In this era of intense competition, both world-wide and domestic, business firms of all sizes and varieties have become more and more concerned with the market-share figures they achieve in the marketplace. From our personal experience, some managers appear interested as much, if not more, in market shares as profits or returns on investment. For product and brand managers in particular, the sense of urgency associated with the gains and losses of market shares for the product/brand in their charge may be likened to what winning or losing of a war front means to generals or the general staff. Though such military analogies are not to be taken literally, one fact seems obvious: Market shares command the attention of business managers as key indices for measuring the performance of a product or brand in the marketplace. Many individuals in business indeed keep a close watch over day-by-day changes in market shares, so much so that market-share movement to them is almost synonymous to market information.
To the extent that market shares are used as market performance indices, it is clearly desirable for the individuals concerned to have thorough knowledge of the processes which generate market-share figures and to be able to analyze the impact of their own actions on market shares, as well as their profit implications. Lacking such knowledge, one might be tempted to oversimplify the cause-and-effect relationships between market shares and marketing variables, or to equate market shares to profitability (a not unusual tendency even among seasoned businessmen) and fall into deadly traps of blindly competing for market shares for their own sake. Despite the obvious importance associated with it in many firms, the approach of many managers to market-share analysis may be described as casual.
The interest in market-share analysis has received new impetus in recent years, especially since the advent of optical-scanning systems - POS (point of sale) systems - at the retail level. A POS system collects sales records (essentially in the form of customer-by-customer receipts) at check-out counters of retail establishments with optical scanners which read bar codes of merchandise labels. It then puts the sales records in a computer (i.e., store controller ) where sales records are tabulated into item-by-item sales summaries. POS systems were originally introduced in retail stores to improve the efficiency and accuracy of store personnel at the check-out counters and in the backroom and have achieved a considerable degree of success in speeding up check-out operations and in improving inventory control. POS -generated sales data also have an obvious potential as the database for merchandising and store management. Some authors even suggest that, by linking POS systems with electronic ordering systems (EOS ) which handle order processing as well as inventory control, store automation will soon become a reality.
POS systems also open up a new source of market-share data at the retail level for manufacturers of consumer products. POS data have many advantages over traditional sources of market-share information such as retail audit, warehouse withdrawal, and consumer panel data, in that they are fast, accurate, low cost, and detailed. Already various marketing-research agencies are in the business of gathering POS data from a sample of stores and supplying manufacturers with summaries of them. In addition, several research agencies operate optical-scanner panels (or scanner panels ) of consumers in a number of communities which generate purchase histories per household. It is often pointed out that scanner panels are superior to the traditional diary panels in their accuracy and speed. (We will give a more detailed description of those and other data collection techniques in Chapter 4.)
Though much has been said of the wonderful powers of POS systems, we believe that so far POS data have been underutilized for marketing-planning purposes. Considering the apparent advantages of POS data, this statement may seem improbable to the reader. Yet the current usage of POS data, whether it be in inventory control or in merchandising planning, is mainly on an item-by-item basis, and little attention has been paid to the interrelationships between items. Single-item summaries and analyses of POS data are no doubt useful for many purposes, but they ignore the complex pattern of interactions which exist among product classes, brands within a product class, and items within a brand. Market-share analysis focuses on the competitive interrelations among brands, and is one area in which POS data are not fully utilized. In our opinion, the chief reason why the application of POS data is so lagging in the analysis of competitive interactions, including market-share analysis, is that the analyst's understanding of the nature of POS data is lacking. How does one describe the competitive structure among products, brands, and items within a store? Unless we understand clearly the process that generates POS or scanner-panel data, we will not be able to analyze them correctly. Here is a case for having a clear conception before we can embark on market-share analysis.
Consider the following conversation between the marketing V.P. (or division manager) and a brand manager.
This conversation is, of course, hypothetical (we hope that no real-world brand manager would be this naive!), but points to the complexities and difficulties associated with market-share analysis. Much confusion seems to arise from the fact that the market share for a firm's brand/product is affected not only by the firm's own actions but also by the actions of competitors. Moreover, there are influences of such factors as seasonal variations in sales and general economic conditions which affect the performance of all brands in the industry. The plight of the brand manager in the above example may be attributable to his inability to isolate the effects of his firm's own actions from the effects of all other variables including competitors' actions. What is lacking here is a systematic approach to market-share analysis.
