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Market mechanics: A study to measure the effect of marketing instruments on the market position of fast-moving consumer goods
Market Mechanics: A Study to Measure the Effect of Marketing Instruments on the Market Position of Fast-Moving Consumer Goods Heino Stowsand, Axe1 Springer Publishing Group Wilfried Wenzel, Axe1 Springer Publishing Group
The objective of the research was to establish the various effects of the marketing instruments on the market shares of fast-moving consumer goods. The marketing instruments analyzed were pn’ce level, price changes, promotion, advertising, and media mix. Within the analysis the integrated effect of the distribution pattern had to be taken into account. The analysis of 186 brands and the data gathered over 7 three-month periods was taken from two models loosely based on Koyck. The results can be used to estimate the effectiveness of the marketing tools under scrutiny and their declining marginal revenue in the German market. A number of different efficiency ratings can be detected between the separate product categories under analysis. For marketing managers there are three particularly interesting points: (1) Brands with a low price index have only relatively small market advantages in comparison with expensive brands; (2) but price changes lead to very strong movements in the market shares; (3) in the case of brands with a small share of the advertising spent, both print and TV advertising have a similar effectiveness. With a larger share of advertising, the TV effectiveness declines because of saturation effects.
In recent years numerous econometric studies have been published which attempt to analyze the components of a marketing policy in order to define optimal allocation of the marketing budget to individual parameters, such as price, distribution, promotion, advertising, and packaging. The majority of the analyses refer to individual brands or small groups of brands, using only a few marketing components in each case. The reason for this is indicated by the difficulty in acquiring quantitative data for all marketing activities of the relevant brands. These studies include analyses by Dorfmann and Steiner [2], Koyck [ 31, Palda [ 51, and Telser [ 61, and deal chiefly with the Address correspondence to: Heino Stowsand, Market Research Department, Axe1 Springer Publishing Group, Kaiser-Wilhelm-Strasse6, 2000 Hamburg 36. JOURNAL OF BUSINESS RESEARCH 0 Elsevier North Holland,
Inc., 1979
243 0148-2963/79/03243-15$01.75
244
Heino Stiiwsand
and Wilfried
Wenzel
effect of advertising. Lambin’s exhaustive studies, on the other hand, cover eight European countries and data from 16 product groups [ 51. This study tries to overcome some restrictions resulting from poor data material: it is based on the market observations of almost 200 brands in the Federal Republic of Germany in 1974 and 1975 and accounts for the five most essential marketing instruments. Only a partial model is presented since not all the factors contribbuting to market success are available as quantitative data.
Objective This “Market Mechanics” model is devised to analyze the influence of some important marketing activities on volume market share. It is not the purpose of this model to answer the question how to maximize profits, but how to allocate the marketing budget to the marketing instruments and especially the advertising budget to the media categories, i.e. TV and print.
Data basis “Market Mechanics” is longing to 26 relatively sumer goods with a fast launches of new brands.
based on statistics covering 186 brands bestrongly advertised product groups of conturnover. The statistics include no data on The following data were available:
market shares (in terms of volume), prices (average prices per quarter), distribution (weighted), promotion, advertising expenditure (in DM) differentiated
for
-consumer magazines, -newspapers, -commercial TV, -commercial radio, for each brand and each quarter of the period of the survey- 19741975. The middle of this period, however, was dominated by a response to the energy crisis. This was at the beginning of 1975 when the number of unemployed reached one million. In reaction to this devel-
Market Mechanics
245
opment there was a short-term swing to low-price products. The atypical period (first and second quarter of 1975) was excluded from the analysis to give representative results.
The model The dependent variable market share calls not so much for the independent marketing variables in absolute terms as in relative terms. To give an example: advertising expenditure of ten million DM for brand A is no indication of its effect on its market share, unless one takes into account the competition. After all, if the competition spends as much on advertising, the effectiveness is reduced. Therefore “Market Mechanics” first of all converts all independent variables into either relative or share values. In doing so-i.e., by linking the activities of one brand with those of rival brands-one also reduces the number of independent variables, provided that we assume a normal competition activity level among those who share the market (“normalized attraction model,” cf. Bell, Keeney, and Little [l]). The price is converted into a price index number: in the quarter and product group under observation the price of each product is expressed as a percentage of the average price of all products whereas the average price is 100. This variable thus measures the relative price position of the individual brands within the product group. The promotion activities were assessed with the help of a special rating system, and each brand was assigned a number of points which take into account: The number of weeks in the quarter; The number of outlets and their effect on turnover; The kinds of activities performed by each brand. Each brand’s promotion points were expressed as a percentage of the total number of points of the product group. The resultant value is the promotion share. The advertising shares were obtained for each of the four media categories: consumer magazines, newspapers, commercial TV, commercial radio, based in this case on the total advertising expenditure per quarter within the product group. The distribution was available right from the beginning in the form of a suitable index value between 0 and 100%.
Heino Stilwsnnd and Wilfried Wenzel
246
All these variables in its general form: MS, = f(Pl,
PRt
are to be included ..
, PI,_,
,
, PI,_,
, PR,_,
, . . . . , PR,_k
ASMt , ASM,_ I , . ASN,
in the model, shown here
, ASN,_l
ASTV/,, ASTV,_
,.
