[Eddie Lee] Capstone Project - AI PM Bootcamp - DataFox.pdf
- 1. Capstone Project AI PM Bootcamp AI real estate listing price comparison The real estate “trivago” - DataFox
- 2. Week 1: The ‘Why’ Real estate agents Pain point - Small agency has insufficient resources and manpower to find enough listing information to show home buyers - They also lack time and manpower to do price updates
- 3. Task #2: Create your main Persona Bring kids to playground, go to gathering with neighbourhoods Build a 7-figure agency agency - Time wasted on doing listing discovery and real estate marketing rather than bringing clients to have home inspection and make sales - Don’t have enough listings to show - Don’t have time to update listing information and engage with homeowners Earn more money Make her agency business revenue stream more stable Don’t have time and manpower to do all the listing discovery and price update Time saving, Hussle free, Get ahead in competition Mobile phone 28hse (Zillow like listing platform) Facebook Instagram Reviews Guides Top 10s blog Reels Real estate coach 35 Real estate agent Higher Education Hong Kong Married Connie
- 4. Task #3: Empathy Map: Caring mom Connie Says. Thinks. Does. Feels. There are too many house listing to update. I don’t have time to do marketing and sales. Don’t have strong brand to generate enough passive leads of listings Sometimes I missed the discounted listing and the golden time to negotiate Homeowners get annoyed if I call them too frequently. Sometimes I can’t answer the call and WhatsApp message during home inspection and some leads become cold. I shouldn’t be doing updates because it’s not the most profitable procedure. We are not tech savvy. We don’t have enough data to win big brands. Call homeowners and landlords to update listing status one by one. Do listing discovery by using expired listing and old database to cold call, browse competitors websites and listing platforms to match own listing one by one Ignore calls during house seeing Incompetent in front of big brands Frustrated in day to day operation and groundworks like updating listing information Insecure - not having enough information for their clients
- 5. Task #4: Write down your Persona’s Use Cases in detail 1. Efficient Listing Discovery ● Pain Points: Real estate agents, especially in small agencies, often lack the resources and manpower to efficiently discover and manage property listings. This results in insufficient listings to show potential buyers and wasted time on manual listing discovery. 2. Price Updates and Price Comparison Across Sites and Agencies ● Pain Points: Agents often lack the time and manpower to keep up with price updates across various real estate websites and agencies. This can lead to missed opportunities for negotiating deals on discounted listings. Manually searching for price information across different platforms is time-consuming and inefficient. 3. Real time notification via app and SMS ● Pain Points: Agent’s doesn’t know information in real time. They can’t have best just in time information to react and help their clients to make best decision with real time information. 4. Lower Client Acquisition Barrier ● Pain Points: Small to medium agency can’t have enough money to burn on listing platforms and ads to acquire customers. Companies that have most money to burnt acquired most customers, yet the pricing information they provided are sometimes not accurate. Listings on real estate platforms are ordered chronologically, not prioritise to those useful to the market, for home buyers or tenants. 5. Market Analysis and Competitive Edge ● Pain Points: Connie needs to stay ahead of the competition but lacks the time to analyze market trends and competitor listings regularly. 35 Real estate agent Higher Education Hong Kong Married Connie
- 6. Task #4: Write down your Persona’s Pain Points for the top 3 Use Cases 1. Efficient Listing Discovery ● Pain Points: Real estate agents, especially in small agencies, often lack the resources and manpower to efficiently discover and manage property listings. This results in insufficient listings to show potential buyers and wasted time on manual listing discovery. 2. Price Updates and Price Comparison Across Sites and Agencies ● Pain Points: Agents often lack the time and manpower to keep up with price updates across various real estate websites and agencies. This can lead to missed opportunities for negotiating deals on discounted listings. Manually searching for price information across different platforms is time-consuming and inefficient. 3. Lower Client Acquisition Barrier ● Pain Points: Small to medium agency can’t have enough money to burn on listing platforms and ads to acquire customers. Companies that have most money to burnt acquired most customers, yet the pricing information they provided are sometimes not accurate. Listings on real estate platforms are ordered chronologically, not prioritise to those useful to the market, for home buyers or tenants. 35 Real estate agent Higher Education Hong Kong Married Connie
- 7. Task #5 Competitor Analysis Datafox Affiliate marketing blogs Own agency website Listing platforms Social media marketplace Real estate analytics companies
- 8. Task #7 Problem Statement Making the real estate market more transparent will lead to an increase of transaction volume and sales, and decrease the length of sales cycle and marketing cost. We make price transparent for real estate market to benefit homebuyers, tenants and individual agents.
