A Pioneering Experiment
in Assessing
Advertising Effectiveness
THOMAS E. COFFIN
According to this article,
there are only two basic
dimensions to the effectiveness of advertising: (I) size
of audience, and (2) depth
of impact.
The advertising industry
has been spending most of
its research dollars in measuring the audience component, with the result that
we can now measure this
dimension reasonably well.
Dr. Coffin believes it is now
time to spend more dollars
in assessing the dimension
of impact—for it is this
area which, for the future,
promises the greatest improvement in advertising
evaluation and sound media
comparisons.
there are only two basics. There are many variINantsadvertising,
of each, and many levels at which each can be described
and measured. But fundamentally these all reduce to two issues:
1. "How many peoj>le you reach"—audience size.
2. "How hard you hit them"—depth of impact.
These two basics apply whether the advertising in question
is a single advertisement, a campaign of advertisements, or a
medium of advertising.
True, there are many refinements and elaborations upon each.
Various qualifiers may be appended to the "how many" question.
For example, it may be decided that certain kinds of people are
more valuable to veach than others—this is "quality" of audience.
But this refinement is easily dealt with by differential weighting
in the audience counts. Heavy product users, for instance, can he
given more weight than light users or nonusers.
And the "how many" can be measured at various levels: circulation, readership, viewership, exposures, noting, sponsor identification, for example. Moreover, the measurement can he elahorated to include the frequency, the duplication, the cumulation,
the gross reach, and the net reach. But all such measures are
still asking basically, "How many?"
Obviously audience is the first dimension of advertising, and
much time and effort has been spent in improving the various
measures of it. But audience figures should be the starting point,
not the stopping point, in advertising measurement. Time and
effort now should he devoted to measurement of the second dimension, the depth-of-impact factor. Until both factors are included,
the advertising industry will continue to be without a proper
measure of the effectiveness of its product.
This is important for all advertising. Growing advertising
budgets are leading top management to press with increasing
urgency the question of advertising's effectiveness. And with the
advent of computers in the media-selection process, the practical
need is becoming more acute for input data on the impact as well
as the audience of media.
The industry tries to answer management's question by pointing
to how many the advertising has reached, of what quality, and with
what frequency. Likewise, this is the principal type of data thus
far at hand to feed into the computer. But in each instance
audience is only half the answer.
Three Historical Stages
Most people in the advertising business have been curiously
reluctant to "face up" to the second half of the question. This
has been evident both on the primary issue of measuring adver-
Journal of Marketing, July, 1963
tising effectiveness per se, and on the subordinate
question of measuring the comparative effectiveness
of different media. Looking back, the industry has
gone through three interesting stages;
Phase 1. For many years, tke accepted view was
to deny that it is possible to measure advertising effectiveness. Concerning advertising, per
se, the cliche was, "There are too many variables." Concerning the comparison of media,
"You can't compare apples and oranges; they
differ too much." But pressure from management continued, eventually leading to Phase 2.
Phase 2. Hesitant agreement that further measurement is needed. But with continued reluctance to address the "effectiveness" issue directly, the measurement became diverted into
amplifications of qualitative attributes: preoccupation with kinds of audiences, numbers of
exposures, reading days, page openings, frequency breakdowns, quintile analyses. This
was the diversionary phase, pursuing attractive
bypaths while avoiding the main issue.
Phase 3. The period of acquiescence. With pres-
sure from top management more intense and
with increasing concern over the "profit
squeeze"—plus the arrival of the computers,
generating additional pressures with their
appetite for explicit figures—industry opinion
is at last swinging toward an affirmative interest in the measurement of advertising effectiveness. Four recent publications have clearly
pointed up this trend.*
A Point of Perspective
Under this changing climate of opinion it may
be wise to inject a cautionary note oi historical
perspective. It has taken audience researchers
some three decades and upwards of a hundred
million dollars spent on audience research of all
varieties to arrive at the point where they can
produce reasonably accurate answers to the question of "how many." It would seem likely that it
may take nearly as long, and as many dollars, to
make comparable progress on the more difficult
question of "how hard."
