Every Livescraper tool is built for one source - so each one stays simple. They share the same exports, the same fair pricing, and the same friendly interface.
Pull places & businesses from Google Maps - name, address, phone, website, email and social handles, filtered by city or category.
Already have the websites? Submit a list of domains and get back the Google Maps listing each one belongs to - address, coordinates and place identifiers.
A place row carries one photo_url and a photos_count. This returns the rest - the photo links behind every location you care about.
Directions and travel time between two points - seven travel modes, plus depart-at or arrive-by so you can compare peak against off-peak. Not footfall.
The businesses inside a venue - mall units, terminal concessions, office suites. Area searches under-surface them; this starts from the building.
Every review on every location you care about - yours or a competitor's. Authors, ratings, timestamps, full text, all delivered as rows.
Re-scan the listings you care about on a schedule - daily, weekly or monthly - and get emailed only the reviews that are new since the last run.
Read reviews from the author’s end. Point it at a contributor profile and get every review that person published - useful when a damaging review looks questionable.
Hand over a list of domains or business names. Get back emails, phone numbers, social handles and meta data - in one clean pass.
Give it a domain, get the people - named contacts with job titles, emails and their source, plus company firmographics. Up to 1,000 domains per run.
Check up to 1,000 addresses against the mail server before you send - the cheapest way to protect the domain you send from.
Sorts up to 1,000 addresses into disposable, free or corporate - catching throwaway signups that pass an ordinary deliverability check.
A domain in, the company out - 20 flat columns covering industry, headcount, revenue, funding, address and social accounts. Built for scoring and market sizing.
Company pages as rows - exact employee count, follower count and self-declared specialities, plus industry, HQ and type. Up to 1,000 companies per run.
Public member profiles for candidate sourcing and account mapping. Personal data with restricted uses - not for screening or monitoring people. Read the limits first.
Rating, review count, claimed and closed flags plus email, phone and address per business - from a domain, a page link, or a whole category at once.
Search by company name or category and get every match - same 17 fields as the lookup, up to 100 businesses per term. For when you have no domain list yet.
The review text itself - title, body, stars, date, plus the author’s country and reviewing history. Cut-off dates make repeat runs cheap.
Carrier and line type for up to 1,000 numbers per run - find out which ones can receive an SMS before you pay to message them.
Checks numbers against public directory listings. US-centric coverage, and restricted uses - not for screening or tracing people. Read the limits first.
Global, category and country rank plus bounce rate, pages per visit and visit duration for up to 1,000 domains. Third-party estimates - strong for comparison.
Reveal what a site is built with - CMS, ecommerce platform, analytics, CDN, hosting and web server, plus a roll-up of every technology detected.
Employee reviews of a company as rows - rating, pros and cons in separate columns, employment status, recommendation, CEO approval and outlook.
A Glassdoor jobs search as ranked rows - title, company, location, advertised salary with its source, and the position each result held.
An app's reviews as rows - text, star rating, ISO date, helpful votes, app version and a stable review id you can deduplicate repeat pulls on.
Search interest by place as rows - one per location per term, with the region code, timeframe and resolution on every row.
Alphabet’s own careers site as rows - full description, minimum and preferred qualifications, responsibilities and a direct apply link per vacancy.
Google’s jobs vertical as rows - nine columns per result, including the board each posting is credited to. Column names verified from real exports.
Handles, channel URLs or search terms in - 20 fields per channel out, including subscribers, views and video count pre-parsed to numbers.
An Indeed search as rows - title, employer, location, advertised pay, contract type, posting age and Indeed’s own job key to deduplicate on.
Employee reviews of a company as rows - star rating, review body, job title, location, five optional category scores and a stable review id.
A delivery listing as rows - restaurant name, rating, review count, estimated delivery window, fee and distance from the address you set.
Department store product pages as rows - name, description, price both as displayed and parsed, brand, availability, every image and both identifiers.
US addresses in, one row each out - normalised address, coordinates and a per-row status. Restricted use; the page reports what our runs actually returned.
The same address question put to a second public-records source. Six columns, one stable shape. Restricted use, and the page is explicit about what came back.
A company's posts as rows - author, text, when it went out, and the reactions, comments and reposts each one collected, with a link and an identifier.
The Google search dropdown as ranked rows - ten suggestions per seed query, with the position each held. Long-tail phrasing straight from real searches.
