Outscraper Alternatives for Google Maps and Yellow Pages Leads
If you are evaluating Outscraper, you are probably running a lead-gen program where Google Maps is the seed source and the downstream question is what to do with each record once you have it. Outscraper is one of the most direct, mature players in this space — clean structured JSON, deep field coverage on Maps, and a reputation for reliability. This post is a practical map of where Outscraper fits, where its scope ends, and what the alternative landscape looks like when the job is a full local-services leads pipeline rather than a Maps-only extraction.
Why People Look for Outscraper Alternatives
Outscraper is genuinely good at what it was designed for: a Maps-first scraping service with a clean schema, sensible defaults, and broad geographic coverage. For one-shot Maps extractions or for teams that already have the rest of their lead pipeline wired up, it is hard to outrun. The friction shows up in three specific places.
Maps is first-class, everything else is secondary. The Outscraper catalog has Maps as the flagship product, with a long supporting list of one-off services — phone validation, email scrapers, review scrapers, individual platform endpoints. They work, but they are not the same depth of investment as Maps. Yellow Pages, in particular, sits at the edge of the catalog rather than at its center, which matters if your US coverage strategy depends on the Maps + YP overlap to widen the long tail of trades and contractor listings. Lead-gen agencies that run weekly territory builds across plumbers, HVAC, electricians, and roofers across mid-sized US metros routinely find that Maps alone misses 15–30% of the actively-operating businesses YP still indexes — especially older operators with no website and minimal Maps profile maintenance.
No chained enrichment under one roof. Outscraper returns the Maps record. What it does not do is take that record's website field, run email-discovery against it, look up the LinkedIn company page, and hand back a single enriched row. That chain is the actual work of a lead-gen pipeline — the Maps pull is the first step, not the destination. Teams using Outscraper typically integrate Hunter or Apollo for email, a SERP scraper for LinkedIn, and a dedupe layer themselves. That works, but it is a multi-vendor stitch-up rather than a single API, and every extra vendor adds its own auth, rate limits, output schema, and renewal cycle. For an agency running this pipeline across multiple client territories, the operational cost of the integration glue often exceeds the per-record scraping cost over a year.
Limited net-new-business monitor primitive. Outscraper has scheduled runs. It does not have a built-in "tell me what businesses appeared in this city + category since last week" primitive. You can build it — pull the result set on a cron, diff against the previous run, post the new rows to a webhook — but you are writing the diff loop and the storage layer yourself, including the edge cases (phone normalization, businesses that shift category, listings that briefly disappear and reappear). For lead-gen teams whose retainer model depends on a steady drip of fresh leads, that gap is meaningful. The whole point of a monitor primitive is that the team consuming the output never sees the duplicates and never has to ask "is this row really new?" — pushing that work back to your in-house engineering is a recurring tax.
None of this makes Outscraper wrong. It makes it a poor fit if your real shape is "I need Maps plus Yellow Pages plus chained enrichment plus net-new monitors, under one API, on a recurring schedule." That is a different category of tool.
What "Alternative" Really Means Here
Before the comparison table, it helps to frame what you are actually choosing between. Maps and directory scraping tools fall into four buckets.
Maps-specialist services. Outscraper is the prototype. Maps is the headline product, with a tight schema and good coverage. Strength: depth on the one platform, mature output. Weakness: directory and enrichment are secondary, monitor primitive is missing.
General actor marketplaces. Apify has a Google Maps Scraper actor (and several community variants) that you rent by the run. Strength: breadth, you can probably find an actor for any niche. Weakness: schema drift between actors, billing complexity, no first-party enrichment chain.
Enterprise proxy stacks with Maps endpoints. Bright Data has a Google Maps dataset and scraper API. Strength: scale and reliability are best in market. Weakness: enterprise sales motion, contract minimums, overkill until you are at a certain volume.
No-code automation platforms. Phantombuster has Maps automations that run inside its broader workflow product, sitting alongside LinkedIn automations and social-media tools. Strength: visual workflow builder, easy onboarding for non-developers. Weakness: per-run pricing model is opinionated, output is tied to the Phantombuster workspace.
Niche directory aggregators. ListYellow, LeadStash, and similar smaller vendors specialize in pre-scraped Yellow Pages-class US directory data, often sold as bulk downloads rather than an API. Strength: the data is ready immediately, no scrape time. Weakness: freshness is whatever the vendor's last update was, and you do not control the query slice.
Multi-platform leads APIs. LogPose sits here. Maps and Yellow Pages and Google SERP under one API, plus the chained enrichment hooks and net-new monitor primitives. Strength: the full local-leads pipeline behind one key. Weakness: scope is the platforms actively supported, no generic actor-marketplace breadth.
Knowing which bucket you want narrows the decision before you compare features.
