10.1177/0092070303257856 ARTICLEJOURNAL OF THE ACADEMY OF MARKETING SCIENCE WINTER 2004Franke et al. / INFORMATION CONTENT OF ADS

Information Content and ConsumerReadership of Print Ads: A Comparisonof Search and Experience Products

George R. FrankeUniversity of Alabama

Bruce A. HuhmannNew Mexico State University

David L. MothersbaughUniversity of Alabama

This study builds on past research involving the economics

of advertising information (Nelson 1970, 1974) to exam-

ine the interplay between advertisers’ provision and con-

sumers’ readership of information. The authors focus on

the prepurchase verifiability of advertising claims in three

product categories: search products, experience shopping

products, and experience convenience products. They use

a broader measure of the information content of advertis-

ing than in past research, together with Starch readership

scores for a sample of ads from nine U.S. magazines. The

results show that the relationship between information

provision and readership is positive for search products,

negative for convenience products, and nonsignificant for

shopping products. Average information levels are signifi-

cantly higher in ads for shopping products than for conve-

nience and search products. These findings suggest that

advertisers may be underinforming consumers when

promoting search products.

Keywords: advertising; ad readership; economics of in-

formation; information content

Provision and usage of advertising information are crit-

ical issues for marketing and public policy. Marketers pro-

vide information in an attempt to enhance consumer brand

perceptions and purchase probabilities, whereas policy

makers want advertisers to provide information to

improve the quality of consumer decisions. However, the

potential benefits of advertising information to marketers,

consumers, and society should be expected to accrue only

to the extent that consumers notice, process, and compre-

hend such information. Thus, effective communication

involves the interaction between information provision on

the sellers’ side and information utilization on the buyers’

side (cf. Calfee and Ford 1988; Friestad and Wright 1994).

Theory and research on the economics of information

(EOI) help to explain the informational interplay between

buyer and seller (e.g., Bloom 1989; Ford, Smith, and

Swasy 1990; Nelson 1970, 1974, 1978; Rubin 2000;

Stigler 1961). First, EOI distinguishes between products

in terms of when consumers can evaluate their critical

characteristics: before purchase for so-called search prod-

ucts and after product purchase and use for so-called expe-

rience products. Second, EOI suggests that consumers

will be most skeptical of information that is the most diffi-

cult and costly to evaluate prior to purchase. Therefore,

consumers may be more skeptical of ad claims involving

experience products than search products. Finally, EOI

suggests a relationship between buyers and sellers such

that sellers, understanding buyers’ beliefs regarding the

Journal of the Academy of Marketing Science.

Volume 32, No. 1, pages 20-31.

DOI: 10.1177/0092070303257856

Copyright © 2004 by Academy of Marketing Science.

nature of information across product types, will provide

information in a manner consistent with those beliefs.

The policy implications of EOI rely on a correspon-

dence between beliefs and perceptions (e.g., skepticism)

on one hand and behavior (e.g., information provision and

usage) on the other. However, there is considerable debate

about the role of advertising information among both aca-

demics and practitioners. One view suggests that more

information is generally desirable and of interest to con-

sumers to the extent that it does not create information

overload (e.g., Abernethy and Franke 1996, 1998; Ogilvy

1961). An alternative view advocates a considerably more

selective and limited approach to information provision

(e.g., Bloom and Pailin 1995; Ziamou and Ratneshwar

2002). The first major objective of this study is to examine

the possibility, consistent with EOI, that both views may

be valid depending on the characteristics of the advertised

product. Specifically, we investigate the relationship

between advertising information and readership across

product types, predicting that greater information provi-

sion may, in some cases, actually reduce information

utilization by consumers as reflected in ad readership.

The second major objective of this study is to investi-

gate whether information provision in print ads (seller

side) corresponds to information utilization (buyer side).

EOI presumes that market mechanisms (primarily, with-

holding of purchases on the part of the consumer) align the

informational exchange of buyers and sellers. Relatively

little research has searched for evidence of such an align-

ment, and the information measures used have not been

very sensitive (Liebermann and Flint-Goor 1996; Norton

and Norton 1988).

We address the core research themes of our study using

a sample of more than 400 print ads from nine relatively

recent U.S. magazines. Information utilization is mea-

sured using Starch readership scores, which have been

demonstrated in prior research to reflect the nature and

extent of processing in naturalistic exposure conditions

(e.g., Finn 1988). Information content is measured using

an adaptation of previous content-analysis coding

approaches (Resnik and Stern 1977; Taylor, Miracle, and

Wilson 1997), expanded to capture total information con-

tent rather than simply counting instances of information

types.

BACKGROUND AND HYPOTHESES

Stigler’s (1961) seminal work on “The Economics of

Information” examined advertising’s role in reducing con-

sumers’ search costs. Search costs include the time and

effort associated with obtaining and processing informa-

tion, while search benefits include lower price and/or

higher quality. A fundamental concept of EOI is that ratio-

nal consumers continue to search for and process

information only to the point where the marginal benefits

of doing so outweigh the marginal costs. Thus, a rational

consumer will not necessarily process all available

advertising information.