The Maps search dropdown as ranked rows - how customers actually phrase a category, ten suggestions per seed, with an optional location bias.
A route search as rows - airline, departure and arrival times, duration, stops and the fare shown, one row per itinerary.
Addresses in, coordinates out - plus country, state, city, street, postcode and an IANA time zone parsed into their own columns.
Coordinates in, the nearest human-readable address out, with a Plus Code and county. Read class and type - the nearest mapped object is not always a building.
A domain’s public registration record - registrar, creation, update and expiry dates, EPP lock codes and nameservers, one row each.
A screenshot of every URL you submit, at the viewport size and format you choose. Candid about what the status column does not tell you.
Company domains in, ZoomInfo’s record out. Fourteen columns declared - and an honest account of what our own runs returned.
The ultimate database for B2B lead generation - vital context on every potential customer, including emails, phones and firmographics.
Pull doctor and healthcare provider profiles from jameda.de - names, specialties, addresses, phones, websites, ratings and reviews.
SERP data without the headache - keywords, ranking positions, links and metrics for any query, any region, any device type.
Up to 1,000 queries per run - headline, snippet, link and ranking position, filtered to the past hour, day, week, month or year.
Image results with the source site and hosting-page link on every row - built for attribution, not for reuse. Up to 1,000 queries per run.
Which videos rank for your keywords, and in what order - query, position, title, link and snippet. A visibility tool, not a video-metadata one.
What's on in a city, as a file. Up to 1,000 city, venue or genre queries per run - for date-clash checks, promoter research and calendars that stay current.
Submit ASINs or product URLs and get title, description, price, availability, rating and review count back as rows - across 17 Amazon marketplaces.
Give it a product list and get the reviews back - reviewer name, verbatim text, star rating and date, across 17 Amazon marketplaces.
ASOS listings as structured rows - names, images, prices, availability, plus the sizes and colours each line is offered in.
Paste an App Store link and export the reviews - rating, title, verbatim text, votes, dates, and the app version each one was written against. Apps and podcasts.
Turn an accommodation search into rows - titles, descriptions, prices, availability, ratings, amenities and host detail for a whole market.
Ratings, comments, dates and reviewer profiles from accommodations. Only completed stays can review - so review velocity doubles as a demand signal.
Keep App Store search results as rows. Apple never shows who else ranked for a term - capturing the search is the only way to see your competitive set.
Employer reviews as rows - rating, headline, pros, cons, date and whether the reviewer would recommend the place. kununu publishes no author names, so the export carries none.
Maker profiles as rows - name, headline, avatar, follower and following counts, products, posts, collections, reviews and stacks, plus the maker and verified flags.
Delivery reviews as rows - reviewer, headline, comment, date and the overall rating, plus the delivery, food and service scores Thuisbezorgd collects as three separate columns.
US home-service contractors as rows - trade, address, rating, review count, six summarised sub-ratings, years in business and seven amenity flags, ranked as Angi returned them.
Marketplace listings as rows - title, asking price, city and state, thumbnail and a permalink to each item. Three columns arrive empty on every row, and the page says which.
Verified merchant reviews as rows - star rating, headline, full text, reviewer name and location, an ISO timestamp and a permalink. A URL or the bare merchant slug both work, and both carry the permalink.
A whole job search as rows - title, link, posted date, budget, job type, experience level, proposal count, skill tags and the full description.
One employer’s whole board as rows - title, location, posted salary range, listing age and Easy Apply. date_posted is an age like 30d+, not a date, and the page says so.
Wholesale offers from 1688.com search as rows - title, price, minimum order quantity, supplier, location and sales figure. Needs your own residential China-exit proxy.
Paste a Pinterest board URL and the pins come back as rows - title, description, outbound link, image, the pin’s own address, the repin count and the account that posted it. One row per pin. Note that the description column is never empty: a pin without one gives you a single space.
Search Home Depot by keyword or URL and the listings come back as rows - name, brand, price, list price, rating, review count, model, SKU, link, image and availability. One row per product, twelve declared columns.
Search Glassdoor by company name or URL and employers come back as rows - rating, review, job and salary counts, industry, size band, headquarters, a profile link and a logo. One row per employer, across twenty-three regional Glassdoor domains.
Search BBB by term, category URL or search URL and the businesses come back as rows - name, BBB letter grade, accreditation, categories, address, phone, email, website, years in business and service area. One row per business, thirty-two declared columns.