- 9. Week 2: The ‘What’ Ideas, solutions, MVP, prototype
- 10. Task #2 Prioritize into a roadmap with the RICE model Feature Reach Impact Confidence Effort Score Automated Listing Discovery 80% 8 7 6 746.67 Price Update Alerts 75% 9 7 5 945 Centralized Dashboard 70% 6 8 6 560 Competitive Analysis 65% 7 6 8 341.25 Customizable Alerts and Notifications 60% 6 5 4 450 Public Search Engine for Home Buyers and Tenants 90% 10 8 7 1028.57
- 11. As a real estate agent at a small agency, Connie wants a platform that automates the discovery and updating price and status of property listings. 1. Automated Listing Discovery: ● AI vision technology automates the analysis and matching of property listings across different platforms and agencies. By using image recognition and data analysis, it identifies similar properties and consolidates information into a comprehensive and accurate database. ● The system should automatically gather and update property listings from multiple real estate platforms, reducing the need for manual discovery. 2. Price Update Alerts: ● AI tools aggregate data from multiple sources and present it in a user-friendly format, enabling real-time price comparison of similar listings. 3. Centralized Dashboard: ● Agents should have access to a centralized dashboard that displays all active listings, their statuses, and recent updates in one place. 4. Competitive Analysis: ● The product should offer features for analyzing competitor listings and market trends to help agents stay ahead in the market. 5. Customizable Alerts and Notifications: ● Agents should be able to customize alerts for specific types of listings or changes, such as new listings in a particular area or significant price drops. 6. Public search engine for home buyers and tenants: ● AI detects which listings are matched and aggregate the information so that it shows the cheapest or most trustworthy listing to show to the homebuyers and tenants. It refers lead to the information providers so that small agencies even they have no cash to burn on buying ads. Instead they win by providing useful information. Task #3: Write down the Functional requirements for the feature(s) you came up with
- 12. 1. Performance: ● The system should be able to handle a large volume of listings and updates without significant delays, ensuring that users can access information quickly and efficiently. 2. Scalability: ● The platform should be designed to scale easily, accommodating an increasing number of users and listings as the agency grows. 3. Reliability: ● The system should have a high uptime percentage, ensuring that agents can access the platform whenever needed, especially during peak business hours. 4. Usability: ● The interface should be intuitive and user-friendly, minimizing the learning curve for agents and allowing them to navigate and utilize the platform effectively without extensive training. 5. Security: ● The platform must implement robust security measures to protect sensitive data, including client information and proprietary listing data, from unauthorized access and breaches. 6. Compatibility: ● The system should be compatible with various devices and operating systems, allowing agents to access the platform from desktops, tablets, and smartphones seamlessly. 7. Maintainability: ● The platform should be easy to maintain and update, allowing for quick deployment of new features and bug fixes without disrupting service. 8. Responsiveness: ● The system should provide real-time updates and alerts, ensuring that agents receive timely information about price changes and new listings. 9. Localization: ● The platform should support multiple languages and regional settings, catering to the diverse needs of agents and clients in different geographic locations. Task #4: Write down the non-Functional requirements for the feature(s) you came up with
- 13. Task #5 Requirements for AI team Including like, retweet, share, and follow Leveraging AI 1. Automated Listing Discovery and Updates: ● Use machine learning algorithms to automatically gather and update property listings from multiple platforms. This reduces manual effort and ensures agents have access to the latest listings. 2. Dynamic Pricing Models: ● Implement AI-driven dynamic pricing strategies that analyze market data, competitor pricing, and customer demand in real-time to optimize listing prices and maximize revenue. 3. AI-Powered Property Valuation: ● Utilize AI algorithms for accurate property valuations by analyzing historical sales data, property characteristics, and market trends. This helps agents provide precise pricing recommendations to clients. 4. Personalized Property Recommendations: ● Use AI to analyze user preferences and behaviors to provide personalized property recommendations, enhancing the client experience and increasing conversion rates. 