Stigler (1961) focused primarily on advertising as a

source of price information, where the perceived benefits

of searching for and processing ads with such information

would vary as a function of various factors including price

variability in the marketplace. Nelson (1970, 1974, 1978)

broadened EOI to include advertising as a source of infor-

mation about product qualities in general, where the bene-

fits of finding and processing such ads could vary as a

function of the type of product or attribute being adver-

tised. Nelson’s analysis focused on consumers’ ability to

verify advertisers’ claims prior to product purchase, how

this ability varies across product types, and how advertis-

ers react to this ability. A core distinction in Nelson’s work

is between search and experience attributes. Consumers

can detect false claims about search attributes, such as a

good’s appearance, by product inspection in the store—

trying on clothing, sitting on furniture, handling a toy, and

so forth. Therefore, advertisers would have no reason to

make false claims about search attributes because they

would not influence sales. Experience attributes—the ser-

vice and food in a restaurant, the comfort of a car on long

trips, the efficacy of a drug—normally require product

purchase to evaluate. Therefore, consumers should be

skeptical about advertising claims for experience attrib-

utes, because if those claims were believed, “advertisers

would have an incentive to extol the virtues of their brand

whether or not those virtues exist. As a result, the advertis-

ing message for experience qualities can contain little

information that is believable” (Nelson 1978:133).

Darby and Karni (1973) extended Nelson’s (1970)

framework to include credence attributes, such as the vita-

min content of foods, which cannot normally be evaluated

even after product purchase. However, other research has

suggested that there may not be much difference in

response to credence and experience attributes during

information search because neither can be evaluated prior

to purchase (e.g., Ford et al. 1990).

Information Utilization: DifferentialEffects Across Product Types

Although distinguishing between search and experi-

ence attributes is appropriate for some research purposes,

it is often more useful or feasible to examine the implica-

tions of EOI for search and experience products. Nelson

(1970, 1974) demonstrated that products can be classified

as to whether they predominantly consist of search attrib-

utes (i.e., search products) or experience attributes (i.e.,

experience products). Search products are goods or ser-

vices for which the most essential attributes can easily be

evaluated prior to purchase. Thus, for search products,

Franke et al. / INFORMATION CONTENT OF ADS 21

consumers can gather sufficient information during search

to make an informed buying decision and choose the brand

that best satisfies their wants and needs. Because consum-

ers can verify claims prior to purchase, they should pos-

sess the least skepticism toward claims for search prod-

ucts. Experience products are goods and services for

which the cost to evaluate the most essential attributes is so

high that direct experience is often the evaluation method

with the lowest costs in terms of time, money, cognitive

effort, or other resources. Because of the difficulty

involved in evaluating claims for experience products,

consumers will be more skeptical of claims for experience

products in comparison with search products (e.g., Ford

et al. 1990; Mitra, Reiss, and Capella 1999; Nelson 1970,

1974; Wright and Lynch 1995).

Because an experience product must be bought to be

evaluated, and greater purchase frequency gives consum-

ers more opportunities to compare alternatives, Nelson

(1970, 1974) distinguished between types of experience

goods based on their purchase frequency. (Nelson consid-

ered this distinction to be far less important for search

products, which may be inspected prior to purchase.) For

simplicity, Nelson referred to goods purchased frequently

(e.g., weekly or monthly) as experience nondurables and

goods purchased infrequently as experience durables.

Because these terms do not apply to services (which Nel-

son did not examine), we use the alternatives convenience

products and shopping products. In addition to being fre-

quently purchased, convenience products tend to be inex-

pensive, widely available, purchased with little effort, and

consumed in a short time. Shopping products tend to be

more expensive, durable, selectively distributed, and

prone to significant service or repair costs, and they are

evaluated in more depth before purchase. Because shop-

ping products are purchased infrequently, consumers gen-

erally have less information from personal experience on

which to draw. Shopping products may also present

greater performance, financial, safety, social, or

psychological risk (Andersen 1994; Mixon 1999; Nelson

1970, 1974; Norton and Norton 1988).

Friends, family, consumer magazines, and other

sources may serve as supplemental sources of information

and provide a partial surrogate for personal experience in

verifying ad claims. Nelson (1970, 1974) predicted that

such “guided sampling” will be greater for experience

shopping products than experience convenience products,

due to the relative costs of making a bad purchase decision.

In general, though, while search attributes may be effec-

tively communicated in advertising, experience is (by def-

inition) the best means of learning about experience attrib-

utes. Wright and Lynch (1995) showed that consumers

pay more attention to information about product attributes

when it is “media-congruent.” Advertising information is

more congruent with search products than experience

products, suggesting a greater effect of information on

readership for search products than for experience prod-

ucts. Furthermore, the greater availability of guided

sampling as a means of checking claims for shopping

products suggests stronger congruency and advertising

effects than found with convenience products.

Another relevant advertising characteristic is message

credibility. Credible information may improve purchase

decisions and should therefore enhance readership, but if

consumers are skeptical of information, they are likely to

feel the effort required to digest the ad does not have com-

mensurate benefits. For example, Heesacker, Petty, and

Cacioppo (1983) found that a highly credible information

source often leads to greater message elaboration than

does a less credible source. Credibility should be highest

for advertising information about search products because

claims can be evaluated prior to product purchase. Con-

versely, skepticism should be highest for advertising infor-

mation about convenience products. These products are

often relatively inexpensive, so consumers have little to

lose from product sampling. For shopping products,

guided sampling may provide a partial check on the truth-

fulness of advertising claims (Nelson 1970, 1974). Thus,

skepticism of advertising claims for shopping experience

products should be between these extremes, as found by

Ford et al. (1990).

Nelson (1974) argued that the crucial determinant of ad

readership is the ad’s value to the consumer relative to the

cost in time and effort taken to read the ad. Media congru-

ency and the verifiability of claims prior to purchase,

which increases message credibility, suggest that the value

of ad information should be highest for search products.