Paste a business's bbb.org customer-reviews URL and the reviews come back as rows - business, reviewer, rating, date, the review text and a stable review id. Eight columns, one row per review, with three sorts and an oldest-first option.
Search Reddit by term or paste a reddit.com/search URL, and the posts come back as rows - title, subreddit, author, score, comment count, date and a link. Nine columns, one row per post, with five sorts including comment count.
Paste eBay item IDs, item URLs or a plain search term - all in one box - and listings come back as rows: title, the price as shown and as a number, currency, condition, shipping, images, result position and the seller on item lookups. 23 columns, one row per listing.
Paste the URL of an app's review page on GetApp and the reviews come back as rows - author, rating, headline, review text and date, alongside the app’s overall rating and review count. Ten columns, one row per review, with five sort orders.
Paste Home Depot product URLs and the review section comes back as rows - author, rating, headline, review text and date, alongside the product’s overall rating and review count. Ten columns, one row per review, with six sort orders including photo reviews.
Paste Etsy listing URLs and each one comes back as a row - name, description, price and currency, availability, rating, review count, brand, the identifier columns, images and a link. Seventeen columns, and a per-row status saying how each row went.
Paste a Costco product URL or a category page and the products come back as rows - name, price, currency, availability, brand, sku, mpn, gtin, rating, reviews, image, link and description. Read from the page’s structured data. No proxy of your own to supply.
Paste a Sams Club product URL or a category page and the products come back as rows - name, price, currency, availability, brand, sku, mpn, gtin, rating, reviews, image, link and description. Read from the page’s structured data. No proxy of your own to supply.
Paste a Tesco product URL or a category page and the products come back as rows - name, price, currency, availability, brand, sku, mpn, gtin, rating, reviews, image, link and description. Read from the page’s structured data. No proxy of your own to supply.
Paste a Zoro product URL or a category page and the products come back as rows - name, price, currency, availability, brand, sku, mpn, gtin, rating, reviews, image, link and description. Read from the page’s structured data. No proxy of your own to supply.
Paste a Lowes product URL or a category page and the products come back as rows - name, price, currency, availability, brand, sku, mpn, gtin, rating, reviews, image, link and description. Read from the page’s structured data. Needs a residential proxy of your own.
Type a search term or paste a Tripadvisor search URL and the results come back as rows - name, category, rating, review count, address, link and image. Narrow to hotels, restaurants, things to do or vacation rentals. One row per result.
Watch a Tripadvisor hotel, restaurant or attraction listing on a schedule - once a day, once a week or once a month - with a negative-review threshold you set and optional email alerts. The export records the monitor and its check in 7 columns, not the reviews themselves.
Paste Twitter/X handles or profile URLs and the accounts come back as rows - name, username, bio, avatar and a canonical profile link, plus columns for followers, following, location, website, verified and join date. One row per profile. Six of the twelve have never been filled in any run we hold.
Paste a Quill product URL or a category page and the products come back as rows - name, price, currency, availability, brand, sku, mpn, gtin, rating, reviews, image, link and description. Read from the page’s structured data. No proxy of your own to supply.
Paste a Customink product URL or a category page and the products come back as rows - name, price, currency, availability, brand, sku, mpn, gtin, rating, reviews, image, link and description. Read from the page’s structured data. No proxy of your own to supply.
Type a place or paste a Zillow search URL and the listings come back as rows - address, price, beds, baths, sqft, status, Zillow's zestimate, latitude, longitude, place id, link and image. Filter by For Sale, For Rent or Sold. Needs a residential proxy.
Submit a zillow.com/profile/ URL and every review on that agent profile comes back as a row - author, rating, date, headline, the review text and its classification. Sort by newest or by rating. Needs a residential proxy.
Submit a zillow.com/profile/ URL and the agent comes back as one row - name, brokerage, phone, rating, review count, sales count, sale price range, location, licence, website, screen name, photo and profile URL. Needs a residential proxy.
Submit a zillow.com/profile/ URL and every transaction on that agent's profile comes back as a row - address, price, transaction type, date, status, beds, baths, sqft, property type, which side they represented and the listing URL. Needs a residential proxy.
A full name plus a company domain in, the work email address out - with the pattern it was built from and a status saying what confirmed it: published address, accepted mailbox, catch-all domain or unconfirmed guess.
