How much info is too much to get the right match?

An optimal amount of information is key to successful matching, whether in dating, hiring, or other quests

Featured faculty: Michael Zhang
Written by Putro Harnowo

There is an app for anything nowadays. Digital platforms have made it easier to shop, work, find jobs, travel, and even date by bridging the two sides in need at their fingertips. With no more face-to-face interaction, searching for the perfect match is as easy as observing pictures and numbers on a screen, as many would imagine.

Perhaps the nitty gritty of the virtual matching is the fact that each user has different preferences. Regardless of the detailed information, a mismatch naturally occurs when preferences from both sides differ, as it prevails in many aspects of life. Imagine when you crave ethnic cuisine but all you see are fine dining eateries, or search for a one-bedroom apartment but all listings offer houses for families.

Information management and strategy become crucial for digital platforms to sustain their businesses. This can explain why Airbnb gives away much data on its interface, but Uber only relies on user ratings and conceals the passengers’ destination until the ride starts. However, less is known about how much information should be shown to alleviate the misalignment.

“Conventional wisdom often suggests that users on platforms should try their best to obtain more information, but we find circumstances where more information can actually hurt the users,” says Michael Zhang, the Wei Lun Professor of Business AI at the Department of Decisions, Operations and Technology at the Chinese University of Hong Kong (CUHK) Business School. “We call this the ‘less information is more’ effect.”

To this extent, dating sites provide a natural setting to analyse such a phenomenon. In a study titled Mr. Right or Mr. Best: The role of information under preference mismatch in online dating, Professor Zhang and his co-authors analysed data from a major dating site in China, and their initial data already suggests notable preference mismatches: men generally prefer a woman 10 cm shorter than themselves, but women like a man 20 cm taller. Such mismatches also exist in other attributes, from income and homeownership to classic astrology.

“The dating market is characterised by a high degree of heterogeneity in terms of both user characteristics and their preferences over potential partners. Therefore, online dating is an ideal context to study preference mismatch,” he adds.

Why is less information more useful?

In the context of dating preferences, it is worth noting that some may argue, “beauty lies in the eyes of the beholder.” While this statement stands true, the preference mismatch in the study describes the preference discrepancy between the two sides of the market, rather than variation within a single side or subjective preference, as the famous phrase refers to.

For two-sided platforms where both sides have preferences and engage in search and matching, the main challenge is creating an effective and efficient search process. Professor Zhang, along with Shen Hongchuan of the University of Macau and Dang Chu of the University of Hong Kong, found that the amount of information influences matching outcomes.

“Conventional wisdom often suggests that users on platforms should try their best to obtain more information, but we find circumstances where more information can actually hurt the users. We call this the ‘less information is more’ effect.”

Professor Michael Zhang

In practice, users receiving a message on the dating app will have the sender’s short profile attached, showing basic information like nickname, age, education and home city. Users can find more details by clicking on a long profile page, which contains information on height, income, Chinese zodiac sign, astrological sign, lifestyle, house ownership and even smoking habits.

Users on the initiation side are called the focal users for easier reference, and those on the other side are called the candidates in whom the focal users are interested. The total data comprises 1,198,943 clicks from 33,504 focal users with search and matching history, including profile-checking, messaging and the reactions from the candidates. A match is considered successful if the focal user and a candidate have exchanged messages at least once.

To measure the preference mismatch, the researchers construct attractiveness scores of each candidate based on the estimated preferences from each focal user. If the candidates whom the focal users like reply to the messages and favour the users back, their preferences are matched, but if the preferences are misaligned, candidates with a higher attractiveness score are less likely to reply.

The analysis found that the preference mismatch happens more often if focal users and candidates click long profiles. Alas, obtaining more information does not enhance the likelihood of matching. On the contrary, candidates approached based on their short profiles are more likely to reply to focal users. The profile photos may influence the outcomes, but after running another set of experiments, the researchers ruled out this factor as a significant concern.

The researchers initially suspected that candidates whose long profiles were clicked may be pickier and, hence, less likely to match. To answer this, they constructed a popularity measure for each candidate based on the number of focal users reaching out. The results show that the average popularity of the candidates in the long profile is lower than in the short bio. Candidates with a lower popularity score are also more likely to be in the long profile group.

“More details about the other side lead to a greater mismatch, likely because when the users learn more about the candidates, misaligned preferences in each attribute start to weigh in and increase the level of mismatch,” says Professor Zhang.

More information can be useful sometimes

While there is no doubt that more information helps make informed decisions, complete disclosure may lead to market failure, especially for two-sided platforms where misaligned preferences are pervasive. However, there are several settings where the “less information is more” effect may be less applicable.

In decentralised platforms like Tinder, Upwork, and Airbnb, where user preferences play a key role in the search process, preference mismatch is likely to exist. Conversely, in a centralised platform like Uber, passengers value time efficiency, and the drivers’ preferences do not matter much, so the platform hides the destination until the ride request is accepted, making preference mismatch negligible.

Considering the mismatch cost—the negative impact a user experiences when failing to find a match that closely aligns with their ideal—a low cost will result in more matches within mutually acceptable preferences, like finding a part-time job. In a setting where mismatch cost is relatively high, like in online dating, users who spend more effort understandably expect to get the best match possible.

Bargaining power between the two sides also matters. “When imbalanced bargaining power exists, the final outcome will depend on the preference of the side with more power,” Professor Zhang says.

While users can reach out to all candidates regardless, time and effort are still wasted on the no-brainer approach. Inevitably, some degree of information helps users screen out candidates who are far from the criteria. “An optimal amount of information is needed before proposing a match,” he adds.