recognition-heuristic

Recognition Heuristic In A Nutshell

The recognition heuristic is a psychological model of judgment and decision making. It is part of a suite of simple and economical heuristics proposed by psychologists Daniel Goldstein and Gerd Gigerenzer. The recognition heuristic argues that inferences are made about an object based on whether it is recognized or not.

Understanding the recognition heuristic

The heuristic makes inferences about a criterion not directly accessible to the decision-maker. Accessibility is reliant upon the ability to retrieve stored information from memory – provided that such information has relevance to an object (or alternative object) in question.

Indeed, for two alternative objects, Goldstein and Gigerenzer stated that:

If one of two objects is recognized and the other is not, then infer that the recognized object has the higher value with respect to the criterion.”

The original recognition heuristic experiment

To demonstrate this heuristic, the researchers quizzed German and U.S. students on the populations of various German and U.S. cities. Students were given the names of two cities and asked to choose which city had a higher population. 

Results showed that 92% of choices were based on city recognition and not on specific knowledge of population size. Interestingly, German students fared better on U.S cities while U.S. students scored better on German cities. The results were attributed to the fact that cities with larger populations were more recognizable than cities with smaller populations.

This is also an example of the less-is-more effect because student decisions were more accurate in domains where they had little knowledge. 

The recognition heuristic in marketing

In marketing and consumer psychology, the recognition heuristic is strongly linked to branding. Businesses spend vast amounts of money advertising their products to increase brand awareness and ensure that their products remain top-of-mind for consumers.

The mechanisms for a consumer choosing one product over another are much the same as the original study on population size.

Consider these scenarios:

  • Publicly listed companies with recognizable names are more likely to attract shareholder investment than those companies that are less well known.
  • A brand of breakfast cereal with a catchy slogan and memorable mascot is likely to be purchased more often than a no-name supermarket brand with plain packaging.

Limitations to the recognition heuristic

Many researchers argue that purchasing decisions are often based on more than recognition alone. This contradicts the notion that the recognition heuristic is a non-compensatory model based on one cue even if other cues are available.

In a mechanism called “recognition plus evaluation”, the consumer may consider a range of cues such as:

  1. The average review rating or the number of stars.
  2. Perceived product desirability. For example, how much of a product is available on the shelf compared to a competitor product?
  3. Negative association, where an individual may recognize a product but for the wrong reasons. For example, the product may be associated with animal cruelty or the business itself has a history of subverting consumer law.

Key takeaways

  • The recognition heuristic argues that recognized objects that satisfy certain criteria have more value than unrecognized objects that do not.
  • The recognition heuristic has significant implications for brand marketing and awareness. Consumers choose products from brands they are more familiar with. 
  • Some argue that the non-compensatory nature of the recognition heuristic is false. While recognition is an important factor in consumer choice, other cues such as the star rating of a product are assessed before a decision is made.

Related Case Studies

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As highlighted by German psychologist Gerd Gigerenzer in the paper “Heuristic Decision Making,” the term heuristic is of Greek origin, meaning “serving to find out or discover.” More precisely, a heuristic is a fast and accurate way to make decisions in the real world, which is driven by uncertainty.
recognition-heuristic
The recognition heuristic is a psychological model of judgment and decision making. It is part of a suite of simple and economical heuristics proposed by psychologists Daniel Goldstein and Gerd Gigerenzer. The recognition heuristic argues that inferences are made about an object based on whether it is recognized or not.
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The representativeness heuristic was first described by psychologists Daniel Kahneman and Amos Tversky. The representativeness heuristic judges the probability of an event according to the degree to which that event resembles a broader class. When queried, most will choose the first option because the description of John matches the stereotype we may hold for an archaeologist.
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The take-the-best heuristic is a decision-making shortcut that helps an individual choose between several alternatives. The take-the-best (TTB) heuristic decides between two or more alternatives based on a single good attribute, otherwise known as a cue. In the process, less desirable attributes are ignored.
biases
The concept of cognitive biases was introduced and popularized by the work of Amos Tversky and Daniel Kahneman in 1972. Biases are seen as systematic errors and flaws that make humans deviate from the standards of rationality, thus making us inept at making good decisions under uncertainty.
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The bundling bias is a cognitive bias in e-commerce where a consumer tends not to use all of the products bought as a group, or bundle. Bundling occurs when individual products or services are sold together as a bundle. Common examples are tickets and experiences. The bundling bias dictates that consumers are less likely to use each item in the bundle. This means that the value of the bundle and indeed the value of each item in the bundle is decreased.
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The Barnum Effect is a cognitive bias where individuals believe that generic information – which applies to most people – is specifically tailored for themselves.

Read Next: Heuristics, Biases.

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