AI-Powered Transformation: Elevating Customer Experience in Real Estate with Azure ML

About Client:

A leading real estate management company with a diverse residential and
commercial portfolio, operating across regions and managing property
maintenance, tenant relations, leasing, and sales.

Background:

For years, the company relied on a patchwork of legacy systems to manage
customer interactions. Their primary CRM was basic, outdated, and lacked
integration capabilities. Most critically, it was completely disconnected from the
company’s most important communication channel—phone calls.
Agents manually summarized conversations, often inconsistently, and much of the
valuable context from these calls was lost. This not only created inefficiencies but
also meant that the organization had no structured way of understanding recurring
issues, customer sentiment, or opportunities for improvement.

Challenge:

The fragmented systems and manual workflows led to four major challenges:

  1. No Actionable Insights from Calls: With no way to analyze call data, client
    struggled to identify recurring issues, trends, or customer pain points.
  2. Inefficient Agent Workflows: Agents spent significant time on note-taking,
    updating multiple systems, and searching for past information. A lack of a
    unified customer view prevented personalized service.
  3. Unstructured Data as a Roadblock: Thousands of hours of call transcripts
    remained trapped as unstructured data. This prevented the business from
    leveraging insights for better processes or proactive service.
  4. Poor Customer Experience: Customers often repeated information because
    agents lacked context. This inconsistency led to frustration and eroded trust.

Solution

To address these challenges, the client embarked on a digital transformation journey powered by Microsoft Azure. Key solution components included:

  • Real-time Transcription and Analysis: Using Azure Cognitive Services, every customer call was automatically transcribed into text in real time. The transcripts created a searchable, structured record of every conversation.
  • Data Ingestion and Unification: Transcripts were stored in Azure Data Lake Storage Gen2. A custom pipeline extracted key entities such as tenant names, property addresses, and issue types, along with sentiment analysis. These insights were seamlessly integrated into Dynamics 365 Sales and Customer Service, creating a single source of truth.
  • Intelligent Agent Experience: Dynamics 365 was enhanced with a modern UI that gave agents a 360° view of each customer, complete with call summaries, sentiment insights, and historical data—all in one place.
  • Proactive Insights and Automation: Azure Machine Learning identified patterns in call data, like frequently reported maintenance issues or common leasing inquiries.

 

Outcome

  • Saved agents 15–20 minutes per interaction with automated call summaries and unified customer histories.
  • Boosted agent productivity and satisfaction by reducing manual tasks.
  • Delivered a seamless, personalized customer experience, eliminating repeated information sharing.
  • Enabled faster issue resolution and improved first-call resolution rates.
  • Empowered leadership with actionable customer insights, spotting recurring maintenance issues and training needs.
  • Optimized self-service channels and FAQs using data on frequently asked questions.
  • Built a scalable, cloud-native ecosystem with the agility to adopt future AI-driven innovations.

 

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