An executive summary for
managers and executive
readers can be found at the
end of this article
A new brand's behaviour in an
established market
Janet Hoek
Associate Professor of Marketing, Massey University, Palmerston
North, New Zealand
Zane Kearns
Lecturer in Marketing, Massey University, Palmerston North,
New Zealand
Kathryn Wilkinson
Media Planner, Promotus Advertising, Wellington, New Zealand
Keywords Market entry, Market share, Brands, New product development
Abstract Although managers can use panel data to monitor their brands' performance in
fast-moving-consumer-goods categories, the regularities researchers have documented apply
to stationary and unpartitioned marketplaces. However, the introduction of a new brand may
alter the structure of a marketplace and thus the behaviour patterns consumers display. This
paper discusses the regularities typically observed in stable markets and considers these in
the context of a market that had just experienced a new brand launch. It is concluded that the
new brand behaved as an established brand very quickly and that the generalisations used to
benchmark existing brands provided accurate predictions of the new brand's performance.
Double jeopardy
Repeat purchase rates
Introduction
Over the last four decades, Ehrenberg and his colleagues have documented a
number of generalisations about brands' behaviour in stationary markets. For
example, they have identified double jeopardy (DJ) trends in numerous
markets and product categories, and across different types of consumer
behaviour (Ehrenberg et al., 1990). The observed DJ patterns mean that it is
perfectly normal for small brands to perform poorly relative to larger brands
on loyalty measures such as average repeat buying rates and proportion of
sole loyal buyers.
The well-known Dirichlet model of consumer behaviour has integrated a
number of other patterns in consumers' behaviour (Ehrenberg, 1988). Dirichlet
patterns enable managers to compare their brands' performance with market
norms and thus to evaluate whether the brands' repeat purchase rates, or
proportion of sole brand-loyal buyers, are above or below what would normally
be expected in that market. Managers' knowledge of DJ, when combined with
Dirichlet predictions, can assist them to estimate important benchmarks in
mature markets. These benchmarks can also be useful when they examine the
behaviour of new brands, in which they may have invested considerable R&D,
production and marketing resources.
How a new brand performs and how it affects the structure of the market it
enters are important questions that researchers have not yet addressed in full.
This paper begins by briefly reviewing two research streams:
The authors would like to acknowledge the generous support of A.C. Nielsen, who
supplied the data and, particularly, the assistance Rob Clark and Chris Morris,
current and former directors of the HomeScan Panel, have provided.
The Emerald Research Register for this journal is available at
http://www.emeraldinsight.com/researchregister
The current issue and full text archive of this journal is available at
http://www.emeraldinsight.com/1061-0421.htm
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(1) the regularities that have been observed in stationary markets; and
(2) the research into new product launches.
We then report findings from consumer panel data that recorded purchases of
all brands before, during, and after the launch of a new brand into an
established category before analysing the new brand's behaviour and effects
on the market structure.
Regularities in consumers' behaviour
Ehrenberg has described several patterns, or regularities, in consumers'
behaviour that he found were consistently apparent in data from a wide range
of stationary markets (see also Barwise (1995)). He argued that these
regularities enabled managers to calculate norms, or benchmarks, against
which they could compare their brands' performance. Knowledge of these
norms thus provided managers with a useful diagnostic tool that they could
use to assess their brands' health.
The Dirichlet predicts many
aspects of buyers'
behaviour
Many of the regularities observed have been linked together in the Dirichlet
model, which Uncles et al. (1995) argue is the best-known empirical
generalisation in marketing. The Dirichlet was foreshadowed by Chatfield
and Goodhardt (1975), discussed in more detail by Bass et al. (1976), and
outlined comprehensively by Goodhardt et al. (1984). The Dirichlet predicts
many aspects of buyers' behaviour, given each brand's market share and the
following assumptions: brand purchases are stationary; the market is not
partitioned or segmented, consumers have split loyalties, and different
consumers hold different brands in their repertoires (Ehrenberg, 1988;
Uncles et al., 1995; East, 1997).
