Case Study: Improvements & New Feature in Dating Apps
Understand the Platform — Approach
To really understand the platform, you need to experience it and which I did for a couple of days looking for many dating apps and here I have thought of a few ideas to improve and also can add a feature.
I chose one of the dating app(I don’t want to name it) in the market for this User Story, Which was based on Match Making & Personality Test.
1) Problem & Possible Improvements:
1.a) Sign up Process: During sign up, it asked me some basic questions which are surely very beneficial like — User’s gender, In which gender user is interested in, whether he/she likes to smoke or not, what does the user want from their partner at what level, etc.
Problem: Since there were so many questions I felt at one point that I started to lose interest to go further. Here I think, if not many but few customers would surely feel overwhelmed and they might bounce from the platform.
Possible Solution: Number of questions in personality test can be reduced (not the ones which are actually super important in the beginning to show the user a better fitted match), so that we will have comparatively less bounce rate at the signup and show users that what really the Dating app is.
Rest of the personality questions can be asked later via other mediums like Notifications, pop-ups, Email Marketing.
1.b) Preferences: During the personality test, I already answered questions like- Preferable Age-bracket of the partner, Distance range within which used is willing for a Partner.
Problem: Even though I did set my criteria of age bracket and set this parameter to very important it showed me people out of the age bracket, and the same goes with the distance.
Possible Solution: Need to work on the matchmaking algorithm in order to make sure that we show the correct recommendation to the user based on his preferences.
2) Features to add:
2.a) Face Recognition: One of the USP of the Dating App says it’s safe & secure, by daily profile quality checks to ensure a safe dating experience with real people.
Idea: Introducing face recognition feature. Few questions may come into mind like- Why, Where & How.
WHY?: Face recognition feature will add more value to the Dating App USP. This feature will attract more customers towards the platform because there will be 0.10% of chances of catfishes.
WHERE & HOW? : Uploading a picture will be compulsory for the user at the time of Signup, after uploading his picture we can ask to take a selfie for which we need to ask his permission to access the camera of his device.
After the user takes the selfie System will use biometrics to map facial features from a photograph, then actual evaluation can be done with the uploaded picture if this is the real user.
By doing this, user will be sure that it is the safe platform because all have to go through with the process meaning Authentic users (not to be afraid of bots anymore).
2.b) Emoji & GIFs: I also noticed that the Dating App don’t offer emoji when anyone tries to write a message on the platform.
Idea: Introducing Emoji & Gifs to the Platform feature. Again, a question may come into mind — Why do we need Emoji/GIFs in the Platform?
Answer: Using emoji would bring uplift in message writing because emoji can express emotions towards the other person and are being mostly used in social media platforms too, The dating App can Introduce Augmented Reality(AR) Emojis and can charge a little to users for that.
Proposal:
Here is the Proposal to add the Face Recognition Feature for the team to Implement.
Signup- Face Recognition Functionality
AS A User
I WANT to have face Recognition
So THAT I will be sure that no catfish will bother me
SCOPE
● Add more value to USP(Security)
● Only front camera should be enable if using mobile.
● User Should be able to retake the Selfie.
● User’s selfie should not be displayed in the user Profile.
Pre Condition
● User should add a Profile Picture during signup.
● User should capture the selfie properly.
Acceptance Criteria
Scenario 1 : User is Verified
GIVEN I am on Verification Page
AND I give Proper Selfie
AND I Click Upload
THEN I will Successfully Verified
Scenario 2 : User is not Verified
GIVEN I am on Verification Page
AND I give not a proper selfie
AND I click Upload
THEN I will get a error Message ‘Please Take selfie Properly’
Scenario 3 : User can retake selfie
GIVEN I am on Verification Page
AND I give not a proper selfie
AND I want to retake a selfie
AND I click Upload
THEN I will successfully Verified
Measure the Success:
Of-course, optimising, adding or thinking of adding a new feature always brings a question — How much uplift or profit can we expect to the business of that particular feature?
Success Measure: In order to measure the success of adding new features is always a great way of testing. We can do an A/B test and then the numbers can tell if the newly added feature brings something to the table or not.
After the implementation of these features I can measure success of the features & changes by following metrics.
a.) Signups
After the implementation of the updated Personality test list during signup, the Dating App will achieve more Signups and also the number of user’s bounce rate will be reduced from signup page.
Also when the Dating App will tell users that how secure it is to use the platform because of the authentication of the face recognition, the platform will definitely gain attraction of the user.
b.) Conversion Rate to Customer
By showing more relevant matches to the user according to their, the conversion rate will definitely increase.
I can measure how many % site members converted to paying members. It doesn’t matter whether they paid 99 cents or 999 dollars.
For example — 10 (paid users) / 100 (registered users) * 100 = 10% conversion rate
c.) Unique Visitors
Security is also a USP of the Platform by implementing the Face Recognition feature the Dating App will achieve unique users, so by real-time verified Profiles the Dating App will definitely Adieu Bye! to Catfishes.
A user with unique characteristics who visited the platform during a certain period of time (usually 1 full day). Most often, under the unique characteristics, several parameters for unique characteristics: registration data, browser, IP address, location and etc.
By measuring the number of unique visitors from each marketing channel, I can also measure the effectiveness of all the marketing campaigns and actions. And although an increasing number of unique visitors per month is an excellent indicator, also by looking at the engagement indicators, such as the average time on the site, the average number of pages visited, repeat visits, email subscriptions, and other similar metrics. These metrics will tell the quality of the traffic, which is no less important than quantity.
d.) Customer Retention Rate
Retention metric is the company’s ability to maintain long-term customer relationships & by improving the matchmaking algorithm we can show more relevant matches to the user that will help the Dating App to retain a user more.
A high score means that users are happy to come back for and recommend the platform to their friends. Work with retention starts from the first contact between platform and user and, ideally, never ends.
e.) Churn Rate
The concept of churn refers to users who have left the platform and is usually expressed as a percentage or monetary value. For example, if your churn rate is 10%, then this means that every month your active client base is reduced by 10%.
After implementing a strong matchmaking algorithm, users who are not happy with the exact match of their preferences will stay with the Dating App. Platform will be able to achieve more engagement with the user, hence reduction in churn rate.
Supposedly at the beginning of the month(after the implementation of the features & changes), there were 100 user on the platform, and by the end of the month 5 of them were gone (they stopped using the platform, changed the tariff, etc.), then the churn rate is: (5 users / 100 users) * 100 = 5% churn
Hence after implementation of these features & changes churn rate will get reduced.
f.) Monthly Recurring Revenue (MRR)
Showing the right match we can gain the trust of the user so that he will again or first time buy premium membership which will gonna increase the Monthly Revenue. Additionally, after the implementation of the Emoji & Gifs feature into the platform, the dating app will definitely gain more revenue.
MRR is the total monthly income received from Premium Members. ARR (Annual Recurring Revenue) is a similar indicator, but for annual income. Tracking these two values is useful for short and long term planning.
For example, say you have 5 customers. Three of them are paying $10/month, one is paying $20/month and one is paying $100/month. MRR in this example is $150 ((3 x $10) + $20 + $100).
But despite seemingly easy math, one needs to keep track of several MRRs:
● New MRR — MRR that you received from new customers;
● Add-on MRR — MRR from current customers (due to switching to a more expensive tariff)
● Churn MRR — MRR that you lost due to customers switching to a cheaper package or when the user canceled (or did not renew) the subscription.
Of-course there can be many ways to work on this case study and I narrated mine.
Thanks for reading, If you have any suggestions to this case study, or maybe something I have missed to include then please feel free to give me feedback in the comments.
STAY HEALTHY! :)
