How to Scrape Apartments Near Me | Real Estate Data Scraper

Extract property listings, amenities, and contact info from Apartments Near Me. Ideal for Memphis real estate market analysis and rental inventory tracking.

Coverage:United StatesTennesseeMemphis
Available Data10 fields
TitlePriceLocationDescriptionImagesSeller InfoContact InfoPosting DateCategoriesAttributes
All Extractable Fields
Community NameStreet AddressCityStateZip CodeBedroom CountBathroom CountMonthly Rent EstimatesCommunity AmenitiesLeasing Office PhoneLeasing Office EmailProperty DescriptionImage Gallery URLsTestimonial TextTestimonial AuthorRenovation StatusPet Policy Details
Technical Requirements
JavaScript Required
No Login
Has Pagination
No Official API
Anti-Bot Protection Detected
Rate LimitingWordPress Application FirewallNone detected

Anti-Bot Protection Detected

Rate Limiting
Limits requests per IP/session over time. Can be bypassed with rotating proxies, request delays, and distributed scraping.
WordPress Application Firewall
None detected

About Apartments Near Me

Learn what Apartments Near Me offers and what valuable data can be extracted from it.

About Apartments Near Me

Apartments Near Me is a specialized property management firm headquartered in Memphis, Tennessee. The company focuses on managing and leasing B-class apartment properties and is widely recognized for its 'second chance' housing programs, which help residents with credit or background challenges find stable homes.

Available Data Assets

The website serves as a digital catalog for several large residential communities, including Cottonwood, Summit Park, Thompson Heights, and Winbranch. The platform provides detailed data on property locations, unit configurations (1-4 bedrooms), community-wide amenities, and newly renovated features. It also hosts a repository of tenant testimonials and blog content related to local living and housing policies.

Strategic Value of Scraping

Scraping this site is highly valuable for real estate investors and market analysts focusing on the Memphis metropolitan area. Because the company specializes in workforce and second-chance housing, the data provides unique insights into a specific niche of the rental market that is often underrepresented on national platforms like Zillow or Apartments.com.

About Apartments Near Me

Why Scrape Apartments Near Me?

Discover the business value and use cases for extracting data from Apartments Near Me.

Benchmark rental rates for B-class multifamily units in Memphis

Identify properties undergoing recent renovations for investment modeling

Collect contact info for B2B lead generation (HVAC, security, and maintenance vendors)

Monitor second-chance housing availability for social service agencies

Analyze tenant sentiment through localized community testimonials

Track geographic expansion of property management portfolios

Scraping Challenges

Technical challenges you may encounter when scraping Apartments Near Me.

Dynamic content rendering within Elementor-based carousels and sliders

Nested HTML structure common in WordPress themes requiring precise CSS selectors

Potential IP blocking from frequent requests to the localized hosting server

Inconsistent data labeling across different community property pages

Scrape Apartments Near Me with AI

No coding required. Extract data in minutes with AI-powered automation.

How It Works

1

Describe What You Need

Tell the AI what data you want to extract from Apartments Near Me. Just type it in plain language — no coding or selectors needed.

2

AI Extracts the Data

Our artificial intelligence navigates Apartments Near Me, handles dynamic content, and extracts exactly what you asked for.

3

Get Your Data

Receive clean, structured data ready to export as CSV, JSON, or send directly to your apps and workflows.

Why Use AI for Scraping

Handles JavaScript-rendered sliders without manual script writing
Automatically bypasses common WordPress rate limits through cloud-based execution
Allows for visual point-and-click selection of complex Elementor elements
Directly exports property data to Google Sheets for real-time portfolio tracking
Schedules daily runs to capture new rental availability as it happens
No credit card requiredFree tier availableNo setup needed

AI makes it easy to scrape Apartments Near Me without writing any code. Our AI-powered platform uses artificial intelligence to understand what data you want — just describe it in plain language and the AI extracts it automatically.