The value of information should be lowest in ads for con-

venience products, due to the lack of media congruency

and higher consumer skepticism toward claims that cannot

be verified prepurchase. The value of ad information for

shopping products should be between the two extremes

because guided sampling can indirectly verify claims to

some degree. Such secondary evidence should enhance

media congruency and message credibility. Thus, differ-

ences in the value of ad information to consumers across

product categories suggest the following hypothesis:

Hypothesis 1: The relationship between informationcontent and readership of advertisements will bepositive for search products, negative for conve-nience products, and intermediate for shoppingproducts.

Information Provision: DifferentialEffects Across Product Types

Hypothesis 1 predicts effects on the buyer’s side of the

informational interplay, which has implications for the

provision of information by sellers. Sellers supposedly

understand and respond to the asymmetry in the amount of

22 JOURNAL OF THE ACADEMY OF MARKETING SCIENCE WINTER 2004

information desired by buyers’across EOI product catego-

ries (e.g., Calfee and Ford 1988; Nelson 1970, 1974;

Rubin 2000). If consumers are more likely to rely on

advertising as a source of information about search prod-

ucts, then advertisers should be motivated to include more

information in ads for search products than ads for experi-

ence products. Furthermore, if guided sampling helps ver-

ify the credibility of ad claims as discussed above, adver-

tising information should be more effective, and therefore

plentiful, for shopping products than for convenience

products.

Using Resnik and Stern’s (1977) measure of informa-

tion content and Nelson’s (1974) examples of product

classifications, Norton and Norton (1988) found the high-

est information levels in ads for experience durables. Simi-

larly, in a sample of ads from Israeli publications,

Liebermann and Flint-Goor (1996) found the greatest use

of rational appeals in ads for durable goods. Both studies’

measures of advertising information are relatively coarse:

Resnik and Stern’s (1977) approach counts types rather

than amounts of information, and Liebermann and Flint-

Goor’s (1996) measure is an index of the relative use of ra-

tional versus emotional appeals. Therefore, these results

do not necessarily provide clear evidence on sellers’ deci-

sions about the use of advertising information. Consistent

with the EOI logic that sellers will provide the amount of

information that is likely to have the greatest effect on

buyers’ purchase behavior, we propose the following

hypothesis:

Hypothesis 2: The information content of advertisingwill be highest for search products, lowest for con-venience products, and intermediate for shoppingproducts.

METHOD

Sample and Readership Measure

To test the hypotheses, a sample of ads was taken from

nine magazines published from March through December

1996: Bon Appetit, Business Week, Country Living, Ebony,

Glamour, Men’s Journal, Newsweek, Parents, and Sports

Illustrated. These magazines were provided by Roper

Starch Worldwide, a professional research service that

measures readership of print ads and whose “Starch read-

ership scores” have been used in many previous studies in

the marketing literature (e.g., Fletcher and Winn 1974;

Hanssens and Weitz 1980; Holbrook and Lehmann 1980;

Zinkhan and Gelb 1986; for a review, see Finn 1988). The

company derives readership figures for ads in a particular

issue from interviews with 100 to 200 of the magazine’s

readers. Using a rotating starting position, interviewers go

through the publication and ask if the reader “noted” the

ad, “associated” it with the advertised brand, and “read

most” (at least half) of the ad copy. The Starch scores for a

particular ad are the proportions of magazine readers that

respond positively to each of these questions.

Other Measures

The other measures used to test the hypotheses were

obtained through a content analysis of the ads in the sam-

ple. The key variables were the amount of information in

each ad and the type of product being advertised. Three

secondary variables were used to control for ad character-

istics that could be confounded with the amount of infor-

mation: ad length, visual size, and amount of copy.

Information content. A widely used measure of the in-

formation content of advertising uses judges to record

which of 14 information types or “cues” are found in the

ad: price/value, quality, performance, components/con-

tents, availability, special offers, taste, nutrition, packag-

ing, warranties, safety, independent research, company

research, and new ideas (Resnik and Stern 1977). This ap-

proach provides a conservative measure of advertising in-

formation because it ignores other types of cues that may

be present and does not give any weight to repeated in-

stances of a particular cue type within an ad (Abernethy

and Franke 1996). A recent expansion of the Resnik-Stern

typology addresses the first of these limitations by using a

total of 30 cues, including Resnik and Stern’s 14 cues plus

others involving method of payment, sensory information

(other than taste), users’ satisfaction/loyalty, superiority

claims, new or improved features, dependability, conve-

nience in use, appropriate use occasions, users’ character-

istics, and company information (Taylor et al. 1997). To

overcome the second limitation, we recorded each in-

stance of any of the 30 types of information in an ad, rather

than simply counting which information cue types are

present. This approach gives a more sensitive and accurate

indicator of information content than previous

information content measures.

Product categories. Following Nelson (1974), al-

though with a change in terminology, we focus on infor-

mation differences between convenience, shopping, and

search products. As in earlier studies (e.g., Liebermann

and Flint-Goor 1996; Norton and Norton 1988), we do not

distinguish between convenience and shopping for search

products because both can be evaluated prior to purchase.

We also do not treat credence products as a separate cate-

gory because, like experience products, they cannot nor-

mally be evaluated prior to product purchase. In addition,

past research suggests that there may not be large differ-

ences in responses to advertising claims between experi-

ence and credence product categories (e.g., Ford et al.

1990).