In part, the preoccupation of many managers with market shares may be the making of the strategic market-planning school of marketing thought, which has been promulgated by such authors as Abell and HammondAbell, D. F. and J. S. Hammond [1979], Strategic Market Planning: Problems & Analytical Approaches , Englewood Cliffs, New Jersey: Prentice-Hall.and Buzzell,Robert D. Buzzell, Bradley T. Gale & Ralph G. M. Sultan [1975], ``Market-Share - A Key to Profitability,'' Harvard Business Review , January-February, 97-106.since the 1970s. They emphasize the importance of market shares so much that, if one accepts their tenets naively, securing market shares will be the primary objective in any firm's marketing strategies. This stance may be justifiable in a new, growing industry, since, according to experience analysis which forms the core of their theory, maintaining the market-share leadership in a new, growing industry will automatically assure a firm the largest experience (i.e., cumulative sales volume) and therefore the lowest production and marketing costs. However, the determination to pursue the largest share in an industry may not be optimal in those situations where the market for a product is already at a saturation level, for the share expansion for one brand may be achieved only at excessive costs in such a situation. Market-share leadership is clearly not a universal objective in every situation.
Though this is an admittedly simplistic description of the strategic market-planning concept, we need to examine more carefully whether such importance attached to market-share expansions is justified, as this school of marketing thought suggests. Again, we will need a conceptual framework in order to perform such an examination.
Market-share analysis is inherently more complex than the sales analysis for a single product/brand simply because one is required to take the competitive factors into account. To a mind which is used to analyzing the performance of one product/brand at a time, the complexity involved in market-share analysis, as described in the preceding paragraphs, might look formidable indeed. However, it is the authors' view that the difficulties lie in the analyst's state of mind rather than in the lack of analytical methodology. We posit that the analyst's task will be greatly facilitated, if he/she has a reasonably accurate view of the market and competition. In a sense, taking a product/brand at a time for analysis represents an extremely distorted view of the market, in which the analyst implicitly assumes that the product/brand (either word would mean the same in this case) partially monopolizes the market. Any strategy or plan based on this implicit assumption is bound for failure sooner or later, if the structure of actual markets tend toward what economists call oligopoly and monopolistic competition . Many have learned this fact, in some cases painfully, by watching their best-laid plans crumble in front of their eyes because of competitors' unexpected responses. It is like taking a picture of competition through a telephoto lens. While one brand may be in excellent focus, the foreground or background are either excluded or out of focus. As pretty as the picture may seem, too much is ignored by this view.
In this book we shall attempt to provide those individuals who are interested in analyzing market shares for some products or brands with a framework for analysis, which in our opinion promises a most meaningful view of the market and competitive structure. The reader will find various models of the market and competition, the most prominent of which is called a ``Multiplicative Competitive Interaction (MCI) Model'' or an ``Attraction Model'' and has the following general structure.
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(1.1) | |||||||||||||||||||||
where:
A detailed discussion of the above model will be given in Chapter 2, and therefore we will only note here that the model is based on a simple idea that market shares are equal to the shares of attractions of respective brands, and that marketing instruments interact to determine, at least partially, the attraction of each brand. We will illustrate throughout this book how using appropriate market-share models such as the MCI model not only increases the analyst's understanding of the market and helps the planning process but also facilitates the analyst's tasks considerably in doing so. Furthermore, we will show that the communication of the results of market-share analysis within a firm will be greatly facilitated by the adoption of a meaningful model. As an illustration consider the following conversation between Marketing V.P. and Brand Manager in another firm.
