's Apple Juice
Ocean Spray Cranberry Juice
Veryfine Apple Juice
Veryfine Apple Juice
V-8 Juice
Tropicana O.J.
Snapple
Nantucket Nectars
Gatorade
Gatorade
Arizona Teas
64 oz
64 oz
64 oz
10 oz
48 oz
1/2 Gallons
16 oz
17.5 oz
32 oz
20 oz
16 oz
Veryfine Juices
16 oz
Bounce Fabric Softener - Sheets
Dish and Hand Soaps
Frozen Foods
Juices
Single Serve Juices
49
Table C.3: The Most Popular Products at LaVerdes - Part III
Ice Cream
Ben and Jerry's
Haagen Daz
Breyer's
Brigham's
Ice Cream Sandwiches
Health and Beauty Care Advil
Aim Toothpaste
Pantene Shampoo
Gillette Deodorant
Secret Deodorant
Pasta and Sauces
Prince Spaghetti
Prince Elbows
Prince Ziti
Prince Rotini
Prego Spaghetti sauce
Ragu Spaghetti Sauce
Kraft Parmesan Cheese
Soups
Campbell's Chicken Noodle
Campbell's Cream of Mushroom
Campbell's Vegetable Beef
Campbell's Tomato Soup
Ramen Dry Noodles
Paper Goods
Bounty Towels
Cottonelle Bathroom Paper
Kleenex Facial Tissues
Scott Napkins
Kleenex Facials
Plates, Cups and Wraps Dixie Plates
Solo Cups
Styrofoam Cups
Reynolds Warp
Glad Trash Bags
Water
Poland Springs
Poland Springs
Poland Springs
50
1 Pint
1 Pint
1/2 Gallons
1 Quart
12 ct
24 ct Tablets
6 oz
13 oz
2 oz
2 oz
16 oz
16 oz
16 oz
16 oz
26 oz
26 oz
8 oz
10.7 oz
10.7 oz
10.7 oz
10.7 oz
3 oz
1 Jumbo Roll
4 Pack
175 ct
50 ct
250 ct
48 ct
20 ct
51 ct
25 ft
10 ct
1.5 Liter
1 Liter
2.5 Gallons
Table C.4: 30 Categories by Fraction-of-Nines
Fractions-of-Nines
1.00
0.75
0.50
0.25
0.00
Categories/Aisles
48 oz Bottled Juices
Canned Vegetables - 15 oz
Categories/Aisles
Bread - 16 oz Packaged
Paper Towels Jumbo Roll
16 oz Bag of Pasta
Shampoo - 13 oz
Corn Flake Cereal 18 oz
Chocolate Chip Cookies - 18 oz
Toothpaste - 6 oz
Water - 1 L Bottle
Dishwashing Soaps - 15 oz Liquid
Ice Cream - 1/2 Gallons
Jam or Jellies - 10 oz
Liquid Detergents - 50 oz
Milk - 1/2 Gallons
Trash Bags - 10 ct
Coffee - 12 oz Can
Tea - Regular 100 ct
Frozen Entrees - 11 oz
Soup - Ready-to-Serve 10 oz Can
Yogurt - 8 oz
Mayonnaise - 16oz
Orange Juice - 64 oz 100% Natural
Ice Cream - 1 Pint
Cereal - approx 16 oz
16 oz Box of Pasta
Cups - 20 oz
Potato Chips - 10 oz Large Bag
Plates - 48 ct
Spaghetti Sauce - 26 oz Jar
51
Appendix D
Figures
52
Average Time per Aisle - Walkins
3
2.5
a)
0
C
a)
1.5
a)
.0
E .1
z
0.5
0
3
10
8
20
22
14
16
18
12
Average Time Spent on a Purchase/No-Purchase (sec)
24
26
Total Number of Aisles Visited - Walkins
4
S3
0
a.02
I I
E
zi1
0
16
18
20
26
24
22
Total Number of Purchase/No-Purchase
Figure D-1: Frequency Histograms of 25 Walk-ins
53
28
30
32
Avergae Time Spent per Aisle Visited - 493 Subjects
40
-T-300
a)
0
20-
E
z
10-
0 -
20
15
10
Average Time Spent on a Purchase/No-Purchase (sec)
5
25
Total Number of Aisles Visited - 493 Subjects
50
a) 40CL
0
a) 30 -
CL
.0
E
z
20 10
0 "
16
18
20
26
22
24
Total Number of Purchase/No-Purchase
Figure D-2: Frequency Histograms of 493 Subjects
54
28
30
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