, ASM,_k . , ASN,_k
1,
. . , ASTV,_k . . , ASR,_k
ASR,
, ASR,_l
,
Dt
, D,_,
,
. . , Dt_-k)
With
- j
MS,-j
: market
Pit-j
: price index number
PR,_i
: promotion
share in period t - j
ASM,_j
: advertising
share of magazines
ASNt_j
: advertising
share of newspapers
in period t - j
ASTV,__j : advertising
share of commercial
TV in period t - j
ASR,-._j
: advertising
share of commercial
radio in period t - j
D,-j
: distribution
forj=
share in period t
1,2 ,......,
- j
in period t
in period t - j
in period t - j k
In other words, the current market share MS, is to be explained on the basis of all marketing activities of the current and the past periods. The following hypotheses are made to get the model equation in an explicit form: Only two derived variables have to be incorDerived Magnitudes: porated into the model equation: (1) Absolute price index change as an index of pricing activities PI,_ j - PI,_ j- 1 . Through the selection of this absolute value the hypothesis is confirmed that consumers are thinking more in terms of absolute
247
Market Mechanics
price changes than of relative price changes. (2) Relative distribution change Dt-j/Dt-j_
1.
With this index the previous market share is weighted to increase its value of predicting the next market share. It was necessary to have a relative index of distribution change because it had to be incorporated into the relative figure of market share. Interactions between Variables: Each marketing activity can only have an impact if the brand is distributed. This implies there are always interactions between the distribution ratings and the marketing tools used. These interactions had been taken into account as follows: 1. Advertising shares had been coupled multiplicatively with the distribution, i.e., of the relative advertising outlays only that part is taken into account for calculating the new market share which can influence the purchases because of the availability at the retail level. 2. Promotion share could be used without being weighted with the distribution because our promotion index already includes distribution in terms of the number of retail outlets with promotional activities for the brands in question. 3. The price index change could be used also without direct distribution weights. As explained in point 4, this price index change is already weighted with the previous market share. Because of a strong correlation the old market share takes the distribution into account. 4. However, with the price index, unlike all the other marketing tools, there was no way of weighting this value with the distribution. This is due to the fact that if a cheap brand is linked to a high distribution, then it will achieve the same index as an expensive brand with a limited distribution. This problem could only have been solved by a model which first calculates a cumulative effect of all the marketing tools considered, and then reduces the effect by the corresponding incomplete distribution. Such a model was not included in this analysis because of its complexity. Nonlinear Effects of the Variables: The decreasing marginal revenue from marketing expenditure was taken into account by nonlinear functions of the independent variables. In order to keep
248
Heino Stb’wsand
and Wilfried
the number of unknown parameters small, a power function as aixl b i, was used. But there were two exceptions:
Wenzel
such
1. The price index change remains linear in the equation. As it can be negative, the above method is not applicable. 2. In the case of the variable “promotion share” the test runs repeatedly showed exponents in the region of 1, so that the value for the definitive run was fixed at 1, which meant the saving of one unknown parameter. The model equation is based Taking Time-Lags into Account: on Koyck who made the following basic assumption: marketing activities of the past influence the present success at a geometrically declining rate, i.e.,
where a2 = h * al a3
ai
=
X * a2
=A
‘ai_j
=
A2
. a,
=Xi-1
*al
,O
Because of
h represents
the general retention rate. In the transformation above the error terms and the intercept were left out for reasons of simplification. In order for this transformation to be correct, all coefficients in the distributed lag must have the same sign. These requirements were met, and this is to include promotions too, because on the one hand there are fast-moving consumer goods and on the other hand there are relatively long time periods (quarter).
249
Market Mechanics
The retention rate X is assumed to be applicable in the same way to all variables and is independent of the exponential weighting. Under the above hypotheses the following structual model, which is loosely based on Koyck can be defined:
MS, = X MS,_1 l
+
a1
-
+
a2
l
(PZ*jb 1 (PI, -- PI,_ 1)
+a3*PR, +a4 * (ASM, .D,)b4 +a5 * (ASN, 'D,)b5 +a6 +
a,
l
*
(ASTV, l Dt)b6 (ASR, .D,)b7
+ao. Three further modifications to this basic model equation to the equations used in “Market Mechanics”:
then led
1. Since with a given demand the market share grows as a result of increased distribution, MS,_ 1 was weighted by (Dt/LI- r ). 2. Moreover, it became apparent that the retention rate determined for all 186 brands produced over-valuations in the case of leading brands; additional exponential weighting appeared to be advisable. Hence,
MS,-, +(MSt_l
lDt/Dt-1)bO
3. An analysis of the marketing effect of the price index change showed that the effect on the market share of a given price change increases with the importance of the affected brand. This fact was taken into account by weighting the price index change with the strength of the brand. The index number defined for this purpose was the market share of the previous quarter The strictly which, the real
modifications admittedly led to an equation which, in mathematical terms, deviates from Koyck’s principle but as a result of detailed preliminary analyses, better reflects market conditions.
