Case study

Automating Listing Information Collection

Stack

Python, PostgreSQL, Flask, HTML, CSS, Linux

DURATION

18 months

TEAM SIZE

2 Backend Developers, 1 Frontend Developer, 1 DevOps Engineer

Our Client:

Our client is a real estate agency, faced with the challenge of efficiently collecting information from various listing sites to streamline their property acquisition process. They required an automation tool capable of extracting detailed information from each listing and customizing the data based on individual client preferences.

The goal of the project:

The primary objective of the project was to develop an automation tool that could:

  • Collect information from multiple listing sites.
  • Extract detailed data from each listing, including property specifications, images, and pricing.
  • Apply client-specific filters to tailor the collected data according to individual preferences.

Advantages:

  • Efficient Automation: The developed tool automated the entire listing selection process, eliminating the need for manual data collection and saving valuable time and resources.
  • Customized Filtering: By applying client-specific filters, the tool ensured that the collected information aligned closely with each client’s requirements, enhancing the relevance and usefulness of the data.

Technical Solutions & Stack:

The solution was implemented using a combination of technologies to achieve the desired functionality:

  1. Python: Utilized for backend development, Python provided the flexibility and robustness required for data extraction and processing tasks.
  2. PostgreSQL: Served as the database management system for storing and organizing the collected listing data efficiently.
  3. Flask: Leveraged as the web framework for building the automation tool’s backend infrastructure, Flask enabled seamless integration and communication between different components.
  4. HTML/CSS: Used for frontend development, HTML and CSS facilitated the creation of a user-friendly interface for configuring client-specific filters and viewing extracted listing data.
  5. Linux Machines: The solution was deployed on Linux machines, ensuring reliable performance and scalability.

Results:

  • Streamlined Data Collection: The automation tool significantly streamlined the process of collecting information from listing sites, allowing the client to gather comprehensive data efficiently.
  • Enhanced Efficiency: By automating repetitive tasks, the tool enhanced operational efficiency within the real estate agency, enabling staff to focus on higher-value activities such as client interactions and property evaluation.
MICHAEL_FLIORKO

Mike Fliorko

Founder, CEO

Michael Babylon

German Representative

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