5. AI Chatbots for Customer Interaction: ● Deploy AI-based chatbots to handle customer inquiries and provide property information, improving client satisfaction and reducing the workload on agents. Input for the AI Model ● Property Data: Characteristics such as location, size, amenities, and historical sales data. ● Market Data: Information on current market trends, competitor pricing, and economic indicators. ● User Interaction Data: User preferences, search behaviors, and feedback on property recommendations. ● Customer Inquiries: Data from customer interactions with chatbots and other communication channels. Data Collection Considerations ● Availability of Data: Ensure access to comprehensive and up-to-date property and market data from reliable sources. ● Data Privacy and Security: Implement robust measures to protect sensitive data, especially client information. ● Data Integration: Develop systems to integrate data from various platforms and sources seamlessly. Trade-offs to Consider 1. Accuracy vs. Complexity: ● More complex AI models may provide higher accuracy but require more computational resources and time to train. 2. Real-time Processing vs. Cost: ● Real-time data processing can enhance responsiveness but may increase operational costs due to the need for advanced infrastructure. 3. Personalization vs. Privacy: ● While personalized recommendations improve user experience, they must be balanced with privacy concerns and compliance with data protection regulations.
- 14. Mockup Link to figma file
- 16. Task #1 Product Positioning What is it? User Persona Benefits The product is an AI-powered real estate platform designed to streamline the process of property listing discovery, price updates, and client engagement for real estate agents. It aims to automate repetitive tasks, provide data-driven insights, and enhance customer interactions, ultimately improving efficiency and competitiveness in the real estate market. Connie ● Age: 35 ● Occupation: Real estate agent ● Location: Hong Kong ● Status: Married ● Motivations: Earn more money, stabilize business revenue ● Challenges: Insufficient time and manpower for listing discovery and price updates ● Technology Usage: Mobile phone, 28hse, Facebook, Instagram ● Time Savings: Automates routine tasks, allowing agents to focus on client engagement and sales. ● Enhanced Efficiency: Provides real-time updates and alerts, reducing the risk of missed opportunities. ● Improved Customer Experience: AI-powered chatbots and personalized recommendations enhance client interactions. ● Data-Driven Insights: Offers market analysis and competitive pricing strategies to stay ahead in the market. Market Characteristic Competition Differentiators ● Competitive Landscape: The real estate market is highly competitive, with a need for efficient listing management and client acquisition strategies. ● Technological Adoption: Increasing use of AI and automation in real estate to improve operational efficiency and customer service. ● Direct Competitors: Other AI-powered real estate platforms offering similar automation and data analysis features. ● Indirect Competitors: Traditional real estate agencies that rely on manual processes and lack advanced technological integration. ● AI Integration: Advanced AI algorithms for automated listing discovery, dynamic pricing, and personalized client recommendations. ● User-Friendly Interface: Intuitive design that minimizes the learning curve for agents. ● Comprehensive Features: Combines listing management, market analysis, and customer engagement tools in one platform. ● Localization: Supports multiple languages and regional settings to cater to diverse markets.
- 17. Task #2 Your Key Metrics 20% Of individual agents in the market subscribed to our platform to acquire information Average log in should be 2 per week Average time spent on dashboard should be 1 hour per log in
- 19. Introduction to the Industry / lightweight image Introduction to the real estate industry Overview The real estate industry is one of the largest and most asset-heavy sectors globally, valued at approximately $379.7 trillion. It encompasses various types of properties, including residential, commercial, and industrial. The industry is currently experiencing significant technological transformation, driven by advancements in AI and automation, which are reshaping how properties are listed, managed, and sold. Emerging Trends ● Digital-First House Hunting: The shift towards digital platforms for property searches is accelerating, with AI and machine learning playing a crucial role in automating and enhancing the property discovery process. ● AI Integration: AI is being used to automate routine tasks, provide personalized recommendations, and optimize property management, offering real estate agents a competitive edge. ● Rising Home Prices: Despite economic challenges, home prices continue to climb, driven by high demand and limited supply.
