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Altum • Ardent
Make dating smart and meaningful and provide you with individualized dating services by integrating AI techniques.
Holder
type
Duration
Tech
initial status
end status
my role
my work
Market research
User research
Information architecture
User flow
Interaction design
Visual design
Usability testing
Front-end development
work directly with
1 Front-end engineer
2 Software engineers
Report to
Chief Executive Officer
Our team aimed to help young singles between the age of 21 and 35 find their partners with long-term relationships for marriage purposes through artificial intelligence.
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4th Design Prototype
Project Overview
By conducting surveys, contextual inquiry, and qualitative interviews, we concluded our findings intowhich we were going to address in our product.
CHALLENGE 1
Users found it difficult to find serious long-term relatinoship with mots of existing dating apps.
71% research participants were looking for a serious relationship but only 10% of them believed that existing dating apps were helpful.
55% research participants who were dating app users regarded "swipe" as a way to kill their leisure time or as a kind of amusement.
86% research participants who were dating app users usually took no more than 2 minutes to learn their matches.
CHALLENGE 2
Users complained that it was hard to find their ideal matches though they had spent lots of time on dating apps.
69% participants who were dating app users believed that matches given to them were mostly random.
32% participants who were dating app users complained that it took a long time to find a prospective match.
CHALLENGE 3
Users had troubles to make the conversations on dating apps effectively and efficiently.
74% research participants who were dating app users indicated that they didn't know how to initiate the conversations when they matched with someone.
Male participants who were dating app users reported that the average response rate for their first messages was lower than 10%.
22% female participants who were dating app users complained that they usually got many messages from males but only replied a few of them.
CHALLENGE 4
Users were worried about their personal safety and information privacy when using dating apps.
40% participants didn't want to use dating apps because they felt embarrassed or they were uncomfortable to be selected.
60% participants were somewhat worried about their information security and privacy when using dating apps.
48% participants were worried about their own safety if they go on the actual date for the first time with people meet on dating apps.
Mapped the experience of a couple from the first encounter to marriage and found out three crucial factors that impacted the courship: physical attractiveness, personality and interests, and social background.
Physical Attractiveness
People in general choose to pursue relationships with those who are attractive to them. Physical attractiveness often serves as a gatekeeper directing people to learn more about their partners.
Personality and Interests
The match of personality is important to ensure that mutual attractiveness can stay long. Mutual interests can create common languages between two people.
Social Background
Social background refers to the objectivec onditions (e.g. education, occupation, income) of a couple. Those conditions play important roles in the level of happiness during the relationship.
During the 4th design iteration, 9 features were defined to target the above four challenges: facial analysis algorithm, personality analysis algorithm, background analysis algorithm, interest comparison, match limitation, match expiration, conversation assistant, feedback system,and designated meetup location.
Facial Analysis Algorithm
85% of interviewees somewhat cared about the appearance of their matches. With the facial recognition system, Ardent developed an AI that had learned facial features from a thousand couples. The facial analysis AI now could predict whether twousers had physical attractiveness at a 75% success rate and paired our users accordingly.
Personality Analysis Algorithm
The personality analysis AI currently took two parts of data into account: the result of the personality test (direct input from users) and users’ behaviors showed up whenusers were using the app (analyzed by the system). The given match would be based on users’ preferences on personality and feedback from successful couples.
Background Analysis Algorithm
Ardent paired two users with similar social backgrounds at first. Location, nationality, occupation, education, income, etc. would be considered at the back-end when the AI matched users. In other words, such kind of information would not be directly released to users’ matches.
Interest Comparison
Ardent would collect information (from interest questions or other social media accounts) about users’ interests and hobbies and compared them with other users. Interests data would be organized into tags shown on the user profile. Two users are more likely to be matched if they have many mutual interests.
Match Limitation
Limited the number of matches that users could get per day so that they would pay more attention to each given match. This way could offer more time for users to learn more about each match and encourage conversations between them. Too many matches might overwhelm users and lower the efficiency of finding the right one.
Match Expiration
Given match for users would expire on certain days. The number of days before the match expired mostly depended on the user’s activity rate. It could motivate users to chat with their matches as soon as possible and plan their physical dates. For safety and privacy purposes, users were unable to retrieve their expired matches unless both sides agreed to move on.
Conversation Assistant
On the chat page, the system would popup small tips on how to initiate conversations with the given match and the tips may be curated based on the match’s recent goals, interests, etc. In addition, Ardent developed several small games to spice up the conversation and help two users learn more about each other (e.g. Truth Or Dare, etc.)
Feedback System
Ardent would ask users for feedback periodically on given matches, meeting places, etc. The system would ask for confirmation and feedback if two users successfully established a love relationship after several dates and their data would be used to improve the algorithms within the system (require permission from two users).
Designated Meetup Location
To encourage online users to meet physically, the system would give recommendations on the meeting place accordingly based on users’ backgrounds and interests (personal safetywould also be considered). Ardent had cooperated with some meeting places and was able to offer users with discounts for those places.
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