With this frame of reference, it is evident that
the following case-history is not regarded as representing perfected techniques or ultimate
Toward Better Media Comparisons, A Report of the
Audience Concepts Committee of the Advertising
Research Foundation {New York: Advertising Research Foundation, Inc., 1961). Russell H. Colley,
Defining Advertising Goals for Measured Advertising Results (New York: Association of National
Advertisers, Inc., 1961). Harry Deane Wolfe, James
K. Brown, and G. Clark Thompson, Measuring Advertising Results (New York: National Industrial
Conference Board, 1962), Darrell Blaine Lucas and
Steuart Henderson Britt, Measuring Advertising
Effectiveness (New York: McGraw-Hill Book Company, Inc., 1963).
answers. Growing out of a long-standing interest
in the assessment of advertising effectiveness and
successive attempts at improving the methods
employed,^ this study represents an experimental
investigation which a few years ago undertook to
extend our efforts into the as yet untried area of
inter-media effectiveness comparisons.
The methodology outlined may prove of interest
and provide some stimulation for further exploration, while revealing some of the problems encountered in assessing advertising impact and
some attempts which have been made to deal with
them.
An Experimental Study
This experiment was a 2-wave panel study, in
which the same individuals were reinterviewed at
two points in time three months apart. The sample
was a prelisted probability sample, representing a
typical medium-sized midwestern market; 91%
of the original respondents were recovered on
Wave II.
The respondents were male and female household heads, with a final sample size of 2,441. The
study covered 22 brands advertised both on network TV programs and in weekly Magazine A,
representing 11 different product categories:
Beer
Canned soup
Cigarettes
Gasoline
Headache remedies
Deodorants
Home permanents
Packaged cheese
Packaged desserts
Razor blades
Toothpaste
Thomas E. Coffin, Tke Hofstra Study: A Measure
of the Sales Effectiveness of TV Advertising (New
York: National Broadcasting Company, Inc., 1950).
TV Today: Its Impact on People and Products (New
York; National Broadeasting: Company, Inc., 1951).
Why Sales Come In Curves (New York: National
Broadcasting Company, Inc., 1954). Strangers Into
Customers: Tke Fort Wayne Study (New York:
National Broadcasting Company, Inc., 1955).
• ABOUT THE AUTHOR. Thomas E.
Coffin is Director of Research of the
National Broadcasting Company, Inc.
The concepts in the present article have
been developed in the course of analyzing a series of major studies into the
effectiveness of television advertising,
conducted by NBC over the past several
yea rs.
Prior lo joinrng NBC tn 1949, Dr.
Coffin was Professor of Psychology and
Chairman of the Psychology Department at Hofstra College. He
received his M.A. and Ph.D. in Psychology from Princeton
Vnlvers'dy.
Jack 8. Landis, formerly Manager of Research Projects at
NBC and now Executive Director of Marketing Evaluations,
has contributed greatly to the development of the ideas and
technicfues described in this article.
A Pioneering Experiment in Assessing Advertising Effectiveness
For each of these categories the respondent was
questioned as to what brands he or she had "personally bought in the last four weeks." The "buying figures" to follow, therefore, represent the
percentage of the total sample (or specified subgroup) who claimed to have bought the advertised
brand in the last four weeks.
In the TV viewing question, a list of programs
was shown and the respondent was questioned
ahout his personal viewing of each in the last
four weeks. In the case of weekly magazines, a
list was also used, with the questioning directed
toward the last four issues. "Readers" or "viewers" here are those who claimed to have read one
or more of the last four weekly issues or watched
one or more of the last four broadcasts. Thus, in
the following sections the unit of exposure is the
advertising vehicle, rather than the commercial or
advertisement.
To maintain comparability, the same questionnaire wordings and sequences were employed on
both waves of the study. To minimize any possibility of the buying responses being infiuenced by
the media questions, these topics were separated
as widely as possible, so as to obtain the information about buying before asking about media exposure, with a number of other questions intervening.
Moreover, several additional products, programs, and magazines were included in the lists,
in order to divert attention further from the
questions of special interest and to lessen the
chance of producing a spurious relationship
between a particular product and a program or
magazine. Careful analysis of previous studies
has shown that such precautions have been effective in minimizing the possibility of inadvertent
"reversal" of cause and effect or of "conditioning"
the responses on Wave II by prior questioning on
Wave I.-^
Results
All of the figures to be reported represent the
unweighted averages of the 22 brands studied. Inspection of the individual brands indicates that
these averages properly reflected the experience
of the majority of the individual brands; about
75% of the individual brands showed the same
patterns as those pictured by the averages, while
25% of the brands deviated from the average
pattern in one way or another.
