Risk and maximum acceptable discount levels

Abstract

Purpose -Studies on optimal discount levels have sometimes yielded contradictory results, leaving practitioners with unclear direction. This paper proposes clarifying the optimum discount levels. Design/methodology/approach -This study asked 453 consumers to choose their own optimal discount levels (from 0-80 percent) for eight product categories across two distribution channels (physical store and online merchant). Then they were asked if the reason if they did not always select the deepest discount. Findings -Only 13 percent selected the 80 percent discount level for each product and each channel, despite seeing the exact price they would pay at each level. In support of attribution theory, 88 percent of the consumers attributed at least one cause for the deepest discounts. Most frequently cited were concerns about quality problems, damaged goods, or stolen goods. Consumers also opted for lower discount levels from the online merchant than from the physical store. There was a wide divergence by product category, with consumers selecting smaller discounts on tires and cereal and the deepest discounts on shirts. Research limitations/implications -Given the divergence across product categories, it is unknown how consumers would respond to categories not studied.Practical implications -This paper has revealed strong consumer perceptions about discount risks and the tradeoffs consumer make between risk and financial benefit across different product categories, both online and off -which can help marketing practitioners in setting discount levels. Originality/value -By allowing consumers to select their own preferred discount levels, it is shown that most customers attribute some risk to them.

Price competition during and after promotions

“…Our fi ndings also support the view that, although there is a positive relationship between the fi rst-period price and the price discount, it is not realistic to continually increase regular prices and offer deeper discounts. These fi ndings are consistent with the empirical evidence that deep discounting in some product categories negatively infl uences consumer perceptions and might decrease the probability of purchasing in both the short and the longterms (Drozdenko & Jensen, 2005;Gupta & Cooper, 1992;Marshall & Leng, 2002).…”

Predicting consumer product demands via Big Data: the roles of online promotional marketing and online reviews

“…The effects of price discounts are often measurable, and because they are able to increase the store traffics, they are able to support relationships between manufacturers and retailers, and ensuring that a particular brand is well stocked and has adequate shelf space in the retail stores (Gendall et al 2006;Liu et al 2015). Despite numerous studies on the influence of discount on product demands, results have shown inconsistent and contradictory outcomes on the effects of price discounts on product demands (Drozdenko and Jensen 2005). Marshall and Leng (2002), for example, found that although product sales increased when discount is being offered from 10 to 50%, additional increase between 60 and 70% has no effect on product sales.…”

“…On the other hand, based on attribution theory, when information is being thoroughly processed, consumers are able to rely on attribute information besides price to evaluate a product's quality (Drozdenko and Jensen 2005). When purchasing products online, there are various information about the product, as well as online reviews which may result in customers viewing discount as a monetary gain, and may increase the intention to purchase the product.…”

Predicting online product sales via online reviews, sentiments, and promotion strategies

“…Furthermore, the quantitatively measurable nature of the price discounts effect enables vendors to guarantee the availability of their products to their consumers (ibid.). However, even though many studies have examined the influence of discount on product demands (Ehrenberg et al, 1994;McNeill, 2013), Drozdenko and Jensen (2005) have highlighted contradictions and inconsistencies on the effect of price discounts on product demands. A study by Gupta and Cooper (1992), for example, has suggested that a price discount threshold level of 15% is enough to encourage purchases of the product in the US.…”

“…Suri et al (2000) and Marshall and Leng (2002) have noted that price information of a product may be used as a cue to determine its inherent perceived quality by customers. Attribution theory posits that consumers rely on price and other attributive information when processing information to come up with a final evaluation of the product's quality (Drozdenko and Jensen, 2005). This attributive information on the product may result in the customers' final evaluations of the product's discount as being perceived to be a monetary gain to them.…”