Short answer: picking an alternative is not decided by the sticker price or by the size of the advertised database. Three things decide it for you. The billing unit first (a result, a credit, a minute of execution, a compute unit): two tools on the same monthly plan can differ by a factor of ten on the cost of a file you can actually use. The starting reference second: starting from a list of named people is not the same job as starting from a trade and a territory, and no price comparison rescues a mistake on that point. What is left to do after the export last: cleaning, deduplication, email verification, legal columns. That work can be measured in hours, and it is almost always missing from comparison tables.
This page compares fourteen tools on those three criteria, using vendor figures, each one dated and linked to its official source. It replaces eleven comparisons we used to publish one tool at a time: they repeated the same reading grid eleven times, less completely each time. Reading rule: every number here comes from a vendor's official page, with the link; anything not sourced is written as an observation and flagged as one.
Three starting points, three families of tools
Before comparing anything, answer one question: what do you already have? The answer eliminates two thirds of the market in a single sentence.
You already have a list of named people (LinkedIn exports, a contact file, a list of managing directors) and what you lack is their contact details. Your need is enrichment: Lusha, Kaspr, Evaboot. These tools start from a person and return an email or a phone number. They will never build the list for you.
You start from a trade and an area (every garage in a metro area, every accounting firm in a county) and the list does not exist yet. Your need is extraction: Outscraper, Scrap.io, Apify, Lobstr.io, Octoparse, ParseHub, Instant Data Scraper, or outsend's Google Maps extraction. These tools build the list; they will not tell you who makes decisions inside each company.
You want to act on LinkedIn (visit, invite, sequence). Your need is automation, not data: PhantomBuster and its family. The list still has to come from somewhere else.
You want to see your territory on a map before prospecting. Your need is geomarketing: smappen, maptive. They draw catchment areas and compute drive times; they do not supply the business data inside those areas.
A tool picked from the wrong family never catches up, whatever the budget. That is the number one cause of subscriptions paid for and abandoned in month two.
The decision table
One row per tool, four columns that decide. The "what is left to do" column is the one nobody displays, and it is the one that sets the real cost.
| Tool | Entry point | Billing unit | What the free plan actually gives | What is left to do afterwards |
|---|---|---|---|---|
| Outscraper | a Maps query, UI or API | by volume extracted (vendor grid, check at purchase) | trial credit, not contractual | cleaning, deduplication, email verification, compliance |
| Scrap.io | a country and an activity | subscription, systematic coverage | vendor trial | check how fresh the records are, add legal data |
| Apify | an Actor picked from the Store | the compute unit, $0.2 on Free and Starter plans | $5 of credit to spend on the Store | pick the right Actor, reprocess the JSON, everything downstream |
| Lobstr.io | a query, a ready-made scraper | 1 credit = 1 unique result, monthly credits, no rollover | 30 rows per query | enrichment, verification, restarting interrupted exports |
| Octoparse | a page and a hand-pointed template | subscription | free plan capped on volume | maintain the template when the source changes |
| ParseHub | a page and a template | subscription | 5 public projects, 14-day retention, 200 pages per run | template maintenance, and dealing with public projects |
| Instant Data Scraper | the page currently on screen | free | everything, as XLS, XLSX or CSV | one page at a time, no resume, no enrichment |
| Lusha | a contact you can already name | the credit: 1 for an email, 10 for a phone number | 40 credits a month, i.e. 4 direct numbers | find the list of names upstream |
| Kaspr | a profile on the professional network | the credit, weighted by data type | 5 phone credits and 5 direct-email credits a month | find the list of profiles upstream |
| Evaboot | a Sales Navigator search | 2 credits per lead exported with its email | no free plan; Sales Navigator seat not included, from €120.99 a month | export capped at 2,500 leads per search |
| PhantomBuster | a LinkedIn profile or list | the minute of execution | 30 minutes of execution a month, 1 slot | find the list, and carry the account risk |
| smappen | an area drawn on a map | subscription | limited areas | all the business data inside the area |
| maptive | a file to put on a map | subscription | time-limited trial | supply the file, the tool does not produce it |
| outsend | a trade and an area | alpha access on application | see the access page | nothing on the standard chain: the output is a cleaned CSV |
How to read this table: the first four columns compare against each other, the fifth compares against your own time. A free tool that leaves you three hours of cleaning per file costs more than a €30 subscription if you produce one list a week.
