Consumer eye movement patterns on yellow pages advertising
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Consumer eye movement patterns
on yellow pages advertising
Gerald L. Lohse
Nelson Peltz Term Assistant Professor of Operations and Information Management
The Wharton School of the University of Pennsylvania
Department of Operations and Information Management
1319 Steinberg Hall - Dietrich Hall
Philadelphia, Pennsylvania 19104-6366
office phone: (215) 898-8541
fax: (215) 898-3664
e-mail: lohse@wharton.upenn.edu
October 3, 1996
Consumer eye movement patterns on Yellow Pages advertising
Journal of Advertising. 26(1), 61-73, (1997)
Acknowledgments
I am grateful to David Fay, Kathryn Dobroth, and two anonymous reviewers for their helpful
comments and suggestions. I also thank GTE Laboratories in Waltham, MA for funding this
research.Consumer eye movement patterns on yellow pages advertising
ABSTRACT
Process tracing data help understand how yellow pages advertisement characteristics
influence consumer information processing behavior. A laboratory experiment collected eye
movement data while consumers chose businesses from phone directories. Consumers scan
listings in alphabetic order. Their scan is not exhaustive. As a result, some ads are never seen.
Consumers noticed over 93% of the quarter page display ads but only 26% of the plain listings.
Consumers perceived color ads before ads without color, noticed more color ads than non-color
ads and viewed color ads 21% longer than equivalent ads without color. Users viewed 42% more
bold listings than plain listings. Consumers spent 54% more time viewing ads they end up
choosing which demonstrates the importance of attention on subsequent choice behavior.INTRODUCTION
In 1992, yellow pages directories were a $9.4 billion dollar information services business that
reached 98% of American households (Mangel 1992). It is the fourth largest advertising medium
in the United States after television, newspaper, and direct mail (Peabody 1991). Consumers
choose from over 6,300 directories nationwide (Meffert 1991). All demographic groups use
phone directories nearly 2 times per week (Mangel 1992). The Yellow Pages Publishers
Association reports that there are more than 46 million references to the yellow pages daily
(YPPA 1992). Phone directories provide an essential link between a business and a customer by
offering information at the moment the consumer is willing to buy. Sixty percent of those who
pick up the yellow pages make an immediate purchase (Mangel 1992). Obviously, the yellow
pages are an important advertising medium for local businesses.
Yellow pages ads also represent a significant cost to businesses. A typical, non-color,
quarter page ad in a midwestern metropolitan telephone directory with a circulation of one million
costs $10,344 per year (YPPA 1992). A color ad costs approximately 50% more. Further,
yellow pages ads represent a fixed cost that must be paid monthly. Unlike newspaper ads that can
be changed daily, yellow pages ads can only be changed once a year. Thus, it is extremely
important for advertisers to have objective, neutral, third-party research that identifies the
effectiveness of particular advertisement characteristics.
Yellow pages research typically examines factors that influence why people choose one
business over another (Berdie 1992, Kelly & Hoel 1991, Butler & Abernethy 1994). Ad
characteristics examined include: size, color, page position, location, amount of information in
the ad, whether the ad listed brand names, whether the ad had a business slogan, whether the ad
contained graphics, and hours of operation. By systematically controlling the design of ads,
1researchers infer which factors influenced decision behavior.
The information content of an ad is one of the most important factors in attracting customers
(Berdie 1992, Kelly & Hoel 1991). The information in the ad must convince the consumer to
purchase from the business by emphasizing information consumers need to make their purchasing
decision. Other effects that do not seem to involve information directly, like the size of an ad, are
probably best understood in information terms as well. A business that can afford to buy a large
ad can be inferred, although not without error, to be stable, prosperous, reliable, have a wide
selection, and so forth. However, there are limits to what can be inferred from the choices people
make. For example, if a particular characteristic of an ad does not seem to influence choice, we
do not know whether people fail to notice it, or whether they notice it, but do not think that
particular characteristic matters. Knowing which is true is important because they suggest
different tactics for improving the impact of ads.
