Define Your Search Criteria
Tell AllyHub the product, the city and radius, and any limits — a price range, a condition, keywords. Plain sentences work; nothing to install.
Pull the Facebook Marketplace listings for a product in your area into one price table — sorted, filtered, ready to compare.
Say the product, the place, and your price filters — get a comparable Marketplace table back.
Tell AllyHub the product, the city and radius, and any limits — a price range, a condition, keywords. Plain sentences work; nothing to install.
It reads the matching Marketplace results, taking each listing’s title, price, condition, location, date, photos, and shown seller name into a row — sorted by price, recency, or distance.
Download the set, send it to analysis for the price map, or save it as a Playbook so a weekly run tells you what’s new and what’s moved.
Marketplace hides its prices in plain sight — every listing is a separate tap, and there’s no view that shows a whole category at once. AllyHub pulls the matches into one table, so a scattered grid becomes a price picture you can read.
Each matching listing comes back as a row — price, condition, location, date, and the seller name shown on it — so the grid you’d have scrolled becomes one sortable table.
New, used, and for-parts sell at different prices — AllyHub keeps them apart, so you see the real spread for each condition tier instead of one blended average that hides it.
Marketplace is local — name a city and a radius and AllyHub pulls only the listings within it, so the prices you compare are the ones a buyer near you would actually see.
The filters run while it collects, not after — a price ceiling, a condition, a keyword, and only the listings that clear them ever land in the set.
From the set AllyHub reads the floor, the median, and the ceiling for that product and place, and flags the listings sitting well below the typical price — the ones worth a closer look.
The finished table drops to CSV, JSON, or Excel — clean columns, ready to pivot or load straight into whatever tool you work in.
Resellers, retail buyers, renovation sourcers, and price analysts — anyone who needs the whole Marketplace price picture, not one listing at a time.
The pain: the deals go to whoever spots the underpriced listing first, and you can’t refresh a category grid fast enough by hand. Pull the whole category, sorted low to high with the below-typical listings flagged, and move on the ones worth grabbing before the next buyer scrolls to them.
The pain: you price against retail and ignore the secondary market, where your customers are quietly checking what the same thing costs used. Benchmark the Marketplace prices in your category and location so your pricing and sourcing account for what buyers actually pay peer-to-peer.
The pain: furnishing a flip or a rental means sourcing appliances and materials across a dozen categories and towns, and checking each by hand eats the margin. Scrape the listings across your categories and radius at once and find the bulk buys and price drops without living in the app.
The pain: secondary-market pricing is where real demand shows, but it’s trapped in a scroll no spreadsheet can hold. Build a clean dataset of Marketplace prices by category and region and study the spread, the regional gaps, and how used prices track the new ones.
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Answers on pulling Marketplace listings, filtering by place and price, and what AllyHub does and doesn’t touch.
A Facebook Marketplace scraper collects the public listings for a product — prices, conditions, locations, and dates — into a structured dataset instead of a grid you scroll. AllyHub pulls them filtered to your place and price range, and can re-run the search on a schedule.
Yes — your first Marketplace pull, with the everyday fields, is free. Sweeping a whole category, comparing several locations, scheduled re-runs, and the price-map analysis sit on the paid plans.
It reads the public Marketplace listings a visitor can see without logging in, and takes the seller name shown on each — not anyone’s private profile or contact details. It works from the aggregate price data only; staying within Facebook’s terms when you use it is your side of that.
Yes — set a city and radius, a price band, a condition, and a keyword, and AllyHub applies all of it while it collects. You get back only the listings that fit, so there’s no sorting a giant dump by hand.
Not from one run — a single scrape is a snapshot of today’s asking prices. Save it as a Playbook and re-run it weekly, and the changes show up: new listings, price drops, and where the median is drifting for your category.
A browser extension scrapes whatever’s on the screen and leaves you to configure proxies and paginate by hand; a single-purpose actor does one thing and re-bills every month. AllyHub takes a plain-language search, filters at the source, and saves the run as a Playbook that gets faster every time — none of the proxy upkeep is yours.