The Honest Comparison
| Tool | Maps coverage | Yellow Pages support | Chained enrichment | Net-new monitor | Geographic slicing | Output shape | Best for |
|---|---|---|---|---|---|---|---|
| Outscraper | Deep, mature schema | Available but secondary | Manual, multi-vendor stitch | Scheduled re-runs, no diff primitive | Lat/lng viewport, query string | Clean structured JSON | Maps-first one-shots and recurring pulls |
| Apify Google Maps Scraper | Broad via marketplace | Separate actors, schema varies | None native | Schedules only | Lat/lng viewport, query string | Varies by actor | Heterogeneous one-off jobs |
| Bright Data Google Maps | Deep, enterprise-tier | Separate dataset product | Optional via Data Collector | Limited via custom builds | Lat/lng viewport, postal | Structured JSON / dataset | Enterprise volume |
| Phantombuster Maps automation | Solid for small-batch | Not first-class | Native LinkedIn automations help | Schedules only | Lat/lng viewport, search query | Workspace-tied JSON | No-code visual workflows |
| ListYellow / LeadStash class | Indirect (resold) | Pre-scraped bulk data | None | None (snapshot product) | Pre-sliced by city + category | Bulk CSV downloads | Quick US directory snapshots |
| LogPose | Direct scrape, full field set | First-class endpoint | Native (Maps → website → email hook → SERP for LinkedIn) | Yes (rule-based, email + webhook) | Lat/lng viewport for Maps, city + category for YP | Consistent JSON across platforms | Full local-leads pipeline under one API |
A few words on each.
Outscraper is the right tool when Maps is the focus and the rest of your pipeline is already built. The schema is mature, the field coverage is generous (categories, popular times, photo refs, lat/lng, full hours), and the team has been at this long enough that the output is predictable. The honest tradeoffs are the secondary status of directory sources beyond Maps, the absence of a native enrichment chain, and the lack of a diff-based monitor primitive.
Apify's Google Maps Scraper is the right call when your scraping needs are heterogeneous and you do not want to negotiate enterprise contracts. The actor marketplace covers more sites than any other tool, and the Maps actors specifically are reasonable. The catch is the schema drift between community actors and the per-actor billing layer on top of the platform subscription.
Bright Data is the enterprise tier. The Google Maps dataset is well-maintained, the scraper API is mature, and the proxy infrastructure under it is genuinely best in market. If you are scraping millions of Maps records per month and have time for a procurement cycle, this is the right answer. If you are doing tens of thousands, it is overkill.
Phantombuster is the right tool when the workflow is more important than the raw data — a visual builder that chains Maps to a LinkedIn outreach automation to a Sheets export, all in one workspace. The Maps automation is solid for small-batch runs. Output is tied to the Phantombuster workspace, which is fine if you stay there and friction if you need to integrate downstream.
ListYellow / LeadStash and similar bulk-data vendors are the right answer when you want a fresh-enough US directory snapshot without running any scrapes yourself. Pricing is per-bundle and the data is whatever the vendor's last refresh was. Good for one-shot list builds, weak for any workflow that needs the geographic or category slice to change weekly.
LogPose sits in the multi-platform leads bucket. Maps, Yellow Pages, and Google SERP under one API key, with a chained-enrichment workflow (Maps record → cleaned domain → email-discovery hook → LinkedIn via SERP) and a monitor primitive for net-new-business diffs. The honest constraint is platform scope — for a niche directory that is not Maps, YP, or one of the other supported sources, an actor on Apify will get you there faster than waiting for a dedicated endpoint.
Per-Use-Case Recommendations
If your job is one-shot Maps extraction with a clean schema and you already have the downstream pipeline built, stay on Outscraper. There is no reason to migrate to shave 10% off a bill that is already small relative to the cost of the downstream tooling.
If you need Maps plus Yellow Pages plus a chained enrichment step (email and LinkedIn) in a single workflow, LogPose. The pipeline is the product rather than a thing you assemble from three vendors.
If your scraping is heterogeneous (Maps plus three other random sites this week, a different three next week), Apify. The marketplace breadth is the right answer for shifting targets.
If you are doing millions of Maps records per month with a procurement department, Bright Data. The pricing only makes sense at that volume but the infrastructure is genuinely best in market.
If you want a visual no-code workflow that includes Maps as one step in a multi-tool automation, Phantombuster. The other automation building blocks (LinkedIn, Sheets, email) are the actual draw.
If you need a US directory snapshot today, not a recurring pull, ListYellow or LeadStash class vendors. One purchase, one CSV, no scrape time.
Code: Same Job, Two Tools
To make the difference concrete, here is the same task — pull dentists in Austin TX from Google Maps — done two ways.
On Outscraper, you submit an async request to the Google Maps endpoint, get a request ID, and poll until the results are available:
# 1) Submit the Maps search
curl -X GET "https://api.app.outscraper.com/maps/search-v3?query=dentists,%20Austin,%20TX&limit=100&async=true" \
-H "X-API-KEY: YOUR_OUTSCRAPER_KEY"
# → {"id": "your-request-id", "status": "Pending", ...}
# 2) Poll the request, then fetch results when status == "Success"
curl "https://api.app.outscraper.com/requests/your-request-id" \
-H "X-API-KEY: YOUR_OUTSCRAPER_KEY"
The output is a clean per-business JSON array with the standard Maps fields. To get an email, you make a second call to a separate Outscraper endpoint (or to an external email-discovery vendor) passing the website domain from each row.
