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How’d That Get in My Cart? How Recommendations and Discounts Affect Online Shoppers’ Trust and Purchase Decisions

How’d That Get in My Cart? How Recommendations and Discounts Affect Online Shoppers’ Trust and Purchase Decisions
January 10, 2022  |  By Emilija Sarma, John Aloysius

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It can sometimes feel like no one knows you better than Amazon. The product recommendations offered by the online retailer can give the impression that it knows what you want even before you do—for better or worse. 

Most of us have had the eerie experience of receiving targeted ads or product suggestions while browsing social media apps and online retailer sites that seem to predict what you’re thinking. Even if you haven’t searched for a specific item yet, breadcrumbs left behind by your browsing and purchase history lead algorithms down a pathway toward revealing your heart’s desire. 

Collecting and analyzing consumers’ personal data allows online retailers to provide personalized suggestions and product discounts meant to make people’s lives easier when making a purchase decision. Although companies are getting to know us better, they’re also inevitably creating a sense of unease about how our data is collected and used, which can deter consumers from shopping online. 

This duality in consumer opinion and feelings over shopping online with privacy concerns looming over them on the one hand, and the drive to purchase goods with ease online on the other, creates the privacy paradox. This paradox represents a conundrum for online retailers. Although our purchase habits have steadily continued to shift toward shopping online (with Forbes reporting that Americans are “on track to spend $1 trillion online—a record amount—in 2022”), consumers continue to wrestle with privacy concerns. Doubts about how our data is sourced and used by online retailers can be powerful deterrents to making a purchase online.

Online Shopping Site Interventions—Facilitating or Deterring the Purchase Intention of Consumers?

In “Being at the cutting edge of online shopping: Role of recommendations and discounts on privacy perceptions,” Viswanath Venkatesh, Hartmut Hoehle, John A. Aloysius, and Hamid Reza Nikkhah set out to interrogate the relationship between inhibitors (such as privacy concerns), enablers (like discounts and recommendations), and their effect on online shoppers in order to provide some insight into what drives and deters people from clicking the “add to cart” button. In particular, they examine how three common interventions used by online retailers impact shoppers’ purchase intention: “(1) recommendations based on product relatedness, (2) language describing product recommendations,” and “(3) product discounts.” The study’s goal was to see how combinations of these interventions may impact the effects of privacy inhibitors (e.g., concerns about the customers’ data collection and usage) and privacy enablers (e.g., trust in the online retailer). 

Online retailers use “interventions,” like discounts and recommendations, to drive consumers to purchase more goods online. These interventions ideally will combat the customers’ fears about privacy. While discounts incentivize the customer to make a purchase by making them feel like they’re getting more bang for their buck, recommendations are meant to make the selections process of products easier, as they are “either based on historic purchase correlations or recommendations suggested by the retailer.” 

However, recommendations can be a double-edged sword. Even though recommendation systems are meant to “enhance customer satisfaction” and make decision-making easier, the analytics involved in recommendation systems can lead people to feel “as if they are under surveillance.” Online shopping sites learn about the customer’s needs and preferences through machine learning algorithms that analyze consumer behavior. This data shapes the customer’s online shopping experience because it allows the retailer to generate relevant product recommendations and “offer appealing discounts by analyzing millions of customers’ profiles.” In this way, what’s supposed to be a helpful feature that would enhance the customer’s shopping experience can become an inhibitor for shopping online.

Still, customers’ attitudes toward privacy remain inconsistent. Though data privacy concerns may dissuade a shopper from purchasing an item online, that same shopper may still make the purchase if their concerns are outweighed by, say, a particularly good deal on that item. People’s perceptions about online shopping may change during “different stages of the shopping process,” when they encounter various interventions set up by the online retailer. It’s thus essential for businesses to be aware of how the interventions they use (i.e., discounts, recommendations, etc.) “may interact with customer privacy concerns to influence online purchase intentions.”