As shown in Table 1, the first overall finding
of the study was that, on a total sample basis,
there was remarkably little difference between
the buying levels for Wave I and Wave II. The
3 Why Sales Come In Curves (New York: National
Broadcasting Co., Inc., 1954), pp. 51-52. Strangers
Into Customers: The Fort Wayne Study (New
York: National Broadeasting Co., Inc., 1955), p. A-7.
TABLE 1
SOME RELATIONSHIPS OP BUYING
TO OVERALL ADVERTISING EXPOSURE
1. Overall results of survey
Total sample. Wave I
Total sample. Wave II
% buying in
past 4 weeks
19.4
19.6
2. Relationship of buying to advertising exposure
% buying,
Wave II
Exposed to advertising (TV and/or
magazine)
20.5
Not exposed to advertising
16.9
3. Relationship of buying to degree of exposure
% buying,
Wave II
Not exposed to advertising (TV and/or
magazine)
16.9
1 unit of exposure (TV and/or
magazine)
18.9
2 units of exposure. <TV and/or
magazine)
20.1
3 units of exposure (TV and/or
magazine)
21.8
4 units of exposure (TV and/or
magazine)
24.0
percentage buying the "average brand" in the
last four weeks was 19.4 for Wave I and 19.6 for
Wave II, three months later. It might seem that
nothing is happening. This appears to support
the view that "you cannot relate advertising to
sales," since a good deal of advertising for these
brands occurred in this period.
This pattern, of minimal change in overall levels
from one period to another, is a common finding
in panel studies. However, if we start breaking
the total sample apart into its component groups,
we begin to find evidence that something is going
on. For example, if we break out those who are
exposed to advertising for these brands (any type,
either television or magazine) as compared with
those not exposed, we note an appreciable difi^erehce in their buying levels on the second wave:
20.5% va, 16.9%.
And going further, if we analyze the exposed
group by degree of exposure, we begin to see a
trend. The more units of advertising a group la
exposed to, the higher its buying level on Wave II
(where exposure to one medium at one period
equals one unit). By Wave II, there was a 42%
spread between the levels of the least-exposed and
most-exposed groups.
Changes in Exposure
One of the most useful features of true panel
data, where the same individuals are interviewed
over successive periods of time, is the opportunity
they afford for "dynamic analysis," the study of
change. The possibility of detecting significant
Journal of Marketing, July, 1963
relationships is enhanced when people are observed in the process of change.
In the present case, analysis of respondents in
terms of changes in their advertising exposure
revealed that changes in exposure were associated
with changes in buying. Respondents who experienced an increase in exposure (to either form of
advertising) showed an increased level of buying;
with no change in exposure, there was no change
in buying level; and with decreased exposure came
decreased buying. See Table 2.
The Increased Exposure group consisted of those
respondents who reported more units of exposure
on the second interview than on the first. The No
Change group were those who reported the same
numbers of units both times. The Decreased
Exposure group were those who reported more
units on Wave I than on Wave II; thus, at the
time they were more heavily exposed, their buying level was higher, and when they became less
exposed, their buying level became lower.
A Master Table presenting the detailed breakdowns of all results, together with the number of
cases in all subgroups, is given in Table 7, page
9. There the Increased Exposure groups have been
further broken down into groups C, I, K, L, and O.
The No Change groups are A, D, G, J, M, P. The
Decreased Exposure groups are B, E, F, H, N.
Buying Dynamics
Dynamic analysis may be applied to the dependent as well as the independent variable. Examination of the "buying dynamics" enables us not only
to measure changes in levels, but to perceive the
mechanism whereby these changes come about.
Those who were buying on Wave I can be divided
into two components. Some were still buying the
same brand on Wave II three months later; they
may be termed the "continue buying" group. Others
reported not buying this brand on Wave II; these
are the "stop buying" group.
Likewise, among those who were not buying the
brand on Wave I, some will be found buying it on
Wave II ("start buying") ; and others are still not
buying it ("nonbuyers").
Do these buying dynamics bear any relation to
changes in advertising exposure? They certainly
do, in a most interesting pattern—see Table 3.
Among those whose exposure to advertising increased, more people started buying than stopped.
