2025 Harshita Dandu
Made with coffee(lots of it) & questionable duck advice
Last updated on 12 Oct 2025

Finding 1
Problem 1
Recommendation 1

Introduce a consistent global nav and unify marketplace flows to make core features easy to find
We added a global bottom navigation bar with clearer icons so students always know where the core app features live, reducing
mis-taps and backtracking between core actions.
Grouped coming-soon features into a single AI tile to reduce visual noise and highlight interest through visible sign-up counts.
For Marketplace, we replaced the split buy/sell pathways with a single entry point and "Sell a product" CTA, and shifted focus from
category-heavy paths to real inventory first.
Finding 2
Roommates
Communicate match logic clearly and design flexible filtering to help students trust and act on the results
To improve search accuracy, we added a dedicated filter page with familiar controls, multi-select options, and a clear display of active
filters. An AI-powered search bar further accelerates discovery by surfacing personalized results quickly
We added visible verification badges and a Compatibility Breakdown so students can immediately see which profiles are real and why
someone is a good match


Problem 2
Recommendation 2
Finding 4
Simplify location selection and expand preference options to make choices feel easier and more intentional
We clarified the purpose of location selection and introduced a more flexible preference model to make onboarding feel intuitive rather than restrictive. This helps students understand why certain inputs were needed and gives them options that better reflect their real-life habits. It encourages students to complete setup without hesitation.

Problem 3
Recommendation 3
Finding 3
Make listings clearer and easier to revisit so students can quickly judge fit now and have strong reasons to come back later
We made oom, roommate, and product listings more scannable by surfacing the most relevant details up front
Added dedicated detail pages so students can review full information before deciding to reach out
Introduced wishlist and saved-search patterns across rooms and products so students can track options they like and revisit them
Problem 4
Recommendation 4


Behind the curtains
🌟 Major Findings & Insights
Transforming notes into insights

From our research, four clear UX issue themes emerged
🌟 Defining Objectives & Goals
High-level goals that defined our study
We started with a kick-off meeting with Saciva’s founder to understand the product’s vision, identify what wasn’t working, and define what
success would look like for the team
Transforming early conversations into north stars.gif

Making it easier for
students to complete
key tasks without
spending too much
time on the app

Increase repeat visits
by encouraging
students to come
back after first use &
adopt more
features over time

Grow the platform’s
inventory by
increasing the
number of listings

Increase the number
of students who
complete onboarding
without dropping off

Understand whether
students want an AI
assistant to help
them find relevant
options faster

"We’re stuck in a
chicken-and-egg loop
Students hesitate to engage because
the app feels too empty, but it stays
empty unless students engage"
- Founder, Saciva
✰ Introduction
For many students, especially those moving to a
new country, finding housing, reliable roommates,
and affordable essentials can feel overwhelming
Saciva aims to simplify that transition by
bringing rooms, roommates, sublets, and a
student marketplace together in one place
⚡ TLDR - Toggle between findings & recommendations
Findings
Recommendations
9:41
Finding 1
Inconsistent navigation and
unclear entry points made it
hard for students to find and
move between core sections
✦
Finding 3
Early onboarding friction hindered smooth entry into the app
✦
Finding 2
A lack of visible verification and unclear filtering behavior reduced students’ trust in the results
✦
Finding 4
Students struggle to confidently evaluate rooms, roommates, and products due to limited clarity in listings
✦
Before
Eliminating early friction & trust gaps to
increase user adoption & return rates

Saciva
Jump to Solution
7 min read
ROLE
User Research
Recruitment
Usability Testing
Interaction Design
TEAM
4 UX Designers,
1 Design Mentor
MADE IN
6 Weeks
(Oct 2025 -
Dec 2025)



✨ AI Feature Insights
In post-test questionnaire, we asked users how an AI assistant could support their search experience and what
role they wanted it to play
💬 Hover to see real user quotes
Students saw value in AI only if it saved them time by reducing manual searching
Recommendation: AI-assisted search alerts & personalized suggestions for new or similar items.
Students wanted AI to enhance, not replace, filtering, they still wanted control over the criteria
Recommendation: Integrate AI-assisted search bar that works on top of existing filters instead of overriding them.
AI was appealing when it helped match very specific lifestyle preferences (spending habits, cleanliness, food choices, amenities)
Recommendation: Introduce richer lifestyle inputs so future AI matching can suggest roommates & rooms that mirror how students actually live together.

Saniya, Harshita, Sriya, Tarun
A huge thank you to my Professor Tankha for his valubale guidance throughout the project & my incredible team!! 🥰
Truly the best people I could’ve asked to learn and create with <3
Meet the team
Final Reflections
Next Steps
This redesign lays the foundation for Saciva’s next chapter, but there’s still more to explore. My next steps would be to validate these solutions through another round of user testing and see whether the new flows actually make it easier for students to onboard, navigate, and complete key tasks.
I’d also love to explore AI more deeply, prototyping different ways an assistant could refine search, suggest matches, or resurface saved items without feeling intrusive.
Feel free to flip through our detailed usability report here!
Thank you!




