Product
B2B, Dashboard (with CMS), AI-Powered System Design
My Role
Research, User Study, UI Design, Prototyping
Timeline
4 weeks
Introduction
As real estate firms grow and manage multiple leads daily, the sales team often struggles to keep track of prospective clients, maintain consistent engagement, and distinguish between serious buyers and casual browsers. This leads to a significant waste of time and effort spent on leads that don’t convert. With this project, I tried to solve this problem.
Research
I started with understanding the pain points of people who work in real estate sales, I conducted interviews with sales professionals at a mid-sized property development firm. I observed their lead tracking processes, communication methods, and their CRM tools. The goal was to identify friction points in client engagement and assess how technology could help.
From these interviews, I was able to map out the typical sales engagement lifecycle and identify the opportunities for automation.
Existing Workflow
Blue boxes represent steps where sales person is completely engrossed and is engaged throughly
Using the interviews, I crafted two personas and user flow to guide the design process:
Personas and User Journey
Observations
Solution Mapping
How it works?
The overall mechanism works as described below.
The chatbot reaches out to interested buyers through platforms like WhatsApp, email, and embedded chat widgets on listing portals and websites.
The bot asks predefined questions to buyers and they respond asynchronously, even outside business hours.
The NLP system extracts key buyer details and forwards them to a centralized web application.
Information Architecture
Following diagram shows the flow of tasks and hierarchical and sequential matrix.
Final Design and User Interfaces
Exploring Lead Details
Here, users can view all leads generated from various sources, along with their associated metadata for easy tracking and analysis.
This dashboard offers an overview of leads collected from multiple channels, showing important details like client status, contact information, response time, and lead source to help sales teams track and manage follow-ups
Viewing Chat Summary
By clicking on the chat icon, users can access access full conversation histories with individual leads. This helps sales teams understand buyer interests, review key questions, and personalize follow-ups based on past interactions.
Organize using Filters
This interface helps sales teams filter leads by status—like "Interested" or "Follow Up Required"—for more focused outreach. The filter icon highlights active filters, while the Mark Favorites feature allows users to star key leads for quicker follow-ups and better lead management.
User Study
We tested the prototype with sales teams and gathered valuable feedback.
Salespeople shared that they often don’t have time to log into the dashboard daily to check on chatbot activity. However, they still want to stay informed about how well their bots are performing and which projects are generating engagement.
“I don’t check the dashboard every day, but I’d love to get a quick summary of how the bots are doing—like how many people they interacted with and how many were actually interested.”
Introspect
A key challenge was designing a dashboard that surfaces actionable insights without overwhelming users. Sales teams needed quick access to lead scores, bot performance, and top inquiries. Through testing, features like engagement scores and favorite leads proved essential for prioritizing follow-ups. This project sharpened my understanding of real-world sales workflows and effective data visualization.
Future Scope
Future iterations can include advanced filters by agent, region, or property, and show deeper trends like conversion rates and resolution times—helping teams make more strategic decisions.