A more direct way of discovering how people acquire information from a phone directory
involves recording a person's eye movements as they scan the yellow pages. Eye movement data
provide a detailed reflection of cognitive information processing in many different kinds of
displays (Ford et al. 1989; Russo & Rosen 1975, Hill 1989). Eye movement data can distinguish
between noticing an ad but not caring, and failing to notice an ad. However, eye tracking
equipment is expensive ($30,000 to $100,000+). Additionally, the data are time consuming to
analyze because the pixel locations of each of each area of interest must be defined and mapped to
(x,y) eye coordinates. Given considerations regarding time and expense, very few studies use eye
movement data (Hill, 1989; Schmid, 1990; Treistman & Gregg, 1979).
Anecdotal evidence abounds regarding what advertisement characteristics -- color, copy
content, size and so forth -- influence consumer viewing characteristics. For example, color ads
2containing red ink inspired yellow pages marketing claims that, “Red gets read." Conventional
wisdom suggests that large color display ads are more effective than other types of yellow pages
advertisements (Maher 1988). To learn how yellow pages ads capture people's attention, this
study collected eye movement data while consumers chose businesses from yellow pages
directories. The eye movement data show what ad characteristics influence attention. Questions
addressed by this research include: (1) what particular features cause people to notice an ad, (2)
whether people view ads in any particular order, and (3) how viewing time varies as a function of
particular ad features. This research explores these questions to provide some practical and
theoretical insights for yellow pages advertisers and publishers.
CONCEPTUAL FRAMEWORK
Much of the literature on directional media focuses on print advertising in magazines,
catalogs, and newspapers. This section draws upon this research, prior yellow pages research and
underlying principles from psychology to develop some propositions about the factors influencing
consumer attention to yellow pages advertisements.
Attention to ads
Until the recent advent of spot and process color ads, a color ad in the yellow pages meant
the ad contained red ink. Such ads beg the question, "What can be said about the use of red ink
to catch the consumer’s eye?" Do people notice more red ads than ads without color? For
magazine ads, Valiente (1973) found that after ad size, color was the second most important
factor explaining ad recognition scores. We also know that people perceive some visual features
more readily than others. For example, people detect and organize color in parallel during visual
processing (Kahneman & Henik 1981). Since color facilitates parallel search, it is about three
times faster than other graphic features, such as shape, that require serial search (Treisman 1982).
P1a Yellow pages users are more likely to notice color ads before any other type of ad.
3The direct relationship between advertisement size and attention is well documented (Berdie,
1986; Rouse, 1991; Feldman and Halterman, 1963; Valiente, 1973). Larger ads are viewed first.
Other studies have been less sanguine about different benefits for large ads. Edwards (1988)
found that some consumers distrust a business whose advertisement is much larger than the
competitor's advertisement. In two of the four industries in their study, Kelly and Hoel (1991)
found that the larger advertisements were never preferred by student subjects.
P1b Yellow pages users are more likely to notice large ads before small ads.
Advertisements with graphics influence attention (Raphel 1988). In a study of ads in Life
magazine, Valiente (1973) found that pictorial benefits, number of separate illustrations, and
square inches of illustration explained 10 percent of the variation in Starch's readership scores.
The benefits of pictures in ads also are supported by evidence that suggests visual memory is
better than verbal memory (Shepard, 1967). Using pictures from a yellow pages directory, Lutz
and Lutz (1977) found that concrete interactive images facilitate recall and memory of a brand.
P1c Yellow pages users are more likely to notice ads with graphics before ads without graphics.
Prototypical patterns of eye movements
People process information using learned spatial patterns. Reading in English begins in the
upper left-hand corner and proceeds from left to right in a top to bottom fashion. Understanding
prototypical patterns for acquiring information helps identify behavior that could alter decision
processes. The American Airlines reservation system, Sabre, provides a classic example of the
effects of scanning order on choice (Phillips & Thomas, 1988). Sabre listed American Airline
flights first. Being first resulted in more bookings. After a 12 year legal battle, Sabre ordered
flights by time of departure with carrier arranged randomly in the event of time ties.
These prototypical information acquisition patterns have important implications for the
4development of future electronic phone directories and perhaps even public policy. Most people
believe that consumers will benefit tremendously from the ability to conduct on-line searches for
businesses that best fit their particular needs. A more likely scenario is that prototypical search
patterns (e.g., alphabetic) direct callers to specific businesses (e.g., Aardvark Gifts). For example,
Rhodes, Teferman, Cook and Schwartz (1979) found that nearness to the headline (e.g., the serial
position) had an impact on recall. Maher (1988) suggests that the most effective placement of a
listing is an early serial position (e.g., "AAA Sports Shop"). Thus, directory publishers may
influence consumer choice behavior by controlling the position of ads on the page.