Three key patterns
identified
Uncles et al. (1995) identified three key patterns in Dirichlet markets: first,
different brand measures tend to vary together. Second, they noted that this
correlation is largely a matter of market share and, third, they suggested that,
aside from expected DJ effects, the loyalty measures of different brands are
very similar (p. G73). Ehrenberg and Uncles (1999) recently overviewed the
body of research examining these patterns and concluded that there appear to
be very few markets that do not exhibit a Dirichlet-type structure. Already,
the Dirichlet model has been used to audit brands' performance (Ehrenberg
and Uncles, 1999); analyse cannibalisation of line extensions (Lomax et al.,
1996a, b); explore price sensitivities (Scriven and Ehrenberg, 1995); evaluate
loyalty programmes (Dowling and Uncles, 1997; Sharp and Sharp, 1997),
and examine new brands' performance (Wellan and Ehrenberg, 1988;
Ehrenberg and Goodhardt, 2000). Ehrenberg (1988) and Ehrenberg and
Uncles (1999) have suggested that Dirichlet norms could be used as a
standard against which new brands' performance can be evaluated.
However, use of the Dirichlet model to assess a new brand's performance
will be complicated if the new brand violates any of the Dirichlet's
underlying assumptions. For example, if a new brand created a partition in
the product category, it would violate the assumption that the market was
unsegmented. Researchers therefore need to explore how quickly markets,
whose structures have been disturbed by a new entrant, return to Dirichlettype patterns.
Another regularity that routinely characterises brands' behaviour is DJ.
McPhee (1963) is credited with first documenting DJ, a term he coined after
discovering that comic strips that were read by fewer people were also
typically liked less by those who read them. He termed this phenomenon
``double jeopardy'' (DJ), since the less popular items seemed to suffer in two
JOURNAL OF PRODUCT & BRAND MANAGEMENT, VOL. 12 NO. 1 2003
53
ways. Ehrenberg et al. (1990) noted that DJ also affected brands: not only do
less popular brands not only have lower penetration but also those consumers
who do buy them purchase them less frequently.
Small brands attract less
loyalty
Other things being equal, small brands attract less loyalty simply because
they are small, a finding that Ehrenberg et al. (1990) documented in
categories as disparate as television programmes, fast-moving-consumergoods and industrial goods. It is thus well established that brands with lower
penetration are bought less frequently than brands with higher penetration;
television programmes with low reach (equivalent to penetration) have a
lower frequency (repeat viewing rate) than do programmes with higher
reach. Similarly, brands with low penetration are viewed less positively by
users than are brands with high penetration (Ehrenberg 1991; Barwise and
Ehrenberg, 1985; Barwise, 1986). Given DJ's ubiquity, it provides a basis for
understanding the effect of market share on brands and thus for predicting
the repeat buying rate of a new brand, once it has settled down. New brands
would typically be expected to suffer DJ effects (since their initial
penetration level is unlikely to rival that of the market leaders), and would
continue to do so if their penetration level settled below that of the market
leader.
A new brand's effect on other brands can be examined using another
generalisation, the Duplication of Purchase Law, which states that: ``In an
unsegmented market, the percentage of buyers of one brand who also buy
another brand varies in a constant proportion with the penetration of this
other brand'' (Ehrenberg, 1991, p. 292). Clearly, where no market
partitioning exists, a new brand's share should come proportionally from the
existing (substitutable) brands in that market. That is, the size of a brand
determines the number of its buyers who will also buy the new entrant; in an
unsegmented market a similar proportion of all brands' buyers would be
expected to purchase the new brand.
Market unsettled for at
least a year
Yet, although regularities such as DJ and the use of Dirichlet norms have
been well documented in established markets, few studies have examined
their application to dynamic rather than stationary markets. When a new
brand is introduced, changes in share almost inevitably occur and the market
structure is generally considered to be unsettled for at least a year following a
new brand's entry (Ehrenberg, 1991). Since the Dirichlet's assumptions
make it clear that the model applies specifically to markets where no major
changes in share are occurring, it has been assumed that markets where some
volatility is present would violate these assumptions. However, the few
studies to explore the relevance of these regularities to new brands have
suggested that the disruption of market structure is short-lived (Ehrenberg
and Goodhardt, 2000). Given this, it is timely to review the length of the
``settling down'' period and the extent to which new brands' behaviour can
be predicted from data collected during the launch period. The following
section examines decisions relating to new brand launches before discussing
the small body of work that has explored some of these regularities in the
context of new brands.