Franke et al. / INFORMATION CONTENT OF ADS 23

A search product is one “that consumers can evaluate

effectively before actually making a purchase. Such a

product is high in search properties: it has many attributes

that can be readily searched out and assessed prior to hav-

ing to make a purchase decision” (Bloom and Reve

1990:61). Conversely, an experience

product is one that consumers can evaluate effec-tively only after they have bought it. Such a productis high in experience properties: it has many attrib-utes that can only be discovered and evaluated by ac-tually trying and using the product. (Bloom andReve 1990:61)

Experience products are further classified as shopping or

convenience products. As described previously, compared

with convenience products, shopping products tend to be

higher in price, durability, service and repair costs, per-

ceived risk, and prepurchase evaluation, and are distrib-

uted more selectively.

Nelson’s (1974) examples of search products include

clothing, jewelry, and furniture. Shopping products that he

evaluated include books, paints, appliances, and vehicles,

and his list of convenience products includes foods, drugs,

tobacco products, and soaps. Additional product classifi-

cations, including services and various goods that did not

exist in 1974, can be found in sources such as Iacobucci

(1992), Jourdan (2001), Liebermann and Flint-Goor

(1996), Mitra et al. (1999), Mixon (1999), Moorthi

(2002), and Zeithaml (1981).

Following extensive review and discussion of the litera-

ture, we developed a consensus classification of product

types as shown in Table 1. Products were classified based

on whether experience or search dominates in the selec-

tion process for typical consumers, rather than those with

special training or experience (e.g., for an automobile

mechanic, car repairs may be a search service rather than

an experience or credence service; cf. Bloom and Reve

1990). This approach resulted in a change in one of Nel-

son’s original classifications. Nelson (1974) treated per-

fume as an experience product even though it can gener-

ally be tried at the store before purchase. Men’s and

women’s fragrances were therefore treated as search prod-

ucts. An example of shopping products is computers,

which are infrequently purchased durables with poten-

tially significant repair costs and which have many fea-

tures that cannot be evaluated based on test reports or in-

store trial—compatibility with existing software and hard-

ware, reliability, quality of technical support, and so on.

Examples of convenience products are pantyhose, which

unlike many kinds of clothing cannot be tried on before

purchase, and consumer long-distance phone service,

which can be obtained with little risk or expense. Most

other advertised services in the sample involved

important, long-term commitments or higher degrees of

risk and were therefore treated as shopping products.1

As a reliability check, a doctoral student familiar with

Nelson’s work provided an independent product classifi-

cation. The results showed 93 percent agreement on prod-

uct categories. Because the sample included very few ads

in the disputed classifications (e.g., baby carriers, Christ-

mas tree stands, and games), agreement on the assignment

of ads to categories exceeded 99 percent.

Other measures. Ad length, visual size, and copy

length may covary with information content and have been

found in several studies to influence attention and reader-

ship (Finn 1988). To control for possible spurious effects,

these ad characteristics were also measured. Ad length

24 JOURNAL OF THE ACADEMY OF MARKETING SCIENCE WINTER 2004

TABLE 1Product Classification Scheme

Search products

Clothing and accessories (e.g., hats, jewelry, and footwear)

Fragrancea

(perfumes and colognes)

Carpeting, floor covering, and furniture

Housewares (e.g., window coverings, bed sheets and comforters,

china, glassware, and cutlery)

Toysa

Greeting cardsa

Experience shopping products

Vehicle related (cars and car parts, car repair,a

heavy equipment,a

tires)

Professional and scientific instruments (e.g., global positioning

satellite units,a

computer hardware and software,a

data storage

devices,a

computer chips,a

photocopy machines,a

binocularsa)

Communications and entertainment (e.g., home electronics,a

prerecorded videotapesa

and CDs,a

satellite TVa)

Appliances, clocks and watches, cameras and photography supplies,

camcorders,a

electric shaversa

Paints and stains, windowsa

Major services (major medical and health care,a

professional

services,a

human resource services,a

manufacturing,a

trucking

and distribution services,a

computer-related services,a

business

telephone services,a

insurance,a

investments,a

credit cards and

credit-related services,a

airline travel,a

hotels,a

vacation spotsa)

Miscellaneous (baby carriers and strollers,a

Christmas tree stands,a

golf clubs,a

gamesa)

Experience convenience products

Groceries (e.g., food, alcoholic and nonalcoholic beverages, pet

food and care,a

aluminum foila

and plastic wrap,a

soap and clean-

ing supplies, diapers, disposable batteries)

Drugs and toiletries (e.g., over-the-counter and prescription drugs,

home pregnancy tests,a

antacids,a

cosmetics,a

skin and hair care,a

tissues, razorsa)

Tobacco products

Miscellaneous convenience products (e.g., weed killer,a

cigarette

lighters,a

baby bottle liners,a

pantyhosea)

Miscellaneous convenience services (e.g., home telephone service,a

motion pictures and TV showsa)

a. Item is an addition to or (for fragrances) a modification of the classifi-cations in Nelson (1974:739).

was classified as less than one page, one page, or more than

one page. The proportion of the ad taken up by photo-

graphs or other graphic material was rated on a 7-point

scale, from minimal visual material (mainly text and/or

blank space) to predominant visual material. Copy length

was also rated on a 7-point scale, from minimal copy to ex-

tensive copy. This approach was meant to reflect the natu-

ral reading experience, where subjective perceptions of

visuals and copy are likely to influence responses to the ad

more than the precise proportion of the ad devoted to

illustrations or the exact number of words.