In the United States, businesses are in alphabetic order within each business heading. The
strong learned spatial patterns for processing information (e.g., alphabetic and reading order)
suggest that people will first view businesses that have early serial positions. Jackson and
Parasuraman (1986) reported that more than 50% of the participants in their study examined
alphabetic listings before viewing the large display ads.
P2 Yellow pages users are more likely to view advertisements near the beginning of the
heading than those near the end of the heading.
Ad viewing time
Color, graphics, bold font, and ad size help a consumer notice ads in the directory. However,
the most obvious factor influencing viewing time is the copy content of the ad. Berdie and Hauff
(1986) reported that the amount of information in an ad is extremely influential in consumer
choice behavior. Since consumers are ready to make a purchase, the ad must emphasize
information consumers need to make their purchasing decision. Feldman and Halterman (1963)
claim advertisements with more copy outperform ads with light copy.
Time spent viewing ads not only demonstrates attention but also may indicate consumer
5preferences. Of course, time is not a "causal" variable. It merely indicates the underlying factors
influencing choice. Viewing time per ad integrates many fixations to the same advertisement.
Some of the viewing time differences relate to comparisons of attributes between businesses.
Russo and LeClerc (1994) also discovered that consumers continued to fixate on the product
display after they had announced their choice as a kind of post-choice verification.
P3 Yellow pages users are more likely to spend more time viewing advertisements of
businesses they end up choosing.
METHODS
Yellow pages directories
Prior research suggests that the quality of the test materials can influence results (Virzi
1989). Therefore, the 32 directory pages were created to control for layout and design effects
while maintaining realism. The pages were virtually indistinguishable from "real" yellow pages in
terms of fonts, ink, and color except that the pages were printed on slightly heavier weight paper.
Each page represented a typical assortment of advertisements for one business heading: two 1/4
page and two 1/8 page displays ads; two, large, and two, small, in-column ads; five bold listings,
and 35 plain listings. There were eight subject headings: Automobile Repair, Banks, Florists, Gift
Shops, Jewelers, Movers, Pizza, and Sporting Goods. Each of the 48 businesses within each
heading had a real address and phone number corresponding to an actual geographic location but
had an artificial name to reduce demand effects. The 32 directory pages were organized into four
books. Each book contained eight right hand side pages -- one page for each heading. The set of
four books statistically controlled for combinations of layout and design features. These included
ad type, location of display ads on the page, size of ad, color, use of graphics, whether or not a
listing has a bold typeface, serial position of an ad (alphabetic order), and the number of types of
information in the ad (hours, years in business, slogan, brand names, specialties).
6Collecting eye movement data
Saccadic eye movements have two parts: a movement phase ranging from 30 to 120 msec
and a latency phase of 100 to 300 msec. A typical fixation averages 230 msec (Russo 1978). The
Eyegaze System from LC Technologies, Inc. (Fairfax, VA) uses the pupil-center, corneal
reflection method to record saccadic eye movements (Young & Sheena 1975). The Eyegaze
System uses an Intel 80486 computer to operate both the eye tracking system and the application
software simultaneously. The Eyegaze System collects data at 60 Hz or about every 16.7
milliseconds within an accuracy of 0.25 inches. The minimum fixation duration was 100 msec.
Specialized software generates x, y coordinates, fixation duration, pupil diameter, and eye blinks.
The individual yellow page was mounted on a special holder on the face of the computer screen in
front of the subject. The observer's eye is about 20 inches from the screen page. No attachments
to the head are required.
Participants
A diverse group of 32 students and staff of a large university volunteered for the study. The
average number of years of education beyond high school was 3.5 with a range of 0 to 11. The
age of participants ranged from 19 to 56. Participants received a payment $10.00 for their
participation in the study. Eight subjects were assigned randomly to each of the four directory
conditions for a total of 32 participants. Because directories were for the Boston suburbs,
subjects who had lived in the Boston area were excluded. Subjects also were screened to insure
that he/she had used or visited a business in each of the eight business headings.