TABLE 2
RELATIONSHIP OP BUYING TO
CHANGES IN ADVERTISING EXPOSURE
Increased exposure
No change in exposure
Decreased exposure
% Buying
Wave I Wave II
19.6
21.0
20.3
20.4
21.0
19.4
Relative
change
+7%
0
-8%
TABLE 3
BUYING DYNAMICS AND CHANGES IN EXPOSURE
Increased exposure
No change in exposure
Decreased exposure
% stop
buying
% con
tinue
buying
% start
buying
8.0
8.1
9^
11.6
|l2.2
11.6
|9.4
8.2
7.8
Indeed, this group showed the strongest tendency
of any of the three groups to "start buying." Those
with no change in exposure were marked by a
somewhat higher rate of "continuing" to buy. And
the most notable tendency among those with decreased exposure was to "stop buying"; in fact,
they stopped buying at a 20% greater rate than
they started. (Note that these figures are additive.
Checking back with Table 2, it will be seen that
the Stop plus Continue percentages add back to the
buying level on Wave I, while the Continue plus
Start figures add to the Wave II level.)
These relationships are highly suggestive of the
double functions of advertising: "generation" and
"preservation." Often advertising is thought of for
its value in inducing people to start buying a brand,
generating new customers; but the figures above
suggest its value additionally in persuading present
buyers to continue, thereby preserving old customers
and reducing the number of "lost customers."
Thus, in a situation where the overall buying
levels appeared static, it is seen that intriguing
dynamic changes—stopping, starting, switching—
were going on beneath the surface, and that these
buying changes had a meaningful relationship to
concurrent changes in advertising exposure. The
dynamic associations between shifts in exposure
and shifts in buying, while not "proof" of a causeand-effect sequence, strongly suggest an interrelationship between the two processes. They suggest
that advertising "works" and imply something of
"how" it works.
Relationships to Individual Media
Thus far the analysis has been in terms of exposure to advertising per se, regardless of type. It
may be useful to pursue this further, examining
some of the relationships to individual media.
The reminder is again in order that the following figures should be regarded as being of methodological rather than substantive interest. Their
purpose is not to represent a thoroughgoing attempt
at assessment of the relative effectiveness of the
two media, but simply to suggest some of the possible analytical approaches for such comparisons.
A number of limitations in the present study prevent it from being considered a full-scale inter-
A Pioneering Experiment in Assessing Advertising Effectiveness
media comparison: the study is restricted to a
single market; it covers only two types of advertising, without reference to other media which may
have been used; the measures of exposure and buying are on a verbal-report basis, without verification by pantry-checks or more elaborate audiencemeasurement techniques; no attempt has been made
to relate results to the costs of advertising; and the
study covers only a cumulative series of exposures,
making no effort to determine the effects of a single
advertisement or single broadcast, nor to assess the
effects of varying frequencies of exposure.
Some of these limitations have been successfully
attacked in other studies by the National Broadcasting Company.^ They are not insurmountable in
future research, but their presence should be kept
in mind.
"Before" and "After" Exposure
With tbese cautions in mind, it is of interest to
examine some of the ways in which a 2-wave panel
survey can be analyzed to yield indications of media
effectiveness.
The most interesting analyses are those whieb
take advantage of "turnover," that is, the changes
which are continually going on in the audience to
any medium. Here we apply to audience the same
kind of "dynamic analysis" previously applied to
the buying process.
Let us start with the population of people not
exposed to a given medium (for example, a television program) at the time of the first survey. These
same individuals can then be followed through on
Wave II. Thanks to the phenomenon of audience
turnover, it will be found that some of them were
in tbe exposed category at the time of Wave II
(that is, they have "begun viewing").
This is a particularly significant group, because
they provide cases on which we now have buying
records "before" and "after" exposure. And since
The Advertising Impact of TV Specials (New York:
National Broadcasting Company, Inc., 1957). Hardgoods and the Impact of Television (New York:
National Broadcasting Company, Inc, 1960). Introducing New Cars on Television (New York:
National Broadcasting Company, Inc., 1960).
tbe group is made up of precisely tbe same people
both times, all variables of a personal and demographic nature which might influence the buying
process are held constant.
Similarly, the remaining segment of the population not exposed on Wave I is a very useful group:
they comprise the people who did not "begin viewing," thus serving as a control for those wbo did
begin viewing.
The comparison of these two groups is especially
significant in that botb of them came from the
same population on Wave I. Starting from the
same condition of nonexposure, we can then follow
them as one group becomes exposed and the otber
does not—what happens to their buying?
Table 4 shows these buying levels. Taking, for
example, the case of television viewing, tbe first
two lines give the ieveis for all those who were not
exposed on Wave I. Of these, the ones who "began
viewing" showed an increase of 10% in the number
buying the brand advertised on the program they
began viewing (again, this is the average of 22
brands, each tabulated against the viewing of its
own program). Those who also started as nonviewers but remained nonviewers showed no change
in buying.