New brands
Managers wishing to introduce a new brand may either develop and launch a
completely new brand or extend an existing brand. The risks and costs of
developing and launching new brands have been well documented (Brown,
1985; Tauber, 1988); thus it is not surprising that many managers develop
line extensions rather than completely new brands. This strategy assumes
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that the use of an existing successful brand name will enhance the new
variant's likelihood of success, and there is some evidence that this strategy
can decrease the costs of gaining distribution and increase the efficiency of
promotional expenditure (Morein, 1975). Employing similar visual stimuli,
such as logos and packaging, and the pairing these similarities create, can
also help to decrease barriers to trial that might otherwise exist.
``Expected'' cannibalisation
However, although they offer benefits, line extensions may cannibalise the
parent brand, particularly if the two are seen as highly substitutable.
Ehrenberg's Duplication of Purchase Law suggests that a new brand will
take share from all existing brands, including the parent brand; a
phenomenon that Lomax et al. (1996b) termed ``expected'' cannibalisation.
Using the Duplication of Purchase Law, Lomax et al. argued that the
expected cannibalisation would be higher for larger brands and lower for
smaller ones. However, they noted the potential for ``excessive''
cannibalisation, which occurs when a brand loses share over and above what
would be expected from its penetration level.
Parent brand can suffer
excessively
Lomax et al. (1996b) analysed three line extensions and found higher than
expected levels of cross-purchasing between all the parent brands and their
line extensions. While they noted that this level of cross-purchasing reduced
over time, as the market settled, it nevertheless remained at a higher than
expected level for some time following launch. This implies that the parent
brand can suffer excessively following the extension's launch, and that it
may continue to sustain a greater than expected loss of share even after the
market has regained equilibrium.
Developing a completely new brand usually involves less risk of
cannibalisation, since the new brand is not usually clearly linked to a parent
brand in the same category. However, although completely new brands may
be less likely to inflict damage on other brands from the same parent
company, some estimates suggest that a high proportion, up to 80 per cent,
fail each year (Smith and Park, 1992; Miller, 1993). Thus, the risk in this
context is not that the parent brand will be excessively cannibalised, but that
the new brand will fail to attract a sufficiently large base of repeat-purchasers
and so will be uneconomical to maintain. Given the expense of developing
and launching brands, it is logical to examine whether empirical
generalisations that apply to established brands might also be used to
improve the management of new brands.
Wide variation in brand
penetration
Ehrenberg (1991) examined this problem by way of case study when he
summarised much of his earlier work and explored the hypothetical entry of
a new brand of coffee into the existing US coffee market. Using this market
as an example, Ehrenberg illustrated the wide variation in brand penetration
(this varied by a factor of four, from 24 per cent to 6 per cent) and the
variation in average purchase frequency, which ranged from 3.6 to 2.0 (less
than a factor of two). The relationship between penetration and average
purchase frequency also displayed a clear DJ pattern, with one or two minor
exceptions, and Ehrenberg argued that brand X, the hypothetical new brand,
would also suffer from DJ, unless it grew to become market leader.
Ehrenberg also noted that the market clearly demonstrated consumers' split
loyalties to brands since, even where consumers had a favourite brand, this
normally accounted for only around a third of their total category purchases
over a 12-month period. That is, consumers bought their preferred brand only
irregularly and were mainly purchasers of other brands. However, the
proportion of purchasers accounted for by a favourite brand, and thus the
JOURNAL OF PRODUCT & BRAND MANAGEMENT, VOL. 12 NO. 1 2003
55
level of split loyalty present, clearly depend on how ``favourite'' is defined.
Although Ehrenberg concluded that favourite brands account for only around
one third of purchases, other researchers have reported that favourite brands
represent up to two-thirds of their purchases within a given category.
Share from other brands
Ehrenberg illustrated the extent to which purchasers of existing brands would
become purchasers of the new brand using the law of purchase duplication.
This enabled an assessment of how the current market structure would
change to accommodate the hypothetical new brand and demonstrated how
brand X would attract share from the other brands, in relation to their size.
The conclusions he drew have been supported by numerous other studies
conducted in mature markets, which confirm the distinctive presence of DJ
patterns (Ehrenberg et al., 1990), the typical lack of sole brand loyalty
(Ehrenberg, 1991), and the duplication law (Ehrenberg, 1988). As Ehrenberg
(1991) pointed out, the strength of his work is that it considered (albeit,
hypothetically) a new brand's performance in terms of consumers' behaviour
within the product category. That is, instead of considering sales or share targets
according to what is required to meet profit or revenue objectives, Ehrenberg
explicitly evaluated what penetration and repeat buying levels would be required
to meet the targets. More important, he analysed how the required measures
compared with consumers' current purchase behaviour. Yet, although
Ehrenberg's work clearly illustrated how a hypothetical new brand would be
likely to behave and what its effect on the existing market could be,
comparatively few researchers have explored the questions Ehrenberg raised in
the context of an actual new brand launch.
