Product Uncertainty x AR

🧑‍🔬 DI in Industry (DIiI)

Andy Weeger

Neu-Ulm University of Applied Sciences

February 13, 2024

Introduction

Relevance

Although online sales have increased significantly over the last decade, many consumers still report dissatisfaction and pursue frequent product returns due to products not meeting their needs 1.

Particularly uncertainty about the product causes these effects.

Modern visualization sytems are expected to attenuate the negative effects of unfamiliar experience goods on product returns and consumer satisfaction.

Product uncertainty

Product uncertainty is defined as the consumer’s difficulty in evaluating product attributes and predicting how a product will perform in the future (Arrow 2004).

Product uncertainty was shown to comprise description uncertainty and performance uncertainty (uncertainty about product quality) (Dimoka, Hong, and Pavlou 2012).

Unlike traditional retail, customers are unable to physically inspect or evaluate products before making a purchase, resulting in greater performance uncertainty (Hong and Pavlou 2014).

However, it is not enough for a product to be described thoroughly and expected to perform well; the product must fit the consumer’s individual preferences.

Product fit uncertainty

Product fit uncertainty can be defined as the degree to which a consumer cannot assess whether a product’s attributes match her preference (Hong and Pavlou 2014).

The nature of product fit uncertainty is an information problem, reflecting consumers’ difficulty in assessing if a product fits to their preferences.

Product fit unvertainty was shown to have a more influential effect on product returns than did quality uncertainty (Hong and Pavlou 2014).

Particularly when concerned with experience goods (i.e., products whose attributes are hard to transfer from one party to another) with which consumers are not familiar (i.e., low product familiarity).

Uncertainty reduction

Retailers could lower information asymmetry by providing diagnostic product descriptions, or include credibility signals such as third-party product assurances, warranties, or customer reviews (Dimoka, Hong, and Pavlou 2012).

Reducing product fit uncertainty requires provision of opportunities for direct product experiences.

However, these measures are costly for retailers (additional shipping and handling costs) and/or are not viable or innaproriate in certain cases (e.g., customized products, personal care products or products that require assembly).

Visualization systems

(Online) markets should use modern visualization systems to reduce product fit uncertainty, especially for experience goods (Hong and Pavlou 2014).

Such systems should

  • Sufficiently convey information on experience attributes before purchase
  • Enable customers to identify their preference for experience attributes of a product before purchase
  • Help consumers identify whether the experience attributes of a product match their individual preferences

Augmented reality

Definition

Augmented reality (AR) is a technology that superimposes virtual objects onto a live view of physical environments, helping users visualize how these objects fit into their physical world (Tan, Chandukala, and Reddy 2022).

In contrast to AR, blending virtual elements into physical environments in real-time, virtual reality (VR) immerses users in a completely digital environment—users are virtually transported to an artificial, simulated world, and are entirely shut out of their surroundings (Tan, Chandukala, and Reddy 2022).

AR in retail

The unique capabilities of AR present marketers with new opportunities to engage customers and transform the brand experience (Tan, Chandukala, and Reddy 2022).

  • Entertain customers by creating novel and engaging experiences
  • Educate customers by deliver content and information in a visually appealing manner (e.g., by demonstrating key feautures, highlight relevant product information, and help to navigate in online stores)
  • Help customers to evaluate product fit (e.g., by visualizing products in their actual consumption contexts, increase customers’ confidence, and accomodate wide product assortments and acommodation)
  • Enhance the postpurchase consumption experience (e.g., by offering new ways of enjoying products after purchase, delivering additional information while usage)

AR and product uncertainty

The value of AR lies in its ability to both

  • help customers visually integrate virtual products into the real-world environment
  • use bodily movements and physical actions to control how products are presented

AR helps to reduce product fit uncertainty as it enables customers to evaluate products as if they are interacting with the actual products (Tan, Chandukala, and Reddy 2022).

Q&A

Literature

Arrow, Kenneth J. 2004. “Uncertainty and the Welfare Economics of Medical Care.” World Health Organization. Bulletin of the World Health Organization 82 (2): 141.
Dimoka, Angelika, Yili Hong, and Paul A Pavlou. 2012. “On Product Uncertainty in Online Markets: Theory and Evidence.” MIS Quarterly 32 (2): 395–426.
Hong, Yili, and Paul A Pavlou. 2014. “Product Fit Uncertainty in Online Markets: Nature, Effects, and Antecedents.” Information Systems Research 25 (2): 328–44.
Tan, Yong-Chin, Sandeep R Chandukala, and Srinivas K Reddy. 2022. “Augmented Reality in Retail and Its Impact on Sales.” Journal of Marketing 86 (1): 48–66.

Footnotes

  1. See https://www.wsj.com/articles/SB121020824820975641