An Analysis of the Fundamentals of Marketing (part 24)

Influencing Buyer Behavior

by

Charles Lamson

How can marketers influence consumer behavior? Ehrenberg and Goodhart (2000) describe a simple sequence known as Awareness, Trial and Reinforcement (ATR) in line with the shaping of behavior.

Awareness. In this respect advertising and other communications may be used to build and maintain a high level of brand awareness and to provoke sufficient interest in a proportion of consumers that will lead them to try the product. Advertising may involve vicarious learning by depicting people who look similar to those from the target group enjoying and benefiting from using the product. The idea behind vicarious learning is that it is cost-free to the extent that one can observe and copy the behavior of others if that is seen to be successfully reinforced - or alternatively one can avoid what they do if one observes negative consequences (Bandura, 1972). Advertisers often promote vicarious learning by showing the negative results that arise if people do not use their products and social approval for those who do. Interest in trial may be further enhanced by means of an introductory trial offer coupled to eye-catching signage and a prominent placement position.

Trial. Perhaps the most obvious means of encouraging trial is to ensure that there is a sufficient stock of the brand available to ensure that every customer can find the shape and size that they require. Here close attention should be paid to the setting and in particular towards estimating the extent to which the setting can be controlled or closed.

Reinforcement. As can be seen, in contrast to cognitive learning theory where attitude is an important pre-behavioral state that is predictive of behavior, the radical behaviorist sees no role for a concept which mediates between intention and overt behavior. Choice is not the outcome of internal mental deliberation but is simply a behavior.

Cognitive Information Processing (CIP)

It is considered the cognitive revolution took place in 1956 when Simon developed a computer program called the General Problem Solver. Unlike previous attempts this was not based on the abstract rules of logic but was an effort to simulate human thinking processes; something called 'artficial intelligence' was in the process of being born (Bruner in Miller, 1983).

Simon made much of the distinction between his outlook and that on the theories based on the principal of homo economicus, in particular, the Subjective Expected Utility (SEU) theory as being ill-fitted to an understanding of human decision making, e.g. in dealing with uncertainty one should assume that knowledge about the future values of one or more variables is given in the form of a probability distribution. Simon thought it highly unlikely that this was the way in which humans formulate estimates of an uncertain future. He offered the following example to illustrate his point:

If you were to ask a sales representative to provide an answer to the question 'What do you think your sales will be for the next twelve months? Then the chances are that although the answers may not be reliable, the question will be meaningful to them. If, on the other hand, you asked them the question 'Please estimate the joint probability distribution of sales over the next twelve months', then, as Simon says, 'I have tried this out a couple of times; fortunately my behavior was interrupted as attemptedly humorous rather than insane.'

(Simon, 1957)

Simon introduces his theory suggesting that a house thermostat is confronted with the same problem as a sales manager. He explains this superficially odd connection by saying that for both to perform optimally (according to SEL theory), the latter would have to predict sales correctly, and the former to predict the weather accurately. However, in reality a house thermostat does not attempt to do this. It regulates temperature not by predicting but by relatively prompt corrective action to climatic deviations between the actual temperature and the desired temperature. In the same way, the sales manager who knows what his desired level of sales is can monitor it against actual sales, which knowledge enables him to make good the deficit should one arise. Put another way then both the thermostat and the sales manager formulate the problem as follows:

• What is the initial state, the current position?
• What is the desired state?
• What is the difference between initial state and goal state?
• What alternatives exist for reducing the difference? 
• Which alternative is best?