Tbe converse of the foregoing analysis is also of
interest. If we start with all those who were exposed to a given medium on Wave I and trace
them through, we find that audience turnover occurred in this group also. Thus, some of the group
were in the exposed category on Wave II as well as
on Wave I (that is, they "continued viewing").
And others were in the nonexposed grOup the second time (they "stopped viewing").
So again we have available two subgroups derived from the same Wave I population. Both were
viewers (or readers) at a given point in time. Some
continued, and some did not. What happened to
their buying behavior?
Certain hypotheses can be formulated as to what
might be expected under these conditions. Given a
group which is exposed to begin with, and continues its exposure, it would be a reasonable hypothesis that if advertising is effective, such a group
should show a high initial level on the first wave
TABLE 4
"BEFORE" AND "AFTER" EXPOSURE TO SPECIFIC MEDIA
% Buying
Wave I
Television: Nonviewers who . . .
. . . became viewers
. . . remained nonviewers
Magazine: Nonreaders who . . .
. . . became readers
. . . remained nonreaders
Wave II
Relative
change
18.7
18.0
20.6
18.0
-M0%
20.5
19.2
21.0
19.8
+3%
+3%
0
Journal of Marketing, July, 1963
TABLE i5
MAINTAINING VERSUS REDUCING EXPOSURE TO SPECIFIC MEDIA
9;? Baying
Wave II
Wave I
Television: Viewers who . . .
. . . continued viewing
. . . stopped viewingMagazine: Readers who . . .
. . . continued reading
. . . stopped reading
(associated with its Wave I exposure) and maintain this high level on the second wave (in keeping
with its sustained exposure). As shown in Table 5,
this is in fact what happened in the case of the
viewing group.
Similarly, the hypothesis would be that a group
which is initially exposed, but subsequently ceases
its exposure, should again start at a high level
(under the condition of exposure) but drop to a
lower level (when no longer exposed). This, too, is
what happened to the viewing group.
This phenomenon of a drop in buying level associated with a reduction in advertising exposure distresses some in the advertising field, on the ground
that it seems to have "negative" implications. Quite
to the contrary, it is important evidence of advertising effectiveness.
If one hypothesizes that buying levels should
rise under increasing advertising pressures and remain high under continuing- pressures, then he
must also hypothesize that under decreasing pressures, they will fall. The latter is a necessary corollary of the former. And the more effective is the
medium, the greater should be the decline if its
pressure is reduced. Consequently, in investigating
the effectiveness of advertising this test rounds out
the full circle of testable hypotheses.
Indeed, as a practical matter, if this did not
prove to be true, why should anyone, once he had
achieved a satisfactory level, continue to advertise?
A 16-Fold Analysis
The above analysis is capable of still further
improvement. Each medium was treated above as
though it were independent of the other. But in actual fact some of the "viewers" were also "readers,"
and some of the "readers" were "viewers." Hence,
the analysis must cope with the phenomenon of
audience duplication.
Possible Advertising Strategies: A Model
To approach the problem systematically, let us
start by laying out all the possible conditions which
may be encountered in dealing with two different
media at two different points in time.
Taking one of the media first (for example, maga-
23.0
21.6
23.2
19.2
21.7
19.9
20.9
19.4
Relative
change
+ 1%
-11%
-4%
zines), there are four—and only four—conditions
of exposure which can obtain across two points in
time. Using a plus sign to signify exposure and a
minus sign for nonexposure, the four possibilities
are:
f- Not exposed on I, exposed on II
("start reading")
+ -\- Exposed on both occasions
("continue reading")
+ — Exposed on I, not on II
("stop reading")
~ — Not exposed either time
("non-reading")
The same four exposure groups—and no more—
can be laid out for the other medium. We have
already examined these four groups for each medium taken separately (Tables 4 and 5).
But when the two media are considered simultaneously, it is evident that there are 4 times 4, or 16,
possible exposure conditions. In conjunction with
each one of the TV groups (for example, "start
viewing") it is possible to have any one of the four
magazine-exposure situations ("start," "continue,"
"stop," or "no" reading), and vice versa.
These 16 possible situations are represented in
Figure 1. An intriguing aspect of this chart is that
it also turns out to be a systematic layout of all the
possible advertising strategies that could be followed—a "model," as it were, of all the possible
decisions which could be made by an advertising
manager under the restriction of two media at two
points in time.
