Alexa, Tell Me More! The Effectiveness of Advertisements through Smart Speakers

ABSTRACT

Smart speakers enable communication through a voice interface and are among the fastest growing consumer technologies globally; they provide a new and innovative medium for the delivery of interactive advertisements and the sale of products, known as “conversational commerce.” However, despite the promising potential of the use of smart speakers as a new advertising channel, little is known about the effectiveness of advertisements made through this medium. Therefore, this article investigates how the distinctive features of smart speakers, namely, interactivity, talker variability, and contextual relevance, influence the effectiveness of advertisements. Through two experiments, we assess the recognition of advertisements for the measurement of advertisements effectiveness through smart speakers. The results of experiment 1 show that the brand and product recognition of advertisements in cases where smart speaker users interact with the advertisements is higher as compared to that of non-interactive advertisements. Experiment 2 further shows that contextual relevance increases the brand and product recognition of advertisement, while talker variability does not affect it. Thus, our findings reveal the nature of the voice interface and provide insights for effective business strategies for advertisements in conversational commerce.

KEYWORDS:

• Smart speaker
• online advertisement
• ad recognition
• interactive ads
• talker variability
• contextual relevance
• voice interface
• conversational interface

Acknowledgments

This work was supported by the Dong-A University research fund. All authors contributed equally.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. Amazon Echo is the product name of the smart speaker developed by Amazon; it was released on November 6, 2014. In addition, Google Home is the product name of the smart speaker developed by Google; it was released on November 4, 2016.

2. Amazon specified the following: “Alexa provides a set of built-in capabilities, referred to as skills. For example, Alexa’s abilities include playing music from multiple providers, answering questions, providing weather forecasts, and querying Wikipedia” (https://developer.amazon.com/docs/ask-overviews/build-skills-with-the-alexa-skills-kit.html).

3. Google’s first attempt to test advertising on Google Home on March 16, 2017. The advertisement message is as follows: “By the way, Disney’s live action Beauty and The Beast opens today. In this version of the story, Belle is the inventor instead of Maurice. That rings truer if you ask me. For some more movie fun, ask me something about Belle.”

4. Engagement rate is a metric to measure how much viewers engage (e.g., likes, favorites, reactions, comments, shares, views, retweets, and sometimes including clicks, depending on platform) with the content. Considering that the click-through rate was less than 1% in the case of audio-only advertisements for similar product groups, this is a very high number [22].

5. It is reported that 53% of smart speaker owners had an Amazon Echo in the U.S. in January 2020 [77].

6. It is reported that 42% of smart speaker owners are millennials or younger (i.e., 18–36 years old) [78].

7. To minimize the impact of interaction contents and methods, we have made the interaction as simple as possible.

8. The exponential value of 0.955 is 2.599 (e°^.955=2.599). Since one order indicates 1/36, the product of 2.599 and 1/36 is 0.072.

Additional information

Notes on contributors

Kyuhong Park

Kyuhong Park ([email protected]) is a senior researcher in KIST. He earned his Ph.D. in Management Engineering from KAIST. His research interests include Internet of Things, digital piracy, and information privacy. His prior research has been published in Information & Management, Electronic Commerce Research and Applications, and several other journals

Yongjin Park

Yongjin Park ([email protected]) is an assistant professor in the Information Systems Department at College of Business, City University of Hong Kong. He earned his Ph.D. in Management Engineering at the College of Business, KAIST. His research interests include e-business, mobile channel, and societal impact of IS. His prior research has been published in Information Systems Research.

Junyeong Lee

Junyeong Lee ([email protected]) is an assistant professor in Department of Management Information Systems at the Chungbuk National University. He received his Ph.D. in Management Engineering at the KAIST. His research interests include collective dynamics and human behavior in information systems. His work has appeared in academic journals including Journal of Management Information Systems, Journal of Business Ethics, and Communications of the ACM.

Jae-Hyeon Ahn

Jae-Hyeon Ahn ([email protected]) is a professor at the College of Business, KAIST. He received a Ph.D. degree in Management Science & Engineering from Stanford University. His research interests are focused on digital strategy in the ICT industry and the evaluation of Internet advertisement strategies with the eye-tracking approach. He has published in such journals as International Journal of Electronic Commerce, Journal of Management Information Systems, Information Systems Research, Management Science, MIS Quarterly, and others.

Dongyeon Kim

Dongyeon Kim ([email protected]) is an assistant professor at the Department of Management Information Systems, Dong-A University. He earned his Ph.D. in Management Engineering from KAIST. His research interests include the business value of data analytics and the mechanisms of change under advanced technology. His prior research has been published in Information & Management, Electronic Commerce Research and Applications, and several other journals.