Competitive strategy
Editor's note: Tim Glowa and Sean Lawson are principals with North Country Research, a Calgary, Alberta marketing science company. Julien Lambert is CEO of CoreStat, an Edmonton, Alberta market research company.
The theory of business strategy stems from the need of managers to be able to counter the effects of external market forces. Without the tools needed to support it, firms may fall back on crisis management in reaction to unforeseen market forces.
One of the foremost authorities on competitive strategy is Michael Porter, a professor of business at Harvard University. Porter argues that the "essence of strategy formulation is coping with competition." 1 Competition in an industry comes not simply from direct competitors, but from the underlying economics of the industry itself. In his book Competitive Strategy: Techniques for Analyzing Industries and Competitors, Porter identifies several major antecedents governing the development of a competitive strategy. He believes that businesses should search for new, sustainable, competitive advantages. These advantages come from developing a distinctive way of competing. An advantage comes from either having consistently lower costs than rivals, or by differentiating a product or service from competitors 2.
Consumers choose which products or services to purchase. In making these purchasing choices, consumers evaluate the product features as well as the brand and price charged. Simple economic theory holds that consumers are utility maximizers, meaning they will select the product that has the highest overall utility from a competing set of product offerings, each constructed with different utilities for the product components. Features in a product offering that customers like are unconsciously assigned higher utility values, while features consumers do not like (such as price) are assigned negative utility scores.
Understanding the behavioral responses of consumers to the actions of businesses and governments is of interest to a wide spectrum of firms. Consider the example of a consumer choosing a credit card. In evaluating which credit card to select, the consumer might narrow the selection down to the two products shown in Table 1.
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A rational consumer in the market for a credit card, faced with the final two options in Table 1, will evaluate the competitors and base a decision on what is best for them (which option provides the highest overall utility). Through evaluating each product, every consumer is unconsciously influenced by his or her own decision-making criteria.
For example, one consumer, who uses the card for business purposes only, and pays the bill every month, may not be as concerned with interest rates, and more concerned with rewards, brand name, and credit limit. As such, these components will affect his or her decision more heavily than the interest rate, for example. On the other hand, a consumer who uses the card infrequently but often carries a balance each month, may be more concerned with the interest rate, and be more price-sensitive. This consumer may attach more utility to price variables than to rewards or credit limit.
Each consumer is unique; they use their decision-making criteria to choose between competing product offerings. It is also impossible for most consumers to define their own decision-making criteria; when asked, most are unable to quantify how or why they select one product over another, other than simply stating that the product is fulfilling a need. However, it is possible to understand how groups or segments of consumers will likely respond to competitive product offerings, and therefore uncover how much importance they assign to each of the product features.
Individuals' choices are influenced by habit, inertia, experience, advertising, peer pressure, environmental constraints, opinion, etc. This set of influences reflects the temporal nature of choice outcomes and segments with the choice constraint itself3.
Therefore, it is important, in defining a competitive strategy, to consider and understand consumer behavior, and specifically, how customers will respond to your product offering. One tool that marketers can use to understand consumer behavior is discrete choice modeling.
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Discrete choice modeling
Discrete choice modeling, the 2000 Nobel Prize-winning mathematical analysis theory, is based on a rigorous and well-tested theory of consumer choice behavior, known as random utility theory. As shown in Figure 1, this theory postulates that the consumer attributes utility (a latent measure of preference) to each product in the marketplace in accordance with the product's attributes and the perceptions of the extent to which each brand meets their needs and benefits. The customer's objective, consistent with economic theory, is hypothesized to be the maximization of utility. Thus, the product that is "best" for them is selected, subject to what they know about competing options and whatever constraints (i.e., income, product delivery) are operating on their choices4.
Specifically, discrete choice models can be used to understand:
- market strategy development;
- new product design;
- market share, profitability or margin optimization;
- branding issues (brand equity, co-branding, affinity branding);
- customer retention and profitability.
The functional power of predictive modeling is illustrated in the example below.
An illustration of discrete choice modeling
Within a competitive arena, firms are struggling against one another to maximize revenues. Consumers make or break a product through their decisions on whether or not to purchase. A choice model can be used to examine the effect on market share of introducing a product change. The change in product, implemented by any competitor included in the model, can be used to optimize a competitive offering, or to measure the effect on market share as a result of a product change from a competitor.