Extracting local data: seven tools, two economics
Every tool in this family can produce a list of business records. The dividing line is not raw power, it is recurrence. A general-purpose scraper gives you a capability, reaching any page, and in exchange you carry the knowledge of every source. A dedicated extractor only knows one source, but when that source changes the vendor fixes it, not you. One-off extraction on an unusual site: the generalist wins. Monthly extraction on a major source: the dedicated tool wins, because template maintenance ends up costing more than the tool.
Outscraper alternative
Outscraper is a public-data extraction service covering Google Maps among other sources, driven either through a web interface or an API. Its real strength is the breadth of the catalogue and the maturity of the API. There is nothing to hold against it on its own ground.
What decides against it, when something does, is everything downstream. An extractor hands you a table and stops. On a prospecting list, that table contains duplicates, invalid numbers, dead websites, and carries no legal columns. The test that separates every tool on this page fits in one sentence: run the same query on two tools and count, not the rows, but the rows still usable after cleaning. It is a ratio, and it rarely exceeds 70% on a raw extraction.
When to stay: you need breadth of sources, or API control from your own code. When to look elsewhere: what you actually need is a finished prospecting file, in which case the thing to compare is the full pipeline, not the extractor alone. Head to head: outsend versus Outscraper.
Scrap.io alternative
Scrap.io takes the opposite angle to an on-demand extractor: systematic coverage of Google Maps by country and by activity, queried like a database. The benefit is immediate, you pick a country and a trade and you get volume straight away. The price of that model is freshness: a pre-built database reflects the state of the last crawl, an on-demand extraction reflects the state of today.
Freshness discriminates far better than volume, and it can be checked in one pass: take twenty records at random from the export, call five numbers and open twenty websites. The share of sites that still respond tells you the real age of the database far better than the date the vendor displays. A dead-URL check automates exactly that measurement.
When to stay: you work across several countries and immediate volume matters most. When to look elsewhere: your area is narrow, your trade is a niche, or you call the same list every quarter. Head to head: outsend versus Scrap.io.
Apify alternative
Apify is not a tool, it is a marketplace: 64,042 Actors published on the Store as recorded on 26 August 2026, including the Google Maps Scraper, one of the most used on the platform. What really sets Apify apart is not its price, it is its billing unit: the compute unit, billed at $0.2 on the Free and Starter plans (Apify, pricing page, 2026). You pay for compute time, not for results.
That difference is structural, and it explains the most common complaint about the tool: the cost of a run is hard to predict, because it depends on how fast the source responds, how many pages are crawled, and how many retries happen. Some Actors normalise the problem by pricing per result, such as the Google Maps Scraper advertised from $1.50 per 1,000 places extracted (Apify, Actor page, 2026). That is the exception, not the platform's rule.
The free plan, $5 of credit to spend on the Store, is an honest test bench: enough to validate extraction quality on a real area, not enough to produce.
When to stay: technical profile, multiple sources, appetite for orchestration. When to look elsewhere: you want a predictable cost per file, and you do not want to arbitrate between twelve Actors that do the same thing.
Lobstr.io alternative
Lobstr.io aims for the shortest path: more than twenty no-code scrapers ready to run, you launch, you get a CSV. It is a good answer to a one-off need, and the tool is clear about what it does.
The pricing model is the thing to check before subscribing: 1 credit equals 1 unique result, credits renew every month and do not roll over (Lobstr.io, pricing page, 2026). The free plan caps each export at 30 rows. In practice: steady prospecting amortises the subscription, campaign-driven prospecting wastes it. A month without a campaign and the credits are gone; a spike and you have to move up a tier.
