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How to Compare Senior Living Facilities in One City

When you are comparing care options, the first job is to make a manageable shortlist. You need to see which communities appear in the same area, the care types they list, and which ones deserve a closer look.

Our Caring.com Senior Living Scraper takes a Caring.com city directory URL or a direct facility URL. A city run returns facility names, addresses, care types, phone numbers, ratings, review counts, and published starting prices where available. Full-detail mode visits each facility profile for deeper price, amenity, room, and review information. Directory data is a research aid, not a care recommendation or an availability check.

Caring.com facility data cards for location, care types, price, and reviews

Make a small city shortlist

Open the Actor on Apify. Under Start URLs, enter the Los Angeles assisted-living directory below. Set Max items to 10 and leave Scrape full facility details off. Start the run, then open Dataset to compare the rows.

In the JSON editor, the same input is:

{
  "startUrls": [
    { "url": "https://www.caring.com/senior-living/assisted-living/california/los-angeles" }
  ],
  "maxItems": 10,
  "scrapeDetails": false
}

maxItems caps facilities across the run, not ten per page. A result contains fields such as name, careTypes, address.formattedAddress, phoneNumber, averageRating, reviewCount, startingPrice, and url. The Actor's documented example includes a Los Angeles facility with assisted living, independent living, and memory care among its listed care types. Values can change between runs.

The Node.js example uses this same ten-facility input and reads the dataset through Apify's API.

Export the rows as CSV and keep the source URL in your sheet. Filter to the care type and area that matter, then put the listed starting price next to the review count. A high rating based on a few reviews and a high rating based on many reviews are different signals. Do not rank facilities solely by either number.

Caring.com senior-living dataset showing Los Angeles facilities, care types, reviews, and listed starting prices

This screenshot shows 12 visible Los Angeles facility rows from a larger run. The ten-facility JSON above is a smaller starting sample.

Inspect the facilities that make the shortlist

For a few promising rows, rerun the Actor with their facility profile URLs and scrapeDetails: true. A detailed row can add published price ranges, amenities, accommodations, services, reviews, and the facility website. The results are one row per facility: detail mode replaces a listing-only row with a richer row when the profile loads, rather than charging for both row types.

If a detail page has no usable facility data, the Actor can fall back to a listing row. Check which fields actually arrived before comparing two facilities. A missing price range is not a zero price; a published starting price may exclude services or a particular room type. Contact each facility to confirm current pricing, availability, licensing, and whether it can meet the person's needs. Public reviews are useful context, but not a substitute for a visit or a qualified care assessment.

Pricing

Pricing as of September 28, 2026 is $0.005 per listing-only facility row or $0.02 per detailed facility row. These are alternative result events, not charges to add together for the same row. Ten listing-only facilities would be $0.05 in Actor result events; ten successful detailed rows would be $0.20. Apify platform usage may be billed separately under your plan. See live pricing before a larger city run.

Frequently asked questions

Does the listed starting price tell me what care will cost?

No. It is a published starting figure, not a personalized quote. Confirm current prices, availability, services, and care needs directly with each facility.

Do I need full details for every facility?

No. Start with listing-only rows for a city, then rerun with scrapeDetails enabled for the facilities you want to examine more closely.

Piotr Vassev

Piotr Vassev

Founder of FalconScrape. Building production-grade web scraping systems and data automation pipelines for businesses worldwide.

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