Enabled Accolade's entry into Indian real estate market by building an AI-driven CRM
Team
4 Designers
3 Researchers
1 Founder
1 CMO
1 COO
Primary role
Lead Designer
Timeframe
5 months project
Background, solution, and impact!
The focus was on identifying opportunities for the MVP
Accolade sponsored the project to bring their prop-tech tool into India real estate market, where brokers face inefficiencies from scattered workflows, disorganized client management, and slow lead qualification.
We built an AI-powered MVP that centralizes client data, streamlines communication, and applies proptech analytics—helping brokers qualify leads faster and work efficiently within India’s real estate practices.
Impact. Identified via user testing with 16 brokers.
~ 6 hrs/week
Lead handling time reduction
Brokers highlighted that the combination of features would significantly boost their workflows.
3x
Faster lead qualification
Brokers noted that the concept could help them spot serious buyers more quickly.
Increased user adoption
Brokers highlighted the MVP’s ability to improve workflows from day one.
The problem
Leading through the tricky space of Indian Real Estate
Imagine you're designing a product for a new market, but your discovery research with property seekers and brokers reveals mixed, conflicting signals about the lead management cycle. That’s exactly where I found myself.
Only one direction became clear—solving brokers' challenges meant understanding the broader ecosystem of participants and tools within the real estate industry.
My approach
Validating insights through mixed-method research
Each unsellable category—from produce to dairy—has unique handling needs. We focused on low-friction products (Ambient goods) to ease Kroger’s first implementation.
12
Contextual inquiries
14
Broker Interviews
21
Renter interviews
80+
Survey responses
For property seekers the trust factor was missing
Even with advanced proptech tools, renters and buyers still turn to trusted brokers within their own networks — not those tied to the platforms.
80% of property seekers don’t trust listings on the internet
6 out 10 property seekers preferences evolve during search
99% property seekers consult with multiple brokers
Brokers: the backbone of the Indian real estate industry.
To match the shifting needs of multiple clients, brokers must navigate a series of early-stage tasks in the lead-to-deal pipeline.
Brokers
Property
Sellers
Property
Seekers
Key Broker tasks in the initial stages:
Match clients to properties
Maintain client relationships
Track deal pipeline
Coordinate property viewings
Manage documentation
Leverage location knowledge
Learning from competitor gaps
Even with advanced proptech tools, renters and buyers still turn to trusted brokers within their own networks — not those tied to the platforms.
Magicbricks
Housing.com
99 Acres
Commonfloor
Nestaway
Quickr
NoBroker
Basic tracking only – CRMs captured just initial lead preferences.
Scattered communication – Brokers had to manage clients across multiple channels.
Missed hidden needs – Tools failed to surface deeper client preferences.
Poor lead validation – Couldn’t separate genuine leads from casual inquiries.
No centralization – Brokers relied on pen, paper, and spreadsheets with no unified digital system.
The execution
An MVP developed with crazy 8's, 12+ user testings, and countless iterations.
Feature 1: Information management
Brokers relied on scattered tools that made it hard to track client progress. Our dashboard consolidated lead management cycle insights and tasks
into a single view.
3/4 brokers said the dashboard helped them prioritize high-value leads more effectively.
4/5 usefulness rating from 2 brokers, citing clarity and reduced cognitive load.
Feature 2: Client profile and preference analytics
Brokers found it hard to track shifting client needs. We designed client profiles to capture real-time changes and use AI insights to surface patterns—helping brokers personalize recommendations for different clients.
4/4 brokers found AI-generated tags and insights helped them spot high-priority leads more easily.
All 4 brokers said AI-generated insights made it easier to spot trends like budget flexibility or location priorities.
Broker - “With live updates, I could spend more time suggesting properties, not re-checking basics needs.”
Feature 3: Client profile and preference analytics
Brokers juggled WhatsApp, calls, and emails to share listings with clients. We designed a communication screen that centralized these interactions—making it easy to message, track liked properties, and share listings directly from the database.
3 of 4 brokers said seeing liked properties in the thread helped them prioritize conversations faster.
Saish Lad
My key learnings:
Balancing conflicting signals
Early research surfaced conflicting insights from brokers and property seekers. By triangulating patterns across stakeholders, I learned to cut through ambiguity and define a clear design direction around systemic pain points.
Scaling vs. Local adaptation
Accolade’s expansion goal met the reality of India’s informal, relationship-driven real estate workflows. Balancing scalability with cultural nuance showed me that global products succeed only when grounded in local context.
Moving beyond feature parity
Competitor CRMs merely digitized spreadsheets, leaving workflows broken. We chose differentiation by leveraging insights. Centralized communication, AI insights, streamlined pipelines, teaching me to prioritize value creation over feature parity.
Thank you!
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