Data Coding

Two undergraduates were trained to code each instance

of information, and one of the authors served as a third

judge. Because the Starch scores are the key variables for

hypothesis tests, codings were based on copies of the ads

with the Starch scores blanked out. In this way, none of the

coders could consciously or unconsciously bias the

results. Agreement between each pair of judges on the

total amount of information in the ads was very good, with

correlations of .938, .943, and .951.

Two additional undergraduate judges coded ad length,

agreeing on 98 percent of the classifications. Because this

assessment involves minimal judgment and the coding

disagreements simply reflected recording errors, the cor-

rected value was treated as a single error-free measure in

the data analysis.

Two trained graduate students and the same author as

before rated the amount of copy in the ads and the domi-

nance of their visual elements on 1 to 7 scales. As in the

evaluation of information levels, the readership scores

were disguised to preclude biasing effects. Reliability was

again good, with correlations between judges ranging

from .870 to .906 for copy and .860 to .907 for visuals.

Data Analysis

Hypothesis 1 was tested using LISREL 8.52 to analyze

a multigroup structural equation model. The focal inde-

pendent variable was the amount of information in the ad.

Ad length, visual size, and copy length were included as

predictors when significant. One dependent variable,

attention to the ad, was treated as a composite of the Starch

noted and associated scores. These scores are highly corre-

lated (r ≥ .93 across product types) and are conceptually

related because noted scores reflect attention to the ad as a

whole and associated scores indicate that attention was

paid to the part(s) of the ad identifying the brand or spon-

sor. Attention, information, and other ad characteristics as

appropriate were treated as predictors of the focal depend-

ent variable, ad readership. Readership had a single indica-

tor, the Starch read most scores. The structural model

tested for direct effects of information on attention and

readership. Because part of the influence of advertising on

readership may be mediated by its influence on attention,

the key test of Hypothesis 1 is the total effect of

information on readership—the sum of its direct and

indirect effects.

Correct results in multigroup analyses require that

covariance matrices be used rather than correlation matri-

ces and that one indicator of each construct be given a

loading of 1 rather than standardizing the latent variables.

The result is that the unstandardized measurement and

structural model coefficients are comparable across

groups and can be interpreted relative to the scales of the

chosen marker variables having loadings set to 1. The

structural coefficients were free to differ across the three

product types. Constraining the measurement models to

be equal across groups had no effect on the hypothesis test

findings compared to a model allowing for partial mea-

surement invariance (Steenkamp and Baumgartner 1998),

so results are shown with the constrained model for

parsimony and simplicity of presentation.

Ads with missing Starch scores for attention or reader-

ship were omitted from the LISREL analysis. Because

Starch scores are not needed for the test of Hypothesis 2,

the available sample size is larger than in the test for

Hypothesis 1. Hypothesis 2 was tested with a one-way

analysis of variance of advertising information across

product types, followed by pairwise t-tests controlling the

Type I comparison-wise error rate between each combina-

tion of product types.

RESULTS

Although the ratings of visual size and copy length

showed high reliability across judges, one judge’s codings

had to be omitted from the analyses due to significant

cross-loadings with other predictors in the structural

model. Therefore, the measurement model included three

indicators of information levels; two indicators of copy

length, visual size, and attention; and one indicator of ad

length and readership. For the test of Hypothesis 1, 444

ads were available: 154 for convenience products, 211 for

shopping products, and 79 for search products. Corre-

sponding figures for the test of Hypothesis 2 were 170,

213, and 101, for a total of 484. Correlations, means, and

standard deviations of the variables for the three product

types are shown in Table 2.

Hypothesis 1

The measurement and structural parameters were esti-

mated simultaneously, but for clarity of presentation, the

measurement model results are shown in Table 3, and the

structural model results are shown in Table 4. The loadings

in Table 3 are large and highly significant (all t‘s > 26.0),

Franke et al. / INFORMATION CONTENT OF ADS 25

reflecting the high coding reliability across judges. Con-

straining the loadings equal across products does not con-

strain the average variance extracted (AVE), which may

vary due to differing construct variances across products.

The lowest AVE is .79, suggestive of high coding reliabil-

ity and well above the conventional standard of .50

(Bagozzi and Yi 1988). The overall model also shows

acceptable fit to the data, with a Comparative Fit Index of

.97, a Non-Normed Fit Index of .96, a root mean square

error of approximation of .079, and a standardized root

mean square residual of .05 or below for all three product

types.2

In the structural model, attention to the ad has a signifi-

cant positive effect on ad readership for all three product

types. Therefore, the ad characteristics’ influence on read-

ership may be direct, mediated by their effect on attention,

or both.

As predicted in Hypothesis 1, the total effect of infor-

mation on ad readership is significantly positive (t = 2.42)

in ads for search products, significantly negative (t = –2.55)

in ads for convenience products, and intermediate (t = .93)

in ads for shopping products. The direct effect of informa-

tion on readership follows a similar pattern, with a positive

coefficient for search products (t = 1.73), a negative coeffi-

cient for convenience products (t = –3.58), and a negligible

coefficient (t = –.12) for shopping products. The pattern is

more varied for the influence of information on attention.

Information has positive effects on attention for search

products and shopping products (t = 2.12 and 1.86, respec-

tively), but little influence in ads for convenience products

(t = –.23).