Experimental procedure
The experiment was conducted separately for each subject in one 60 minute session. First,
subjects practiced using the eye tracking equipment. Once calibrated, participants read
instructions for the yellow pages choice study. Subjects were instructed to imagine that they had
7just moved to Boston and needed to use the yellow pages directory to locate products or services.
For each heading, participants were given a goal (e.g., "You want to purchase flowers for a
friend" or "Your car needs repair"). Participants chose the three businesses for each heading that
they were most likely to patronize. The experimenter recorded the participants' choices in rank
order. After the choices were made for a particular heading, the experimenter mounted another
individual yellow page into the special holder on the face of the computer screen. The procedure
continued until each subject made a total of 24 choices (8 headings x 3 choices per heading).
After completing the task for all business headings, subjects completed a questionnaire.
Experimental design
A factorial design examines all possible combinations of color, graphic, types of information,
bold fonts, and ad size for each ad. Such designs require a large amount of time and resources to
create many different versions of each ad. To reduce costs, the current study used a fractional
factorial design examining only a portion of these factorial combinations. The unbalanced design
permits ANOVA estimation of all main effects and some two-way interaction effects with
Heading and Chosen. However, other interaction effects are not estimable. The fractional
factorial design used least-squares means to test various treatment effects. Least square means
are simply estimators of the class or subclass marginal means that would be expected had the
design been balanced with all covariates at their mean value (Searle, Speed, & Milliken, 1980).
RESULTS AND DISCUSSION
Figure 1 familiarizes the reader with the eye fixation data. Each circle represents a fixation.
The area of the circle codes fixation duration; the larger the circle the longer the subject looked at
that area. Lines connecting fixations show the subject's scan path. A large square shows the first
fixation. Figure 1 shows a serial scan of the alphabetic listings of subject 29 for the heading
Banks. She first viewed the bold listing for American Savings Bank. The two large quarter page
8display ads on the right were not viewed until after all the listing were scanned. Collectively, the
statistical analyses examined the effects of advertisement features on attention to ads, search
patterns, and viewing time. Table 1 describes the variables used in the eye fixation data analysis.
Attention to ads
Figure 2 shows the percentage of ads noticed for each ad category. Noticed ads had at least
one eye fixation. Subjects noticed 93% of the large display ads but only 26% of the plain listings.
This effect is primarily a function of size. The larger the ad, the more likely people notice the ad.
A multivariate ANOVA model examined what particular features cause people to notice
display ads. There were 32 display ads (8 headings x 4 display ads per heading) that could be
noticed by each of the 32 subjects for a total of 1,024 observations. The main effect for color was
significant [F(1,973)=7.07; p=.0080]. A statistical comparison of least squares means shows that
people noticed color ads more than ads without color (92% versus 84%). Thus, color ads lower
the visual search cost by making target information more noticeable. There were no significant
differences for ads with and without graphics. However, subjects noticed 96% of the ads with
graphics. The lack of a difference between ads with and without graphics might be a ceiling
effect. Thus, it is difficult to determine whether a display ad with graphics would be noticed more
than an equivalent display ad without graphics.
Prototypical patterns of eye movements
This set of analyses examines whether people view ads in any particular order. For example,
are listings viewed in alphabetic order? Are color ads viewed first? Search pattern is indicted by
the fixation number sequence. Fixations were numbered serially from 1 to n. The average value
of the fixation number indicates the relative order people viewed an ad. Serial position of each
business corresponds to the alphabetic order of each listing on a page. There are 48 serial
positions on each directory page. The data collection program numbers each fixation on a page in
9consecutive order. Average fixation number on a business indicates search order.
There was a significant correlation between the serial position of a business and average
fixation number (r = .7065, p = .0001). Figure 3 presents a scatter plot of these data with a
regression line depicting trend. The simple regression explains 49% of the variation in average
fixation number. Clearly, people scan listings in the phone directory in alphabetic order.
A separate analysis examined search effects for display ads. The ANOVA for search patterns
is based on 11,231 fixations for the display ads actually viewed on each of the eight headings by
the 32 subjects. The fixations not on display ads were on the listings, in-column ads, filler,
headings, index, and margins or were off the page. A multivariate ANOVA model found that
consumers viewed color ads before ads without color [F(1,11183)=13.77, pappears that subjects compared other businesses to their initial choice to justify their selection.