For example, assume the simple credit example investigated earlier was part of a larger study that included four key competitors in a targeted market (obviously a real model could include more competitors and more product variables). Their initial product offerings and corresponding market shares are illustrated in Table 2.
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For example, suppose that Citibank, realizing that it has less market share, is considering lowering its interest rate in an attempt to capture more market share. Using discrete choice modeling, analysts at Citibank can quickly identify how the market will respond to lower interest rates. Consider the change from 21.99 percent to 17.99 percent and the corresponding change in market share as illustrated in Table 3.
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The model predicts that such a change would increase market share for Citibank by eight percentage points, while decreasing the market share for the other competitors in an industry.
However, product changes, such as in this example, are not made in isolation. For this information to have strategic and tactical value, additional analytical powers are needed. This is where discrete choice modeling becomes highly valuable. For example, consider that the Bank of America decides that it is not willing to wait and watch its customers migrate to another institution. It decides to lower both the interest rate and the annual fee for its credit card. This change is reflected in Table 4. The market shares for Bank of America have gone up, effectively taking market share away from competitors.
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Market strategy development
This type of tool is invaluable for decision makers within these firms. Not only can an optimal product offering be quickly identified, a firm can also determine how best to respond to a competitive change. For example, when Citibank lowered interest rates, other competitors, if they had such a tool, could quickly determine the consequences on market share of this change within the industry. This information could be used to define an optimal competitive reaction; how should MBNA respond, for example? Should it lower interest rates further, or ignore the threat altogether?
Additionally, a firm using this tool cannot only define the optimal product for itself, it can also measure and examine possible consequences of having a competitor react to these changes.
The functionality of the model also applies to new product development. For example, suppose Wells Fargo is deciding on issuing all credit cards with a photo of the user imprinted on the back. Wells Fargo could use this type of modeling to determine not only if customers are interested in such a feature but if they are willing to pay more for the additional security it offers (and if so, how much more) and where the bank will be positioned should competitors copy similar measures. By understanding how much customers are willing to pay for such a product feature (if they are willing to pay anything at all), Wells Fargo can conduct a cost/benefit analysis to determine whether the costs associated with developing the new product (including receiving and scanning customer photos, etc.) is worthwhile.
It is important to realize that not every customer will have the same sensitivities. Some will be more price-sensitive than others. Some target markets will respond differently to various product offerings. Therefore, it is important to include a segmentation measurement with discrete choice models for the ability to define the optimal strategy by targeted segment, or measure the sensitivity differences across segments.
Lastly, by fundamentally understanding what drives a customer to purchase (is it price? is it brand? is it loyalty programs?) a firm can incorporate these latent measures into its marketing communications strategy to ensure the message gets into the marketplace. In a sense, this is like truly understanding what the hot buttons are for each customer segment.
Include a range
In developing a discrete choice model, it is important to include a range of variables that will be relevant to the strategy investigation at hand. Once a model is created, it is not possible to go back and include additional variables without developing an entirely new model.
On the other hand, discrete choice modeling allows a firm to quickly identify the optimal product strategy. Rather than simply introducing a product change, and waiting weeks or months to measure its effectiveness, an analyst can quickly identify the appropriate strategy using this powerful model. This shortens the time to market and can effectively eliminate strategic product errors.
Firms can use the powerful tool of discrete choice modeling to maximize their competitive advantage. If a new competitor is entering the market, firms can proactively identify not only the potential loss in revenue this entrant might cause, but also identify and develop the appropriate response to protect market share. Firms can also leverage their brand and optimize their product offerings in the most efficient manner possible.
References
1 Porter, Michael E., Competitive Strategy. New York: Free Press, 1980.
2 Pamela, Goett, "A man with a competitive advantage." Journal of Business Strategy, September 1999.
3 Louviere, Jordan J., David Hensher and Joffre Swait, Stated Choice Methods: Analysis and Applications . Cambridge University Press, 2000.
4 Glowa, Tim and Sean Lawson, "The North Country Research Approach to Consumer Choice Modeling." Unpublished white paper, North Country Research Inc., July 2001.