Melzner explains that “The rapid propagation of voice technology raises a vital question: Do consumers disclose more or less information about themselves when they interact with technology orally rather than manually? To answer this question, one needs to consider that consumers can disclose information about themselves both verbally, that is, by voluntarily providing information through language, as well as nonverbally, that is, by involuntarily revealing information through vocal paralanguage and ambient sound.”
Verbal Disclosure
The researchers also identify mechanisms that arise from fundamental differences between oral and manual communication. They integrate these mechanisms into a verbal disclosure decision-making framework illustrating the complex ways in which communication modality can affect consumers’ likelihood to disclose information. This modality-dependent framework not only provides impetus for future research, but can be used as a tool by marketers to gauge when and how oral versus manual communication may increase or decrease consumers’ likelihood to disclose information verbally.
Nonverbal Disclosure
Oral communication with connected technologies allows one to capture information beyond language in the form of nonverbal disclosures, which are largely absent in manual communication. When consumers speak to connected devices, vocal paralanguage (e.g., the sound of their voice or how something is said) and ambient sounds (e.g., sounds in the current environment and from activities) are inherently captured and reveal information about consumers. The article provides an overview of marketing relevant information around consumer states (e.g., emotions, health conditions, current activities) and traits (habits, ethnicity, personality, identity) that can be inferred from such auditory nonverbal disclosures. Additionally, it provides an overview of industry patents attesting both to the wide range of information about consumers that can be extracted from audio data and to industry interest in leveraging such data.