The data from a 2-wave survey can be analyzed
according to this model. Since each respondent will
be found to fall into one, and only one, of the 16
exposure groups (and these 16 groups account for
all respondents), the 16 groups can be broken out
and their buying levels and changes tabulated.
For completeness, this "master table," setting
forth the full results of the present survey, is shown
in Table 7. However, in the interests of simplicity
some of the more meaningful comparisons are presented for easier examination in Table 6. Each
group in Table 6 is keyed by letter to the corresponding line in Table 7.
A Pioneering Experiment in Assessing Advertising Effectiveness
Magazine Compaign
_
I
Start
start
Both
-+ +StortTV
Keep Mag.
+ + - + + -I- + +
S
Keep TV
Start Mag.
Continue
Switch from
Mag. to TV
Switch from
TV to Mag.
__ __
„
^
Keep TV
StopAlag.
No TV
Start fAag.
None
FIGURE
5top
Both
Stop TV
KeepA\ag.
-"
-I- +
No TV
Keep Mag.
Start TV
No fAa^.
++ +- + +
Keep
Both
+ - + + + - -HStop
None
+-
-+ - +
„ , , I.
Stop
Continue
Start
_
.^
Keep TV
No Mag.
+Stop TV
No Mag.
1, .
No TV
Stop Mag.
No
Advg.
1. Possible advertising strategies: A model-
Possible Advertising Strategies:
Their Relationship to Buying
Following are some of the more interesting comparisons which can be drawn from the complete
breakout of results of such a 2-wave, 2-media survey. Such comparisons not only take proper account
of but even take advantage of the duplication and
nonduplication between media, as well as of the
changes in exposure to the media (stops, starts,
and switches) in order to raise for examination
various hypotheses regarding the effectiveness of
advertising in general, and of the two media in
particular.
To render the exposure symbolism somewhat
more meaningful, each of the groups is tagged with
a descriptive phrase indicating the "advertising
analog" which it represents. Thus, each group can
be thought of as representing, in a sense, a "simulation" of an interesting advertising strategy. However, there are definite limitations to such analogies, in that here the exposure-condition is brought
about by self-selection on the part of the respondent, rather than having been experimentally imposed from without by the investigator.
Moreover, the principal focus is not on the substantive content of the figures themselves, which
represent only the findings of a single study done
a few years ago in a single market, but on illus-
trating one possible approach to the investigation
of advertising effectiveness and intermedia comparisons.
For each group in Table 6 are shown the buying
levels on Waves I and II and the change from I to
II, plus the "buying dynamics" which generated
these levels. As a visual aid in noting points of
special interest, all comparisons showing a spread
of 2 or more percentage points are enclosed.
Thus, in the first comparison the most noteworthy difi'erence is that the group exposed to
TV-only both times showed an unusually high
"continue-buying" rate, plus a higher "start-buying" rate than the magazine-only group. However,
in the second comparison the group which switched
from TV to magazine exposure showed more "continue-buying" than those who switched from magazine to TV exposure.
By pairing the appropriate groups, it is possible
to set up a comparison in which one medium remains constant, while the other is varied. Comparison 3, for example, brings together the two groups
who maintained exposure to one medium while reducing exposure to the other. Reduced exposure to
TV seemed to have more effect on the buying level
than reduced magazine exposure; this resulted from
the fact that with reduced TV went a lower rate of
"starting" to buy and a higher rate of "stopping."
Journal of Marketing, July, 1963
TABLE 6
EELATIONSHIPS OP POSSIBLE ADVERTISING STRATEGIES TO BUYING
Group TV
Magazine
1
Advertising analog
1. A continuing campaign in a single medium
D
+ +
A continuing TV-only campaign
M —_
+ +
-A. continuing Magazine-only campaign
2. Switching campaigns from one medium to another
Switch from Magazine to TV
J
- + -]—
G + - + Switch from TV to Magazine
3. Dropping a cwm-paign
B
- ! - + + _
Keep TV but drop Magazine
Keep Magazine but drop TV
E
-H + -H
4. Starting a campaign
O
++ Start Magazine campaign, no TV
L - +
• — Start TV campaign, no Magazine
K
- 4- - -1-1- Start campaign in both
5. Extremes of change in advertising strategy
K
— •\- — -f
Start campaign in both media
F
+ — + _
Drop all advertising
6. Extremss of advertising weight
A
+ +
+ 4 - Continuous advertising in both media
P
No advertising in either
Comparison 4 presents the reverse case, comparing the two groups who remained nonexposed to one
medium, while increasing, their exposure to the
other. Increased exposure to TV seemed to have the
greater effect, due chiefly to the greater rate of
"start-buying" in this group. However, the greatest change of all is observed in the group which
increased exposure to both media. Here the buying
level increased markedly, again principally as a
result of more "start-buying."