250
Heino Stb’wsand and Wilfried Wenzel
The global model used in the analyze the all-brands-group :
“Market
Mechanics”
study
to
+a3 *PRt + a4 - (ASM, - D,)b4 + a5 - (ASN, + a6 - (k?TV,
* D,)b5 * D,)b6
+ a7 - (ASR, - D,)b7 + a0 .
The solution of the equation was arrived at by means of the method of least-squares. An iterative modified Newton procedure on the first order was used. In mathematical-statistical terms, therefore, a multiple nonlinear regression analysis was carried out. The estimated dependent variable should be a figure between 0 and 100%. This requirement was satisfied without exception for the researched data. An additional comment on the data basic: “Market Mechanics” uses moving cross-section data, i.e. time series of cross-sections. The advantages are obvious: reducing the risk of colinearity, adequate degrees of freedom, the use of time-lags. On the other hand there is the danger of an estimation bias. Variables like seasonality or product-group-specific actions are omitted, although they could have some effects. These effects have been tested by adding dummy variables, which did not show any significant influence. Nevertheless the global model with its coefficients determined by pooling all 186 brands from 26 different product groups is susceptible to criticism because certain product-specific factors are not taken into account.
251
Market Mechanics
For this reason separate analyses-independent of the global analysis-were made in respect of the following eight product groups : 1. cleaning products;
2. detergents; 3. body-care products total; 4. body hygiene products; hair care products; ;: alcoholic drinks; 7. food ; 8. pet food; However, owing to the greatly reduced observation material for each product group, a simpler model with fewer parameters was made: All exponents were fixed at 1. The number of variables was reduced: Advertising shares in consumer magazines and newspapers were taken together (print media). Commercial TV and radio were defined as “electronic media.” The product-specific
equation therefore reads as follows: ASPRINT ASELECT
= ASM + ASN = ASTV
+ ASR.
model was used to analyze The following product-specific smaller groups of brands representing eight different product groups.
MSt=h*MS,_l.--
Dt
Dt- 1
+ a3 * PR, + a4 . ASPRINT,
* Dt
+ a5 * ASELECT,
* Dt
+ a, .
2.52
Heino Stb’wsand
and Wilfried
Wenzel
The results of this equation thus reflect the conditions of individual submarkets, but for the reason mentioned earlier they do not show any phenomena of declining marginal revenue. Moreover, one has the possibility of comparing these eight independent analysis results with one another and also, with certain restrictions, with the global model. So, in addition to the verification of the results by means of plausible values such as known market effects (at least as far as the sign is concerned), i.e., a verification based on practical experience, one can check the consistency of all analysis results. Moreover, one can look for the t-values. Yet, for the global model the t-values are not calculable because of the power functions. The Results All results are shown in Table 1 and Table 2. Example: In the product group detergents an increase of the price index change by 1 index point results in a loss of -2.486% X 50% = 1,243% of the market share if the previous market share of the brand was 50%. This effect is significant, because of a t-value = -5.86. It indicates the market forces of pricing activities in terms of market shares in percentage. Out of all results these are the eight most interesting findings for the marketing practioneers: 1. The retention rate in the global model indicates, that to abandon marketing activities leads to an average drop in the market share of 5% per quarter. 2. In product groups with strong pricing activities and promotion activities, consumers switch brands more readily. In this case the retention rates are smaller. For instance, the product group detergents shows a retention rate of 0.878, which corresponds to a lapse effect of approximately 12% per quarter. 3. Brands with a low price index have only relatively small market advantages compared to expensive brands. The cheaper a brand, the less the consumers accept differences in the price level to the even cheaper brands (see Figure 1). 4. The high coefficient of -0.904 for the price index change variable in the global model indicates the very positive effects achieved by price-offs, i.e., the effects on the volume if the market share is great. But as soon as the original price is restored, the gain in the market share is “automatically” lost. One can easily
253
Market Mechanics
Table 1: The Influence-Coefficients and the Marginal Revenue of the Marketing Parameters Calculated by the Global Model Covering All 186 Brands*
MS, = o.948.(lwS,1.~ )0.997 Dt-1 - o.o19.(&)0.‘= M&-l ~ 100
- 0.904.(PIf -H,,)* + 0.014.m*
+ 0.049*(z4SMt.Dt)‘=‘3 + 0.045 +W,.D,)1J”’ + 0.041+mV~‘DpJ57 + o.049+ISRt~Dt)0~96 + 0.613 * coefficient
of determination:
R2 = 0.96
The market effect of the price level
A
%
market forces
-0.4
brands
-0,l
I
io
cheap brands
price index
7b
ii0
GO
li0
The diagram shows that cheap brands wdh a price mdex number of 80 compared to an expanswe brand wth a price Index of 120 (see horizontal axis) has a market advantage Of 0 08 % of the market share (see vertical axis) The dngram shows moreover that the market effect of a price difference of 10 Index points an each case is lowr for two ex~a”slv.3 brands than for two cheap brands