Any page URL plus the attributes you want, and those attributes come back as the columns. No per-site parser and no fixed schema - for the long tail of sites that will never get a dedicated scraper.
Local business results from Bing as rows - name, category, style, phone, website, full address, rating, latitude, longitude and Bing place id. A plain search is the input. Note: the reviews column never fills.
New York property listings as rows - address with and without the unit, price, building type, beds, baths, size, neighbourhood, ZIP, latitude and longitude. Price is a formatted string. Needs a residential proxy.
Restaurant listings from Uber Eats as rows - name, cuisines, rating, review figure, price band, five-part address, E.164 phone, store link and image. A city URL returns every restaurant on it. No residential proxy needed.
Restaurant listings from Deliveroo as rows - name, cuisines, rating, review figure, price range, split address, phone, link and image. A search URL returns every restaurant on it. Needs a residential proxy.
Restaurant reviews from Deliveroo as rows - author, rating and its scale, review text, date and whether they would order again. Sort by rating or date. Needs a residential proxy.
Apollo people or company search results as rows - name, title, email, phone, company, domain, industry, employees, location and LinkedIn URL. Needs a JSON export of your own Apollo cookies.
Company profiles from the Dutch review platform as rows - name, id, average score out of 10, review count, website, domain, email, telephone and address. Ten of the 26 columns are duplicates.
Classifieds listings as rows - title, asking price, currency, condition, neighbourhood, link, photo and a description preview. Price "-1" means none was posted.
Marketplace products as rows - title, price and currency, condition, seller, rating and review count. Every run export we hold came back empty, so the page documents column names without a verified sample.
Property listings as rows - title, price, currency, address, city and postcode fields, rooms, living and plot area, link, image and description. One row per property.
Vehicle listings as rows - title, price and currency, mileage, year, fuel, gearbox, power, location and seller. Every run export we hold came back empty, so the page documents column names without a verified sample.
Austrian classified listings as rows - title, price, currency, town, postcode and province, condition, every photo URL, and the dealer name, address and phone where the advert has one.
Merchant reviews as rows - the score with the scale it was given on, the recommendation, the text, a full publication timestamp and the merchant reply where one exists.
Captions as timed rows - one row per segment with its text, start time and duration, plus the full transcript in a single field. The video needs captions for there to be anything to return.
Company profiles from organization pages - name, description, website, founding date, headcount, industries, location, rank, operating status and social links. Needs your own residential proxy.
Classifieds listings from any OLX country - title, description, price with the currency it is quoted in, city, region and district as separate columns, the seller and whether they are a business, and every image.
Find companies on Crunchbase by name, domain or URL - matched name, profile link, permalink, short description and entity type. One row per match. Needs your own residential proxy.
Company profiles as rows - company and website, phone, employee and revenue figures, industry, founding, the address split into city, state and country, ticker and logo. Needs a residential proxy.
Shopping reviews as rows - author, rating, date, headline, review body and the source it came from, joined to the item by product id. Country is selectable. Needs your own residential proxy.
Business photos as rows - the query you sent, the business, a direct link to the image file and a caption. Input a /biz/ URL, a slug or an id. Needs your own US residential proxy.
Business reviews as rows - the reviewer and their own location, a five-star rating, the date and the review text, keyed to the business. Input a /biz/ URL, a slug or an id. Needs your own US residential proxy.
Chinese place data as rows - name, address, phone, Baidu’s own category tag, coordinates and a stable place id. Categories and cities are combined into a grid. Needs a China-exit residential proxy.
Local business search as rows - name, rating, review count, categories, price band, phone, address, listing link and image. Every category searched in every location. Needs your own US residential proxy.
A category and a city as a lead table - name, phone, street, categories, rating, hours and website, plus enriched emails with a deliverability verdict, social profiles and details read off the site. 63 columns.
Vacation rental listings as rows - name, price, beds, baths, sleeps, rating, review count, location, listing link and image. Paste a Vrbo search URL; one row per rental. Needs your own residential proxy.
A channel, playlist or keyword as a video table - id, title, link, channel and channel id, views as displayed text and as an exact number, age, running time and thumbnail. Shorts or regular videos, one per run.
Industrial catalogue as rows - name, price, currency, availability, brand, sku, mpn, gtin, rating, reviews, image, link and description. Point it at a product or a whole category. Needs your own residential proxy.