Comparison 5 contrasts the extremes of change
in advertising exposure, comparing those who
"started" both media with those who "stopped"
both. When both media were working together the
"starts" went up (due to high "start-buying"),
and the "stops" went down (due to high "stopbuying").
The final comparison contrasts the extremes of
advertising pressure: full exposure to both media,
compared with absence of exposure. Here, witb
relatively constant advertising exposure, one does
not hypothesize change in buying, but differences
in levels of buying. And that is what happened. The
continuously exposed group was buying at a continuously higher level—and the difference was due
to their much higher rate of "continuing to buy,"
with this group showing the highest percentage of
"loyal customers" of all 16 exposure groups.
Thus, the analysis seems to "make sense," and to
document the value of advertising in terms which
management could readily appreciate. Although on
% buy brand
//
Change
Buying dynamics
Continue
Stop Start
21.8
19.3
23.0
18.7
1.2
-.6
14.2
11.9
7.6
7.4
8,8
6.8
18.6
22.5
18.8
20.8
.2
-1.7
9.4
12.4
9.2
10.1
9.4
8.4
22.2
23.2
23.0
19.8
-3.4
13.8
12.7
8.4
10.5
9.2
7.1
17.7
18.1
17.6
18.0
20.9
21.7
.3
2.8
4.1
9.9
11.1
10.2
7.8
7.0
7.4
8.1
9.8
11.5
17.6
19.7
21.7
17.6
4.1
-9.A
10.2
9.9
7.4
9.8
11.5
7.7
23.7
16.0
24.0
16.9
.9
16.1
9.3
7.6
6.7
7.9
7.6
.8
an overall, total-sample basis the buying levels
appear to remain static and little seems to be
happening, on breaking out the interrelationships
between exposure and buying, it is found that
movement and change is going on.
And these changes relate to advertising exposure
in meaningful ways. Under increasing exposure,
more people start buying, and buying levels rise.
Under decreasing exposure, more stop buying, and
buying levels fall. Under continuing' advertisingpressure, more continue buying, and levels remain
high. And finally, different media can be examined
to see which are associated with these effects to a
greater and which to a lesser degree.
Further Improvements Desirable
We have carried the analysis of this case-history
through several successive levels of refinement, each
of which has considerably improved it. However,
the process of improvement is not by any means
complete.
The fundamental objective in all "effects" comparisons is to confront what did happen in a given
circumstance (for example, under the influence of
a given advertising strategy) with what would have
happened, if that circumstance had not obtained.
The difference, all other things being equal, is the
"effect" of that circumstance. Since the "did happen" is known, the problem is always to find the
"would have happened."
In the present case, for example, there may still
A Pioneering Experiment in Assessing Advertising Effectiveness
TABLE 7
MASTER TABLE, SHOWING COMPLETE RESULTS FOR BOTE[ WAVES*
Exposure
Group TV Magazine
24.0%
23.0
23.3
23.0
16.1%
13.8
13.7
14.2
23.2
Keep Magazine, drop TV
Drop all advertising
19.7
Substitute Magazine for TV campaign 22.5
No Magazine, drop TV
21.0
19.8
17.6
20.8
18.5
12.7
9.9
12.4
11.3
10.5
9.8
10.1
9.7
7.1
7.7
8.4
7.2
70
55
49
147
7.8
9.4
11.5
9.8
60
39
56
137
analog
A
E
C
D
-j- -{-
+
-t—
—
+
—
+
—
Continuous advertising in both media
Keep TV but drop Magazine
Add Magazine to TV campaign
Continuing TV-only campaign
E
F
G
H
-f —
+
-f
—
—
+
—
+
—
I
J
K
L
^
M
— —
N
0
P
23.7%
22.2
24.2
21.8
+ +
-1
— +
— —
Add TV to Magazine campaign
Substitute TV for Magazine campaign
Start campaign in both media
Start TV-only campaign
20.5
18.6
17.6
18.1
21.0
18.8
21.7
20.9
13.2
9.4
10.2
11.1
7.3
9.2
7.4
7.0
+
+
—
—
Continuing Magazine-only campaign
No TV, drop Magazine
Start Magazine-only campaign
No advertising in either
Total (weighted)
19.3
18.8
17.7
16.0
19.4%
18.7
18.2
18.0
16.9
19.6%
11.9
10.4
9.9
9.3
11.5%
7.4
8.4
7.8
6.7
7.9%
+
—
-i—
Start No. in
Stop
buying
7.6%
8.4
10.5
7.6
Advertising
% buy' brand Continue
Wave I Wave II buying
buying
1.9%
9.2
9.6
8.8
6.8
7.8
8.1
7.6
8.1%
group
158
86
101
290
228
151
197
617
2441
* Each figure is the average of the corresponding figures for 22 different brands.