In one of the first such studies, Wellan and Ehrenberg (1988) examined the
launch of a new brand, Shield. They suggested that Shield could have evoked
several quite different responses from consumers, ranging from strong trial
with low repeat purchase rates through to more limited trial, characterised by
subsequent high levels of repeat purchase. Their analyses revealed that
Shield's penetration growth was in line with Dirichlet norms, and that its
repeat purchase rate was consistent with its penetration level. Overall, they
concluded ``Shield looked like an established brand even during its initial
launch period'' (Wellan and Ehrenberg, 1988, p. 40).
Shield's performance with respect to other brands was also normal: it had a
very similar level of sole loyal buyers (14 per cent over 32 weeks against
13 per cent for other brands) and those buyers bought at a similar rate to
other brands' sole loyalists (3.5 purchases/32 weeks against 3.1 purchases/32
weeks). Despite Shield's unique attributes, it competed with other brands in
line with the Duplication of Purchase Law.
Shield quickly became the
market leader in its
category
These findings suggest that the ``settling-in'' period for Shield was very short
and the strong consistency between its behaviour and theoretical norms implies
that Dirichlet predictions could be used in ``dynamic'' as well as stationary
markets. However, as Wellan and Ehrenberg noted, ``Shield was `positioned to
succeed''' and it did'' (p. 36); it quickly became the market leader in its
category. Shield's success, and the strong level of support underpinning the
brand, raises the question of whether its behaviour can be generalised to other
less distinctive or well-supported brands. In other words, did the favourable
circumstances surrounding Shield catalyse its metamorphosis from a new brand
to market leader, and so make it a less typical ``new'' brand?
Wright and Sharp's (1999) work also explored how a new brand behaved
following launch and its effects on existing brands. Like Wellan and
Ehrenberg, they concluded that the new brand behaved like an existing brand
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within six to eight weeks and that there were no obvious short-term effects
on the marketplace. However, discontinuities in the data used mean Wright
and Sharp's conclusions require replication before they can be viewed as
robust confirmations of Wellan and Ehrenberg's conclusions.
More recently, Ehrenberg and Goodhardt (2000) analysed 23 successful new
brands to explore further the questions Wellan and Ehrenberg (1988) raised.
Using quarterly data for brands in several different product categories,
Ehrenberg and Goodhardt compared the penetration and average purchase
frequency for the new and existing brands and concluded that the average
purchase frequency following launch was very close to what the brand
ultimately achieved, although the penetration took longer to stabilise.
Overall, the first quarter data typically revealed penetration levels that were
lower than established brands and lower than those finally achieved by
quarter three, by which time penetration had levelled off.
New brands quickly reach a
regular repeat purchase
rate
Ehrenberg and Goodhardt's study suggests that new brands quickly reach a
regular repeat purchase rate, although the brands' final penetration level may
take longer to stabilise, somewhere around 30-36 weeks, according to their
results. However, their study used quarterly data; while these data provided
further evidence that new brands are quickly assimilated into the overall
market, the aggregation of the data into quarterly periods obscured specific
details of the rate at which the brands grew.
Overall, although the work in this area has begun to converge, further studies are
required to explore whether the findings advanced to date hold in other product
categories. In addition, more disaggregated data might provide additional
insights into how new brands grow and stabilise. This study thus aimed to:
.
compare pre-launch, launch and post-launch behaviour in a product
category into which a new brand had entered and, more specifically:
.
examine the growth in penetration levels and repeat purchase rates; and
.
investigate the duplication of purchases in this market.
Methodology
The data used in this study came from A.C. Nielsen's HomeScan Panel, a
panel of New Zealand households that was established in 1997. This panel
initially collected data from 500 Auckland households, but subsequently
expanded to become a fully national sample in early 1999. Respondents are
recruited to the Panel via an initial establishment survey in which they
indicate their willingness to participate. Those who agree to participate form
a pool from which a highly stratified sample representative of different
geographic areas, household size and composition, and income is drawn.