Product catalogue as rows - name, price, currency, availability, brand, sku, mpn, gtin, rating, reviews, image, link and description. Point it at a product, a category or a search. No proxy of your own needed.
An event listing as a row - name, start and end, venue, address, price, currency and organizer, from a URL or a bare event id.
Name, brand, SKU, rating, description and images per product URL. Vistaprint prices by quantity, so the price columns come back empty - the page says so and shows why.
Submit one category URL and get a row per product on it - our run returned 24. Seventeen columns with real prices, the CDW part number and the manufacturer part number kept apart.
Seventeen columns per product URL. Newegg answers with an anti-bot interstitial and every run we hold was blocked - the page says so first, and names the documented requirement.
A search results page becomes ranked rows - eleven columns including the position each listing held. Not the seventeen-column catalogue shape, and the page explains what that costs you.
One collection URL returned 66 rows in our run - a row per size and colour, each with its own SKU and its own stock status. Rating and reviews are empty because the source publishes neither.
One category listing returned 99 priced rows, each with its own S-number. Prices are published openly - and they are per pack, with the quantity in the item name rather than a column.
Seven runs, zero product rows - four blocked and three 404, with a 403 on a direct check. Published as a negative result so you find out before you build around it.
The product name and image came back; the price columns did not. Both the vendor note and the live page agree on why - Target serves prices from a separate protected API.
Five attempts against one real product URL, five blocks, zero rows - and a 403 behind a Cloudflare challenge on a direct check. Published as a negative result.
Untested rather than blocked: neither run we hold ever addressed groupon.com. The page says so, and flags that the site's robots.txt asks general crawlers to skip /search.
One IP address per line, one row back: city, region, country, postcode, coordinates, timezone and network operator. Country and network are solid; the page shows how far the city estimate moved.
The fullest row we hold on this seventeen-column schema - fifteen of seventeen columns filled from one product URL, and every value confirmed against the live listing.
The same URL was blocked and then served eleven minutes later, so blocking here is intermittent. The page also explains why the one row we got describes a search page rather than a product.
Untested rather than blocked: neither run we hold ever addressed autozone.com. What they did return is a status naming the input the service wants - a category or listing URL.
Our catalogue marks it blocked, our export contains no attempt to check that against, and the robots.txt read cleanly. Three sources, no conclusion - the page reports all three.
One row per search result - hotel, score, review count, neighbourhood, room type and price. Ninety rows showed that which columns arrive depends on the presentation the site served, not on the hotels.
The promotional-products storefront, on twenty-three columns. The price is a quantity ladder rather than a single figure - and the URL column points at the supplier, not at WB Mason.
Our catalogue marks it blocked, our export holds no attempt against the site, and our own three requests were each refused at the edge. The page reports all three and what they do not establish.
Eight columns per shopping offer - query, title, price, store, rating, reviews, link and thumbnail. One row per offer, so the same product sold by five merchants is five rows.
Seventeen columns per item URL, with the distributor item number and the manufacturer item number as separate values. Prices sit behind Waxie sign-in, so those columns come back empty.
Seventeen columns per product URL from one of Germany largest general retailers. The listings assemble in the browser, so a plain HTTP fetch returns nothing.
Seventeen columns per product URL - name, description, price twice, currency, availability, brand and both identifiers. The catalogue renders in JavaScript, so a plain HTTP fetch returns nothing.
Four columns per video URL and a per-row status. No comments came back in our runs - not even a count - and the page names the reason rather than hiding it.
Twelve columns per video URL - id, author, caption, timestamp and the engagement counts, with saves and reposts added in July. Our runs used placeholder URLs and the page says so.
Three columns per query - the term, the search tab and a per-row status. No search results came back in our runs and the page says so plainly.
A hashtag as a row - the tag normalised with a leading #, plus a per-row status. The view and video counts did not populate in our runs and the page says so.
A Yahoo results page as rows - position, title, URL and snippet, one row per result, with position returned as a sortable number.
A search phrase as a results table - video id, title, channel, the exact view count, running time, age, link and thumbnail, in the order YouTube returned them. Runs on the free proxy pool.
An office-supplies catalogue as a product table - name, price, currency, availability, brand, sku, mpn, gtin, rating, reviews, image, link and description. Read from the page's own structured data.
Customer reviews from a walmart.com product listing - reviewer, headline, full comment, date, star rating, the verified-purchase flag and the helpful counts, with the Walmart item ID on every row. Six sort orders.
