Message fit: Link the content of a message to the pre-existing beliefs, experiences, and knowledge

Of the recipient

 Both Plato (in Gorgias) and Aristotle advised would-be influence agents to link their arguments and appeals to the beliefs and experiences of their audiences. The Institute of Propaganda analysis referred to this as tabloid thinking – reducing complex issues to one simple, widely-accepted slogan, commonplace, or truism (Werkmeister, 1948). Similarly, Pratkanis and Shadel (2005) find that

fraud criminals often tailor a scam or pitch to the psychological and other characteristics of their target of victimization. Considerable research in a variety of domains demonstrates the effectiveness of this

technique. For example, Cacioppo, Petty, and Sidera (1982) presented messages based on religious and

legalistic arguments to religious- and legalistic-oriented subjects and found that message arguments were rated as more convincing when those messages fit the subject’s orientation. Snyder and DeBono (1989) demonstrated that high self-monitors found ads emphasizing image and appearance to be more appealing and convincing whereas low self-monitors found ads emphasizing argument quality to be most persuasive. Howard (1997) obtained increased persuasion for messages that used familiar phrases or slogans (compared to unfamiliar phrases conveying the same meaning), especially in limited-thinking situations. In implementing this tactic, the message can be tailored to fit a variety of pre-existing beliefs, experiences, and knowledge including the attitude heuristic (Pratkanis, 1988), balancing processes (Heider, 1958), ideal and ought self (Evans & Petty, 2003), experimentally-induced needs (Julka & Marsh, 2000), slogans (Bellak, 1942; Sherif, 1937), commonplaces (or widely accepted arguments; Pratkanis, 1995), prejudice and stereotypes (Ruscher, 2001), wishful thinking (Lund, 1925), natural heuristic (Rozin, Spranca, Krieger, Neuhaus, Surillo, Swerdlin, & Wood, 2004), tendency for egocentric thought (e.g., Barnum statements; Petty & Brock, 1979), laws of sympathetic magic such as physical contagion (Rozin & Nemeroff, 2002) and a host of cognitive biases such as representativeness, availability, accessibility, fundamental attribution error, illusory correlation, naïve realism, and hindsight (Gilovich, Griffin, & Kahneman, 2002; Kahneman, Slovic, & Tversky, 1982; Nisbett & Ross, 1980). 

 

Placebic reasons

A placebic argument is a reason that appears to make sense but is really vacuous and without information. Langer, Blank, and Chanowitz (1978) attempted to cut in line to make photocopies of either a small or large number of papers. The request was made with no information (e.g., “Excuse me,…May I use the Xerox machine?”), with a real reason added (“because I am in a rush?”), or with a placebic reason (“because I have to make copies?”). Langer et al. found that real reasons increased compliance with both small and large requests (compared to controls) whereas placebic arguments increased compliance for a small but not a large request. However, it should be noted that Folkes (1985) attempted replication of the Langer et al. findings yielded inconsistent results, and thus additional research is required before we fully understand the effectiveness of placebic arguments. 

 

Misleading inference

Another way to increase the effectiveness of an argument is to induce a misleading inference – in other words, “say what you don’t mean, and mean what you don’t say” while giving the appearance of “saying what you mean, and meaning what you say.” For example, Harris (1977) found that consumers would falsely assume that juxtaposing two imperative statements in an ad would implya causal relationship, and Shimp (1978) found that incomplete comparatives in an ad are often used by consumers to incorrectly infer that a product is superior to competitors. Such misleading inferences can result in inflated product beliefs, evaluations, and purchase intentions (Burke, DeSarbo, Oliver, & Robertson, 1988; Olson & Dover, 1978). Preston (1994) presents a scheme for classifying misleading

inferences and deception in advertising (see also Geis, 1982).

 

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