When to stay: steady monthly rhythm and stable volumes. When to look elsewhere: campaign-driven activity, with months at zero and months at 5,000 records. Head to head: outsend versus Lobstr.
Octoparse alternative
Octoparse belongs to the visual no-code scraper family: open a page, click the elements you want, the tool infers a template. The promise holds on plenty of sites. It also carries a cost nobody quotes at purchase: that template has to be maintained.
And its failure mode is the worst kind, because it does not look like a failure. The template runs, the export happens, the file has the right number of rows, but one column is empty or shifted by one field. You find out when you use the file, often after importing it somewhere. The countermeasure does not depend on the tool: compare the fill rate column by column against an earlier extraction. A column that drops from 90% to 0% signals a structural change in the source, not a volume problem.
When to stay: your sources are genuinely varied and none of them is major. When to look elsewhere: 80% of your real need is "every business of one trade in one area", in which case a generalist is a detour.
ParseHub alternative
ParseHub plays the same game as Octoparse, as a desktop application, and plays it well. Two clauses in its free plan decide for you, and both are written in plain sight: the 5 free-plan projects are public, data retention there is 14 days, and each run is capped at 200 pages against 10,000 on the paid plan (ParseHub, pricing page, 2026).
"Public" is not only about the output: it is the project configuration, therefore the source you target and the fields you extract, that becomes visible. If your targeting is your edge, this is not a free evaluation plan, it is publication.
When to stay: occasional extraction on non-sensitive sources, or a paid plan you have accepted. When to look elsewhere: your targeting is confidential, or you need history beyond two weeks.
Instant Data Scraper alternative
The Instant Data Scraper extension is free, claims 1,000,000 users and a 4.9 rating from 7,700 reviews on the Chrome Web Store, and infers on its own the structure of the page on screen to export it as XLS, XLSX or CSV (Chrome Web Store, official listing, 2026). On a table displayed on screen it does the job, for free, in three clicks.
Its limit is not weak execution, it is its unit of work: an extension starts from the page on screen, an area-based extraction starts from the territory. No improvement to the extension closes that gap. The day your target no longer fits on one screen, or needs to resume after an interruption, the tool drops out by construction.
Does it actually need replacing? Often not. If your need is to grab what you can see, one page at a time, keep it: it is free and it is enough.
Enriching named contacts: the credit is the unit that misleads
In this family every vendor prices in credits, and no two credits are worth the same. It is the one place in this market where comparing monthly prices is frankly misleading.
Lusha alternative
Lusha is strong on direct dials, and its pricing says so plainly: revealing an email costs 1 credit, revealing a phone number costs 10 (Lusha, pricing page, 2026). The free plan of 40 credits a month is therefore worth 40 addresses or 4 direct numbers. That is usually the exact moment people start looking for an alternative. The Starter plan is listed at $49.90 a month for 400 credits. The vendor claims 290 million contacts and 28 million companies, with stated accuracy of 98% on emails and 86% on phone numbers (Lusha, official page, 2026): vendor figures, to be treated as such.
The 1-to-10 ratio is not arbitrary commercial policy, it is an admission of cost: a person's direct number is rare data and expensive to maintain. It also implies a different legal regime. A generic company address and an employee's mobile are not processed the same way, and public accessibility is not by itself a legal basis for processing.
When to stay: your target is a job function inside a structured company, and the phone is your channel. When to look elsewhere: your target is a trade across a territory, and the list of names does not exist yet. Head to head: outsend versus Lusha.
Kaspr alternative
Kaspr works through an extension, on a profile or a list of profiles from the professional network. The free plan gives 5 phone credits and 5 direct-email credits a month (Kaspr, pricing page, 2026); the Starter tier details 100 phone credits and 5 direct-email credits a month, or 1,200 and 60 on an annual commitment (Kaspr, help centre, 2026). The vendor claims more than 200 million European B2B contacts fed by more than 120 sources (Kaspr, Our data page, 2026).