A video's comment section as rows - author, channel id, comment text, likes and reply count. Sort by Top or Newest; replies are opt-in.
Watch company profiles on a schedule and get the new reviews as rows. Daily to quarterly, with a negative-review threshold you set.
Reviews from a Tripadvisor hotel, restaurant or attraction listing - author, rating, date, headline, full review text, the trip type the reviewer selected and the language it was written in.
An MRO catalogue as a product table - name, price, currency, availability, brand, sku, mpn, gtin, rating, reviews, image, link and description, read from the structured data the pages publish. This retailer needs a residential proxy.
Handles or profile URLs in, one row out for each - username, nickname, bio, followers, following, likes, video count, verified badge, avatar and profile URL.
A fashion catalogue as a product table - name, price, currency, availability, brand, sku, mpn, gtin, rating, reviews, image, link and description, read from the structured data the pages publish. Price arrives as text; this retailer needs a residential proxy.
A walmart.com listing as a product row - item id, name, brand, price, currency, rating, review count, stock status and the selling merchant, plus category, description, image and link. The seller column shows who is actually shipping it.
Reviews from a target.com product - author, rating, headline, full review text, date, the verified mark, the helpful count and the reviewer's location. Takes a product URL or a bare TCIN; four sort orders.
Product or category URLs in, one row per product out - name, price, currency, availability, brand, sku, mpn, gtin, rating, reviews, image, link and description. No proxy needed.
App Store listings as rows - app name, developer, rating, review count, pricing label, tagline, listing link and icon. A single app URL runs on the standard pool; search and category pages need a residential connection.
Product URLs in, one row per review out - author, rating, comment, date, helpful votes, the variation bought, the product and images. Filter to comments or media only.
A Shopify storefront as a catalogue table - id, title, handle, description, vendor, type, tags, price, sku, availability and the variant itself, plus ISO timestamps and the store's variants, images and options as JSON. ONE ROW PER VARIANT, read from the store's public product feed.
A product URL or slug in, one row per review out - author, rating, date, the review text and a permalink to each one. Sort by Best, Most Recent, Most Positive or Most Negative.
A foodservice catalogue as a product table - name, price, currency, availability, brand, sku, mpn, gtin, rating, reviews, image, link and description, read from the structured data the pages publish. Start from a search URL, not a part number.
An office catalogue as a product table - name, price, currency, availability, brand, sku, mpn, gtin, rating, reviews, image, link and description, read from the structured data the pages publish. Start from a category URL, not a part number.
Product URLs in, one row per product out - name, brand, price, currency, availability, sku, rating, reviews, images, plus a status column reporting what happened to each request.
Hotels.com guest reviews as rows - reviewer, rating, date, headline and full review text. Four sort orders are set before the run, so a small limit on “lowest guest rating” buys the complaints rather than the whole history.
Hotels.com search results as rows - name, price, rating, review count, location, deal label, link and image. Destination, dates and occupancy ride in the URL you paste, so a set of searches is a set of scenarios.
Expedia guest reviews as rows - reviewer, rating, date, headline and full review text. Takes a hotel URL or the bare numeric hotel id, so a column of ids in a spreadsheet is already a valid input list.
A G2 product URL or just its slug in, one row per review out - title, rating, the full text, and pros and cons as separate columns, alongside reviewer name, company size, date and verified status. Sixteen columns, five sort orders.
Expedia hotel search results as rows - name, price, rating, review count, location, deal label, link and image. Destination, dates and occupancy ride in the URL you paste, and the link column hands the shortlist straight to the reviews scraper.
Paste Etsy listing review URLs and the reviews come back as rows - author, rating, title, review text and date, alongside the listing’s overall rating and review count. Ten columns, one row per review, with four sort orders.
Capterra software reviews as rows - product, author, rating, headline, review text and date, with the product's own overall rating and review count alongside. A tenth column, status, records how each query went, so a run that returns nothing says why.
Brady Industries product pages as rows - name, description, price and currency, availability, brand, stock codes, rating, reviews, images and links. Seventeen columns, the widest in this family, and a status column that records how each request went.
Paste Booking.com hotel URLs and each property comes back as one wide row - the details, geo fields and guest scores, then every room type with its prices, occupancy options, facilities and booking conditions in their own columns. Check-in dates are added automatically.
