MOBILE APP
Subscription offer
DURATION
June - August 2023
COMPANY
Umatch
TOOLS USED
Figma
Miro
TEAM OF 4
PD: Aline Saruhashi
PM: Cayo Syllos
Front-end: André Navarro​
Back-end: Gabriel Okamoto
Overview
My role
As the principal Product Designer at Umatch, I led the UX initiative of this project from initial discovery to final implementation. My responsibilities were multifaceted, encompassing user research, design strategy, copywriting, prototyping, and collaboration with the development team to ensure a seamless user experience.
About Umatch
Launched in 2020, Umatch is a dating app designed for college students. With over 500,000 registered users and 120,000 monthly actives, Umatch operates on a subscription-based business model with two tiers: Plus and Premium.
Problem background
Our main goal for the third quarter of 2023 was boosting our users' Lifetime Value (LTV) by 20%. To meet this target, my PM and I focused on understanding the journey of our paying users.
Problem statement
How can we increase user-to-subscriber conversion to boost LTV?
Solution overview
We implemented a time-limited promotion, granting a 50% discount on our Plus subscription to two targeted groups: new subscribers and those who had previously canceled their plans.
This project increased LTV by over 10%, while maintaining subscription retention.
Filter additional banner
Main modal
Unlock additional banner
Discovery
Survey
Goal: Identify the primary factors behind the cancellation of subscriptions by users.
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Method: We sent the survey to users who had subscribed and then canceled their subscription plans. We got 60 survey responses.
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Key findings
Cost is the leading factor in subscription cancellations
52% of the participants canceled due to the price of the subscription plan.
Enhanced user experience for subscribers
Participants reported a fivefold better user experience when subscribed compared to their time as non-subscribers.
User interviews
Goal: Analyze the user journey of our subscribers to identify opportunities and pain points.
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Method: We interviewed 10 users who who had subscribed and then canceled their subscription plans. We asked questions regarding the following stages of their journey:
Key findings
Interestingly, the interviews reaffirmed the two insights we captured in the survey and uncovered a new one related to the primary triggers for app subscriptions.
Cost is the leading factor in subscription cancellations
​"I've bought the plan to try it out, but I cannot justify this payment every month to my parents..."
Enhanced user experience for subscribers
"My experience in the app was a lot better as a subscriber. I spent more time in the app since I had unlimited swipes."
2 primary triggers for app subscriptions
Users cited the primary reasons for subscribing to the app as the desire to access exclusive benefits, specifically: 1) the ability to view all users who liked their profiles, and 2) have unlimited swipes with an applied filter.
1) See who liked you
2) Filter
Key hypotheses
After analyzing the research data, I came up with two key hypotheses:
1. Reducing the subscription price, as cost is the main cancellation factor, may lead to increased purchases.
Success metric: LTV
2. Users who subscribe and experience the enhanced features are likely to retain their subscriptions.
Success metric: Subscription Retention
Benchmarking
Goal: Analyze the special offers and promotional strategies employed by our competitors, Bumble and Tinder.
Tinder
Main modal
Bumble
Main modal
Additional banner
Key findings
1. Both Tinder and Bumble present a 24-hour, 50% discount on their subscription plans.
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2. While Bumble extends this discount for the duration of an ongoing subscription, Tinder limits it to the first month of a subscription.
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3. Bumble further emphasizes the visibility of their promotion with an additional banner within their "See who liked you" feature.
Definition & Ideation
Solution strategy
1. Offer a 24-hour, 50% discount on our Plus subscription plan to two user groups:
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New users: Aimed at individuals who have never subscribed to the app, this incentive is based on the hypothesis that a trial of the subscription features will encourage ongoing subscription.
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Former subscribers: Aimed at individuals who have previously subscribed and then cancelled. The hypothesis is that re-engaging with the premium features at a reduced cost will motivate them to renew their subscription.
Wireframe
Iterations
Main modal
2. Identify optimal locations within the app interface to prominently display the special offer, thereby enhancing the likelihood of user conversion.
Based on user feedback (See "Key takeaways" inside User Interviews) highlighting 'See Who Liked You' and 'Filter' as key subscription motivators, I have integrated promotional banners within these features to boost conversion rates.
Additional banners
See who liked you
Filter
Usability test
Method: Tested an interactive prototype of the special offer flow with 5 users.
Key findings
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Main modal: Users didn't understand that the promotion was only valid for the first month of subscription.
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Design implication: enhanced the visibility of this information in the main modal design.​
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Before
After
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Additional banner: Users thought that the additional banner was promoting a different offer, separate from the main modal promotion.
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Design implication: changed the flow by introducing the main modal between the additional banner and the subscription purchase, clearly indicating that both elements are promoting the same offer.
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Flow before
Flow after
Final designs
Main modal
Additional banners
See who liked you
Filter
Interactive prototype
Interested in looking at the interactive prototype? ​
Send me an email so I can share it with you!
Results
Impact measurement
10% increase in LTV
By comparing May's LTV with August's, we achieved a 10% increase. Combined with early quarter deliveries, we saw a total LTV increase of 40%. This far exceeds our initial target of a 20% increase, marking a significant achievement for us
Stable subscription retention
Our restrictive metric, subscription retention, stayed consistent with May's figures. This supports our hypothesis: the offer motivated first-time subscribers to both sign up and continue their subscription, demonstrating the offer's effectiveness and its value to our users.
Reflection
Learnings
Integrating qualitative and quantitative insights
While quantitative data is typically prioritized in offer analysis, direct user feedback can unveil insights not apparent in numbers alone.
Clarity in communication is key
Feedback revealed a common misconception that the offered discount would apply indefinitely, while it was actually a one-month introductory offer. This underscores the importance of clear and transparent communication regarding offer details to prevent misunderstandings and enhance user experience.
Next steps
A/B test with the Discount Value
Conduct an A/B test offering a smaller discount to users who have previously subscribed. The goal is to test if a smaller discount for this group, who has already recognized the value of the subscription, maintains the conversion rate.
A/B test with the Discount Duration
Evaluate if a longer discount period of more than 48 hours increases the conversion rate by offering users a larger window to view and consider the offer.
A/B test with the Discount Copywriting
Conduct an A/B test to evaluate the effectiveness of different copywriting approaches on our offer modal. For example, compare the effectiveness of 'You won 50% off' against 'Don't miss out on 50% off' and analyze which generates a higher conversion rate.