The other significant ad characteristics have consistent

signs but different magnitudes across the product types. In

all three product categories, ad length and visual size

increase attention to the ad, and longer copy reduces read-

ership. The negative effect of copy length on readership is

direct for search products, mediated by attention for con-

venience products, and both direct and mediated for

26 JOURNAL OF THE ACADEMY OF MARKETING SCIENCE WINTER 2004

TABLE 2Correlations, Means, and Standard Deviations

Starch Starch Starch

Variable Noted Associated Read Most Information Ad Length Visual Size Copy Length

Convenience products (n = 154)

Starch noted 1.00

Starch associated .96 1.00

Starch read most .67 .69 1.00

Information –.19 –.25 –.36 1.00

Ad length .33 .29 .05 .21 1.00

Visual size .49 .45 .34 –.16 .05 1.00

Copy length –.38 –.43 –.45 .64 .03 –.34 1.00

M 53.59 48.31 21.35 8.93 1.10 4.99 3.45

SD 11.38 12.12 9.69 5.61 0.50 1.30 1.12

Shopping products (n = 211)

Starch noted 1.00

Starch associated .93 1.00

Starch read most .57 .56 1.00

Information –.03 –.02 –.26 1.00

Ad length .32 .25 –.06 .15 1.00

Visual size .52 .42 .28 –.17 .11 1.00

Copy length –.25 –.21 –.50 .56 .15 –.34 1.00

M 48.11 41.61 16.28 11.59 1.21 4.27 4.43

SD 10.23 10.11 6.92 7.70 0.57 1.52 1.24

Search products (n = 79)

Starch noted 1.00

Starch associated .93 1.00

Starch read most .38 .35 1.00

Information .27 .29 –.09 1.00

Ad length .36 .23 .09 .29 1.00

Visual size .30 .21 .49 –.04 .24 1.00

Copy length –.01 .01 –.60 .47 .12 –.43 1.00

M 58.56 52.44 23.41 10.80 1.27 5.32 3.45

SD 11.57 12.65 8.91 12.54 0.50 1.10 1.34

NOTE: Information, visual size, and copy length are averaged values of the individual indicators used in the LISREL analysis.

shopping products. Ad length has a negative direct effect

on readership for experience products but not for search

products. Visual size increases readership in all three cate-

gories, but the effect is due to longer visuals’ effect on

attention rather than a direct effect on readership.

Hypothesis 2

Hypothesis 2 proposes that information levels will be

highest in ads for search products, second highest in ads

for shopping products, and lowest in ads for convenience

Franke et al. / INFORMATION CONTENT OF ADS 27

TABLE 3Measurement Model

AVE

Variable Measure Loading Convenience Shopping Search

Information (number of cues) .79 .88 .95

Coder 1 1.00

Coder 2 .92

Coder 3 .87

Ad length (< 1, 1, > 1 page) Coders 4 and 5 1.00 1.00 1.00 1.00

Visual size (1-7 scale) .89 .92 .86

Coder 2 1.00

Coder 6 .97

Copy length (1-7 scale) .82 .86 .88

Coder 2 1.00

Coder 6 .90

Attention .95 .95 .94

Starch noted 1.00

Starch associated .98

Readership Starch read most 1.00 1.00 1.00 1.00

NOTE: AVE is average variance extracted, an indicator of coding reliability. Loadings of 1.00 are fixed parameters. Coder numbers identify distinct judges(e.g., Coder 2 rated information content, visual size, and copy length; Coders 1 and 3 rated just information content). Because coding ad length involves lit-tle judgment, the corrected classifications of Coders 4 and 5 were treated as an error-free measure. The loadings are constrained equal across product typesand are all significant (t > 26.0).

TABLE 4Structural Model

Direct Effect on Attention Direct Effect on Readership Total Effect on Readership

Type of Product Predictor Coefficient t-Statistic Coefficient t-Statistic Coefficient t-Statistic

Convenience products Information –.05 –0.23 –.37 –3.58 –.40a

–2.55

Ad length .75 5.03 –.24 –2.02 .18 1.32

Visual size .35 5.47 — .20 4.87

Copy length –.26 –2.37 — –.15 –2.30

Attention .57 10.66 .57 10.66

Variance explained .41 .53

Shopping products Information .17 1.86 –.01 –0.12 .06a

0.93

Ad length .50 4.87 –.19 –2.84 .02 0.21

Visual size .30 7.17 –.07 –2.46 .05 1.72

Copy length –.19 –2.87 –.22 –5.33 –.29 –6.09

Attention .40 9.26 .40 9.26

Variance explained .38 .51

Search products Information .20 2.12 .12 1.73 .16a

2.42

Ad length .51 2.01 — .13 1.78

Visual size .30 2.63 — .08 2.18

Copy length — –.45 –7.03 –.45 –7.03

Attention .25 3.85 .25 3.85

Variance explained .23 .53

NOTE: Coefficients are not standardized. Effects of ad characteristics other than information content are included only if significant. For the measurement

model (Table 3) and structural model together, χ2= 253.83 with 126 df; root mean square error of approximation = .079; Non-Normed Fit Index = .96; Com-

parative Fit Index = .97; and standardized root mean square residual = .041, .050, and .047 for convenience products, shopping products, and search prod-ucts, respectively. Reduced-form R

2’s for readership, which do not include variance explained by attention, are .27, .29, and .45.

a. Coefficient used to test Hypothesis 1.

products. As shown in Table 5, the information means par-

tially match the expected pattern. As predicted, the least

information (M = 8.3 cues) is found in ads for convenience

products. However, the most information cues (M = 11.5)

are found in ads for shopping products rather than in ads

for search products (M = 9.1 information cues). One-way

analysis of variance shows that the differerences in means

are significant, F(2, 481) = 7.80, p < .001. Pairwise t-tests

show that information levels in ads for convenience prod-

ucts and search products are both significantly (p < .02)

lower than in ads for shopping products, but the difference

between convenience and search products is not signifi-

cant (p > .40).

