When shopping online for wine, fragrances, or books, consumers frequently encounter recommendation lists. These product selections usually arrive in two distinct forms. Some are curated by a human expert, like a journalist or a sommelier. Others are compiled by an automated data aggregator that summarizes ordinary customer reviews to find the most popular options.
A recent study published in Psychology & Marketing investigated how the length and source of these lists influence consumer behavior. The researchers found that short lists curated by human experts carry a distinct advantage. Shoppers spend more time learning about products, skip the most obvious choices, and select more expensive items when presented with a brief, expert-driven selection.
Victor D. Mejía of Univ. Grenoble Alpes and Samy Guesmi of Université Côte d’Azur designed the research to explore a gap in consumer psychology. Previous research has heavily explored personalized algorithms that recommend products based on a user’s past browsing history. However, static recommendation lists are impersonal and deliver the exact same items to everyone. In addition, previous studies usually looked at experts and aggregators in isolation rather than comparing them directly.
The intent behind the list
The researchers wanted to know how shoppers interpret the intent behind these static lists. Human experts generally rely on subjective, refined tastes to select items. Data aggregators summarize mass consumer ratings to reflect mainstream appeal. The authors argued that the length of a list interacts with these source types to send entirely different signals to the buyer.
To test this dynamic, Mejía and Guesmi conducted four experiments involving 1,100 participants. They built mock e-commerce websites featuring hedonic products. Hedonic goods are experience-based items like wine or candles where the quality is highly subjective and difficult to evaluate before purchasing. Participants were asked to browse the items and make a selection just as they would in a real online store.
In the first study, 159 participants browsed premium teas priced around twenty dollars. The site displayed either a short list of 10 items or a long list of 70 items. The source was explicitly labeled as either a “tea sommelier” or “our customers.”
The analysis of participant feedback revealed that shoppers viewed the short expert lists as driven by product quality and diversity. They assumed the sommelier actively selected varied items to cover different flavor profiles. In contrast, participants viewed the long lists and the customer-generated lists as simple popularity contests based on sales volume. The long lists also triggered widespread feelings of choice overload across both the expert and aggregator conditions.
Tracking shopper behavior
The second study tracked the specific browsing behaviors of 423 participants shopping for unisex fine fragrances. The mock site presented lists ranging from 10 to 70 items. The software recorded how much time participants spent clicking on and reading about each fragrance.
The researchers measured both the breadth of the search and the depth of the search. Breadth referred to the total number of different items a participant clicked on. Depth referred to the amount of time they spent reading the specific details of each clicked item.
The source of the list did not change the breadth of the search. Across all conditions, people inspected a smaller percentage of the total items as the lists grew longer. However, the source did change the depth of the search. When browsing a short expert list, participants spent significantly more time reading about the individual items they clicked.
This deeper engagement changed their final purchase decisions. Shoppers looking at short expert lists were less likely to take the easy way out and select the very first item on the page. They also opted for relatively more expensive fragrances compared to those browsing aggregator lists. The researchers interpret this as a sign that short expert lists create a high-end price image that makes buyers comfortable spending more money.
The role of human motives
The final two studies examined how these lists affect purchase intention and overall satisfaction. For these experiments, the researchers focused on the psychological process of understanding another person’s motives. When people receive a human recommendation, they naturally try to figure out why the recommender chose that specific item.
In the third study, 296 participants browsed high-end spirits. Half of the group was instructed to simply browse, while the other half was asked to actively try to understand the reasoning behind the recommendations. The results showed that this effort to understand the recommender is a primary driver of future sales.
When participants actively thought about the expert’s reasoning, they reported much higher purchase intentions for the spirits. The fourth study, which involved 222 participants browsing luxury candles, mirrored these results. Participants who tried to understand the expert’s choices reported greater post-choice satisfaction with the candle they selected.
This psychological chain of events did not hold true for the aggregator lists. Because algorithms and crowd averages lack a personal mind, shoppers could not attribute a specific reasoning to the recommendations. Trying to understand the motives of an algorithm or a massive crowd of reviewers did not increase their satisfaction or their likelihood to buy.
Retail strategies and limitations
For online retailers, these findings offer a clear strategy for presenting premium goods. Highlighting a small number of items chosen by a named expert can increase user engagement and drive higher spending. Retailers can maximize this effect by explaining the expert’s selection process, which helps the consumer understand the reasoning behind the list.
The researchers note that this effect was tested exclusively on experience-based goods where quality is subjective. Consumers frequently rely on expert guidance when buying wine, tea, or fragrance. The same response may not occur for utilitarian products like batteries or cleaning supplies where standard customer ratings provide all the necessary information.