- 20. Introduction to persona: Connie Connie is a 35-year-old real estate agent based in Hong Kong. She is married, has higher education, and is motivated by the desire to build a successful 7-figure agency. As a real estate agent working in a small agency, Connie faces several challenges related to time management and resource allocation. Characteristics ● Age: 35 ● Occupation: Real estate agent ● Education: Higher Education ● Location: Hong Kong ● Status: Married Interests and Goals ● Interests: Enjoys spending time with her kids at playgrounds and attending neighborhood gatherings. ● Goals: Aspires to build a 7-figure agency and stabilize her business revenue stream. Motivations and Challenges ● Motivations: Connie is driven to earn more money and make her agency's revenue stream more stable. ● Challenges: She struggles with insufficient time and manpower to efficiently discover and manage property listings. This results in insufficient listings to show potential buyers and wasted time on manual listing discovery and price updates. Technology and Content Preferences ● Technology Usage: Frequently uses her mobile phone, 28hse (a Zillow-like listing platform), Facebook, and Instagram. ● Content-Type Preferences: Prefers reviews, guides, top 10 blogs, and reels.
- 21. Introduction to pain point 1. Inefficient Listing Discovery: ● Challenge: Small agencies often lack the resources and manpower to efficiently discover and manage property listings. This results in insufficient listings to show potential buyers and wasted time on manual listing discovery. ● Impact: Agents spend valuable time on repetitive tasks instead of focusing on client interactions and sales, leading to missed opportunities and decreased productivity. 2. No time for Price Updates and Comparison: ● Challenge: Agents frequently struggle to keep up with price updates across various real estate websites and agencies. This can lead to missed opportunities for negotiating deals on discounted listings. ● Impact: Manually searching for price information across different platforms is time-consuming and inefficient, preventing agents from making timely and informed decisions. 3. High Client Acquisition Barrier: ● Challenge: Small to medium agencies often lack the financial resources to invest heavily in listing platforms and advertisements to acquire customers. This puts them at a disadvantage compared to larger companies with more substantial budgets. ● Impact: Listings on real estate platforms are typically ordered chronologically, not prioritized based on market usefulness, which can make it difficult for smaller agencies to attract potential buyers or tenants.
- 22. Hypothesis / Problem Statement / Mission Hypothesis If real estate agents, particularly those in small agencies, have access to an AI-powered platform that automates property listing discovery and price updates, then they will be able to manage more listings efficiently, reduce time spent on manual tasks, and improve client engagement. This will lead to increased transaction volumes, shorter sales cycles, and reduced marketing costs. Problem Statement Real estate agents in small agencies face significant challenges due to insufficient resources and manpower, which hinder their ability to efficiently discover and manage property listings. They struggle to keep up with price updates across various platforms, leading to missed opportunities for negotiating deals on discounted listings. This inefficiency results in wasted time, decreased productivity, and a lower competitive edge in the market. Mission The mission of the AI-powered real estate platform is to make the real estate market more transparent and efficient by providing agents with automated tools for listing discovery, price updates, and client engagement. By leveraging AI, the platform aims to empower agents to focus on building relationships and closing sales, ultimately benefiting homebuyers, tenants, and individual agents through increased transparency and reduced transaction friction.