DISCUSSION

Implications

This study examines the informational interplay

between buyers and sellers on the basis of the theoretical

underpinnings of EOI. Consistent with EOI theory, the

results suggest that buyers differ in the marginal value they

assign to advertising information across convenience,

shopping, and search product categories. The results are

less consistent with the theoretical implication that sellers

respond to buyers’ information preferences by providing

more or less advertising information across product types

as appropriate.

There is an extensive literature on factors affecting

print ad readership, but few studies have specifically

focused on advertising information (see Finn 1988 for a

review). Consistent with the present study’s findings, one

earlier study showed a negative effect of information

(“number of product facts”) on readership of ads for a con-

venience product, foods (Fletcher and Winn 1974). Inter-

estingly, Twedt (1952) found that the numbers of product

facts and benefits were positively correlated with reader-

ship scores in a study of American Builder ads. Possibly

the magazine’s readers had special expertise, such that the

advertised products were largely search products from

their perspective. If so, Twedt’s findings are also consis-

tent with the present results. However, no previous studies

that compared advertising information and readership

across product types distinguished between search and

experience products or between convenience and shop-

ping products. Also, past research focused more on the

effects of advertising copy than information. As shown in

Table 4, copy length and advertising information can have

very different effects on readership, depending on the type

of product being advertised.

The EOI and the structural model results suggest that

marketers should put the most information in ads for

search products and the least in ads for convenience prod-

ucts. The findings show that average information levels in

ads for shopping products exceed those for convenience

products, as expected, but also exceed those for search

products, contrary to expectations. Similar findings have

been reported in past research based on alternative mea-

sures of information content (Liebermann and Flint-Goor

1996; Norton and Norton 1988). Therefore, the evidence

is consistent with the EOI logic that ads for shopping prod-

ucts should have more information than ads for conve-

nience products. Shopping products often involve high

economic risks to consumers, so guided sampling and the

potential legal risks to marketers of making false claims in

ads may enhance the credibility, usefulness, and reader-

ship of advertising information for shopping products rel-

ative to convenience products. Given the positive effects of

information on readership in ads for search products, the

lower information levels in the category suggest that mar-

keters may be underinforming consumers. Friestad and

Wright (1994) suggested that asymmetries between buy-

ers’ and sellers’ knowledge of the others’ persuasion

knowledge are continually evolving. If further research

helps to substantiate consumers’ responses to information

in ads for search products, buyers may be found to adjust

their information provision strategies accordingly over

time.

The results for the buyers’ side of the informational

interplay have important implications for critics of adver-

tising, who generally feel that more information is better

(see Pollay 1986). In contrast, our findings indicate that

information increases readership of ads on average only

for search products and actually reduces readership of ads

for convenience products. This pattern supports Calfee

and Ringold’s (1994) conclusion, based on six decades of

survey data, that policy makers should not assume that

consumers are naturally inclined to believe and rely on

advertising claims. Regulatory efforts to increase the qual-

ity and amount of information in advertising appear not to

have the desired effect on advertisers (Abernethy and

Franke 1998), but even if policy makers succeeded in

changing advertising content, the current findings suggest

that consumers often may not read the information as

intended.

Information levels in an ad are easy to increase or

decrease, subject only to government- or media-required

28 JOURNAL OF THE ACADEMY OF MARKETING SCIENCE WINTER 2004

TABLE 5Information Levels by Product Type

Product Type M SD N

Convenience 8.30a

5.70 170

Shopping 11.49b

7.74 213

Search 9.15a

11.66 101

NOTE: The means differ significantly overall, F(2, 481) = 7.80, p < .001.Pairwise t-tests controlling the Type I comparison-wise error rate showthat means with different superscripts differ significantly (p < .02),whereas means with the same superscript do not (p > .40).

disclosure requirements. With many major magazines

charging more than $100,000 to run a one-page ad, even

modest influences on readership may have practical rele-

vance. Therefore, marketers should consider the potential

costs and benefits of each bit of information included in an

ad. Conversely, regulators should recognize that the effect

of government-mandated disclosures for a convenience

product may be lessened by putting them in the context of

many other information cues. Of course, it is important not

to overgeneralize the role of advertising information from

these findings. The positive effects of information in ads

for search goods are countered by negative effects of long

copy. Concise, interesting information is likely to have

more impact on readership than the same information bur-

ied in verbiage. Furthermore, if the audience is not moti-

vated or able to process the message in detail, dual-process

models of persuasion suggest that peripheral or heuristic

processing of ads may take place (e.g., Chaiken,

Lieberman, and Eagly 1989; Petty and Cacioppo 1986).

Informative ads with long copy could evoke a length-

strength heuristic, resulting in persuasion without close

reading or processing of the ad. Consistent with this idea,

noted copywriter David Ogilvy (1983) concluded that

“advertisements with long copy convey the impression

that you have something important to say, whether people

read the copy or not” (p. 88).

Limitations and Research Directions

The use of Starch scores is both a strength and a weak-

ness of this study. Using Starch scores enhances

generalizability because the readership measures studied

are based on the general public’s natural exposure to hun-

dreds of professionally created ads for a wide variety of

products and brands. However, Starch scores cannot

establish whether the differential effects of information

across EOI product categories are due to greater credibility

of ad claims that can be verified prior to purchase, as pre-

supposed here, or to some other effect. Laboratory studies

are better for testing the processes involved in responding

to advertising information (e.g., Ford et al. 1990; Wright

and Lynch 1995). For example, laboratory research would

allow control of individual differences in product involve-

ment or expertise, which may moderate responses to infor-

mation or determine whether a product predominantly

involves search or experience attributes. Controlled exper-

iments could also reveal effects of information on addi-

tional response measures, such as attitude toward the ad or

brand and purchase intentions.