remain some variance between the groups being
compared, due to differences in their composition
and makeup (that is, "all other things" are not yet
equal). In the search for further methodological
improvement in future studies, one of the most
promising, tools with which to attack this problem
might be multiple regression analysis, with large
numbers of variables handled simultaneously.
Implications
It was our initial thesis that there are two basics
in advertising, reach and impact.
The significance of this observation, however,
goes well beyond the mere naming of two factors.
If each of these factors could be measured and reduced to a number, and if these two numbers were
multiplied together, the resulting product would
be a third number which would have the highly
significant property of being a true measure of the
total effectiveness of the advertising in question.
Thus, the two factors of audience and impact
represent far more than simply different emphases
in evaluating advertising. They represent the two
necessary and sufiicient conditions for performing
a true measure of advertising effectiveness.^ As
such, they are capable of formulation in a simple
but powerful equation. The total effectiveness of
advertising is the product of size of audience multiplied by impact per member of the audience:
E = A X I
See Thomas E. Coffin, '"Total Effect' Concept in
Media Comparisons," Media/scope Vol. 3 (February, 1959), pp. 44-48 and 52.
This equation is applicable both to the problem
of measuring the effectiveness of any single advertisement or campaign, and to that of properly comparing different advertising media. In the latter
application, it effectively solves the "apples-andoranges" dilemma in media comparison.
It is indeed true that a "reader" and a "viewer"
may be worth different values and should not be
compared. But if the impact per reader could be
measured, and multiplied by the number of readers,
the product would represent the total effect of the
reading. By putting each medium through the same
process, all would be converted to the same terms
and become comparable. Thus, the end-products of
the effectiveness equation are comparable, although
the separate components are not.
The effectiveness equation also has the property
of being self-adjusting for differences in the level
at which the audience factor is measured. Thus, if
a "loose" definition of audience is used, audience
size will be large; but due to the inclusion of many
"lightly-exposed" people, the impact per person will
be small. The product of these two will be similar
to that obtained from a "tight" definition, yielding
a smaller audience but a correspondingly higher
impact factor. Since a key problem in the comparison of media has been how to define their audiences
with equal "tightness," this self-adjusting property
of the effectiveness equation is a major benefit.
A great deal remains to be done, of course, before
such an ideal procedure can become a matter of
daily practice. "Audience times impact" yields a
true measure of total effectiveness, but the precision
10
Journal of Marketing, July, 1963
of final figure is a direct function of the precision
with which each of its components is measured. At
present, the precision of audience measures far exceeds that of impact measures.
The advertising industry has been spending most
of its research dollars in measuring the audience
component, with the result that we can now measure this dimension reasonably well. It is now time
to start spending more dollars in pursuing the
measurement of impact, for it is this area which
in the future promises the greatest improvement of
overall efficiency in advertising evaluation.
MARKETING MEMO
Factors Leading To Inventiveness . . .
Inventiveness appears to emerge from situations where personal and social conditions of the following types are encountered: high drive (ambition); frequent marginalism; high relationism; and high operationalism. By high drive is meant that
cultures and individuals of high inventiveness make strong demands of their environment, have high hopes and expectations,
and value persistence in endeavors. By frequent marginalism, we
mean that uncommon views, deviant personality types, and conflicting Weltanschauung are endemic in the inventive culture and
express themselves through inventive individuals. Relationism
is defined as the ability to perceive connections of all kinds among
things and events; it is needed in greater degree for newly combining relations, the salient feature of the invention. High operationalism denotes the strong tendency to regard fulfillment of an
idea as requiring- its expression in activity.
—Alfred de Grazia, "Elements of Social
Invention," The American Behavioral
Scientist (December, 1961) p. 8.
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