The above conversation is, of course, hypothetical, and may sound suspiciously like science fiction. The authors have no intention of creating an illusion that marketing decision making can be mechanized or even automated by using computers. However, note that in this case both the product manager and brand manager are looking at the situation from the same analytical framework. In fact, a computer is not an essential element in this conversation. Although the marketing workbench as a set of powerful computer-based tools and models is a growing reality,See McCann, John M. [1986], The Marketing Workbench: Using Computers for Better Performance , Homewood, IL: Dow Jones-Irwin.no workstation or personal computer will help if the individuals involved do not share a common understanding of the market and competition.
The persons in the above conversation are primarily thinking in terms of elasticities (an economic concept which many readers no doubt consider as abstract as demand curves). They are communicating well enough because both of them have the same understanding of this term. We may add that nothing is said about models in this conversation. The concept of elasticities is generic in the sense that it does not depend on a specific model of the market or competition. A model comes into the picture when one tries to estimate actual elasticities or predict future ones. The MCI (attraction) model mentioned above will give one set of estimates; other models will give other estimates. To the extent that one model is accepted by the managers in a firm as a meaningful view of the market and competition, elasticity estimates based on the model will be also acceptable as the basis for marketing decisions. This is why we believe that decision processes, as well as communication processes, in a firm will be greatly facilitated by the organizational acceptance of a model of the market and competitive structure.
Formally adopting an analytical framework has another advantage: it will help the firm to build an effective market information system . The emphasis in this marriage between information-systems concepts and market-response modeling is simply that structuring data so that they are relatable to consumer demand provides a powerful organizing principle for the information system and provides the potential for addressing issues such as the effectiveness of marketing efforts. As will be discussed in more detail later, what data should be collected and how they are analyzed are largely dependent on the firm's view of the market and competition. If, for example, the market is seen as virtually consisting of a single segment, the analyst's task will be greatly simplified. Or if the firm sees competition as having negligible effects on the performance of its product/brand, there will be no sense in collecting competitive data. But such simplistic views are often inadequate. If the firm accepts that there are distinct and heterogeneous consumer segments and that the marketing instruments of the firm and its competitors all interact to create the attractiveness of the products/brands to these segments, the analyst will have to collect the types of data which will allow him/her to perform more comprehensive analyses of the effectiveness of the firm's marketing activities in a competitive environment. Thus an analytical framework, i.e., a view of the market and competition, determines essentially the requirements for a firm's information and analysis system.
The reader should be reminded that there is no single correct analytical framework for market-share analysis. The preponderance of the MCI model (or any other model for that matter) in this book should not suggest the authors' insistence that this model is the correct view of the market. A model is merely one approximation to the reality of the market and competition, and it would be unwarranted to insist one model represents the truth . Even though we believe that the MCI model allows us rich interpretation of market-share data without imposing heavy demand on our analytical capacity, the analyst will have to choose consciously among several alternative representations (i.e., models) of the structure of market and competition which fits best the specific conditions he/she faces. This requires a thorough understanding of the characteristics and implications of each model. In the next two chapters of this book, basic concepts necessary to analyze market-share data and several alternative models will be explained as comprehensively as possible. The deeper the reader's understanding of necessary concepts and models, the easier it will be for him/her to follow the subsequent discussions of data requirements and collection techniques (Chapter 4) and parameter-estimation techniques (Chapter 5).
Before we begin to describe the methodology of market-share analysis, it is perhaps beneficial to define its basic characteristics so that the reader will not be misled as to its relevance and eventual applicability to his or her own problems. The three key characteristics are that market-share analysis is competitive , descriptive as well as predictive, and profit-oriented .
First, market-share analysis is competitive . This implies that the effects of one's actions must be analyzed in conjunction with the market positions and actions of competitors. (In economic jargon, the marginal effect of a marketing variable is a function of competitors' actions and their market shares.) This also means that one will have to distinguish those factors which affect one's product/brand from more general factors which affect the entire industry (e.g., seasonality in product usage, and business and economic conditions). Finally, this means that, given competitors who are free to adopt any marketing strategies, market-share prediction also involves the prediction of competitors' future actions, which is a difficult undertaking in itself. Many experienced managers know that their best-laid plans mean little if they fail to predict correctly the courses of action the competitors are going take.
