Online Dating App (PIIN) Case Study
It is a location-based, mobile dating and social network app that uses geolocation to enable real-time natural connections. The idea of the project includes: Set up your status and check-in the location (bar, club, restaurant, event, beach, gym) and instantly view information about the users around you. You will be able to view profiles based on your preferred filters.
The main areas of investigation included finding out how people feel about online dating, their frustrations, and potential improvements on those ones apps in the market already.
The dating app market is saturated, so what would make users switch from their current app to a new one?
What feature would engage a new set of users?
The group conducted 19 in-person interviews and 39 online surveys submitted focusing on the main target market: young professionals.
Examples of questions for the interview:
What do you think about online dating?
When was the last time you went on a date?
What are the feature(s) on a dating app you use that you dislike most? Why?
Profile of the interviewees
The main age was between 25- to 31 followed by 32–36. 70% of the interviews have an established profession, most of them were consultants or managers.
Online dating is easy and convenient and that’s the reason I use it.
Both males and females scored high on the importance of attraction, profession, and similar interests when choosing a partner.
This specific audience doesn’t like the lack of personal information. They want to have a deeper understanding of what people actually like, motivations, and hobbies. They believe the description on the profile is really important as well.
The “gamification” of Tinder doesn’t attract them. They don’t want to spend their time swiping left or right on a huge amount of people.
The result shows that people prefer tags rather than icons when displaying interests and hobbies.
As busy professionals, they think that location is an important factor as they don’t need to spend their time commuting.
People also like to have filters about ethnicity, relationship status, and height.
“People are the same the world over, and all the usability guidelines remain the same. After all, usability guidelines are derived from the principles of human-computer interaction (HCI), which are founded on the characteristics of computers and the human brain and the many ways the two differ.”
There are many apps that allow users to connect with other people. Some of them are focus on “gamification” and prioritize quantity over quality such as Tinder. Other apps and websites are focused on finding the “perfect match” and attracting people inclined to have a serious relationship eg. E-Harmony.
There are also apps that connect people for networking (Shapr)or specific apps for a casual relationship such as Happn, which shows you where you and other users have crossed paths.
The domain research focused on the apps with similar features as an app and also the most popular ones in the research.
the app is the only app that coordinates the 3 main features including advanced filters, girls messaging first, and check in a specific location.
Most apps allow users to see the distance between their connections but the app allows users to see exactly where their connections are, whether it’s a coffee shop, a museum, or a gym.
At this stage we organized the features we believed would be more valuable for users, mainly focusing on early adopters for the first launch of the app. The features considered were validated on the research process.
Must have: Check-in, Map, Profile, Connections List (incl. msgs), Match Pop Up, Settings, Profile, Preferences, Onboarding.
Discover — How do users date online?
First, I created a provisional persona for a typical user based on online research and the base of users within my friends and family. This
persona was created with assumptions and not fully research-based, but it was something that I came back to throughout my project to
guide my design decisions and priorities. (If this was a bigger project I would want to validate with more user interviews.)
Matt socializes a lot with his friends and never misses a happy hour after work. He also doesn’t want to spend a lot of time setting up dates, for him convenience is extremely important.
It was created to bring a better understanding of our target market, using the persona as the protagonist and developing the situation involving her problem and the solution for it.
It’s 4 pm and Catherine doesn’t have any more meetings for today, she decides to go to a coffee place 5 minutes walk from her office. She wonders if someone around here could be free for a coffee, so she decided to enter this new app which she can connect with people around her for dates or networking.
She downloads Pain and checks herself in the location. After the check-in, she was able to see her potential matches. She clicks “like” in one specific profile, Jack, who is 30 meters away from her in another coffee place. She sends him the first message and they start a conversation. They decide to meet each other and arrange the location for the date 5 minutes after.
User flow + Experience Maps
The user flow below refers to a female user that already downloaded the app (there is no onboarding process).
The steps involve the user checking in to a location, browsing users, clicking “like” in a profile, receiving a match notification, sending a message and a virtual gift to the matched profile, receiving a reply from that message, chatting through the message system inside the app, meeting the match in person, going back to the map screen and unpinning her location.
Once we had collated our research, we created a user journey map to help us visualize the entire end-to-end experience and understand pain points in the user's current journey. We started the journey from the downloading stage right through to chatting with a match. It gave me an idea of where improvements could be made especially on the onboarding process.
The task was to use the app considering you already passed the onboarding process.
Pain Point (a)
As soon as the users click on “check-in” (central icon at the bottom nav bar), they weren’t able to find the profiles of the potential matches that were in the “Discovery” screen (first left icon at the bottom nav bar)
Instead of 2 screens, we used the same screen for the check-in and matches (there is no need for 5 icons).
Pain Point (b)
Some users were confused by the 2 screens as they were too similar. The first one they could browse profiles and the second is the profile page.
Instead of 2 screens with a similar design, we decided to use the same screen for the check-in showing the map with the potential matches at the bottom and another one as the main profile screen.
In order to improve the experience of users, the group conducted contextual inquiries explaining the scenario for the test in a semi-structured interview.
We interviewed 9 people in person using the Guerilla Usability Test approaching busy executives at We Work Aldwych House, Central London. A platform for prototype: Adobe XD
Scenario for the test
You are Lucy, she is single. Lucy is at We Work. It’s 4 pm and she doesn’t have any more meetings for today, she is having a coffee. She wonders if someone around here could be free for a coffee, so she decided to enter this new app which she can connect with people around her for dates or networking.
1 — Start using the app, browse and send a message to someone
2 — Change the age of people you want to connect (Preferences)
3 — Change your profile information
check-in, matching with a profile and sending a message
Profile, settings, and preferences
The color is picked carefully to match the flat aesthetic of the app design
Continuing with the UI, Kept the category page pretty similar to the standard eCommerce layout as not to confuse the user. Keeping a filter for Home try on if the user is focussed is pretty sure to try before buy whatever the item is.
A solution to keep both — the normal and Test fit products in a single card as discussed in the pain points, hence the toggle button will help me identify the product and its further lifecycle.
In case there is no product for a test fit, the user will simply proceed with the regular checkout
Selecting the timing is very critical since the task mentioned to me the delivery to be in hours — I am not using the date selection here, assuming it is for the same day.