Even though we used a reasonably large sample of

more than 400 ads, collecting a larger sample of ads would

allow finer distinctions between product categories. It

would also increase power to detect smaller effects, such

as a direct effect of information on readership for search

products ads. However, coding information content and

other ad characteristics is both arduous and time-consum-

ing. A stratified sampling approach designed to obtain

more ads for search products would improve efficiency.

Examining the effects of information across product

types in other media would be a useful extension of this

study. Syndicated data on television commercial effec-

tiveness could be used to compare responses to informa-

tion across EOI product categories (cf. Stewart and Kos-

low 1989). Buyers’ use of sites for search-oriented and

experience-oriented products on the World Wide Web or

click-through rates in response to information in banner

ads for such sites also merit investigation (cf. Klein 1998).

Some evidence suggests that information provision in

telephone directory advertising, as reflected in the use of

display ads, is consistent with predictions from EOI (e.g.,

Mixon 1999). Shoppers also appear to respond positively

to information in the Yellow Pages (Fernandez and Rosen

2000). However, potential moderating effects of product

types on consumer responses to directory information do

not appear to have been studied.

CONCLUSION

Empirical research in marketing on EOI has largely

focused on individual experience and search attributes

(e.g., Ford et al. 1990; Smith 1990; Wright and Lynch

1995). The current study gives an illustration of certain

EOI propositions being supported at the overall product

level. This demonstration is useful because implications

of EOI have often been drawn at the level of products

rather than attributes in areas such as policy (Bloom 1989;

Rubin 2000), branding (Moorthi 2002), and promotional

strategy (Bloom and Pailin 1995; Klein 1998; Liebermann

and Flint-Goor 1996).

Our findings suggest that advertisers should consider

putting more information on average in print ads for

search products because it tends to have a more positive

effect on ad readership than information in ads for experi-

ence products. Of course, this tendency is not a universal

law. Depending on the skill of the copywriter and the inter-

ests of the target audience, providing information may

help or hurt the success of an advertising campaign in any

product category. Ogilvy (1983), for example, described a

variety of successful campaigns for experience products in

which the ads contained hundreds or even thousands of

words. Infomercials are replete with information for prod-

ucts that cannot be experienced prior to purchase (Elliott

and Lockard 1996), and advertising information has also

been influential in affecting demand for such experience

products as foods and cigarettes (Calfee 1997).

Subject to this important caveat, this study provides a

useful extension of past research streams on the econom-

ics of advertising information and the information content

of advertising. Marketers, policy makers, and critics of

Franke et al. / INFORMATION CONTENT OF ADS 29

advertising should recognize that increasing information

levels do not always increase ad readership and in many

cases may reduce it.

ACKNOWLEDGMENTS

The authors gratefully acknowledge the assistance of

several students who coded advertisements, as well as the

helpful comments of Jack Calfee, former editor Rajan

Varadarajan, and the anonymous reviewers.

NOTES

1. The production and consumption of services are inseparable,

meaning that services cannot be inventoried and quality control is diffi-

cult to achieve (e.g., Zeithaml, Parasuraman, and Berry 1985). Therefore,

services cannot normally be evaluated before purchase in the same way as

tangible goods. However, to reflect the conceptual breadth of the search

category, and for consistent labeling of product types, the term search

product is used throughout the article, even though all search ads in the

sample were for goods rather than services.

2. One indicator of visual size for experience shopping products had a

small negative error term (–.006). Because constraining it to zero had no

effect on the results, it does not appear to be a cause for concern.

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ABOUT THE AUTHORS

George R. Franke (gfranke@cba.ua.edu) is a professor and

Reese Phifer Fellow of Marketing at the University of Alabama.

His Ph.D. is from the University of North Carolina. His research

interests include public policy, ethics, advertising, and research

methodology. His previous research on the information content

of advertising includes articles that received best-paper awards

from the Journal of Advertising and the Journal of Public Policy

& Marketing.

Bruce A. Huhmann (bhuhmann@nmsu.edu) is an assistant pro-

fessor of marketing at New Mexico State University. His Ph.D. is

from the University of Alabama. His research interests include

advertising, consumer behavior, and international marketing.

His primary stream of research focuses on verbal and visual ap-

peals in advertising. He has also coauthored a study on sources of

information used in consumer decision making. He has pub-

lished articles in the Journal of Consumer Research, the Journal

of Advertising, the Journal of Health Care Marketing, the Asia

Pacific Journal of Management, and in other journals and confer-

ence proceedings.

David L. Mothersbaugh (dmothers@cba.ua.edu) is an associ-

ate professor and Board of Visitors Research Fellow in market-

ing at the University of Alabama. His Ph.D. is from the

University of Pittsburgh. His research interests include advertis-

ing, rhetorical language, consumer knowledge, search and deci-

sion making, e-commerce, and services marketing. He has

publications in journals such as the Journal of Consumer Re-

search, the Journal of Retailing, the Journal of Business Re-

search, and the Journal of Consumer Affairs, as well as in various

conference proceedings.

Franke et al. / INFORMATION CONTENT OF ADS 31

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