FIGURE
1
total
pet food
food
alcoholic
drinks
hair care products
products
products
body hygiene
body-care
detergents
cleaning
product groups
t
t
t
t
t
t
t
t
+ 0.946 53.1
+ 0.946 60.5
+ 0.921 47.9
+ 0.916 48.1
+ 0.886 28.7
+ 0.924 74.9
+ 0.878 22.4
+ 0.938 31.2
retention rate
-0.004 -0.40
-0.009 -1.79
-0.007 0.85
-0.003 0.85
-0.006 1.56
-0.002 0.88
-0.027 -2.34
-0.013 -1.38
-0.888 2.90
-0.900 -4.19
-0.620 2.08
-0.599 2.74
-0.521 -1.87
-0.640 4.29
-2.488 -5.86
-2.638 7.69
+0.023 2.34
+0.014 1.60
+0.054 3.64
-0.014 1.17
-0.001 0.07
-0.005 0.64
+0.038 1.97
+0.016 1.19
studied
+0.030 1.54
+0.024 1.27
+0.045 2.45
+0.117 2.73
+0.141 2.85
+0.071 3.59
+0.134 1.69
+0.039 0.82
in product
group-specific
+0.009 0.44
+0.020 1.67
+0.021 0.52
-0.002 0.10
+0.012 0.64
+0.012 0.83
+0.099 2.95
+0.036 1.76
+0.666
+1.165
+0.593
+1.389
+1.687
+0.889
+2.639
+1.55
analyses
intercept
Groups Calculated
advertising share electronic media
in Eight Product
advertising share print
variables
promotion share
Parameters
Weights of the marketing
price index change
of the Marketing
price index number
Table 2: The Influence-Coefficients Product-Specific Model
99.2
98.0
97.0
96.8
95.1
96.4
96.2
96.4
R2
by the
Market Mechanics
255
verify that in the average of all brands price-offs produce a less favorable effect on the market share in terms of value than in terms of volume. 5. Price index changes have the greatest positive as well as negative effects on detergents and cleaning products. 6. Promotions have very different effects in the various product groups. The highest value of 0.054 is to be found in the alcoholic drink group. As alcoholic drinks on the one hand are bought relatively sporadically-that is to say without any fixed buying pattern-and on the other hand are typical equipment products, promotions seem to be a reminder to stock up one’s supplies. Thus, the size of the price reductions usually associated with promotions is not so decisive-as was shown by the small pricing coefficient. The situation seems to be different in the case of detergents: here too we find above-average promotion values-but accompanied by enormously high values for price change. In this group promotions mean primarily “This will save you money.” Promotions are of little value to body hygiene and hair care products: two coefficients are almost exactly zero and one even shows a negative trend. In these three product groups consumers react negligibly to differences in price level and at the same time only moderately to price changes. In these groups the buying decision is strongly influenced by considerations of quality and/or safety, and a buying decision of this sort seems not to be influenced positively by promotions. 7. In Germany the four media groups have roughly the same effectiveness as long as the budgets are small, i.e., as long as they do not produce saturation. But there are considerable differences in the saturation effects. The exponents of 0.67 of commercial TV indicates a very high saturation effect. (Commercial TV in the Federal Republic is exclusively transmitted during fixed block times which are not slotted into normal transmissions.) Figure 2 shows the declining marginal revenue of commercial TV. Experts consider that excessive repetition of very similar spot material and the relatively small coverage of the TV advertising blocks in Germany are one explanation for this saturation effect. 8. The product specific results show that the electronic media are less effective than the print media with respect to younger target groups. But where the target groups includes older individuals (for instance in the case of food), electronic and print media show similar results.
Heino Stiiwsand and Wilfried Wenzel
256
Efficiency of the media categories at 90% distribution %
Market forces
Radio
02
The ,,,a,ke, etfect o, crmventicm4 adverttsm9 depends on the d,str,bubon The d,a9ram shows the etttctency cures of the four media categories at a distnbutm of 90% The ho,tzontal axis ‘advertising share’ only 9~s as far as 5%. because there IS no reliable evidence concerning the ettect of hither radio and newspaper advertlsmg shares es thzse could onty be observed 8” very rare cases
FIGURE 2
Summary This research is based on observation of 186 branded fast-moving consumer goods during 1974 and 1975 in Germany. The models were designed to analyze the influence of some important marketing activities on the market share. The analyses cover on the one hand the total data, to determine, among others, saturation effects, and on the other hand they cover individual product groups. The models are loosely based on the Koyck formulation using a geometrical time lag. The results arrived at allow an estimation of the effectiveness of some important marketing parameters in the German market, such as the effectiveness of print and TV advertising on the brand performances.
257
Market Mechanics
References 1.
Bell, David E., Keeney, Ralph E., and Little, rem,J. Mark. Res. 12 (May 1975), 136-141.
2.
Dorfmann and Steiner, Rev., 64 (no. 5, 1954).
3.
Koyck, J. M., Distributed dam, 1954.
4.
Lambin, J. J., Advertising, Competition Time, North Holland, Amsterdam, 1976.
5.
Palda, K. S., The Measurement Englewood Cliffs, NJ,
6.
Telser, L. G., Advertising
Optimal
Advertising
John
and
D. C., A Market
Optimal
Am. Econ.