Consumers' behaviour
within categories
monitored
Respondents are provided with a scanning wand, which they use to scan
every grocery item they purchase, and a keypad into which they enter the
outlet from which they purchased, the number of units purchased and the
price paid for each item. This information enables consumers' behaviour
within categories and across stores to be monitored. Consumers' brand
repertoires, their repeat purchase behaviour, and their responsiveness to
variables such as price can all be estimated using these data.
Analysis of relevant trade publications revealed a number of brands that had
been launched recently. When selecting from these we were mindful to select
a category that had high penetration, so that the data set included a large
proportion of panel members. In addition, we sought a category that had a
short consumption cycle so that a high number of purchases were recorded
JOURNAL OF PRODUCT & BRAND MANAGEMENT, VOL. 12 NO. 1 2003
57
within the data collection period. Overall, we hoped to obtain several
observations for a high proportion of panel members.
First new brand to enter
category for over 12
months
For confidentiality reasons, specific details of the product category and brands
analysed cannot be released until the data are considered to be no longer
commercially sensitive. However, the category involved a frequently purchased
food product and contained several diverse brands. Similar in structure to the
biscuit market, this category contains some well-established brands that have
existed for several years as well as newer speciality and store brands. The
category is dominated by a small number of manufacturers each of which offers
several distinct brands. The brand selected for analysis was the first new brand
to enter this category for over 12 months prior to the data period analysed.
Results and discussion
Panel data can be used to explore a number of variables that provide insights
into a market's structure. In this section, we first examine brand X's penetration
and the rate at which buyers bought and re-purchased it to gain an understanding
of its performance; we then turn to explore its effects on the overall market.
Brand X was launched with strong promotional support into a product
category that is both cluttered and very competitive. The cumulative
penetration of brand X (i.e. the percentage of households buying Brand X at
least once); increased steadily over the 32-week period. Table I contains
details of brand X's penetration.
In early weeks of the
launch, brand X fell slightly
short of theoretical level
Table I compares brand X's actual performance with the theoretical norms
provided by the NBD model. Using the 16-week period as the base period to fit
the NBD, the model predicts that, in a single week, 4 per cent
of households would have purchased X and, by 32 weeks, 25 per cent of
households would have purchased it at least once. As Table I shows, in the early
weeks of the launch, brand X fell slightly short of the theoretical levels, although
these were close to the observed values from week 4. Overall, the penetration
growth for brand X was virtually normal from shortly after the brand's launch.
That is, brand X's penetration grew as predicted by the Dirichlet model from
very early in the data collection period, and considerably earlier than researchers
have suggested was normal (see Ehrenberg, 1991; Ehrenberg and Goodhardt,
2000, for further discussion of commonly held views about new brand entry).
By week 16, the period from which data were used to fit the model, accurate
predictions of penetration at week 32 were obtained.
The speed with which brand X was assimilated into the market is also clear
from Figure 1, which outlines the rate at which consumers trialled the brand.
The cumulative percentage of households trialling line represents the data
from Table I, while the bottom line represents the percentage of households
trialling brand X. Since the pool of potential triallists decreases over time,
the bottom line slopes downward and the pool of triallists appears to be close
to saturation by period seven. This finding also suggests that consumers
trialled brand X very quickly; trial peaked in period four (week 16) and
Percentage
Oa
Tc
Brand X
Notes:
a
Observed;
b
Percentage buying at least once in:
One week
Four weeks
16 weeks
32 weeks
2
4
8
10
(20)b
20
25
25
Used to fit NBD; c NBD theoretical values
Table I. Penetration growth: brand X and established brands
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JOURNAL OF PRODUCT & BRAND MANAGEMENT, VOL. 12 NO. 1 2003
Figure 1. Trial rate of brand X
declined steadily thereafter, suggesting that, by around the end of its first
quarter, brand X was close to the penetration level it ultimately achieved.
Table II examines the rate at which brand X's purchasers bought it. As Wellan
and Ehrenberg (1988) point out, the new brand's buyers could be either onceonly triallists or brand converts who go on to develop a repeat-purchase habit.
Brand X generally in line
with expected DJ pattern
In line with Ehrenberg and Goodhardt's (2000) findings, brand X also had a
``normal'' average purchase rate from shortly after launch; the only deviation in
average purchase rates came in week 32, when the observed rate of 5.7 was less
than the predicted rate of 6.2. However, further data are required to assess
whether this difference is sustained over time. It is not clear from these data
whether the deviation is real or simply a response to an ad hoc event, such as
increased promotional activity in an extremely competitive market. Overall,
both Tables I and II show that brand X settled down shortly after launch and its
behaviour was soon in line with the overall market structure.