Ad viewing time
Viewing time measured the total time (in seconds) a subject viewed an ad. There were 348
possible ads (8 headings x 48 ads per heading) for each of 32 subjects for a potential of 12,288
observations. Of course, subjects did not view every ad. Thus, the ANOVA examines how total
viewing time varied as a function of particular features on the 4,886 ads actually viewed. Chosen
ads were any of the three businesses participants chose to call. On average, subjects spent about
one minute per page to make their three choices. Viewing time for individual pages ranged from
19 to 188 seconds.
Ad size had the largest effect on viewing time [F(1,4758)=137.90, p < .0001]. On a per ad
basis, people spent more time viewing large ads. However, on a per page basis, people spent
almost as much time per page viewing plain listings (Table 2). Thus, viewing time is a function of
the number of ads per page as well as the amount of time per ad. Figure 4 graphs the relationship
between fixations per ad and ad size. The straight line is a base line reference of one fixation per
square inch. Bars note a 95% confidence interval for number of fixations around each of the six
ad size means. All ads except large display ads had at least one fixation per square inch. Small
display ads (five square inches) maximized the number of fixations per square inch. Figure 4
demonstrates limits to the benefits of large ads. Figure 5 graphs seconds of viewing time per ad.
Larger ads command a longer viewing time.
Business choice had the next largest effect. People spent 54% more time viewing ads they
end up choosing [F(1,4758)=64.95, p < .0001]. A significant interaction effect between ad
category and whether an ad was chosen (Figure 6) explains the viewing time effect. People spent
more time viewing display ads and in-column ads for businesses they chose to patronize. Bold,
11plain and anchor listings did not have any significant difference in the amount of time spent
viewing chosen ads and ads not chosen. The information content of the ads explains this
interaction effect. Display ads and in-column ads varied the number of additional types of
information. Bold, plain and anchor listings do not contain any additional types of information.
Subjects could only make a decision to patronize businesses with bold or plain listings on the basis
of the name and address. As a result, the additional viewing time can be attributed to the
evaluation of the additional information in the display and in-column ads.
The type of heading significantly influenced the amount of viewing time per ad. Subjects
spent more time viewing ads for Banks and Movers than for Pizza [F(7,4758)=3.38, p < .0013].
It seems reasonable to assume that subjects spent more time viewing headings less familiar to
them. Also subjects may spend more time viewing headings whose products or services have a
higher value (e.g. cost of pizza versus cost of moving service). There was also a significant
interaction between Heading and Chosen [F(7,4758)=2.84, p < .0059]. Subjects spent more time
viewing ads for businesses they end up choosing for all business headings except automobiles.
Color had a significant main effect on viewing time. Color not only captured initial viewing
attention but also resulted in additional viewing time. People spent 21% more time viewing a
color ad than the equivalent ad without color [F(1,4758)=3.93, p < .0476]. For one heading,
Banks, people spent 100% more time viewing color ads [F(7,4758)=4.76, p < .0001]. This is
significantly above the 21% average increase for color ads. No other business heading had a
significant amount of additional viewing time beyond the 21% average increase for color ads.
There was also a marginally significant main effect for ads with graphics [F(1,4758)=3.15, p
< .0759]. Subjects spent 13% more time viewing ads with graphics. Unlike color ads, ads with
graphics did not have an interaction effect with different business headings.
12Bold listings capture attention by making ads easier to read. People viewed 42% more bold
listings than plain listings. The number of fixations on bold listings (2.0) did not differ statistically
from the number on plain listings (1.7). Bold listings did improve the likelihood of being chosen.
The alphabetic order of the listing did not influence average viewing time per ad. Subjects
did not spend more time viewing ads they saw earlier in the listing than those viewed later in the
listing. Figure 7 shows the significant effect of the number of types of additional information on
viewing time [F(5,4778)=3.83, p < .0018]. Viewing time increases as the number of types of
additional information increases from zero to three. Viewing time decreases with any further
increase in the amount of information per ad. Too much information in an ad decreases viewing
time. Ad size mediates the effect of the amount of information in an ad. Too much information in
a small area makes the ad difficult to read.
LIMITATIONS
It is important to note several limitations of this research. First, the finding that subjects only
viewed 26% of the plain listings is lower than we might expect for the general population.