Quality,
Lags and Investment Analysis, North
Holland,
Amster-
and Market Conduct in Oligopoly Over
of Cumulative Advertising Effects,
and Cigarettes,
Share Theo-
Prentice-Hall,
J. Politi. Econ. 70, (5) 471-499.
The objective of the research was to establish the various effects of the marketing instruments on the market shares of fast-moving consumer goods. The marketing instruments analyzed were pn’ce level, price changes, promotion, advertising, and media mix. Within the analysis the integrated effect of the distribution pattern had to be taken into account. The analysis of 186 brands and the data gathered over 7 three-month periods was taken from two models loosely based on Koyck. The results can be used to estimate the effectiveness of the marketing tools under scrutiny and their declining marginal revenue in the German market. A number of different efficiency ratings can be detected between the separate product categories under analysis. For marketing managers there are three particularly interesting points: (1) Brands with a low price index have only relatively small market advantages in comparison with expensive brands; (2) but price changes lead to very strong movements in the market shares; (3) in the case of brands with a small share of the advertising spent, both print and TV advertising have a similar effectiveness. With a larger share of advertising, the TV effectiveness declines because of saturation effects.
In recent years numerous econometric studies have been published which attempt to analyze the components of a marketing policy in order to define optimal allocation of the marketing budget to individual parameters, such as price, distribution, promotion, advertising, and packaging. The majority of the analyses refer to individual brands or small groups of brands, using only a few marketing components in each case. The reason for this is indicated by the difficulty in acquiring quantitative data for all marketing activities of the relevant brands. These studies include analyses by Dorfmann and Steiner [2], Koyck [ 31, Palda [ 51, and Telser [ 61, and deal chiefly with the Address correspondence to: Heino Stowsand, Market Research Department, Axe1 Springer Publishing Group, Kaiser-Wilhelm-Strasse6, 2000 Hamburg 36. JOURNAL OF BUSINESS RESEARCH 0 Elsevier North Holland,
Inc., 1979
243 0148-2963/79/03243-15$01.75
244
Heino Stiiwsand
and Wilfried
Wenzel
effect of advertising. Lambin’s exhaustive studies, on the other hand, cover eight European countries and data from 16 product groups [ 51. This study tries to overcome some restrictions resulting from poor data material: it is based on the market observations of almost 200 brands in the Federal Republic of Germany in 1974 and 1975 and accounts for the five most essential marketing instruments. Only a partial model is presented since not all the factors contribbuting to market success are available as quantitative data.
Objective This “Market Mechanics” model is devised to analyze the influence of some important marketing activities on volume market share. It is not the purpose of this model to answer the question how to maximize profits, but how to allocate the marketing budget to the marketing instruments and especially the advertising budget to the media categories, i.e. TV and print.
Data basis “Market Mechanics” is longing to 26 relatively sumer goods with a fast launches of new brands.
based on statistics covering 186 brands bestrongly advertised product groups of conturnover. The statistics include no data on The following data were available:
market shares (in terms of volume), prices (average prices per quarter), distribution (weighted), promotion, advertising expenditure (in DM) differentiated
for
-consumer magazines, -newspapers, -commercial TV, -commercial radio, for each brand and each quarter of the period of the survey- 19741975. The middle of this period, however, was dominated by a response to the energy crisis. This was at the beginning of 1975 when the number of unemployed reached one million. In reaction to this devel-
Market Mechanics
245
opment there was a short-term swing to low-price products. The atypical period (first and second quarter of 1975) was excluded from the analysis to give representative results.
The model The dependent variable market share calls not so much for the independent marketing variables in absolute terms as in relative terms. To give an example: advertising expenditure of ten million DM for brand A is no indication of its effect on its market share, unless one takes into account the competition. After all, if the competition spends as much on advertising, the effectiveness is reduced. Therefore “Market Mechanics” first of all converts all independent variables into either relative or share values. In doing so-i.e., by linking the activities of one brand with those of rival brands-one also reduces the number of independent variables, provided that we assume a normal competition activity level among those who share the market (“normalized attraction model,” cf. Bell, Keeney, and Little [l]). The price is converted into a price index number: in the quarter and product group under observation the price of each product is expressed as a percentage of the average price of all products whereas the average price is 100. This variable thus measures the relative price position of the individual brands within the product group. The promotion activities were assessed with the help of a special rating system, and each brand was assigned a number of points which take into account: The number of weeks in the quarter; The number of outlets and their effect on turnover; The kinds of activities performed by each brand. Each brand’s promotion points were expressed as a percentage of the total number of points of the product group. The resultant value is the promotion share. The advertising shares were obtained for each of the four media categories: consumer magazines, newspapers, commercial TV, commercial radio, based in this case on the total advertising expenditure per quarter within the product group. The distribution was available right from the beginning in the form of a suitable index value between 0 and 100%.
Heino Stilwsnnd and Wilfried Wenzel
246
All these variables in its general form: MS, = f(Pl,
PRt
are to be included ..
, PI,_,
,
, PI,_,
, PR,_,
, . . . . , PR,_k
ASMt , ASM,_ I , . ASN,
in the model, shown here
, ASN,_l
ASTV/,, ASTV,_
,.
