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Conversation reveals more than forms ever couldEvery interaction should feel magical, not mechanical
Can't Google answers in real-time conversationNo editing means genuine first thoughtsVoice tone reveals personality that text cannotNatural conversation flow prevents overthinkingSpeaking: ~150 words per minuteTyping on mobile: ~20-30 words per minute2-minute conversation = 300 words spoken vs 40-60 typedStories emerge naturally in conversation vs forced in promptsNo prompt selection paralysisNo writing and rewritingNo comparison to others' answersConversation feels natural, not like homework
Hinge has 35+ onboarding screens :)Hinge offers 60+ prompts to choose fromUsers must select 3 prompts from this overwhelming listUsers can (and do) Google "best Hinge prompt answers"The same witty answers appear across multiple profiles
Progress bar = task = workHeart = journey = emotionThe progressive filling of the heart, triggers emotion to complete it and make it full
To remove cognitive load → one decision per screenbinary choices reducing analysis paralysisauto advance builds momentum (gamified)List of buttons + forms would feel like surveySwiping gesture is slow and would have needed 20 cards instead of 10 to understand user preferences
Voice after rapid-fire creates momentum (binary → complex)Gives us guardrails to not make the user disinterested with random AI questionsExample: If someone selects that they like staying in vs going out, and if the AI then asks them about their recent travel adventure, the users motivation will drop mid-convo.
Post-conversation = increases chances as heart is almost full and mentioned final step before big revealPre-conversation = too soon, adding pictures last makes them feel we care about them, as humans and less about their looks, app decisions translate thisContextual request ("Show me those hiking photos you mentioned") = +20% quality
Step 1-3: What users expect (phone, verification, basics)Step 4: Delight moment (zodiac) signals this is differentStep 5-6: Heart gamification warms up sharing mindsetStep 7-8: Innovation (voice) when trust is establishedStep 9-11: Commitment phase (photos, preferences)Step 12-13: Reward (magical reveal)
What if the user skips the conversation request? → This will be a required step in the process. We’ll experiment with the conversation length, the request message, conveying that how this is super important for us to get the best matches for them and other similar strategies will have to be tested.What if the users don’t like the AI generated profile content and the number of edits are significantly higher than anticipated (>50%)? → We’ll identify the personality traits the user is mostly editing. We have multiple sections on the profile so we’ll track edits there as well. We’ll also modify the system prompt of the AI and setup the right feedback loop to improve content.Why didn’t we have ID verification as a part of the onboarding? → Id verification is a hindrance in the flow. Not everyone has accessibility to their documents all the time, and even the place / time might not be the best for this. Keeping the process natural was the goal, and this would have been very mechanical.
We’ll not show the transcript, it will be a 100% voice based interaction.The profile design is not scrollable as the functionality was difficult to build while using a browser for showing mobile app.Users will be able to edit their profile in case they’re not happy with any parts. Plus, there will be a corpus of information the AI will have to give them ample options for different sections. [Can also be through on-demand AI conversations]The content on the app is a mock version of what we might have for the rapid fire or AI conversation, this is something which has to be researched before finalising.The layout and structure could be lot better, but there are certain limitations to the current tools and I also exhausted my build credits.
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Case Brief
Dating apps have a tradeoff between quantity and quality of profiles. The more detailed onboarding , richer the customer profile but more the drop offs at each step. Reimagine the customer onboarding given the genAI tools at your disposal that solves the problem.
Product Notes
Our Approach
Transform onboarding from data collection into conversation. By introducing AI-powered voice interaction, we capture 10x more personality insights in half the time, creating the richest profiles in the industry through the most natural interface: conversation.
Key Principles
How are we building rich profiles?
Our 2-minute conversation combined with rapid-fire questions creates a multi-dimensional personality profile equivalent to 15-20 traditional prompts.
Core Personality: Rapid-fire + AI Conversation
Through the rapid fire sequence as well as through the conversation, we’re able to identify key traits of the user’s personality. We can use this to build a persona which would help us build a holistic profile of the user.
We can analyse things like → Introvert vs Extrovert signals; Adventure-seeking vs Stability-oriented (dates or convo starters); Direct vs Nuanced (communication compatibility); Surface-level vs Deep-connector (emotional depth); Career vs Relationships vs Experiences vs Growth (long-term compatibility prediction)
We use the answers to all the rapid fire questions to build our guardrails for the AI conversation. We then during the conversation, go deep into conversations to identify values and personality of the user.
This is super unique. Why? Everything else in terms of dating more about optimising, finding the right kind of information to mention, the exact prompting style - it has not been about finding your partner lately!
Why Voice?
Even the normal day-to-day conversation could lead to building a holistic persona of the user. Think understanding on the level of self-love, openness, gratitude, understanding - all of these unlock deeper level values which are great for compatibility testing.
Authenticity Through Constraint
Information Density
Cognitive Load Reduction
Hinge Friction
In the dating world, Hinge is considered to have one of the most rich user profiles. The profiles are high effort and require upwards of 12 mins to build it with precision and care. But even with this approach, there are a lot of frictional points that could help us win.
Observable Friction Points in Hinge's Model
Hinge vs Us
Design Choices
Every design decision was evaluated against one question: "Does this make users feel more themselves or more like they're performing?"
1. Using “filling the heart” as progress bar
2. Why using rapid-fire with binary options?
3. AI Conversation after Rapid-Fire
4. Photo request AFTER voice conversation, contextualized to what they shared
5. Onboarding Flow + User Emotions Journey
Phase 1: Familiarity (45s) → Build trust through expected patterns before introducing innovation.
Phase 2: Personality Discovery (2 min 40s) → The magic happens here - rapid-fire choices + natural conversation.
Phase 3: Commitment (45s) Users who've shared their voice will complete photos and preferences at 95% rate.
Emotion Triggers through the Onboarding Journey:
Curiosity (Welcome screen) → Trust (Phone verification) → Delight (Zodiac surprise) → Excitement (Heart appears) → Flow (Rapid-fire) → Vulnerability (Voice conversation) → Pride (Photo upload) → Anticipation (Loading) → Joy (Profile reveal)
Product Analytics
Our analytics framework operates on two levels: 4 primary KPIs that define success (65% completion rate, <4 minute time-to-profile, 75+ quality score, 40% 3-day retention) and 10 screen-level diagnostic metrics that pinpoint issues when KPIs falter.
Profile Completion Score: I have given higher weightage to number of words (Voice_Ccore) → based on our target set for each conversation; and number of photos (Photo_Score) as these 2 dimensions cover the profile aspect of a user.
KPIs + Why? + Post Launch
Screen Level Data
Questions to Think About
Notes about the Prototype
Please feel free to drop your feedbacks.
Prepared by Navin for Meant2B
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