How to scrape with AI:
  1. Describe What You Need: Tell the AI what data you want to extract from Apartments Near Me. Just type it in plain language — no coding or selectors needed.
  2. AI Extracts the Data: Our artificial intelligence navigates Apartments Near Me, handles dynamic content, and extracts exactly what you asked for.
  3. Get Your Data: Receive clean, structured data ready to export as CSV, JSON, or send directly to your apps and workflows.
Why use AI for scraping:
  • Handles JavaScript-rendered sliders without manual script writing
  • Automatically bypasses common WordPress rate limits through cloud-based execution
  • Allows for visual point-and-click selection of complex Elementor elements
  • Directly exports property data to Google Sheets for real-time portfolio tracking
  • Schedules daily runs to capture new rental availability as it happens

No-Code Web Scrapers for Apartments Near Me

Point-and-click alternatives to AI-powered scraping

Several no-code tools like Browse.ai, Octoparse, Axiom, and ParseHub can help you scrape Apartments Near Me. These tools use visual interfaces to select elements, but they come with trade-offs compared to AI-powered solutions.

Typical Workflow with No-Code Tools

1
Install browser extension or sign up for the platform
2
Navigate to the target website and open the tool
3
Point-and-click to select data elements you want to extract
4
Configure CSS selectors for each data field
5
Set up pagination rules to scrape multiple pages
6
Handle CAPTCHAs (often requires manual solving)
7
Configure scheduling for automated runs
8
Export data to CSV, JSON, or connect via API

Common Challenges

Learning curve

Understanding selectors and extraction logic takes time

Selectors break

Website changes can break your entire workflow

Dynamic content issues

JavaScript-heavy sites often require complex workarounds

CAPTCHA limitations

Most tools require manual intervention for CAPTCHAs

IP blocking

Aggressive scraping can get your IP banned

No-Code Web Scrapers for Apartments Near Me

Several no-code tools like Browse.ai, Octoparse, Axiom, and ParseHub can help you scrape Apartments Near Me. These tools use visual interfaces to select elements, but they come with trade-offs compared to AI-powered solutions.

Typical Workflow with No-Code Tools
  1. Install browser extension or sign up for the platform
  2. Navigate to the target website and open the tool
  3. Point-and-click to select data elements you want to extract
  4. Configure CSS selectors for each data field
  5. Set up pagination rules to scrape multiple pages
  6. Handle CAPTCHAs (often requires manual solving)
  7. Configure scheduling for automated runs
  8. Export data to CSV, JSON, or connect via API
Common Challenges
  • Learning curve: Understanding selectors and extraction logic takes time
  • Selectors break: Website changes can break your entire workflow
  • Dynamic content issues: JavaScript-heavy sites often require complex workarounds
  • CAPTCHA limitations: Most tools require manual intervention for CAPTCHAs
  • IP blocking: Aggressive scraping can get your IP banned

Code Examples

import requests
from bs4 import BeautifulSoup

# Target the communities page
url = "https://www.apartmentsnearme.biz/community/"
headers = {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36"
}

try:
    response = requests.get(url, headers=headers)
    response.raise_for_status()
    soup = BeautifulSoup(response.text, 'html.parser')

    # Communities are often in Elementor carousel elements
    communities = soup.select(".elementor-carousel-image-overlay")
    for item in communities:
        name = item.get_text(strip=True)
        print(f"Property Found: {name}")
except requests.exceptions.RequestException as e:
    print(f"Error during scraping: {e}")

When to Use

Best for static HTML pages where content is loaded server-side. The fastest and simplest approach when JavaScript rendering isn't required.

Advantages

  • Fastest execution (no browser overhead)
  • Lowest resource consumption
  • Easy to parallelize with asyncio
  • Great for APIs and static pages

Limitations

  • Cannot execute JavaScript
  • Fails on SPAs and dynamic content
  • May struggle with complex anti-bot systems

How to Scrape Apartments Near Me with Code

Python + Requests
import requests
from bs4 import BeautifulSoup

# Target the communities page
url = "https://www.apartmentsnearme.biz/community/"
headers = {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36"
}

try:
    response = requests.get(url, headers=headers)
    response.raise_for_status()
    soup = BeautifulSoup(response.text, 'html.parser')