BestBuy customer reviews as rows - rating, headline, full text, author and ISO date, plus the product SKU and three shopper signals: recommended, verified purchase, and helpful and not-helpful votes kept as separate columns. Takes a product URL or a bare SKU.
A standing watch on Booking.com hotel reviews rather than a one-off export - re-scanned from once a day to once every three months, with a negative threshold you set out of ten and a report emailed to you. Eleven columns per review, including Booking's split of liked and disliked.
Paste Booking.com hotel URLs and the guest reviews come back as rows - reviewer name and country, what they liked and what they disliked in separate columns, alongside the score, the stay dates, the room type and the traveller type. Eleven columns, one row per review, with five sort orders.
The TikTok Shop catalogue as a product table - name, price, currency, availability, brand, sku, mpn, gtin, rating, reviews, image, link and description, read from the structured data the pages publish. The shop side of TikTok, not the feed: no creators, videos or view counts here.
Paste any page URLs, then describe what you want - as a prompt, or as a schema you build field by field with types and required flags. Claude reads each page and the fields you name come back as the columns. No per-site parser, and no fixed column set.
Meetup event listings as rows - name, description, start and end time, venue with coordinates, topics, ticket cap and RSVP tallies, plus the full profile of the group hosting each one. 125 columns, the widest export here; a search term is enough to start.
The comments on a Reddit post as rows - author, comment body, score, created, a permalink to each individual comment and a status column. Seven columns, one row per comment, in six sort orders including Controversial and Q&A. The text itself, not a count of it.
Give it app IDs or Play Store links - movies and books too - pick a scan frequency from daily to quarterly, and set the star rating that counts as negative. Every new review comes back in the same ten columns as the Google Play Reviews Scraper, with the bad ones flagged and emailed to you.
Drop in your list. Out come the deliverable addresses - spam traps, hard bounces, disposable and catch-all addresses filtered out.
Each tool follows the same three steps - so once you've used one, you've used them all.
Free tier activates instantly. No card, no sales call, no setup.
Choose what you want to extract and the filters that matter.
CSV, JSON or Excel - clean, deduped, ready for your workflow.
500 free usages every month - across the whole toolkit. Spend them however you like.
Livescraper brings every data extraction job you need under one roof. Our web scraping services cover six purpose-built tools - the Google Maps Scraper, Google Maps Reviews Scraper, Email Scraper, B2B Lead Generation Database, and more - so you can collect, enrich, and export business data without writing a single line of code.
Traditional data scraping services hand you raw HTML or charge enterprise rates for a custom crawler. Livescraper is different: each scraper is a guided, no-code workflow. You choose what to collect, apply filters like location, category, or rating, preview the output, and download clean CSV or Excel files ready for your CRM, outreach tool, or analysis.
Teams rely on our data scraping services for lead generation, market research, competitor monitoring, and list building. Because every tool shares the same export format and dashboard, you can combine sources - scrape businesses from Maps, pull their reviews, then enrich the list with verified emails - in one connected flow.
There are no setup fees and nothing to maintain. Our infrastructure handles proxies, rate limits, and parsing, so your data arrives structured and deduplicated every time. Start with 500 free rows, no credit card required, and scale with flexible credits only when you need more. Whether you need a one-off export or a repeatable pipeline, Livescraper's web scraping services give you reliable, accurate business data on demand.
For acquisition teams working with unstable public records, Livescraper delivers structured extraction from Maps, reviews, search results, domains, contact pages, and business directories without forcing internal staff into code, proxy handling, or brittle browser routines. Manual collection becomes unnecessary. Across sales, SEO, recruiting, research, and agency operations, our web scraping services convert visible public information into usable datasets for outreach, ranking checks, competitor review, account mapping, and location-based prospecting. Clean inputs reduce downstream dispute risk.
Where source sensitivity, campaign liability, or vendor governance requires tighter evidence trails, Livescraper applies auditable execution parameters across collection, parsing, enrichment, deduplication, export, and user handoff. We verify record structure, field completeness, visible source logic, and export consistency before delivery.
For teams comparing data scraping services with internal research labour, Livescraper provides a narrower operating model built around clean records, repeatable parameters, and lower technical dependency. Fewer moving parts help. Service engagement remains practical, not theatrical. Search criteria, output fields, refresh cadence, and delivery routes are defined before extraction begins, allowing marketers, founders, agencies, and sales operators to act from verified public records with stronger contractual alignment.