Table III contains the average purchase frequencies of brand X and the other 15
major brands in this product category over the 32-week analysis period. Brand
X's market share of 3 per cent and its average purchase rate of 5.7 suggest that it
is slightly more popular than some other brands with a similar penetration level,
although it is still generally in line with the expected DJ pattern.
Brand stabilised within
three months of launch
Overall, the results in Table III reflect many of the generalisations Ehrenberg
(1991) outlined: market share varies widely (by a factor of over 30). while
average purchase frequency varies less (by a factor of four). There is a clear
DJ pattern evident reading down the Table: brands with higher penetration,
such as brands A, B and C, also have higher average rates of buying levels
while smaller brands, such as brands N and O, have lower repeat purchase
rates (Ehrenberg, 1988; Ehrenberg et al., 1990).
Four-weekly period
w
Repeat purchase
1
2
3
4
5
6
7
8
9
10
1.0
1.5
1.8
2.1
2.2
2.3
2.3
1.9
2.4
2.3
±
0.8
0.3
0.5
0.6
0.6
0.6
0.6
0.6
0.6
Table II. Average purchase rate growth
JOURNAL OF PRODUCT & BRAND MANAGEMENT, VOL. 12 NO. 1 2003
59
Brands
Percentage market share
Average purchase
frequency per buyer
3.0
5.7
17.4
16.6
13.9
9.1
7.1
5.4
5.3
4.6
3.4
3.3
2.7
2.7
2.7
1.0
0.5
8.9
6.9
6.5
7.9
5.7
6.2
5.0
6.1
5.6
2.3
4.2
3.4
4.4
2.3
2.1
Brand X
Brand
Brand
Brand
Brand
Brand
Brand
Brand
Brand
Brand
Brand
Brand
Brand
Brand
Brand
Brand
A
B
C
D
E
F
G
H
I
J
K
L
M
N
O
Table III. Average purchase frequencies over 32 weeks
Over half of brand X's buyers had become regular buyersAlthough there is
some volatility in the repeat buying rates of some of the smaller brands,
brand X's repeat purchase rate is similar to brands I and K, and is clearly in
line with the overall pattern represented in Table III. To analyse how well
brand X fitted the overall market structure, we used Dirichlet predictions for
a brand with the observed penetration and purchase frequency of brand X.
Table IV illustrates that brand X performed as predicted.
Brand X now looks very similar to the average brand; over the 32-week
period, its performance was very consistent with what would normally be
expected for a brand of this size, in this particular market. Further
examination of brand X's buyers provides additional evidence that the brand
stabilised within three months of its launch. Figure 2 details the number of
households that purchased brand X in one four-week period and that then
purchased again in the following four week period.
As Figure 2 reveals, just over 60 per cent of brand X buyers who had
purchased in one month had also purchased in the previous month, a pattern
that is evident throughout the analysis period and that is first apparent by the
end of quarter one (the third four-weekly figure). In other words, over half of
brand X's buyers had become regular, or even frequent, buyers of the brand.
This is further confirmed by the analysis presented in Table V, which shows
that the incidence of infrequent and frequent buyers of brand X was also
largely in line with NBD norms.
Brands
Percentage market share
O
Purchases per buyer of the brand
O
T
Brand X
3.0
5.7
5.7
Brand
Brand
Brand
Brand
Brand
3.4
3.3
2.7
2.7
2.7
5.6
2.3
4.2
3.4
4.4
6.4
6.4
6.3
6.3
6.3
I
J
K
L
M
Table IV. Dirichlet predictions for an average brand
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Figure 2. Repeat purchasing of brand X
Brand X's buyers are in fact
buyers of other brands
Table V suggests that brand X has attracted more frequent buyers than
expected; 17 per cent of households were predicted to buy brand X on seven
or more occasions within the 32-week period, whereas 27 per cent actually
did so. As expected, the proportion of households predicted to purchase less
frequently was lower than envisaged (66 per cent of households were
expected to purchase brand X fewer than four times in the 32 weeks, while
59 per cent actually did so). There are two possible explanations for this
result. First, the findings may be attributable to heavy launch promotions that
explicitly fostered repeat purchase and whose effect would normally be
expected to diminish over time. Alternatively, comparatively small
deviations such as this are quite normal in marketplaces and may reflect little
more than the ``noise'' that is typically present.