    # Communities are often in Elementor carousel elements
    communities = soup.select(".elementor-carousel-image-overlay")
    for item in communities:
        name = item.get_text(strip=True)
        print(f"Property Found: {name}")
except requests.exceptions.RequestException as e:
    print(f"Error during scraping: {e}")
Python + Playwright
from playwright.sync_api import sync_playwright

def scrape_community_data():
    with sync_playwright() as p:
        # Launching browser with headless mode
        browser = p.chromium.launch(headless=True)
        page = browser.new_page()
        page.goto("https://www.apartmentsnearme.biz/community/", wait_until="networkidle")

        # Wait for the dynamic Elementor slider content to load
        page.wait_for_selector(".elementor-carousel-image-overlay")
        
        # Extract names of all communities listed
        elements = page.query_selector_all(".elementor-carousel-image-overlay")
        for el in elements:
            print("Community:", el.inner_text())

        browser.close()

scrape_community_data()
Python + Scrapy
import scrapy

class ApartmentsSpider(scrapy.Spider):
    name = 'apartments_spider'
    start_urls = ['https://www.apartmentsnearme.biz/community/']

    def parse(self, response):
        # Scrapy extracts listing names from the community overview
        for listing in response.css('.elementor-image-box-wrapper'):
            yield {
                'name': listing.css('.elementor-image-box-title::text').get(),
                'link': listing.css('a::attr(href)').get(),
                'description': listing.css('.elementor-image-box-description::text').get()
            }
        
        # Example of pagination or internal links to individual community pages
        links = response.css('.elementor-button-link::attr(href)').getall()
        for link in links:
            yield response.follow(link, self.parse_details)

    def parse_details(self, response):
        yield {
            'address': response.css('.elementor-icon-list-text::text').get(),
            'phone': response.css('a[href^="tel:"]::text').get()
        }
Node.js + Puppeteer
const puppeteer = require('puppeteer');

(async () => {
  const browser = await puppeteer.launch();
  const page = await browser.newPage();
  
  // Setting viewport to ensure all elements load
  await page.setViewport({ width: 1280, height: 800 });
  await page.goto('https://www.apartmentsnearme.biz/community/', { waitUntil: 'networkidle2' });

  // Extract data from the Elementor carousel overlay
  const results = await page.evaluate(() => {
    const titles = Array.from(document.querySelectorAll('.elementor-carousel-image-overlay'));
    return titles.map(t => t.textContent.trim());
  });

  console.log('Communities Extracted:', results);
  await browser.close();
})();

What You Can Do With Apartments Near Me Data

Explore practical applications and insights from Apartments Near Me data.

Lead Gen for Service Vendors

HVAC and roofing contractors can identify properties listing 'recent renovations' to offer maintenance contracts.

How to implement:

  1. 1Scrape community descriptions for keywords like 'newly renovated' or 'updated'.
  2. 2Extract phone numbers and email addresses of the leasing offices.
  3. 3Match the community name to public records to find the LLC ownership.
  4. 4Initiate outreach to property managers with targeted maintenance proposals.

Use Automatio to extract data from Apartments Near Me and build these applications without writing code.

What You Can Do With Apartments Near Me Data

  • Lead Gen for Service Vendors

    HVAC and roofing contractors can identify properties listing 'recent renovations' to offer maintenance contracts.

    1. Scrape community descriptions for keywords like 'newly renovated' or 'updated'.
    2. Extract phone numbers and email addresses of the leasing offices.
    3. Match the community name to public records to find the LLC ownership.
    4. Initiate outreach to property managers with targeted maintenance proposals.
  • Market Rate Benchmarking

    Local real estate investors can use the data to set competitive rents for B-class properties in the Memphis area.

    1. Scrape unit sizes (1, 2, 3, 4 bedrooms) and specific community amenities.
    2. Store the data in a CSV to compare with other local management firms.
    3. Identify price gaps where similar properties are charging higher or lower rates.
    4. Adjust investment models based on the current inventory of workforce housing.
  • Social Service Resource Mapping

    Non-profits can build a live database of 'second chance' friendly housing for clients with difficult backgrounds.

    1. Scrape all community pages for mentions of 'Second Chance' or 'Low Credit' policies.
    2. Geocode the property addresses to create an interactive map for case managers.
    3. Extract current office hours and phone numbers for immediate inquiry capability.
    4. Update the database monthly to ensure the policies haven't changed.
  • Historical Renovation Tracking

    Analysts can track the speed of gentrification and neighborhood improvement by monitoring update cycles.

