Bringing back the
social energy
of
2016.
A fun way for university students to create spontaneous, low-stakes hangout moments, like the good ol' days.
Our inspirations
Imagine this
It's a friday night and
18-year old you met
amazing people
that you'll
never see again.
————————————————————————————————————————————-
200 hours
is how long it takes for someone to become a close friend
49%
of Americans lost a friend simply because they drifted apart
Investigating 2016
What made 2016
iconic?
Intrinsic Value
Sharing online was low-stakes and genuine. Posts were for friends, not for performance. Self-expression online was not a substitute for real life.
Creator-to-Community Relationships
Creators were driven by craft, not conversion rates. They built real relationships with their audiences at conventions, through long-form content with value.
Self-Expansion Through Exploration
The internet was a place to discover what you liked, not to be told what to like. Tastes evolved organically as users navigated a globalized digital world
It was the year of realizing things - Kylie Jenner
Connection Founded On Shared Interest
Tumblr, Vine, and early Twitter made community an automatic consequence of interest. Finding what you loved meant finding the people who loved it too
User feedback
Personas
and
user insights
that shaped our
product
Micheal Spataro
"2016 felt like the last year the internet was actually social. Now it's a highlight reel optimized for strangers. I miss logging on because I wanted to, not because I felt like I had to."
Jenny Contento
"Pre-COVID things were lighter. Memes were weird and abstract and nobody took themselves too seriously. Now everyone's performing all the time, including me, and I don't know when that started."
Sung Yu
"Back then your online presence just... happened. Now it precedes you. I catch myself curating my life to fit a profile nobody asked me to maintain. It's exhausting."
Sophia Lu
"The hardest part of making friends in uni goes beyond finding people, you’re surrounded by them. The activation energy to initiate a connection between you and a stranger is so important. Nobody wants to be the one who plans something, so nothing happens. We're all waiting for someone else to shuffle the deck."
Persona
What the
pain points
of a
student seeking deeper friendships?
Decision Fatigue Kills Spontaneity
When every hangout requires group consensus, venue research, and a plan, the cognitive load exceeds the reward. The default becomes staying in.
Socializing Feels Performative
For Gen Z, digital media is the primary record of lived experience. Photos and videos define them, creating pressure to engineer experiences worth posting.
Critical Window for Self-Discovery
University represents the highest-density environment for identity formation most people will ever experience. Students have unparalleled access to people, interests, and new experiences, but don't always capitalize on this.
The Key Problem
Our problem
analysis
key findings
Decision Paralysis
Coordinating unstructured social time is high-friction by default. Without a structured starting point, group plans collapse under deferred decisions. Passive consumption fills the gap. The activation energy required to hang out has measurably increased for a generation that socialized primarily through screens during its most developmental years.
Algorithmic Displacement of Play
Engagement-optimized platforms are structurally incentivized to maximize time-on-screen. The attention economy competes directly with the spontaneous, low-stakes interactions that build genuine social connection. Average daily social media use among 18-24 year olds is 3+ hours (GWI, 2024), with self-reported satisfaction declining alongside usage.
Creator Economy Pressure
The normalization of the creator economy has restructured how users relate to self-expression. Likes, views, and follower counts function as social validation proxies. 72% of Gen Z report feeling pressure to present a curated version of themselves online (Morning Consult, 2023). Sharing has become strategic rather than spontaneous.
How might we reduce the
activation energy
of
in-person hangouts
so that authentic connection
becomes the path of
least resistance?
Our Final Product
Introducing
shufflr
The Shuffle
Input a few loose preferences, vibe, group size, distance, and available time, and Shufflr generates a curated shortlist of activities for you.
Interest-Based Proximity Matching
Shufflr surfaces activities where people with overlapping interests are already showing up nearby.
Memory Capture
After each activity, Shufflr prompts your group to take a photo. The app then creates a record of what you did, who you did it with, and what it felt like.
Connection Founded On Shared Interest
Invite and join as many different communities as your choosing.
features
view trending activities
features
plan low-stakes hangout sessions
features
strengthen your friend groups
features
plan low-stakes hangout sessions
features
strengthen your friend groups
features
view trending activities
features
join nearby communities
features
find events near you
features
meet like-minded friends
features
find events near you
features
meet like-minded friends
features
join nearby communities
features
plan our your outings
features
join different chats
features
send invites to friends
features
join different chats
features
send invites to friends
features
plan our your outings
features
plan low-stakes hangout sessions
features
find your new passions
features
filter based on price
features
plan low-stakes hangout sessions
features
filter based on price
features
find your new passions
features
gamified interface
features
sense of mystery
features
adventure-like
features
adventure-like
features
gamified interface
features
sense of mystery
features
ensure your memories live
features
share photos with friends
features
build a digital album
features
build a digital album
features
share photos with friends
features
ensure your memories live
Our USP
What makes
shufflr
different?
Frictionless Activity Generation
Preference-aware randomization reduces time-to-hangout from 47 minutes of group negotiation to under 60 seconds.
Removes the primary drop-off point in social coordination, leading to high repeat-open rate.
Interest-Based Proximity Matching
Users discover new connections through co-presence in physical space, not through cold follow requests.
Each activity is a potential new user touchpoint with no CAC.
Memory Capture
Private memory capture builds emotional investment over time. The longer a user stays, the more the archive means to them.
Retention flywheel: switching cost increases with every memory logged, structurally improving LTV.
Implimentation and
feature validation
Desirability
Targets the loneliness and social friction most acutely felt by 18-24 year olds, a cohort that over-indexes on mobile usage and under-indexes on self-reported social satisfaction
The shuffle mechanic directly addressing the nostalgia brief through behaviour design, rather than aesthetics alone.
Viability
The digital archive creates a structural retention flywheel: emotional investment in the product increases with usage, improving long-term LTV without requiring continuous feature novelty.
Feasibility
Activity generation and location-based discovery build on well-established infrastructure (Google Maps, Eventbrite, Yelp APIs); Shufflr synthesizes existing surfaces rather than rebuilding them.
Success Metrics
How are we measuring
success
using the North Star Metric?
Weekly Active Completers
The percentage of weekly active users who complete at least one Shufflr-initiated activity with another person in a given week.
Shuffle-to-Hangout Conversion Rate
% of generated shuffles that result in a confirmed activity. Primary measure of the algorithm quality.
Memory Capture Rate
Retention flywheel: switching cost increases with every memory logged, structurally improving LTV.
7-Day Return Shuffle Rate
% of users who re-shuffle within 7 days of completing their first activity. Measures if a single use is enough to drive habitual behaviour.
Risks and
mitigations
Cold Start Problem (High Likelihood / High Impact)
Without sufficient user density in a given geography, social discovery feature has no network to draw from.
Mitigate by launching exclusively on dense university campuses to guarantee geographic concentration from day one.
Novelty Fatigue (Medium Likelihood / High Impact)
The shuffle mechanic may feel compelling on first use but lose pull once the activity library feels repetitive.
Mitigate by: Introducing seasonal and campus-specific shuffles to maintain freshness. Possibility of opening up a user-submitted activity layer to create community-generated inventory at no marginal cost
Memory Capture Misalignment (Medium Likelihood / Medium Impact)
If the photo prompt feels like an obligation rather than a reward, it risks replicating the performative social media behaviour the product is designed to move away from. Mitigate by: Trigger the prompt as an opt-in, celebratory end-of-activity moment rather than a push notification mid-experience