Examination of purchase duplication behaviour provides further evidence of
brand X's ``normal'' behaviour within this market. Given our knowledge of
consumers' brand repertoires (Ehrenberg, 1991), it would seem logical that
the 25 per cent of households who purchased brand X also purchased other
brands. Table VI contains the proportion of brand X buyers who also bought
other brands in this category.
These results show quite clearly that brand X's buyers are in fact buyers of
other brands who also occasionally buy brand X. According to the
Duplication of Purchase Law, the proportion of the other brands' buyers who
also bought brand X should vary in line with the other brands' penetration.
That is, the percentages reported should decline from brand A to brand O.
Several deviations
However, it is clear that, although this general pattern is present, it is
characterised by several deviations. Overall, the observed level of
duplication is higher than the theoretical values. Marked deviations occurred
with brands I, J, K, N and O, which have unexpectedly low or high levels of
duplication. The most obvious explanation of these results is that there is
some partitioning in this product category, with brand X seen by consumers
as more readily substitutable for some brands (such as brands J, K, L, N and
O), and functioning less as an alternative to other brands (such as brand I).
Examination of the brands present within the product category supports this
Percentage
1
2
Number of purchases in 32 weeks
3
4
5
6
7
8
9
10+
O
T
39
37
13
18
7
11
1
2
19
10
Brand X
8
8
4
5
2
4
2
3
5
2
Table V. Frequent and infrequent buyers of brand X
JOURNAL OF PRODUCT & BRAND MANAGEMENT, VOL. 12 NO. 1 2003
61
Percentage of brand X buyers who also bought . . .
O
T
Deviation
Brand
Brand
Brand
Brand
Brand
Brand
Brand
Brand
Brand
Brand
Brand
Brand
Brand
Brand
Brand
A
B
C
D
E
F
G
H
I
J
K
L
M
N
O
65
81
74
67
63
52
50
47
15
52
42
56
18
33
14
67
65
59
44
37
29
29
26
20
19
16
16
16
6
3
±2
16
15
23
26
23
21
21
±5
33
26
40
2
27
11
Table VI. Overlap with other brands in 32 weeks
explanation, since brands J, K, L, N and O share common features with brand
X, while brand I differs in several ways from X.
Conclusions
Overall, these results support several of the major findings reported by
Wellan and Ehrenberg (1988) and Ehrenberg and Goodhardt (2000),
although some differences are also apparent. Like these earlier studies, the
new brand, brand X, settled down early in the launch period. Our findings
suggest that, within two quarters of its launch, Brand X had reached a
relatively stable penetration and average repeat purchase rate, and that it was
in these respects no different from established brands.
Effect on established
brands not in line with
duplication prediction
For managers, these results imply that a brand's performance stabilises earlier
than previously thought and its movement up the DJ curve occurs quickly,
within about three months in the case of this brand from a high-frequency
category. Although this result clearly requires replication before it can be
generalised, it is consistent with other work that suggests new brands are
assimilated within existing markets more rapidly than researchers had hitherto
believed.
These findings also highlight how critical the launch period is to the brand's
future success. Assuming the product formulation has undergone careful
evaluation to identify any barriers to uptake, managers ought to ensure their
promotions stimulate trial and encourage repeat purchase. For example, in
the case of a food product such as X, in-store product-sampling booths are
known to foster trial, while continuity promotions may assist the
development of a repeat-purchase habit.
Partitions are easily
identified
However, while brand X's behaviour closely paralleled NBD predictions, its
effect on established brands was not in line with duplication predictions. One
possible explanation of this result is that the market was partitioned. This finding
implies that markets' structures need to be carefully considered before
diagnostic tools such as the NBD or law of purchase duplication are applied.
While such assessments may seem rather subjective, in many markets partitions
are easily identified (for example, breakfast cereals comprise muesli cereals;
``lite'' cereals; children's cereals, and porridges).
Overall, our results provide further evidence of regularities that Ehrenberg
and others have catalogued. More specifically, the findings lend support to
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JOURNAL OF PRODUCT & BRAND MANAGEMENT, VOL. 12 NO. 1 2003
the emerging view that new brands are quickly assimilated into a market, and
that even completely new brands soon display the characteristics of mature
brands and can be reliably treated as such.