Finally there is execution, or implementing the best alternative. The above is an example of a rule of thumb or heuristic that Simon argued is prevalent in human problem solving known as means-ends analysis. this requires some explanation. Where Freud conceived of human intention as a vehicle for the transmission of psychic energy, Simon was drawn to its limitations. In perceiving the world, everything around is not perceived but rather selective attention is made to those aspects that are salient, while others are blocked out. When a decision has to be made, precious time is not wasted in considering every possibility, assigning a probability to it., projecting this towards a number of potential future states and selecting the optimum. Indeed this could not be done even if it were desirable because of a lack of the processing capacity; the working memory is limited. Instead, Simon argues, heuristics, or rules of thumb, are used in selecting operators. Frequently, means-end analysis is used heuristically by people faced with complex situations. Means-end analysis works by determining differences between a current state of a problem and a goal state; differences between where we are now and where we want to be - and selecting operators known to be useful in reducing such differences. The basic idea is that people have knowledge about the means (operators) at their disposal for achieving certain ends or goals. For example, on arrival at Heathrow airport and wanting to go to Harrod's store in central London, the goal is to get from Heathrow airport to Harrods. The goal is to transform 'you at Heathrow' to 'you at Harrods'. The first task is to compare the two states and to find the difference between them. The difference is one of location. The means of reducing differences in location are operators such as 'walk', 'go by underground', 'go by taxi' and 'go by bus'. Some operators are not feasible. The individual may be a particularly lazy one who will not walk the sixteen miles involved. It is decided to go by airport coach (bus) because this is the cheapest. The new sub-goal is made to reduce the difference between 'you at Heathrow airport baggage collection' and 'you at the coach stop for Victoria coach station'. When the coach arrives at Victoria the problem is transformed once more, and so on until arrival at Harrods. Means-end analysis is used extensively in managerial decision making.

Marketing and CIP

From the above, cognitive learning theorists view human decision making as a form of problem solving. researchers employ the analogy of a computer to investigate the working of the mind, which is taken to be an information processing unit. In contrast to behaviorists, cognitive theorists seek to understand internal mental states. Consumers are conceived of as being motivated by goals and researchers seek to learn more about the operators that people use in order to seek to move from initial states to goal states. Some salient aspects of the CIP approach are that it is:

• Adaptive. Problem-solving involves a fit between the problem solver and the situation.
• Selective. Perception does not simply mirror the world, it works selectively to organize it.
• Bounded. Processing is limited primarily due to constraints in working memory. Often heuristics are relied upon to make up for lack of processing capacity. Only in the simplest situations will consumers reach a decision in one giant step. It is much more likely that they will use the heuristic of means-end analysis by splitting large problems into more manageable sub-problems. Examples of other heuristics commonly used in marketing contexts are described in the box.

BOX 1

THE USE OF HEURISTICS IN MARKETING Often behavior as consumers is far from optimal, e.g. prospect theorists have found that people are willing to take more risks to avoid losses than to realize gains. Tversky and Kahneman (1974) identified three simple heuristics, or rules of thumb, that lead to predictable errors in many cases allowing the reduction of cognitive effort. Availability The frequency of an event with which it can be summoned as an example from memory. Economically, this is important because the performance of different products has often to be evaluated. The most effective consumers are those who do not place too much weight on recent performance. Representatives Patterns in random sequences are noted, e.g. people often judge probabilities by the degree to which A is representative of B or A resembles B, even when there are major differences between A and B. For example, in 1993 more than half the stock price of Dell computers, amounting to $2.3 billion, was wiped off the company’s balance sheet because the company had been categorized in a group with IBM and Digital Equipment. The latter was faring much worse at the time. Another example is regression to the mean. A group scores high on the test, gaining 80-100 percent. On retest usually the score is much lower. This is not due to any change in the innate intelligence of the group, but do to a certain randomness in performance. Usually, good performance is followed by lesser, and bad performance is followed by better. Often this is not recognized, which has implications for perceived customer service and brand loyalty. Anchoring and adjustment The first choice is an estimate and then the estimate is maintained. For example, on being asked how many countries belong to the UN a person sticks with the number twenty-five, even though this was generated by spinning a wheel. In like manner, a person believes that a discount computer store is more likely to sell computers cheap than a department store, although they may be surprised if they actually check the difference. The view that the best deals are available on the Internet has been discounted.

