Google Places API Alternative: Cheaper Scraper Options

The cheapest Google Places API alternative is a Google Maps scraper running on Apify, which costs roughly $0.50–$2 per 1,000 results compared to Google's $17/1,000 for Place Details requests. You get the same business data — name, address, phone, website, ratings, reviews — without API quotas, billing tiers, or field masks that quietly inflate your bill. For lead generation workflows, a scraper also returns data Google's API won't, like every result on a query page instead of just the top 20.

Quick Answer

The best Google Places API alternative for cost-sensitive scraping is an Apify-based Google Maps scraper, which charges $0.50–$2 per 1,000 places versus Google's $17 per 1,000 Place Details calls. Apify actors run pay-per-use with no monthly minimums and no field-masking penalties. You can scrape thousands of leads in a single run, export to CSV/JSON, and skip the OAuth setup entirely. For prospecting workflows that also need website data, scrapers can enrich results with technology stacks (Shopify, WordPress, HubSpot) in the same pass — something Google's API doesn't offer at any price.

Why is the Google Places API so expensive?

Google restructured Places API pricing in March 2025, moving to per-field SKUs that make even simple lookups costly. Here's the current rate card for high-volume use:

• Place Details (Advanced): $17 per 1,000 requests
• Place Details (Preferred): $20 per 1,000 requests
• Nearby Search (Advanced): $32 per 1,000 requests
• Text Search (Advanced): $35 per 1,000 requests
• Autocomplete (per session): $17 per 1,000 sessions

If you're building a lead list of 50,000 restaurants in California, a naive Text Search + Place Details pipeline runs roughly $35 + $17 = $52 per 1,000 = $2,600 minimum. Add field upgrades for reviews or photos and the bill doubles. Google offers a $200 monthly credit, but that covers only ~5,700 Place Details calls before you start paying.

The pricing model also penalizes exploration. Every test query against your code hits the meter. Developers building proofs of concept often burn $50–$100 just iterating on filters.

What's the cheapest Google Places API alternative for scraping?

Apify-based Google Maps scrapers are the price leader. The actor model means you pay only for the compute and proxy bandwidth used — typically $0.50 to $2 per 1,000 places depending on how much detail you extract.

A practical comparison for 10,000 business records with name, address, phone, website, and rating:

The Google Maps Scraper & Tech Stack Audit actor falls in the lowest bracket because it runs on Apify's pay-per-use infrastructure with no subscription. You also get a bonus the Places API can't match: it audits each business's website and detects the technology stack — useful if you're selling Shopify apps, WordPress plugins, or competing against a specific SaaS.

Is scraping Google Maps legal as an alternative?

Public business data on Google Maps — names, addresses, phone numbers, hours, ratings — is generally treated as public information under U.S. case law, most notably hiQ Labs v. LinkedIn (Ninth Circuit, 2022). The court held that scraping publicly accessible data does not violate the Computer Fraud and Abuse Act.

That said, here are the practical guardrails:

1. Don't scrape personal data of private individuals. Business contact info is fine; reviewer profiles are a gray zone.
2. Respect rate limits. Aggressive scraping that degrades service can trigger TOS claims.
3. Cache results. Don't re-scrape the same data daily if a weekly refresh works.
4. For EU data, GDPR applies even to publicly listed personal information — have a lawful basis.

Apify actors handle proxy rotation and request pacing automatically, so you're not hammering Google directly. For most B2B lead-gen and competitive-research use cases, scraping is the lower-risk and lower-cost path.

What data can a Maps scraper return that the Places API can't?

This is where the cost comparison flips into a feature comparison. The Places API is a paid pipe to Google's database, but it intentionally limits what you can pull. A scraper sees the same DOM a logged-out browser sees, which often includes:

• All results for a query, not just 20 paginated entries
• Full review text without per-review billing
• Image URLs and counts
• "Popular times" histograms
• Menu items, services lists, and Q&A sections
• Owner-attribute tags like "Black-owned" or "Veteran-owned"

The Practical Tools actor adds another layer most scrapers skip: it visits each business's website and runs a tech-stack audit. For each lead, you get fields like:

• CMS: WordPress, Shopify, Squarespace, Wix, Webflow
• E-commerce platform: WooCommerce, BigCommerce, Magento
• Analytics: Google Analytics 4, Plausible, Fathom
• Marketing tools: HubSpot, Mailchimp, Klaviyo
• Hosting clues: Cloudflare, Vercel, AWS

That's a B2B sales team's dream column. If you sell a Shopify app, you can filter 10,000 scraped restaurants down to the 600 actually running Shopify and pitch them directly.

How do I switch from Places API to a scraper in production?

Migration usually takes a few hours, not days. The mental model is different — you submit a search query and get back an array, instead of calling separate nearbySearch and placeDetails endpoints — but the output JSON maps cleanly to whatever you already have.

A typical workflow:

1. Define your search inputs: query strings like "dentists in Austin TX" or "coffee shops near 90210", plus a max result count.
2. Trigger the actor via Apify's REST API or schedule it through the dashboard.
3. Poll for completion or use webhooks — runs usually finish in 2–10 minutes for under 1,000 results.
4. Pull the dataset as JSON, CSV, or Excel. The Apify SDK has one-line dataset clients for Node and Python.
5. Insert into your CRM or database the same way you would with Places API responses.

Code-wise, the swap from a googleMapsClient.placesNearby() call to an apifyClient.actor("...").call() is usually one function. Cost-wise, a job that used to run $400/month often drops to $15–$30.

What about Google's $200 monthly credit?

The $200 credit sounds generous until you do the math. At $17/1,000 for Place Details, you get 11,764 free requests per month. That's enough for a single hobby project, not a sales pipeline.

For comparison, $200 spent on the Apify Maps scraper at $1/1,000 returns 200,000 places — roughly 17× the volume. And the credit only applies to the original card-attached project; multi-region or multi-account architectures don't multiply it.

If your monthly Places API bill is over $200, you're already losing money compared to a scraper. If it's under $200 but growing, you're 90 days from the same problem.

FAQ

Q: How much cheaper is a scraper than the Google Places API? For comparable data, Apify-based scrapers typically cost 10–30× less than the Places API — roughly $1 per 1,000 places versus Google's $17–$35 per 1,000. The savings scale linearly, so high-volume users save the most.

Q: Can I use a Google Places API alternative for real-time lookups? Scrapers are best for batch jobs, not millisecond lookups. A scrape run takes seconds to minutes, so use them for nightly lead enrichment or weekly list refreshes. For real-time autocomplete in a user-facing UI, the Places API or a cached scraper dataset works better.

Q: Will Google block my scraper? Apify actors run on rotating residential and datacenter proxies with built-in pacing, so blocking is rare for normal-volume runs. If you scrape millions of records per day from one account, expect throttling — but for typical lead-gen jobs of 10K–100K places, blocks are uncommon.

Q: Does a scraper return the same place_id as the Places API? Yes, Google Maps scrapers extract the same place_id (also called CID or feature ID) that the Places API uses. This means you can mix scraped data with Places API calls if you ever need a specific field only the API provides.

Q: What if I need photos and reviews at scale? Scrapers return review text, ratings, and photo URLs in the main response without per-field surcharges. The Places API bills reviews and photos as separate Advanced or Preferred SKUs, so a scraper saves the most money exactly where the API costs the most.