- 23. Solution The AI-powered real estate platform is designed to address the key pain points faced by real estate agents, particularly those in small agencies. By leveraging advanced AI technologies, the platform aims to streamline property listing discovery, automate price updates, and enhance client engagement. Here’s how the solution works: Key Features 1. Automated Listing Discovery: ● AI Vision Technology: The platform uses AI vision technology to automatically analyze and match property listings across different platforms and agencies. By employing image recognition and data analysis, it identifies similar properties and consolidates information into a comprehensive and accurate database. ● Real-Time Updates: It gathers and updates property listings from multiple real estate platforms in real-time, reducing the need for manual discovery and ensuring agents have access to the latest listings. 2. Price Update Alerts: ● Data Aggregation: AI tools aggregate data from various sources and present it in a user-friendly format, enabling real-time price comparison of similar listings. This allows agents to act quickly on discounted properties and make informed pricing decisions. 3. Centralized Dashboard: ● Unified View: Agents have access to a centralized dashboard that displays all active listings, their statuses, and recent updates in one place. This simplifies management and enhances productivity. 4. Competitive Analysis: ● Market Insights: The platform offers features for analyzing competitor listings and market trends, helping agents stay ahead in the market and make strategic decisions. 5. Customizable Alerts and Notifications: ● Personalized Alerts: Agents can customize alerts for specific types of listings or changes, such as new listings in a particular area or significant price drops, ensuring they receive relevant updates. 6. Public Search Engine for Home Buyers and Tenants: ● Information Aggregation: AI detects matched listings and aggregates the information to show the most cost-effective or trustworthy options to homebuyers and tenants. This feature helps smaller agencies compete by providing valuable information without heavy advertising costs. Benefits ● Time Savings: Automates routine tasks, allowing agents to focus on client engagement and sales. ● Enhanced Efficiency: Provides real-time updates and alerts, reducing the risk of missed opportunities. ● Improved Customer Experience: AI-powered chatbots and personalized recommendations enhance client interactions. ● Data-Driven Insights: Offers market analysis and competitive pricing strategies to stay ahead in the market.
- 24. Prototype Link to figma file
- 25. Metrics 20% Of individual agents in the market subscribed to our platform to acquire information Average log in should be 2 per week Average time spent on dashboard should be 1 hour per log in
- 26. Roadmap framed as future work Phase 1: Foundation and Initial Launch ● Objective: Establish the core functionalities of the platform to address immediate pain points faced by real estate agents. ● Key Features: ● Automated Listing Discovery: Implement AI vision technology to automate the analysis and matching of property listings across platforms. ● Price Update Alerts: Develop a system for real-time price comparison and alerts. ● Centralized Dashboard: Create a user-friendly dashboard for agents to manage listings and updates efficiently. ● Timeline: 3-6 months ● Milestones: ● Complete development and testing of core features. ● Launch beta version for initial user feedback. Phase 2: Expansion and Enhancement ● Objective: Enhance platform capabilities and expand feature set to improve user experience and market competitiveness. ● Key Features: ● Competitive Analysis: Introduce tools for market trend analysis and competitor listing insights. ● Customizable Alerts and Notifications: Allow agents to personalize alerts for specific listing changes. ● Public Search Engine: Develop a search engine for home buyers and tenants to access aggregated listing information. ● Timeline: 6-12 months ● Milestones: ● Gather user feedback from beta version and iterate on features. ● Expand user base and enhance platform stability. Phase 3: Advanced AI Integration ● Objective: Integrate advanced AI functionalities to provide predictive insights and personalized recommendations. ● Key Features: ● AI-Powered Property Valuation: Utilize machine learning algorithms for accurate property valuations. ● Personalized Property Recommendations: Implement AI to analyze user preferences and behaviors. ● AI Chatbots: Deploy chatbots for customer interaction and support. ● Timeline: 12-18 months ● Milestones: ● Conduct pilot tests for advanced AI features. ● Refine algorithms based on user interactions and data analysis. Phase 4: Market Leadership and Innovation ● Objective: Position the platform as a market leader by continuously innovating and adapting to industry trends. ● Key Features: ● Integration with Emerging Technologies: Explore integration with technologies like blockchain and IoT for enhanced functionality. ● ESG Reporting and Compliance: Develop features to support environmental, social, and governance (ESG) initiatives. ● Timeline: 18-24 months and beyond ● Milestones: ● Establish partnerships with technology providers for integration. ● Launch new features that align with market demands and regulatory requirements.