Understanding the Role of Interactions on Consumer Purchase Intention

The Venkatesh et al. study analyzed the data of 496 participants who were asked to browse one of eighteen randomly assigned online bookstore simulations “to experience shopping with different conditions.” The storefronts were created to mimic the Amazon bestselling book category. The various iterations of the online bookstore simulation were designed to provide different combinations of interventions like “no retailer recommendation/language suggesting other customers’ preference—historic purchase correlations (correlated/uncorrelated),” and discounts “(no discount/discount/bundle discount).”

The data was collected from online shoppers in the U.S. “who were recruited from a consumer panel of a research firm,” to ensure that the research sample was representative “of online customers in terms of gender, age and other demographics.” The researchers worked with the assumption that product recommendations would enhance the intention of customers to shop online because recommendations provide “more interaction with the retail site.” This in turn develops the customer’s confidence and level of trust in the online retailer. The more the online shopping experience mimics the experience of shopping in person, the more willing the consumer becomes to interact with an online store and provide their personal information. The study also posited that the recommendations would assist with developing the customer’s “sense of the alternative products that are available.”

Venkatesh et al. assumed that correlated product recommendations will have a stronger effect on purchase intention than uncorrelated recommendations since “correlated recommendations provide personalized offerings.” Prior research has shown that consumers are “expected to conform more to the recommendation,” and make a purchase if it comes by way of a personalized recommendation. 

The researchers also posited that when people are having a positive online shopping experience through enhanced trust and encountering information richness on the shopping site, adding discounts as a factor will “create a sense of greater overall value” of products for the customer. So, if recommendations were to have the opposite effect and bring about fears of privacy for the online shopper, that’s where discounts would come in and mitigate customer apprehension creating an overall positive shopping experience.

The Impact of Recommendations and Discounts in Creating a Positive Consumer Experience

The study found that, ultimately, “explicit product recommendations” and discounts can “each enhance the effect of privacy enablers on purchase intention.”  What this means for online retailers is that customers can be expected to react positively to product recommendations, whether they are correlated or uncorrelated, and to discounts even if they generally hold some degree of distrust toward shopping online. Recommendations did not seem to have the negative effect of increasing privacy inhibitors in the participants of the study.

What particularly stood out in this study was the effectiveness of discounts, which could “ameliorate the negative moderating effect of recommendations on the relationship between privacy inhibitors and purchase intention.” Consumers actively seek out ways to “lower the cost of their purchases,” so they’re already on the hunt for online retailers that offer discounts. 

Importantly, regular discounts or “discounts for a single product” were found to be “more influential than bundle discounts” in motivating consumers to buy products. Bundle discounts were not as effective in contrast and the study determined that only regular discounts mitigated the negative effect of privacy inhibitors.

The study found that “[w]hen shopping sites become more interactive and adopt interventions that facilitate purchase activities,” consumers are more inclined to make a purchase, so interventions like the use of recommendation systems that enable personalized product suggestions didn’t “seem to [have] a downside.”

Even so, the researchers cautioned online shopping sites to be strategic about using algorithms to give product recommendations, as findings show that “only recommending products known to have historic purchase correlations with the focal product sought by a customer” could positively impact the “customers’ purchase intention.” Unrelated product suggestions would then do little to benefit the customers’ shopping experience and would be unlikely to drive them to make a purchase.

Although consumers might look at product recommendations with some suspicion, targeted recommendations and discounts still seem to outweigh the apprehension over privacy. A great deal on a product or a recommendation that really hits the nail on the head may catch even the biggest skeptic of online shopping off guard. Mitigating user privacy concerns is no easy task, so to build consumer trust, it is imperative that online shopping sites examine what interventions are effective and which ones might actually be driving consumers away. 

Post Researcher/Author:

Matt WallerJohn A. Aloysius is professor and the Oren Harris Chair in Logistics in the Department of Supply Chain Management in the Sam M. Walton College of Business at the University of Arkansas. His research interests are in two main streams in retail supply chain: behavioral operations and technology. His publications have appeared or will appear in leading operations and supply chain journals as well as other journals in business and economics. His research has been sponsored by Walmart Stores Inc., the Retail Industry Leaders Association (RILA), and the Association for Supply Chain Management (ASCM).