Although the CIP approach stresses that it is important to understand the fit between the problem solver and the situation, much research focuses on aspects of internal processing and tends to ignore the situational aspect. According to Foxall (2005), it almost entirely ignores the environment in which the behavior takes place. The ideas of selectivity and boundedness focus attention on the problem-solving process. A simple representation of a CIP system is shown in Figure 1.

Figure 1 Simplified Cognitive Information System

The funnel shown in Figure 1 indicates that information processing deals with relatively few stimuli present in the external world. For example, when sitting in class, students are exposed to a number of different sounds, smells and draughts in addition to the visual stimuli. Thankfully, the perceptual process linked to the sensory register directs attention towards those stimuli that are salient and relevant to the situation. Perception is a complex process which ranges from exposure to attention, comprehension and retention of information from the environment. Consider personal exposure to a communication advertising a new product. If perceived to be relevant then this may enter the sensory store, and if it goes no further this may last for micro-seconds. Within that time it may be admitted into working memory, where its visual and auditory components might persist for up to fifteen or twenty seconds. If the information is considered important enough to repeat or rehearse, it may last for around 20 minutes and will have a chance of entering long-term memory. It is clear that only a minority of stimuli such as advertisements will be attended to, comprehended and retained in memory.

Working memory is considered to be similar to computer RAM. The term 'working' implies that the system is active and split into a number of sub-routines whereby a central executive assigns inputs to visual and auditory stores (Baddeley and Hitch, 1974). Working memory capacity is limited to the ability to process five units of information at one time, plus or minus two with an average of four (Cowan, 2001). Manipulation of longer lists is possible by categorization, chunking and by linking new information with existing knowledge. Chunking is the process of grouping several pieces of information and treating them as a single unit - for example 'a', 'c', and 'r' to make 'car' - or by grouping individual numbers into a composite phone number. Novel stimuli must be processed serially, i.e. one at a time. Those stimuli that are important are selected, and precious attention is directed to them in order to figure out those aspects that are relevant. Information that is found to be useful is retained.

Long-term memory contains a huge amount of declarative 'this is' knowledge in addition to procedural or 'how to' knowledge. Declarative knowledge may be gained by learning what a bicycle is and what its components are by reading a book. Procedural knowledge, like learning how to ride a bicycle or to drive a car, is gained initially by slow, incremental and serial action. However, once the novelty has worn off this is routinized. Long-term memory contains episodic memories that reflect on how previous life experiences have been remembered and connect to the sense of who we are and our past. Semantic memories relate to meaning and learning.

Levels of processing. Some authors disagree with the separation of short-term and long-term memory (Cowan, 2005). Craik and Lockhart (1972) suggested that it would be more useful to conceive of different levels of processing where stimuli can be processed at a range of different levels depending on the character of the information. Stimuli can be processed in a shallow manner, e.g. by attending to the colors, or the brightness of a visual stimulus such as an advertisement, but with no processing of meaning. On the other hand, stimuli that are considered to be important because they are relevant to life experience and identity can be subjected to deeper semantic processing. Petty and Cacciopo (1986) adopted a similar line of reasoning in seeking to understand how individuals might process a persuasive advertising message. They suggested two routes to persuasion, central and peripheral, with the differences between being accounted for by contextual and personality factors. Where there was a degree of complexity in choice, and where the perception that a person's identity was important, a person would be likely to elaborate the message by means of conscious information processing. This active processing by the central route involves a sequential process that moves from pre-attention to focal attention, comprehension and elaboration to the reception of information in memory and then further processing to produce attitudes. By contrast, processing by the peripheral route moves straight from pre-attention directly into memory, avoiding costly expenditure of time and effort. The idea of levels of processing is central to the cognitive explanation of involvement.

*SOURCE: FUNDAMENTALS OF MARKETING, 2007, MARILYN A. STONE AND JOHN DRESMOND, PGS. 99-105*

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