, ASM,_k . , ASN,_k
1,
. . , ASTV,_k . . , ASR,_k
ASR,
, ASR,_l
,
Dt
, D,_,
,
. . , Dt_-k)
With
- j
MS,-j
: market
Pit-j
: price index number
PR,_i
: promotion
share in period t - j
ASM,_j
: advertising
share of magazines
ASNt_j
: advertising
share of newspapers
in period t - j
ASTV,__j : advertising
share of commercial
TV in period t - j
ASR,-._j
: advertising
share of commercial
radio in period t - j
D,-j
: distribution
forj=
share in period t
1,2 ,......,
- j
in period t
in period t - j
in period t - j k
In other words, the current market share MS, is to be explained on the basis of all marketing activities of the current and the past periods. The following hypotheses are made to get the model equation in an explicit form: Only two derived variables have to be incorDerived Magnitudes: porated into the model equation: (1) Absolute price index change as an index of pricing activities PI,_ j - PI,_ j- 1 . Through the selection of this absolute value the hypothesis is confirmed that consumers are thinking more in terms of absolute
247
Market Mechanics
price changes than of relative price changes. (2) Relative distribution change Dt-j/Dt-j_
1.
With this index the previous market share is weighted to increase its value of predicting the next market share. It was necessary to have a relative index of distribution change because it had to be incorporated into the relative figure of market share. Interactions between Variables: Each marketing activity can only have an impact if the brand is distributed. This implies there are always interactions between the distribution ratings and the marketing tools used. These interactions had been taken into account as follows: 1. Advertising shares had been coupled multiplicatively with the distribution, i.e., of the relative advertising outlays only that part is taken into account for calculating the new market share which can influence the purchases because of the availability at the retail level. 2. Promotion share could be used without being weighted with the distribution because our promotion index already includes distribution in terms of the number of retail outlets with promotional activities for the brands in question. 3. The price index change could be used also without direct distribution weights. As explained in point 4, this price index change is already weighted with the previous market share. Because of a strong correlation the old market share takes the distribution into account. 4. However, with the price index, unlike all the other marketing tools, there was no way of weighting this value with the distribution. This is due to the fact that if a cheap brand is linked to a high distribution, then it will achieve the same index as an expensive brand with a limited distribution. This problem could only have been solved by a model which first calculates a cumulative effect of all the marketing tools considered, and then reduces the effect by the corresponding incomplete distribution. Such a model was not included in this analysis because of its complexity. Nonlinear Effects of the Variables: The decreasing marginal revenue from marketing expenditure was taken into account by nonlinear functions of the independent variables. In order to keep
248
Heino Stb’wsand
and Wilfried
the number of unknown parameters small, a power function as aixl b i, was used. But there were two exceptions:
Wenzel
such
1. The price index change remains linear in the equation. As it can be negative, the above method is not applicable. 2. In the case of the variable “promotion share” the test runs repeatedly showed exponents in the region of 1, so that the value for the definitive run was fixed at 1, which meant the saving of one unknown parameter. The model equation is based Taking Time-Lags into Account: on Koyck who made the following basic assumption: marketing activities of the past influence the present success at a geometrically declining rate, i.e.,
where a2 = h * al a3
ai
=
X * a2
=A
‘ai_j
=
A2
. a,
=Xi-1
*al
,O
Because of
h represents
the general retention rate. In the transformation above the error terms and the intercept were left out for reasons of simplification. In order for this transformation to be correct, all coefficients in the distributed lag must have the same sign. These requirements were met, and this is to include promotions too, because on the one hand there are fast-moving consumer goods and on the other hand there are relatively long time periods (quarter).
249
Market Mechanics
The retention rate X is assumed to be applicable in the same way to all variables and is independent of the exponential weighting. Under the above hypotheses the following structual model, which is loosely based on Koyck can be defined:
MS, = X MS,_1 l
+
a1
-
+
a2
l
(PZ*jb 1 (PI, -- PI,_ 1)
+a3*PR, +a4 * (ASM, .D,)b4 +a5 * (ASN, 'D,)b5 +a6 +
a,
l
*
(ASTV, l Dt)b6 (ASR, .D,)b7
+ao. Three further modifications to this basic model equation to the equations used in “Market Mechanics”:
then led
1. Since with a given demand the market share grows as a result of increased distribution, MS,_ 1 was weighted by (Dt/LI- r ). 2. Moreover, it became apparent that the retention rate determined for all 186 brands produced over-valuations in the case of leading brands; additional exponential weighting appeared to be advisable. Hence,
MS,-, +(MSt_l
lDt/Dt-1)bO
3. An analysis of the marketing effect of the price index change showed that the effect on the market share of a given price change increases with the importance of the affected brand. This fact was taken into account by weighting the price index change with the strength of the brand. The index number defined for this purpose was the market share of the previous quarter The strictly which, the real
modifications admittedly led to an equation which, in mathematical terms, deviates from Koyck’s principle but as a result of detailed preliminary analyses, better reflects market conditions.
250
Heino Stb’wsand and Wilfried Wenzel
The global model used in the analyze the all-brands-group :
“Market
Mechanics”
study
to
+a3 *PRt + a4 - (ASM, - D,)b4 + a5 - (ASN, + a6 - (k?TV,
* D,)b5 * D,)b6
+ a7 - (ASR, - D,)b7 + a0 .
