Real Estate Lead Generation for the US Market

Real Estate Lead Generation

Our client requested a lead generation web application. The requested platform provides the possibility to search through the US real estate market and send emails to the house owners. With over 150 million properties, the client needed a precise solution development plan and a unique web scraping tool.

156 mln

real estate objects

2 sec

search run

About the client

Stantem enables lead generation automation in the US real estate market.

Tech stack

Python

Django

ReactJS

Redis

AWS

The client's needs

Our initial client approached us seeking data scraping and web development services. They aimed to parse over 150 million real estate listings from the project's inception at the beginning, while Dataforest carefully considered and planned the future expansion of the system from the start.

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As we progressed with the data scraping solution, our client introduced their vision for a web application to leverage the database. Dataforest took up the challenge and successfully executed the development of this web application, aligning it with the client's requirements.

Challenges & solutions

Challenge

Clients like realtors would like to be able to know the property value, but this information is usually closed.

Solution

Each real estate in the lead base has a property value range. It’s based on information like the sold prices of similar real estate and other collected data.

Challenge

Implementing a fast and efficient Map View mode to enable convenient and swift viewing of a vast dataset of 150 million objects.

Solution

The filtering system filters based on map bounds, displaying only the essential data on the screen.
To optimize performance, we introduced a brief request delay, preventing unnecessary requests when scaling the map.
We streamlined the information generation process, eliminating the need for a serializer.

Challenge

Fast and easy search through the high-volume database (150 million records).

Solution

The ElasticSearch database was selected as the most effective solution

Challenge

Implementing subscription management, payment processing, multiple tariff plans, and discount functionalities.

Solution

We seamlessly integrated the Stripe payment system, to efficiently handle subscription management, payment acceptance, diverse tariff plans, and discount processing.

Challenge

Scraping substantial volumes of real estate data, including addresses, number of rooms, and state information, from various sources and incorporating it into a single database.

Solution

Dataforest devised a solution that comprised detailed documentation and a versatile framework. The framework streamlined the process of data scraping and validation from various websites with minimal adjustments, ensuring accurate data integration.

Challenge

Solution

Challenge

Solution

Challenge

Solution

Results

The web application features user authentication, registration and Stripe integration.

Users can use a fast search function for over 156 million objects both in lists and maps search format, including building photos via GoogleMaps integration.
Dataforest implemented email campaign functionality with the Tiny text editor, simplifying email composition and formatting.

Another functionality covers the dedicated page with advanced algorithms for object comparison and analysis, enhancing data processing capabilities.

Real Estate Lead Generation slider image 1

Stantem enables lead generation automation in the US real estate market.

Steps of providing
data scraping services

Step 1 of 5

Free consultation

It's a good time to get info about each other, share values and discuss your project in detail. We will advise you on a solution and try to help to understand if we are a perfect match for you.

One of our , hence we work with either one page high level requirements or with a full pack of tech docs. At this stage, we need to ensure that we understand the full scope of the project. Receive from you or the following : list of features with detailed description and acceptance criteria; list of fields that need to be scraped, solution architecture. Ultimately we make a project plan which we strictly follow. We are a , and that is one of our core values as well.

How we provide data integration solutions

Step 1 of 5

Free consultation

It's a good time to get info about each other, share values and discuss your project in detail. We will advise you on a solution and try to help to understand if we are a perfect match for you.

One of our , hence we work with either one page high level requirements or with a full pack of tech docs. At this stage, we need to ensure that we understand the full scope of the project. We receive from you or the following : integration pipeline (which data we should get and where to upload), process logic (how system should work); use cases and acceptance criteria; solution architecture. Ultimately we make a project plan which we strictly follow.

After quality assurance tests are completed, we deliver solutions to the client. Though we , we are expecting client’s participation in the project. While developing the integration system, we provide midterm results so are and provide us with feedback. By the way, a high-level of .

Steps of providing web applications services

Step 1 of 7

Web development discovery

In the initial stage of the web-based development project, professional business analysts make detailed documentation of the project requirements and the approximate structure of the future web application. DATAFOREST is a custom web application development agency, guided by extensive experience in multiple industries. We give you detailed project documentation and then assemble the team according to your time and budget.

The way we deal with your task and help achieve results

Step 1 of 5

Free consultation

It's a good time to get info about each other, share values and discuss your project in detail. We will advise you on a solution and try to help to understand if we are a perfect match for you.

One of our , hence we work with either one page high level requirements or with a full pack of tech docs. In Data Science, there are numerous models and approaches, so at this stage in order to define project objectives. We elaborate and discuss a set of hypotheses and assumptions. We create solution architecture, a project plan, and a list of insights or features that we have to achieve.

The work starts with . helps to determine your variable and build several models for the initial review. Further modeling requires for the further development. Ultimately, we interpret the results. Nevertheless, data modeling is about a process that requires lots of back and forth iterations. We are as well.

Data Science solutions can be a list of insights or a variety of different models that consume data and return results. Though we , we expect client’s participation in the project. While modeling, we provide midterm results so and provide us with feedback. By the way, a high-level of .

The way we deal with your issue and achieve result

Free consultation

Step 1 of 5

It's a good time to get info about each other, share values and discuss your project in detail. We will advise you on a solution and try to help to understand if we are a perfect match for you.

One of our , hence we work with either one page high level requirements or with a full pack of tech docs. Depending on project objectives, , , performing monitoring and checking logs. By having a set of interviews, we ensure that we understand the full scope of the project. Ultimately we make a project plan which we strictly follow. We are a result-oriented , and that is one of our core values as well.

Success stories

Check out a few case studies that show why DATAFOREST will meet your business needs.

All Success Stories

Data parsing

We helped a law consulting company create a unique instrument to collect and store data from millions of pages from 5 different court sites. The scraped information included PDF, Word, JPG, and other files. The scripts were automated, so the collected files were updated when information changed.

14.8 mln

pages processed daily

43 sec

updates checking