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&
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63
This summary has been
provided to allow managers
and executives a rapid
appreciation of the content
of this article. Those with a
particular interest in the
topic covered may then read
the article in toto to take
advantage of the more
comprehensive description
of the research undertaken
and its results to get the full
benefit of the material
present
Executive summary and implications for managers and
executives
You do not get much time to make your product launch count
The ``Dirichlet model'' and the idea of ``double jeopardy'' are perhaps the
most depressing concepts in brand management. The idea not only that my
brand has fewer customers than the market leader but also that those
customers are less loyal is bad news. When the research then says that there
is not very much we can do about this problem, then the sensitive brand
manager might be tempted to slit his wrists.
Ehrenberg's extensive investigation of brand behaviour ± pointing out that it
is ``. . . perfectly normal for small brands to perform poorly relative to large
brands on loyalty measures'' ± applies to ``stable'' market situations rather
than to circumstances of market disruption. The question for Hoek et al. is
whether these depressing concepts remain in dynamic market situations.
New product development and the market
The launch of a new product must, ipso facto, disrupt market conditions.
After all, a choice has been presented to the consumer that was not present
prior to the product launch. It does not matter (in considering disruption to a
stable market) whether the new product is an entirely new brand or an
extension of an existing brand.
It is true to say that new product development has been treated as a
specialised field of marketing and brand management. Within the firm,
product development is all too often managed discretely and, as a result,
does not benefit from the insights emerging from regular brand management
and marketing. While it is widely recognised that new brands and brand
extensions will have a cannibalistic effect on the firm's existing brands, this
is usually treated in a straight line ± we get more new sales as a result of the
new or extended brand than we lose from the existing brand; therefore the
launch is a success.
However, there is the potential for a wider effect from new brands ± the
dynamics of a disrupted market suggest that changes to market share across
that market are possible as a result of disruption in a way that is not
achievable in a stable market because of the Dirichlet effect and double
jeopardy.
What happens when we launch our new brand?
Hoek et al. discover that new launches do disrupt the market but that this
disruption is short-lived as the market settles down to normality again.
Indeed, Hoek et al. conclude (rather depressingly) that ``. . . new brands are
quickly assimilated into a market and that even completely new brands soon
display the characteristics of mature brands and can be reliably treated as
such''.
The window of opportunity for us to reorder the structure of the market is
extremely limited (perhaps as short as two or three months) and this
reinforces the importance of the launch itself. We cannot sneak the product
out quietly and hope it will build up market share over time. Such an
approach suggests that the impact of market restabilisation and the
accompanying ``normal'' market effects (the Dirichlet model and double
jeopardy) will compromise any endeavour to secure market share.
In most consumer goods markets the two or three dominant brands stand
above the lesser brands. Since these big brands enjoy the overwhelming
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JOURNAL OF PRODUCT & BRAND MANAGEMENT, VOL. 12 NO. 1 2003
market share, it does not really matter how many smaller brands there are
competing with these big brands. The only way to succeed is to make a major
inroad into the share of one or other of these big brands during the launch
period itself.
Practicality suggests that breaking a market stranglehold in such a short
period of time will be a rare occurrence and extremely difficult to achieve
through the normal incremental brand and product development process.
So what can we do to break out of the ``stable market''?
First, there is nothing wrong with being a smaller brand so long as you
recognise the limitations and that the big brands will continue to eat into
your customer base. We should remember that the wider issue of consumer
behaviour applies ± consumers are not especially loyal to anything and, in
the main, select from a ``basket'' of brand choices. If you are in the
consumer's basket, you will continue to maintain sales. Less easily than the
market leading brands but more easily than brands outside the ``basket''.
Second, we can apply the idea that markets themselves can be broken down
into smaller components. This is not a question of premium quality or other
market sub-divisions and brand extension strategies but separating a part of
the market. Such a niche marketing strategy can succeed in protecting
market share within the wider market, since the Dirichlet effect and double
jeopardy will apply to competitors within the niche you dominate (even the
big brands).
Third, we can recognise that market share gains are marginal but, if we can
achieve positive marginal increases in share over a period of years, then we
can begin to compete on a level (or slightly less uneven) playing-field with
the big brands.
In many ways this study suggests that our launch strategies are now very
restricted. We have to go for rapid market penetration, since this is the only
way we can possibly take advantage of the market disruption created by new
launches. Equally, defensive strategies lead us towards aggressive response
to new launch, since this presents an opportunity during the unstable period
to secure sustainable changes in market share.
(A preÂcis of the article ``A new brand's behaviour in an established market''.
Supplied by Marketing Consultants for Emerald.)
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