On LogPose, the Maps call is the same async submit-poll-fetch pattern, with the same shape applied across every supported platform:
# 1) Submit
curl -G "https://api.logposervices.com/api/v1/ecommerce/googlemaps/search" \
-H "X-API-Key: lp_xxxxxxx" \
--data-urlencode "url=https://www.google.com/maps/search/dentists/@30.2672,-97.7431,13z" \
--data-urlencode "pages=5"
# → {"job_id": "gm_8f3a..."}
# 2) Fetch result once status == "completed"
curl https://api.logposervices.com/api/v1/jobs/gm_8f3a/result \
-H "X-API-Key: lp_xxxxxxx"
The same submit-poll-fetch flow works against /api/v1/ecommerce/yellowpages/search for the YP side of the same city + category combo, so the second source plugs into the existing code path with a path change rather than a vendor change. From there the chained enrichment — domain normalization, email discovery, LinkedIn lookup via SERP — runs against the same API key without integrating a separate platform.
The Chained Enrichment Difference
The thing that separates a Maps-only tool from a leads pipeline is what happens after the first record arrives. The Maps record gives you a website URL for roughly 70–80% of small businesses. From there, the next three steps decide whether the row becomes an SDR-usable lead.
# Step 1: Maps pull (covered above)
# Step 2: Normalize the website to a clean domain
# Step 3: Email-discovery against the domain
# Step 4: LinkedIn company page via SERP lookup
On a Maps-specialist tool, steps 2–4 are your problem — you integrate two or three more vendors, write the domain-normalization regex, manage the rate limits, and build the dedupe layer. On a chained-enrichment API, they are configuration. Same submit-poll-fetch flow, same API key, four endpoints in sequence. The full walkthrough of that pipeline (domain normalization, the realistic 30–60% email match rate, the SERP-based LinkedIn lookup, and the merge step) is in How to enrich business leads with emails, phones, and socials.
Common Gotchas When Migrating Off Outscraper
Schema field renames. Outscraper's Maps schema has its own field names — phone, site, full_address, borough. Other tools use website, address, neighborhood. Map the columns explicitly in your pipeline before you switch, or your downstream consumers will silently see empty columns.
Async patterns vary. Outscraper's async pattern uses a request ID and a status endpoint. Most alternatives use a job ID and a separate wait=true shortcut for short jobs. Re-read the async docs for whichever tool you migrate to before you assume the polling logic transfers.
Geographic slicing primitives differ. Outscraper accepts a query string with a city name and resolves it to a viewport internally. Most Maps scrapers expect an explicit @lat,lng,zoom viewport in the URL. The mapping is straightforward but it is not the same primitive — if your existing code generates "dentists in Austin, TX" strings, you will need to convert those to viewports before they work against a URL-driven API.
The Yellow Pages output is not interchangeable with Maps. Two different sources, two different field sets, two different identifiers. YP has phone and address but rarely returns a website. Maps has website but its category taxonomy is different from YP's. The dedupe key — phone normalized to E.164 — is the field that makes the merge possible.
Monitor logic moves from cron to configuration. If you were running your own diff loop on top of Outscraper's scheduled runs, switching to a tool with a native monitor primitive replaces a custom cron + storage + diff job with a single configuration. Plan the migration of the historical keyset into the new monitor's storage so you do not get a one-time flood of "new" rows that are actually carried over from the old setup.
The Honest LogPose Fit
LogPose works well when the shape is "I need Maps plus Yellow Pages plus chained enrichment plus net-new monitors, behind one API key, with the same submit-poll-fetch flow across all of it." The async pattern is identical across every endpoint, the JSON shape stays consistent, and monitors are a single API call rather than a custom diff job. It is not the right fit if your job is purely Maps with a depth-of-Maps-schema requirement that exceeds anything else — Outscraper's flagship product is worth the standalone-tool cost in that case — or if your scraping is heterogeneous enough that a marketplace of community actors will serve you better.
Get Started
Sign up at logposervices.com, generate an API key from Tool → API Keys, and submit a request against /api/v1/ecommerce/googlemaps/search?url=... to confirm the Maps path works. From there, the Yellow Pages endpoint at /api/v1/ecommerce/yellowpages/search accepts the same submit-poll-fetch pattern, and the chained enrichment steps plug into the same key. The free tier is large enough to validate the integration on real city + category slices before you commit.
Related reading: How to scrape Google Maps for local business leads, How to enrich business leads with emails, phones, and socials, How to build a B2B lead list from Yellow Pages (no code), How to monitor Yellow Pages for new businesses.