Nestohub, Real-Estate SaaS
Real-Estate SaaS Case Study
I restructured the product journey to make property discovery, builder trust, and conversion paths more transparent.
About Nestohub
Nestohub is a real-estate product where buyers discover projects, compare them, assess builder credibility and send enquiries. This case study covers restructuring that journey so trust signals and conversion paths were legible at every step rather than buried.
The problem
Nestohub's buyers were comparing purchases worth years of income with less structured information than they get buying a phone. Builder credibility in particular was effectively invisible at the moment of decision.
User pain
- Property details were scattered, making comparison difficult.
- Trust signals were buried below promotional content.
- Inquiry paths required too many decisions too early.
Business pain
- Low lead quality due to unclear listing context.
- Users dropped before reaching inquiry intent.
- High top-funnel traffic converted weakly.
Product gap
- No structured progression from discovery to inquiry.
- Builder credibility evidence lacked hierarchy.
- Decision-support features underexposed.
What I owned
Owned
- Product strategy, user flows, and information architecture
- Wireframes, interaction model, and high-fidelity UI
- Validation synthesis and iteration decisions
- Developer handoff with behavior states and edge cases
Collaborated
- PM on scope, sequencing, and KPI alignment
- Engineering on technical feasibility and state visibility
- Stakeholders on domain constraints and rollout priorities
Out of scope
- Backend implementation and infrastructure changes
- Pricing, growth campaigns, and sales operations
- Post-launch paid acquisition strategy
The results
+31%
qualified inquiry submissions
-26%
drop-off on listing exploration
2.1x
faster project comparison flow
Buyers evaluated options faster with stronger confidence. Discovery-to-inquiry flow became more coherent and intentional. Lead quality improved with better trust communication.
The approach
I treated trust as an information-architecture problem rather than a visual one, and asked what a buyer must be able to see before they are willing to raise their hand.
Discover
Mapped user and business friction through interviews, workflow audits, and benchmark analysis.
Prioritize
Ranked opportunities by impact on activation, task success, and decision confidence.
Design
Built IA, interaction patterns, and high-fidelity solutions with clear state behavior.
Validate
Tested critical flows, measured drop-offs, and iterated before development handoff.
The decisions
The calls that shaped the product, with what each one cost. Anything crossed out here was a real option at the time.
Decision 1: Listing narrative
Users could not evaluate project fit quickly.
Considered
- Marketing-first layout
- Decision-first layout
- Minimal card listing
Chose
Decision-first layout with summary, proof, and CTA order
Gave up
Less space for emotional storytelling
On what evidence
Users asked for practical filters and proof before visuals
What happened
Exploration drop-off reduced by 26%
Decision 2: Trust architecture
Builder trust signals appeared too late in journey.
Considered
- Footer trust cluster
- Inline trust modules
- Separate trust page
Chose
Inline trust modules near high-intent actions
Gave up
Slight increase in above-the-fold content
On what evidence
Users paused on payment safety and developer credibility
What happened
Qualified inquiries increased to 29%
Decision 3: Comparison flow
Users opened many tabs to compare projects.
Considered
- Manual compare
- Structured compare board
- Export sheet
Chose
Structured compare board with pinned criteria
Gave up
Additional state management complexity
On what evidence
Observed repetitive back-and-forth browsing
What happened
Comparison time improved by 2.1x
The work
Comparison became structured rather than freeform, and builder proof moved inside the listing where the decision actually happens instead of sitting on a separate page nobody reached.
Discovery module
Expose key project context without information overload.
Comparison workspace
Reduce memory load with side-by-side decision criteria.
Trust and inquiry
Pair confidence evidence with conversion CTA timing.
Targets, set up front
Metric
Baseline
Target
Result
Measured in
Qualified inquiry rate
Baseline 18%
Target 24%+
Result 29%
pilot release
Listing exploration drop-off
Baseline 42%
Target <34%
Result 31%
funnel review
Comparison task time
Baseline 7.4 min
Target <4 min
Result 3.5 min
task test
Outcomes in detail
Higher quality pipeline
Improved exploration depth
Faster decision readiness
Reflection
What worked
Decision-first narrative improved both user clarity and conversion quality.
What to improve
Add financing readiness segmentation in inquiry journey.
Next experiment
Test personalized project ranking by user intent signals.
Vinit Chaudhary
I'll personally review your brief and get back to you within two hours.
Product Designer
Contact
I usually respond to all digital enquiries within 2 business hours.
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