Second, the sample is skewed towards people with higher levels of education. Additional
research would determine how well the eye movement findings generalize to different segments of
yellow pages users. Third, the sample size is small. Additional data are needed to determine
whether the results will hold for a more heterogeneous sample. Fourth, the experimental design
can not test some higher order interactions (e.g., heading x graph x color). Thus, the results must
be interpreted subject to these caveats.
Ideally, the study would have used a local, phone directory and local residents with
knowledge about the local suburban area, roads names, and driving conditions as well as a large
sample size like the study by a major phone directory publisher that used 192 home owners
13recruited from a local shopping mall. However, the equipment is not mobile and very expensive
($30,000-$100,000+). Thus, it is not very feasible to conduct the study at a shopping mall.
Nevertheless, the current study replicates not only the significance but also the size of the effect
for every variable, except location, in the study noted above by a major phone directory publisher.
Thus, these results should generalize to other phone directory users.
SUMMARY AND CONCLUSION
The results from this yellow pages study are consistent with previous findings on print
advertising in magazines, catalogs, and newspapers. Ad size, graphics, color and copy all
influence attention to advertisements (Hornik 1980; Rossiter 1981, 1988; Schindler 1986;
Valiente 1973). In the current study, information content of the ad had a large effect on attention
and choice. People spent 54% more time viewing ads they eventually chose because display and
in-column ads contain additional information not found in plain listings. Ads with a high
information content were viewed before ads with a low information content; however, too much
information on an ad decreased viewing time.
Ad size also influenced attention. In general, the larger the ad, the more likely subjects will
noticed the ad. Subjects noticed 93% of the large display ads but only 26% of the plain listings.
The density of fixations is another measure of attention. Small display ads (five square inches)
had the greatest density of fixations per square inch of space.
Color ads and ads with graphics capture attention. Subjects noticed more color ads than ads
without color (92% versus 84%) and subjects viewed color ads before ads without color.
Subjects viewed color ads 21% longer than equivalent ads without color. Subjects also viewed
96% of graphic ads. However, unlike color ads, graphics ads did not capture initial consumer
attention. Additional research will help understand if graphics are more effective for some
14business headings than others as well as if the information content of the graphic influence its
effectiveness.
The position of an ad on the page had a large effect on whether people view a business, even
though the position says nothing informative about the business. Position matters because people
scan ads on a page in alphabetic order and their scan is not exhaustive; as a result, people never
read some ads. Aardvark Gifts is better than Zodiac Gifts, if the ads are otherwise equal (same
size, same page, same font, etc.). Unfortunately production layout of yellow pages cannot
guarantee a certain position on the page. Further it is not know whether the serial position effect
is valid across multiple pages in a business heading.
In a previous study, travel time to a business had the largest effect on consumer choice
(Jackson and Parasuraman 1986). In the current study, we screened subjects to insure location
would not affect consumer choices as much. Subjects were not familiar with the Boston suburbs,
roads names, or driving conditions and made their selections without local maps. As a result,
subjects may have paid more attention to the information found in display and in-column ads and
less attention to plain listings that were distinguishable only on the basis of their locations.
The lack of consumer focus on business location emulates yellow pages usage for 42 million
residents that move each year -- 14.8 million of them to a different county or state (US Bureau of
Census 1995, p32 Table 33). While this market niche only represents a small segment of the US
population, people that move to a new city make many major purchasing decisions over a very
short period of time. Further, the newly mobile market segment are heavy users of the yellow
pages and tend to be more affluent then the general population (Butler and Abernethy 1994).
While the results indicate how newly mobile consumers would use the yellow pages, they
generally underestimate the effect of location for the typical consumer.
15The paper adds to the existing body of literature on print advertising and validates the
previous findings regarding size of ad, color, and information content. The paper also highlights
the importance of serial position in an alphabetic listing on choice. The unique contribution of this
research lies in the novel use of eye tracking equipment. Just as computers have rapidly increased
in power and performance, eye tracking equipment has also improved significantly. Contemporary
eye tracking equipment no longer requires bite bars and other attachments to the head. Current
eye tracking systems are able to detect regions as small as 1.5 square centimeters. Thus, it seems
time to reevaluate the importance of eye tracking equipment as a tool for print advertising
research.
