
Designing a smoother Saciva experience to encourage student return and engagement

What is Saciva ?
Saciva is a community-driven platform designed to help students in the U.S. manage housemates, subletting, and peer-to-peer buying and selling in one place. Built primarily for international students, the app aims to make it easier to navigate life beyond the classroom through trust and connection.
My Role
Responsible for moderating Usability testing, Research Planning and UX Documentation
Team
4 UX Researchers, 1 Product Manager, 1 Developer
Duration
Sept 2025; 6 Weeks
Saciva had previously conducted a beta test & launched a survey with 250+ students where they found

76.4%
Students strongly wanted an app for housing + reliable roommates

Trust gap
Students wanted real profiles (no spam/fake accounts/ads)

Safety Concern
Privacy and security made social groups feel risky
At the kickoff meeting, the founder mentioned

"The app faces a classic chicken-and-egg challenge: low activity reduces trust, and low trust makes users hesitant to join"
To solve this,

01
We Framed our research to
Understand whether students can complete core tasks efficiently and confidently
Identify where AI could meaningfully reduce effort and improve clarity
Evaluate whether the experience encourages return & feature adoption
Completing core tasks without friction
Housing, Housemates and listings
First impressions and early trust
Onboarding and confidence despite low sign ups
Knowing where to go next
Navigation and information architecture
Opportunities for AI support
Tasks that felt slow, repetitive, or confusing
8 International students in the U.S. actively looking for housing, flatmates, or marketplace options.
How we tested?
Relatable Task-based scenarios across onboarding, search, and listing flows
Observation of behavior, errors, hesitation, and confidence
" You’re about to begin your Master’s program at [Pratt/UIC] University, and you’re searching for a suitable place to live nearby. Find a room close to campus that includes all the amenities you consider essential. "
What we learned from the Usability Tests
We synthesized the findings using affinity mapping to uncover recurring patterns and prioritize the most critical usability issues as follows :

Trust
4/8
Users questioned whether they would continue using the app.

Look & Feel
5/8
Users prefer dark mode, whereas 1 user didn’t like it and prefers simpler visuals.

Features
4/8
Users mentioned they'd come back for Marketplace, 4/8 for Finding housemates, and 2/8 for Finding Rooms.
We uncovered 4 key opportunities to improve the usability of Saciva
Insight
01
Onboarding
Users faced some friction during onboarding , which blocked a smooth entry into the app and a clear understanding of its value.
02
Navigation & Trust
Users struggled to recognize the meaning of features , causing friction in navigation
throughout the app.
03
Marketplace
Users felt Marketplace was cluttered and split into separate buy/sell flows, leading to confusion, empty states, and lower perceived value.
04
House Listings
Users struggled to evaluate the suitability of house listings due to ambiguous lease terms, missing context on the listing creator, and missing location metrics
Design Opportunity
Onboarding could be simplified by clarifying required steps, improving guidance copy, using a more intuitive date picker, and refining preference selection.
The homepage and navigation could be simplified to make key actions easier to find
Marketplace could start with “All Products” and add product pages with a wishlist.
House listings could provide more specific, decision-ready details instead of high-level summaries.
Now, let’s dive into the changes we recommended to improve the experience.
01
Simplify Onboarding
BEFORE
AFTER


Suggesting nearby universities and improving the copy makes it easier to understand.
BEFORE
AFTER

Providing a third
option for more
variation and to avoid
decision paralysis.
Refined the UI so the selected option feels familiar and the description is more noticeable.
Adding a mid-range choice for preferences that don’t fit a simple either-or and improving the UI
03
Redesigning Marketplace to improve product discovery, evaluation, and selling
BEFORE
AFTER


Prominent “Start Selling” button gives users an obvious entry point to create a listing without searching through other menus.
Add a “Sell” toggle inside Marketplace so users can browse, list, and manage their items in one place, matching their expectations and making it easier to add new inventory
Users can browse, list, and manage their items in one place.
BEFORE
AFTER


Added a wish list count to show how many people saved the product
Product cards show only key details (title, cost, distance, “negotiable” tag, and chat), making them easier to scan

Tapping a card opens a dedicated product page with full details, matching user expectations from other marketplace apps.
Introduce product pages and wishlist features to support confident decision-making
04
Improving house listings with clearer owner/housemate details, lease context & commute estimates
BEFORE
AFTER


Addition of commute estimate time gives users extra confidence in choosing the room.

"Listed By" card identifies the host role
Specific tags
clarify the
contract type.
(Sublet / Lease
transfer)
High-contrast CTA improves discoverability.

but that's not it,
We also noted what users liked about Saciva
01
Visually appealing onboarding with helpful preference options.
02
Good interactive map while browsing rooms.
03
Match rate feature for roommates felt helpful
04
Negotiable / non-negotiable option when adding a product.
05
Excited for the upcoming AI feature!
and on that note,
We asked users in what way can an AI assistant help them enhance their search on the Saciva app and this is what they said…
01
They see value in AI if it saves time (e.g., notifying about new listings, narrowing down options).
Proposed solution : Include alerts and personalized filters driven by AI for new listings or matching amenities, reducing manual searching.
02
Many would only use AI if filters or search functions are insufficient.
Proposed solution : Integrate AI as an enhancement to existing filters, not a replacement, e.g., "AI-assisted search" as an optional layer.
03
AI is appealing when it can match very specific interests (e.g., roommate preferences, house amenities).
Proposed solution : Build fine-grained preference matching where AI considers detailed constraints and scores options for users.
So, what's next ?

Validate
Fix bugs and Test the updated flows with students to confirm improved task success and confidence.

Measure
Track key funnel metrics (onboarding completion, listing creation, chat starts, and return rate).

Iterate
Use results to refine the highest-friction steps and ship improvements in small, fast cycles.
But before I sign off

Saniya, Harshita, Sriya & Tarun

A big shoutout to the team for making this project so fun and impactful and to Prof. Madhav Tankha for his guidance throughout.


