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.

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