The solution of the equation was arrived at by means of the method of least-squares. An iterative modified Newton procedure on the first order was used. In mathematical-statistical terms, therefore, a multiple nonlinear regression analysis was carried out. The estimated dependent variable should be a figure between 0 and 100%. This requirement was satisfied without exception for the researched data. An additional comment on the data basic: “Market Mechanics” uses moving cross-section data, i.e. time series of cross-sections. The advantages are obvious: reducing the risk of colinearity, adequate degrees of freedom, the use of time-lags. On the other hand there is the danger of an estimation bias. Variables like seasonality or product-group-specific actions are omitted, although they could have some effects. These effects have been tested by adding dummy variables, which did not show any significant influence. Nevertheless the global model with its coefficients determined by pooling all 186 brands from 26 different product groups is susceptible to criticism because certain product-specific factors are not taken into account.
251
Market Mechanics
For this reason separate analyses-independent of the global analysis-were made in respect of the following eight product groups : 1. cleaning products;
2. detergents; 3. body-care products total; 4. body hygiene products; hair care products; ;: alcoholic drinks; 7. food ; 8. pet food; However, owing to the greatly reduced observation material for each product group, a simpler model with fewer parameters was made: All exponents were fixed at 1. The number of variables was reduced: Advertising shares in consumer magazines and newspapers were taken together (print media). Commercial TV and radio were defined as “electronic media.” The product-specific
equation therefore reads as follows: ASPRINT ASELECT
= ASM + ASN = ASTV
+ ASR.
model was used to analyze The following product-specific smaller groups of brands representing eight different product groups.
MSt=h*MS,_l.--
Dt
Dt- 1
+ a3 * PR, + a4 . ASPRINT,
* Dt
+ a5 * ASELECT,
* Dt
+ a, .
2.52
Heino Stb’wsand
and Wilfried
Wenzel
The results of this equation thus reflect the conditions of individual submarkets, but for the reason mentioned earlier they do not show any phenomena of declining marginal revenue. Moreover, one has the possibility of comparing these eight independent analysis results with one another and also, with certain restrictions, with the global model. So, in addition to the verification of the results by means of plausible values such as known market effects (at least as far as the sign is concerned), i.e., a verification based on practical experience, one can check the consistency of all analysis results. Moreover, one can look for the t-values. Yet, for the global model the t-values are not calculable because of the power functions. The Results All results are shown in Table 1 and Table 2. Example: In the product group detergents an increase of the price index change by 1 index point results in a loss of -2.486% X 50% = 1,243% of the market share if the previous market share of the brand was 50%. This effect is significant, because of a t-value = -5.86. It indicates the market forces of pricing activities in terms of market shares in percentage. Out of all results these are the eight most interesting findings for the marketing practioneers: 1. The retention rate in the global model indicates, that to abandon marketing activities leads to an average drop in the market share of 5% per quarter. 2. In product groups with strong pricing activities and promotion activities, consumers switch brands more readily. In this case the retention rates are smaller. For instance, the product group detergents shows a retention rate of 0.878, which corresponds to a lapse effect of approximately 12% per quarter. 3. Brands with a low price index have only relatively small market advantages compared to expensive brands. The cheaper a brand, the less the consumers accept differences in the price level to the even cheaper brands (see Figure 1). 4. The high coefficient of -0.904 for the price index change variable in the global model indicates the very positive effects achieved by price-offs, i.e., the effects on the volume if the market share is great. But as soon as the original price is restored, the gain in the market share is “automatically” lost. One can easily
253
Market Mechanics
Table 1: The Influence-Coefficients and the Marginal Revenue of the Marketing Parameters Calculated by the Global Model Covering All 186 Brands*
MS, = o.948.(lwS,1.~ )0.997 Dt-1 - o.o19.(&)0.‘= M&-l ~ 100
- 0.904.(PIf -H,,)* + 0.014.m*
+ 0.049*(z4SMt.Dt)‘=‘3 + 0.045 +W,.D,)1J”’ + 0.041+mV~‘DpJ57 + o.049+ISRt~Dt)0~96 + 0.613 * coefficient
of determination:
R2 = 0.96
The market effect of the price level
A
%
market forces
-0.4
brands
-0,l
I
io
cheap brands
price index
7b
ii0
GO
li0
The diagram shows that cheap brands wdh a price mdex number of 80 compared to an expanswe brand wth a price Index of 120 (see horizontal axis) has a market advantage Of 0 08 % of the market share (see vertical axis) The dngram shows moreover that the market effect of a price difference of 10 Index points an each case is lowr for two ex~a”slv.3 brands than for two cheap brands
FIGURE
1
total
pet food
food
alcoholic
drinks
hair care products
products
products
body hygiene
body-care
detergents
