A Content Analysis of Television Ads: Does Current Practice Maximize Cognitive Processing?

Abstract

Television advertising is a 67 billion dollar a year industry (McCann, 2008). To help evaluate whether or not advertising dollars are earning the best return on investment, it is important to know how effectively television ads capture and maintain audience attention and engage viewers. Television ads use varied designs to meet many goals including capturing attention, creating brand awareness or product knowledge, motivating consumer behavior, and remembering information. According to the limited capacity model of motivated mediated message processing (LC4MP), structural complexity has the ability to enhance attention and memory for messages, including television ads (A. Lang, 2006). However, complexity can also overload cognitive processing capacity which can have a negative impact on television advertisement objectives of message encoding. Specifically, this dissertation derived ten best practices that articulate the most advantageous ad design for achieving optimal cognitive processing suggested by LC4MP. These include: construct ad copy in chronological order, use simple syntax, and use concrete words in advertising copy. A sample of 619 television ads was content analyzed to compare ad structure to these best practices. The average ad employed six of ten best practices. The best practice most frequently followed was the use of product or service images in ads. The best practice least followed involved the appropriate mix of message complexity and orienting eliciting structural features. Television ads can be improved and this study helps lay the groundwork from which to build theoretically sound production elements.

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Document Details

Document Type
Technical Report
Publication Date
Dec 11, 2008
Accession Number
ADA494365

Entities

People

  • Ky M. De Ros

Organizations

  • Indiana University

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Air Force
  • Best Practices
  • Cognition
  • Cognitive Science
  • Commerce
  • Computer Programming
  • Computers
  • Human Behavior
  • Information Processing
  • Information Systems
  • Message Encoding
  • Message Processing
  • New York
  • Psychology
  • Psychophysiology
  • Recognition
  • Social Psychology

Readers

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