The asymmetry of the paid tier is instructive: twenty times more phone credits than named emails. It shows where the vendor places its value, and it also tells you that if your channel is the named email, this is not the right door.
The structural constraint sits elsewhere: the extension needs a profile to work. If your target is "the 300 garages in this metro area", there is no starting profile, and no credit quota solves that. Head to head: outsend versus Kaspr.
Evaboot alternative
Evaboot cleans and exports a Sales Navigator search, and its billing model is one of the most honest on the market: 1 credit for the exported lead, 1 credit for the email found, and nothing to pay when no email is found (Evaboot, pricing page, 2026). Charging for results rather than attempts deserves to be said out loud.
But the unit of decision is not the tool, it is the chain. Evaboot starts at $9 a month for 100 credits, while the Sales Navigator Core licence it requires starts at €120.99 a month or €1,088.88 a year (LinkedIn Sales Solutions, 2026, indicative entry price, taxes possibly excluded). More than 90% of the real cost of the chain sits in the seat, not in Evaboot. The export ceiling comes from the same place: a Sales Navigator search is paginated at 2,500 leads or 1,000 companies, a LinkedIn limit rather than an Evaboot one.
When to stay: you already hold the Sales Navigator seat and your targets are well described there. When to look elsewhere: your target is a local fabric of very small businesses, often absent or poorly described on the network, while the French business register lists 36 million establishments, updated daily and free of charge (Insee, 2026). That total is a cumulative count since 1973, closures included: the live stock is smaller, 14,310,906 active and publicly listed establishments as of 5 September 2026. Head to head: outsend versus Evaboot.
Automating LinkedIn: PhantomBuster and the minute of execution
PhantomBuster alternative
The query "phantombuster alternative" covers two needs that have nothing to do with each other. The first is acting on LinkedIn: visiting, inviting, sequencing. The second is building a file of companies to approach. PhantomBuster answers the first; the second needs a data source, not an automation runner.
Its billing unit is execution time, and that is where the real cost sits: the free plan gives 30 minutes a month with 1 slot and 50 MB of storage, with no AI credits and no email credits; paid plans include 20 h, 80 h and 300 h for $69, $159 and $439 a month, or $56, $128 and $352 effective monthly on an annual commitment (PhantomBuster, official page, 2026). You cannot estimate a bill without timing one representative run and multiplying it by your cadence: that is the useful test, and it takes ten minutes.
The second thing to weigh is not financial. Automating an account commits that account, and the network's user agreement explicitly addresses third-party software (LinkedIn User Agreement, section 8.2, 2026). That risk is carried by you, not by the vendor.
When to stay: LinkedIn is your channel and your targets are on it. When to look elsewhere: your target is a trade across a territory. See also PhantomBuster, Hunter and lemlist against a single chain, what a LinkedIn scraper is and its clean alternatives, and outsend versus PhantomBuster.
Mapping a territory: smappen and maptive
These two are not alternatives to the tools above; they answer a different question: "where is my area", not "who is inside it". smappen computes catchment areas by drive time, maptive maps a file you supply. Neither produces business data. We kept them as dedicated pages because their search intent is distinct: smappen alternative and maptive alternative.
The three questions that actually decide
1. What is the billing unit? The result (Lobstr, Evaboot), the credit weighted by data type (Lusha, Kaspr), the minute of execution (PhantomBuster), the compute unit (Apify), or a flat subscription. Convert everything into one measure: the cost of one usable row after cleaning. It is the only one that compares.
2. What is the starting reference? A named person, or an establishment on a territory. Contact databases describe job functions inside structured organisations; a public business register describes establishments, including the neighbourhood craftsman with no social presence at all. Neither covers the other.
3. What is left to do after the export? Deduplication, email verification, dead-site detection, registration and VAT number matching. Put those steps in hours before you compare subscriptions: that is where the real gap opens between two tools at the same price.