cleaning
product groups
t
t
t
t
t
t
t
t
+ 0.946 53.1
+ 0.946 60.5
+ 0.921 47.9
+ 0.916 48.1
+ 0.886 28.7
+ 0.924 74.9
+ 0.878 22.4
+ 0.938 31.2
retention rate
-0.004 -0.40
-0.009 -1.79
-0.007 0.85
-0.003 0.85
-0.006 1.56
-0.002 0.88
-0.027 -2.34
-0.013 -1.38
-0.888 2.90
-0.900 -4.19
-0.620 2.08
-0.599 2.74
-0.521 -1.87
-0.640 4.29
-2.488 -5.86
-2.638 7.69
+0.023 2.34
+0.014 1.60
+0.054 3.64
-0.014 1.17
-0.001 0.07
-0.005 0.64
+0.038 1.97
+0.016 1.19
studied
+0.030 1.54
+0.024 1.27
+0.045 2.45
+0.117 2.73
+0.141 2.85
+0.071 3.59
+0.134 1.69
+0.039 0.82
in product
group-specific
+0.009 0.44
+0.020 1.67
+0.021 0.52
-0.002 0.10
+0.012 0.64
+0.012 0.83
+0.099 2.95
+0.036 1.76
+0.666
+1.165
+0.593
+1.389
+1.687
+0.889
+2.639
+1.55
analyses
intercept
Groups Calculated
advertising share electronic media
in Eight Product
advertising share print
variables
promotion share
Parameters
Weights of the marketing
price index change
of the Marketing
price index number
Table 2: The Influence-Coefficients Product-Specific Model
99.2
98.0
97.0
96.8
95.1
96.4
96.2
96.4
R2
by the
Market Mechanics
255
verify that in the average of all brands price-offs produce a less favorable effect on the market share in terms of value than in terms of volume. 5. Price index changes have the greatest positive as well as negative effects on detergents and cleaning products. 6. Promotions have very different effects in the various product groups. The highest value of 0.054 is to be found in the alcoholic drink group. As alcoholic drinks on the one hand are bought relatively sporadically-that is to say without any fixed buying pattern-and on the other hand are typical equipment products, promotions seem to be a reminder to stock up one’s supplies. Thus, the size of the price reductions usually associated with promotions is not so decisive-as was shown by the small pricing coefficient. The situation seems to be different in the case of detergents: here too we find above-average promotion values-but accompanied by enormously high values for price change. In this group promotions mean primarily “This will save you money.” Promotions are of little value to body hygiene and hair care products: two coefficients are almost exactly zero and one even shows a negative trend. In these three product groups consumers react negligibly to differences in price level and at the same time only moderately to price changes. In these groups the buying decision is strongly influenced by considerations of quality and/or safety, and a buying decision of this sort seems not to be influenced positively by promotions. 7. In Germany the four media groups have roughly the same effectiveness as long as the budgets are small, i.e., as long as they do not produce saturation. But there are considerable differences in the saturation effects. The exponents of 0.67 of commercial TV indicates a very high saturation effect. (Commercial TV in the Federal Republic is exclusively transmitted during fixed block times which are not slotted into normal transmissions.) Figure 2 shows the declining marginal revenue of commercial TV. Experts consider that excessive repetition of very similar spot material and the relatively small coverage of the TV advertising blocks in Germany are one explanation for this saturation effect. 8. The product specific results show that the electronic media are less effective than the print media with respect to younger target groups. But where the target groups includes older individuals (for instance in the case of food), electronic and print media show similar results.
Heino Stiiwsand and Wilfried Wenzel
256
Efficiency of the media categories at 90% distribution %
Market forces
Radio
02
The ,,,a,ke, etfect o, crmventicm4 adverttsm9 depends on the d,str,bubon The d,a9ram shows the etttctency cures of the four media categories at a distnbutm of 90% The ho,tzontal axis ‘advertising share’ only 9~s as far as 5%. because there IS no reliable evidence concerning the ettect of hither radio and newspaper advertlsmg shares es thzse could onty be observed 8” very rare cases
FIGURE 2
Summary This research is based on observation of 186 branded fast-moving consumer goods during 1974 and 1975 in Germany. The models were designed to analyze the influence of some important marketing activities on the market share. The analyses cover on the one hand the total data, to determine, among others, saturation effects, and on the other hand they cover individual product groups. The models are loosely based on the Koyck formulation using a geometrical time lag. The results arrived at allow an estimation of the effectiveness of some important marketing parameters in the German market, such as the effectiveness of print and TV advertising on the brand performances.
257
Market Mechanics
References 1.
Bell, David E., Keeney, Ralph E., and Little, rem,J. Mark. Res. 12 (May 1975), 136-141.
2.
Dorfmann and Steiner, Rev., 64 (no. 5, 1954).
3.
Koyck, J. M., Distributed dam, 1954.
4.
Lambin, J. J., Advertising, Competition Time, North Holland, Amsterdam, 1976.
5.
Palda, K. S., The Measurement Englewood Cliffs, NJ,
6.
Telser, L. G., Advertising
Optimal
Advertising
John
and
D. C., A Market
Optimal
Am. Econ.
Quality,
Lags and Investment Analysis, North
Holland,
Amster-
and Market Conduct in Oligopoly Over
of Cumulative Advertising Effects,
and Cigarettes,
Share Theo-
Prentice-Hall,
J. Politi. Econ. 70, (5) 471-499.