Real Estate Leads
Real Estate leads Improvement via Speech-to-Speech Communication

Overview

This project introduces a comprehensive reporting tool to meticulously analyze customer support agencies and representatives within the real estate domain. The tool incorporates a range of features, including statistical insights into generated leads, calls, and missed opportunities for each support representative. Additionally, an AI-powered module assesses sales quality by comparing it against a base script. By leveraging NLP techniques, the project transcribes and contextually analyzes calls, capturing visual descriptions of how real estate agents adhere to scripts. Semantic and syntactic analyses further enable the evaluation of exact and varied word sequences.

Challenges

Inadequate Customer Support Evaluation:
  • – Real estate lacks tools for comprehensive assessment of support agencies and agents.
  • – Monitoring interactions and lead quality is challenging without systematic analysis.
Sales Quality Assessment Complexity:
  • – Evaluating agent adherence to scripts is time-consuming and complex.
  • – Manual methods don’t provide accurate insights into sales effectiveness.
  • Missed Opportunities and Data Inaccuracy:
    • – Unclear insights into missed leads and sales inefficiencies.
    • – Incomplete or inaccurate call data hampers meaningful analysis.

Solution

Robust Reporting Tool:
    • – Create a tool for precise analysis of support performance, lead generation, and missed opportunities.
AI-Driven Sales Evaluation:
      • – Develop AI module to assess sales quality by comparing with base script using NLP.
      • – Analyze calls’ context and adherence to scripted conversations.
Optimized Insights:
      • – Utilize AI and call data to pinpoint missed opportunities and refine sales strategies.
Reliable Data Handling:
      • – Collect, generate, and clean call records for accurate analysis.
      • – Ensure data quality for reliable agent performance evaluation.
Efficient Technology Stack:
    • – Employ Python/Flask, Twilio, DeepSpeech, and AWS for efficient performance.

Development Process

1

Research

2

Planning

3

Designing

4

Development

5

Maintenance

Sales & ROI

As a result of the new properly designed website, our client FINews, was able to engage with the
audience well and close more sales in a short span of 2 months. They gained the ROI after 3
months with our assistance.

20%

Conversion rate
in 2022

80%

Increase in monthly
revenue

Team & Role

A dedicated team of 4 individuals contributes their expertise to this project, including:

  • UI/UX Designer
  • Frontend Engineer
  • Backend Engineer
  • Data Scientist

Tools / Technologies

The project leverages a robust technology stack to ensure efficient performance and reliability.

Python/Flask

Twilio

DeepSpeech

AWS

Conclusion

FINews’s objective was to build a user-friendly and aesthetically pleasing website that would
encourage greater traffic and sales. Deline Media was able to develop a user-friendly and
responsive website for them which enabled their customers to explore the capital market and
current forex rates fast enough.

Technical Achievements

Advanced NLP Techniques:
Utilizing NLP techniques for contextual analysis of real estate agent phone calls, including semantic and syntactic analysis. This process evaluates the agent’s effectiveness in property sales.

Data Gathering and Cleaning:
Ensuring accurate call data by gathering, generating, and meticulously cleaning call records to facilitate analysis.

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New York, USA
Lahore, Pakistan
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