Two recent papers also tout the advantages of eye tracking data in improving catalog sales
by improving the customers’eye flow (Hill, 1989; Schmid, 1990). The use of eye movement data
distinguishes between noticing a particular characteristic of an ad or not. Whether or not an ad
was noticed suggests different tactics for improving the impact of ads. Ads that are not noticed
require features to attract the readers attention, whereas noticed ads that did not influence choice
require better copy.
These results also have some practical implications for pricing decisions regarding ads in
phone directories, marketing of directory advertisements, and the graphic layout for paper and
electronic phone directories. For example, current directory practices place large display ads at
the front of a heading and reward senior clients with better serial position in a heading. Since
consumers direct more attention to ads at the beginning of a listing, what is it worth to be first?
By understanding how consumers view businesses in the yellow pages, the research provides
insights about training the sales force (Sales), providing guidelines and recommendations for
advertisers (Advertising), improving the graphic layout of yellow pages directories (Production),
16recommending pricing strategies based on perceived value (Marketing), and designing future
electronic yellow pages (Product Development).
The future of the yellow pages relies in electronic technology such as CD-ROM, interactive
television, and multimedia services. As phone companies develop new information products and
services, knowledge about the effect of attention and information acquisition strategies can be
used to design systems that influence consumer choice. Thus, information acquisition patterns
also have implications for the interface design of future electronic phone directory services.
17Table 1: Variables included in the data analysis
Variable Description
subject 1 to 32
book 1 to 4 - each book contained different ad positions
heading text version of business category name
auto, banks, floral, gift, jewel, movers, pizza, sports
adcat ad categories for large and small display ads, large and small
in-column ads, bold and plain listings, and anchor listings for the large
and small display ads
bold 0=plain listing; 1=bold listing
sbus serial position of ad on the page (1-48)
asize ad size in square inches
.167=plain listing
.375=bold listing
1=small in-column
3=large in-column
5=small display
20=large display
sum number of types of information in the ad (range=0-5)
information types: hours, years in business, slogan, brand
names, specialties
color 0=black, 1=at least some red
graphic 0=no graphic, 1=graphic
chosen 0 if ad was not chosen; 1 if ad was 1st, 2nd or 3rd choice
fix_num ordinal number of each fixation on a page (1=first to N=last)
seconds fixation duration in seconds
Table2: Viewing time per ad
Number Percent of Ads viewed Seconds Seconds
Ad Type per page ads viewed per page per ad per page
Large Display 2 93.0 1.9 6.4 12.2
Small Display 2 88.5 1.8 4.4 7.5
Large In-column 2 83.6 1.7 4.2 7.1
Small In-column 2 58.2 1.2 2.2 2.6
Bold 9 37.4 3.4 1.7 5.8
Plain 35 26.4 9.3 1.2 11.2
TOTAL 52 36.7 19.1 2.4 46.4
18Figure 1 Example of serial scan of alphabetic listings.
19Figure 2: Percent of ads noticed by ad category
Plain 26
Bold 37
Small In-column 58
Large In-column 84
Small Display 89
Large Display 93
0 20 40 60 80 100
Percent
Figure 3: Relationship between serial position of business
and average fixation number
70
Average fixation
60
number
50
40 y = 0.33x + 51.6
30 R2 = 0.4992
20
10
0
0 10 20 30 40 50
Serial position of business
Figure 4: Fixations per ad as a function of ad size
with 95% confindence intervals
20.0
Fixations per ad
15.0
10.0
5.0
0.0
0 2 4 6 8 10 12 14 16 18 20
Ad Size in square inches
20Figure 5: Viewing time as a function of ad category
8
6
Seconds
4
2
0
Large Small Large Small Bold Plain Large Small
Display Display Column Column Listing Listing Anchor Anchor
Figure 6: Ad x Chosen means with 95% confidence intervals
9
8
7
6
Seconds
5
4
3
2
1
0
Large Small Large Small Bold Plain Large Small
Display Display Column Column Listing Listing Anchor Anchor
Ad is not chosen Ad is chosen
Figure 7: Viewing time with 95% confidence intervals
3.6
3.0
Seconds
2.4
1.8
1.2
0.6
0.0
0 1 2 3 4 5
Number of types of information
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