At this juncture we emphasize that the market-share analysis we explore in this book is basically for products in either the growth or maturity (i.e., saturation) stages of their product life cycle. In this context, it is important for one to distinguish between a new brand for a firm in an established industry and an entirely new product which is creating a new industry. We do not belittle the importance of being able to predict the future shares for a new product, but we envision that the analytical approach for predicting the performance of a new product is substantially different from that for an established product. When a radically new product is introduced by a firm in the market, it usually holds a temporarily monopolistic position due to technological advantages or legal protection (i.e., patents). Because the structure of the market and competition in the introductory stage of the product life cycle is so different from that in either the growth or maturity stages, the approaches to market-share analysis in this book may not be directly applicable to new products.
Second, market-share analysis must be descriptive as well as predictive. A common tendency among business managers is that if they can make good forecasts of market shares, they expect nothing more. The ability to make accurate predictions of future shares is indeed a major contribution of market-share analysis, but we do not believe that it is enough. Market-share analysis should provide the managers with much-needed information on the structure of the market and competition and the influence of marketing actions on brand performance - all of which are indispensable for them to be able to establish viable marketing strategies. An example is given by the competitive-map analysis of Chapter 6. Knowing that competitor A is vulnerable to our actions, but competitor B is not, or knowing one's share is much affected by the actions of competitor C, clearly gives a manager a better sense of competitive moves he/she can make in order to deal successfully with competitors.
Third, market-share analysis is profit-oriented in the sense that any firm is interested in not only market-share movement, but also its profit consequences. One might talk about a plan to expand the market share for a firm's product/brand, by improving quality, reducing price, advertising more, employing more sales persons, etc. But the key question obviously is, ``Is it worth our effort to increase the market share?'' Experience analysis , for example, tells us to try to expand one's market share if the increase in share allows the firm to have the leading position on the experience curve , that is, if the resultant share is the largest among the competitors. This in turn suggests that for firms with currently small shares the mad rush to become the industry leader may have dire consequences. The ability to predict the cost of achieving a certain market-share level should be as valuable for a firm as the ability to estimate the likelihood of achieving that share. We will return to this theme in the brand-planning exercises in Chapter 7 of this book.
Based on the above characterization, we assert that the basic goal of market-share analysis is to evaluate the effectiveness of marketing actions in a competitive environment. We propose the following scenario for the process of market-share analysis. (See also Figure 1.1.)
Figure 1.1: The Process of Market-Share Analysis
This stage is for the selection of appropriate models for describing market-share movement and changes in overall (industry) sales volume. (In a simplest specification, a firm's sales volume is equal to the product of industry sales volume and its market share.) At the time when a firm is developing a system for market-share analysis, this stage is indispensable since the models determine data requirements in the data-collection stage. If the firm already has an ongoing data stream, the specification task becomes one of choosing a model which will allow the analyst to assess the impact of the variables in the data stream on demand. After the initial specification, this stage is only repeated when the analyst feels that the underlying structure of the market and competition is changing or has changed, and that it is necessary to modify or recalibrate the model. Modification may also be motivated by new data becoming available or by the desire for a more comprehensive explanation or assessment. Techniques for this specification step, such as time-series and experimental analyses, can help address issues concerning the duration of marketing effects and whether marketing instruments interact.
Market-share data may be obtained from many sources. A traditional source was the so-called retail store-audit data, but since the adoption of optical scanners (i.e., POS systems) more data at the retail level are being generated by scanners. Wholesale warehouse withdrawals are also used as a source of market-share data for many consumer products. Consumer surveys and diary panels are sometimes used for market-share estimation. For many firms the only way to get own market-share figures is to divide the firm's own sales volume by what it can estimate of the industry sales volume for the same period and area.
One critical problem with the data collection stage for market-share analysis is the need for information on marketing activities of competitors as well as the firm's own activities. Any reasonably designed market information system should be able to meet adequately the information requirement on the firm's own activities, but the information on competitors' activities is a different matter. This requires careful monitoring of competitors' activities in the market and compiling a comprehensive file for each competitor.