    1. Scrape blog posts and property updates regularly.
    2. Time-stamp when a community changes status from 'Standard' to 'Renovated'.
    3. Compare renovation timelines with neighborhood crime and economic data.
    4. Predict future investment hotspots based on the management firm's activity.
More than just prompts

Supercharge your workflow with AI Automation

Automatio combines the power of AI agents, web automation, and smart integrations to help you accomplish more in less time.

AI Agents
Web Automation
Smart Workflows

Pro Tips for Scraping Apartments Near Me

Expert advice for successfully extracting data from Apartments Near Me.

Use a headless browser like Playwright or Puppeteer because the community names are often nested inside JavaScript sliders.

Target the specific property subpages (e.g., /cottonwood/) to find granular detail like floor plans and office hours.

Monitor the 'Blog' section of the site to find historical context on property renovations and price shifts.

Implement a 2-5 second delay between page requests to avoid triggering basic WordPress firewall blocks.

Scrape at least once a month to track changes in the 'Second Chance' policy descriptions which vary by vacancy rates.

Verify address data against Google Maps as the site occasionally lists regional office addresses rather than site-specific ones.

Testimonials

What Our Users Say

Join thousands of satisfied users who have transformed their workflow

Jonathan Kogan

Jonathan Kogan

Co-Founder/CEO, rpatools.io

Automatio is one of the most used for RPA Tools both internally and externally. It saves us countless hours of work and we realized this could do the same for other startups and so we choose Automatio for most of our automation needs.

Mohammed Ibrahim

Mohammed Ibrahim

CEO, qannas.pro

I have used many tools over the past 5 years, Automatio is the Jack of All trades.. !! it could be your scraping bot in the morning and then it becomes your VA by the noon and in the evening it does your automations.. its amazing!

Ben Bressington

Ben Bressington

CTO, AiChatSolutions

Automatio is fantastic and simple to use to extract data from any website. This allowed me to replace a developer and do tasks myself as they only take a few minutes to setup and forget about it. Automatio is a game changer!

Sarah Chen

Sarah Chen

Head of Growth, ScaleUp Labs

We've tried dozens of automation tools, but Automatio stands out for its flexibility and ease of use. Our team productivity increased by 40% within the first month of adoption.

David Park

David Park

Founder, DataDriven.io

The AI-powered features in Automatio are incredible. It understands context and adapts to changes in websites automatically. No more broken scrapers!

Emily Rodriguez

Emily Rodriguez

Marketing Director, GrowthMetrics

Automatio transformed our lead generation process. What used to take our team days now happens automatically in minutes. The ROI is incredible.

Jonathan Kogan

Jonathan Kogan

Co-Founder/CEO, rpatools.io

Automatio is one of the most used for RPA Tools both internally and externally. It saves us countless hours of work and we realized this could do the same for other startups and so we choose Automatio for most of our automation needs.

Mohammed Ibrahim

Mohammed Ibrahim

CEO, qannas.pro

I have used many tools over the past 5 years, Automatio is the Jack of All trades.. !! it could be your scraping bot in the morning and then it becomes your VA by the noon and in the evening it does your automations.. its amazing!

Ben Bressington

Ben Bressington

CTO, AiChatSolutions

Automatio is fantastic and simple to use to extract data from any website. This allowed me to replace a developer and do tasks myself as they only take a few minutes to setup and forget about it. Automatio is a game changer!

Sarah Chen

Sarah Chen

Head of Growth, ScaleUp Labs

We've tried dozens of automation tools, but Automatio stands out for its flexibility and ease of use. Our team productivity increased by 40% within the first month of adoption.

David Park

David Park

Founder, DataDriven.io

The AI-powered features in Automatio are incredible. It understands context and adapts to changes in websites automatically. No more broken scrapers!

Emily Rodriguez

Emily Rodriguez

Marketing Director, GrowthMetrics

Automatio transformed our lead generation process. What used to take our team days now happens automatically in minutes. The ROI is incredible.

Related Web Scraping

Frequently Asked Questions About Apartments Near Me

Find answers to common questions about Apartments Near Me