What outsend does, and what it does not
outsend takes the pipeline angle rather than the standalone extractor: Google Maps extraction is one module, followed by modules that clean, deduplicate, find the professional email, check deliverability and attach legal data. The output is a directly usable CSV, and the step that touches personal data is a separate module, therefore an explicit choice rather than a side effect.
Its limits, stated plainly: the source catalogue is narrower than Outscraper's or Apify's, the product is in alpha, and it does not start from a named person. If your need is the mobile number of one identified director, Lusha or Kaspr do a job outsend does not do. The most common setup among our users is in fact mixed: one chain to build the list by territory, one enrichment tool for the handful of named accounts that really matter.
Request access or browse the full set of modules.
About this page
This page replaces eleven comparisons published one tool at a time. Eleven pages repeating the same reading grid serve a reader worse than a single page that runs through it once, completely. The old addresses redirect here permanently, and no figure was lost on the way: every vendor figure from the original pages is repeated above with its source and its date.
Two comparisons keep their own page: smappen and maptive, because their search intent is geomarketing rather than data extraction, and because they answer a different question: where is my area, not who is inside it. The head-to-head comparisons remain reachable from each section above.
FAQ
What is the best alternative for extracting Google Maps?
There is no single answer, and it depends on recurrence. For a one-off extraction, a free extension like Instant Data Scraper or a no-code scraper like Lobstr.io is enough. For a monthly need, a tool dedicated to the source bills per result, whereas a generalist bills compute time and leaves the extraction template for you to maintain. For a finished prospecting file, compare full pipelines rather than extractors.
Can a free plan really be used to evaluate a tool?
It lets you judge quality, never produce. 40 Lusha credits are worth 4 direct numbers, 5 Kaspr credits are worth 5 numbers, 30 PhantomBuster minutes are worth a few short runs, $5 on Apify is worth one test area. Run the test on your real target rather than on well-known companies, where every database looks the same, and judge accuracy rather than volume.
Why is the cost of an extraction so hard to predict?
Because the billing unit is not the result. When you pay for compute time (Apify's compute unit) or execution time (PhantomBuster), the bill depends on how fast the source responds, how many pages are crawled and how many retries occur, three variables nobody knows before launching. Tools that charge per unique result, like Lobstr.io or Evaboot, are predictable by construction.
Do you need a Sales Navigator subscription to use Evaboot?
Yes, the seat is required and it is not included. It is the most expensive part of the chain: a Sales Navigator Core licence starts at €120.99 a month while Evaboot's entry tier is $9 a month. Comparing Evaboot with a tool that depends on no third-party licence, on advertised prices alone, makes no sense.
Is extracting data from Google Maps legal?
A business listing carries public company data: trading name, address, the venue's phone number. As long as you stay there, you are handling company data. As soon as a field identifies a natural person, a director's name, a named email address, a personal mobile, you are in the scope of data protection law, whatever the source. Public accessibility is not a legal basis: you must be able to say why you are processing the data, inform the person, and honour an objection.
Can you get email addresses straight from Google Maps?
Almost never. Listings carry the phone number and the website, rarely an email address. Finding the email is a separate step, starting from the website's domain rather than from the listing. That is exactly why comparing extractors on record volume alone is misleading: it compares incomplete outputs.
Is a no-code visual scraper enough for prospecting?
For a one-off extraction, yes. For recurring use, the template becomes the problem: it breaks silently when the source changes structure, producing empty columns rather than an error. The countermeasure is a systematic fill-rate check, column by column, after every extraction, whatever the tool.
What does "public projects" mean on ParseHub's free plan?
That the project configuration is visible, therefore the source you target and the fields you extract, not just the output. Combined with 14-day retention, that clause disqualifies the free plan as soon as your targeting is your edge. It is not a hidden defect, it is written on the vendor's pricing page.
Figures recorded in 2026 on vendors' official pages, each linked where it is cited. Pricing grids change: check the vendor's page at the time of purchase. Last revision of this page: 4 September 2026.