Optical scanner data at the retail level, if they are available, are capable of supplying competitive information for a limited set of marketing variables such as shelf price and store displays. These data may be combined with available information on newspaper features, and manufacturers' and stores' coupons. Advertising expenditures or benchmarks such as target-audience rating points (TARPs) or gross rating points (GRPs) can be used to assess how these efforts relate to demand. Scanner panels can be tapped for measures such as brand inventories in panel households, indices of brand loyalty or time-since-last-purchase. These panels are also rich sources for potential segmentation by usage frequency or style, or demographic characteristics.
Simple, graphical summary relating market shares to other collected data can reveal a great deal about the nature of market response and competition.
Once necessary data are collected for an adequate number of periods and/or areas (to give sufficient degrees of freedom), the analyst can proceed to:
1. Estimation of Model Parameters: Once the appropriate models are chosen, the next step is to estimate the parameters of the models. Statistical techniques such as log-linear regression analysis and maximum-likelihood estimation will be used in this step. Even though the model specification is not changed, it may be necessary to re-estimate parameters periodically. This is desirable not only for the purpose of adapting parameter values to changing conditions but also for the purpose of improving the accuracy of estimates.
2. Conversion to Decision-Related Factors: Model parameters themselves provide the analyst or manager with little information as to the structure and occurrences in the market and competition. From a decision maker's viewpoint, more immediately useful information may be the responsiveness of market shares toward marketing activities of the own firm and competitors as summarized by market simulators. Or it may be the visual presentation (map) of the relative market positions of competing products/brands. It takes some ingenuity to produce a representation that is easily understood by managers who are not quantitatively oriented.
The planning stage may be divided into two steps.
1. Strategy Formulation: In this step the information obtained in the analysis stage is used for the formulation of marketing strategies.In this book the term strategy is used in a rather loose sense, and strategy and tactics will be used interchangeably. Since an understanding of tactical response is fundamental to strategy formulation, and given the short-term nature of market-share analysis, maintaining the distinction would be too tedious.It is hoped that descriptive, rather than predictive, types of analysis will give the analyst and manager(s) concrete suggestions for formulating marketing strategies. The graphic summaries, for example, may suggest more effective marketing strategies.
2. Forecasting and Planning: Future market shares and sales volumes will be forecasted on the basis of a marketing plan. It will be nonsensical to speak of forecasts without an explicitly stated plan. Market simulators require, for example, explicit assumptions about competitive activities. Consequently, they produce conditional forecasts (i.e., conditional on these assumptions). A plan can be evaluated against various competitive scenarios. Also, it is theoretically possible, but not always practical, to search for an optimal (i.e., profit-maximizing) plan.
It is critically important that the analyst reviews the performance of the firm's product/brand after marketing plans are put into effect. A careful review of one's plans and actual performance will improve not only future planning but also the techniques for market-share analysis. In doing a follow-up, it is not enough just to look at whether market shares were accurately forecasted. Market shares and consequently actual sales volume differ from the forecasted values for three basic reasons.
If the actual performance is at variance with the planned, It is essential for the analyst to pin-point the cause of variance by careful analysis. The so-called variance analysisHulbert, James & Norman Toy [1977], ``A Strategic Framework for Marketing Control,'' Journal of Marketing , 41 (April), 12-20.may be a useful technique for this purpose.
We have summarized here the process of market-share analysis as we view it. The reader will find that the organization of Chapters 2 through 7 of this book follows closely the stages of this process. Chapters 2 and 3 describe issues related to modeling (Stage 1: Specification of Models). Chapter 4 deals with the issues related with data collection and aggregation (Stage 2: Data Collection). Chapter 5 describes various techniques of parameter estimation (Stage 3: Analysis. Parameter Estimation). Chapter 6 (Competitive Maps) is related to reduction of data to decision-related factors (Stage 3: Analysis. Conversion to Decision-Related Factors). Chapter 7 is devoted to decision-support systems for planning (Stage 4: Strategy and Planning). Stage 5: Follow-Up is also dealt with in Chapter 7. Chapter 8 will discuss various remaining problems associated with market-share analysis and the potential avenues for future research in this area.