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Part Six Monitoring, Evaluation, and Control
Belch: Advertising and
Promotion, Sixth Edition
Exhibit 19-5 Example of
a Starch-scored ad
VI. Monitoring, Evaluation,
and Control
19. Measuring the
Effectiveness of the
Promotional Program
© The McGraw−Hill
Companies, 2003
25,000 ads in more than 400 issues representing more than 100 consumer,
farm, and business magazines and newspapers per year and provides a
number of measures of the ad’s effectiveness. An example of a Starchscored
ad is shown in Exhibit 19-5.
Starch claims that (1) the pulling power of various aspects of the ad can
be assessed through the control offered, (2) the effectiveness of competitors’
ads can be compared through the norms provided, (3) alternative ad
executions can be tested, and (4) readership scores are a useful indication
of consumers’ involvement in the ad or campaign. (The theory is that a
reader must read and become involved in the ad before the ad can communicate.
To the degree that this readership can be shown, it is a direct indication
of effectiveness.)
Of these claims, perhaps the most valid is the ability to judge specific
aspects of the ad. Many researchers have criticized other aspects of the
Starch recognition method (as well as other recognition measures) on the
basis of problems of false claiming, interviewer sensitivities, and unreliable
scores:
1. False claiming. Research shows that in recognition tests, respondents
may claim to have seen an ad when they did not. False claims may be a
result of having seen similar ads elsewhere, expecting that such an ad
would appear in the medium, or wanting to please the questioner. Interest
in the product category also increases reporting of ad readership. Whether this false
claiming is deliberate or not, it leads to an overreporting of effectiveness. On the flip
side, factors such as interview fatigue may lead to an underreporting bias—that is,
respondents not reporting an ad they did see.
2. Interviewer sensitivities. Any time research involves interviewers, there is a potential
for bias. Respondents may want to impress the interviewer or fear looking
unknowledgeable if they continually claim not to recognize an ad. There may also be
variances associated with interviewer instructions, recordings, and so on, regardless
of the amount of training and sophistication involved.
3. Reliability of recognition scores. Starch admits that the reliability and validity of
its readership scores increase with the number of insertions tested, which essentially
means that to test just one ad on a single exposure may not produce valid or reliable
results.
In sum, despite critics, the Starch readership studies continue to dominate the
posttesting of print ads. The value provided by norms and the fact that multiple exposures
can improve reliability and validity may underlie the decisions to employ this
methodology.
Recall Tests There are several tests to measure recall of print ads. Perhaps the best
known of these are the Ipsos-ASI Next*Print test and the Gallup & Robinson Magazine
Impact Research Service (MIRS) (described in Figure 19-15). These recall tests
are similar to those discussed in the section on pretesting broadcast ads in that they
attempt to measure recall of specific ads.
In addition to having the same interviewer problems as recognition tests, recall tests
have other disadvantages. The reader’s degree of involvement with the product and/or
the distinctiveness of the appeals and visuals may lead to higher-than-accurate recall
scores, although in general the method may lead to lower levels of recall than actually
exist (an error the advertiser would be happy with). Critics contend the test is not
strong enough to reflect recall accurately, so many ads may score as less effective than
they really are, and advertisers may abandon or modify them needlessly.
On the plus side, it is thought that recall tests can assess the ad’s impact on memory.
Proponents of recall tests say the major concern is not the results themselves but
how they are interpreted. In one very interesting study of the effects of brand name
suggestiveness on recall, Kevin Keller, Susan Heckler, and Michael Houston found
that suggestive brand names (those that convey relevant attribute or benefit information
about the product) facilitate the initial recall of the brand’s benefits but inhibit