Shopify Store Finder
Shopify Store Finder
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Find Shopify stores by keyword, niche, location, and popularity filters. Get a curated list with URLs, tags, and brief summaries for faster market research.
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Discover Store Data Faster with ThunderbitUse Thunderbit to scrape Shopify sites and directories quickly, then extract structured fields with minimal setup. Automate collection across pages and subpages while you browse.
Install fromChrome Web Store
Discover Store Data Faster with Thunderbit
Collect Shopify store names, URLs, categories, and tags from directories, search results, and niche lists using Thunderbit’s AI web scraper. Scrape paginated pages, follow subpages for richer details, and extract data from PDFs, docs, and images into a clean table.
After extraction, have Thunderbit summarize, categorize, and format fields for analysis, then export to Google Sheets, Airtable, or Notion. Keep research current by scheduling recurring scrapes and re-running workflows without code.
How to Find Shopify Stores Using Thunderbit
STEP 1Download and InstallDownload and install the Thunderbit Chrome Extension from the Thunderbit Chrome Extension Download Page. Once installed, log in or create a free account to get started.
STEP 2Open ExtensionOpen the Thunderbit Chrome Extension, then go to the Shopify Store Finder tool and select the "Find Shopify Stores" tab. Enter your search criteria: add keywords (such as product type or theme), choose a niche/category, and optionally provide a location. Refine the results by selecting a popularity filter, a recent activity filter, and the number of stores to return.
STEP 3Click the Find Shopify Stores ButtonClick the "Find Shopify Stores" button to generate a table of matching Shopify-based stores. Review the output rows, which typically include store name, URL, description, tags, and any available signals such as popularity or recent activity. Export the table to Excel, Google Sheets, Airtable, or Notion, or download it as CSV or JSON.
Learn how to find Shopify stores by niche, location, and popularity signals
Discover Shopify stores with keyword and niche filters
Shopify Store Finder helps you generate a targeted list of Shopify-based online stores using keywords and a selected niche or category. It’s built for marketers, ecommerce operators, and founders who need real examples of stores to study, partner with, or benchmark. Instead of manually searching and opening dozens of tabs, you enter your criteria and get a structured list with store names, URLs, descriptions, and tags.
Refine results with location, popularity, and recent activity
Narrow your research by adding a city, state, or country, then optionally prioritize stores using popularity and recent activity signals when available. This is useful when you want stores in a specific market, or when you want to focus on brands that appear to be gaining traction or staying active. The result is a cleaner shortlist that better matches your go-to-market, competitive set, or outreach goals.
Research competitors and trends for ecommerce strategy
Use the output to map competitors in a niche, spot common product angles, and identify patterns in positioning, merchandising, and branding. Ecommerce teams can build a swipe file of store examples, track how categories are evolving, and validate demand signals by comparing multiple stores side by side. Agencies and consultants can also use the list to qualify prospects and prepare more relevant audits and pitches.
Build lead lists and export store data into your workflow
Turn the store list into a working dataset for outreach, partnerships, or supplier research. With Thunderbit, you can take the URLs and scrape additional details from each store using subpage scraping, then export the table to Excel, Google Sheets, Airtable, or Notion. This helps teams move from discovery to action by keeping research, enrichment, and sharing in a single, structured workflow.
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What users say about Thunderbit
Taryn W.Growth Strategist@Thunderbit changed how I run competitor research. I click 'AI Suggest Fields,' and it builds a clean table across paginated results—no coding, no CSS. Huge time-saver when analyzing product data from long-tail marketplaces.
Miles T.Sales Development ConsultantI use Thunderbit to grab emails and phone numbers from directories. It extracts clean contact info in one click, and exporting to Sheets or Notion takes seconds. No extra setup, no coding—just usable data ready to work with.
Rhea C.E-commerce AnalystThunderbit helps me monitor SKU data across multiple pages. I scrape the listings, then use Subpage Scraping to pull full product specs, pricing, reviews, and stock. The AI organizes everything into columns I define.
Cassian B.Real Estate AdvisorThunderbit's Scheduled Scraper makes real estate tracking easier. I describe the interval in plain English, and it automatically pulls updated listings, prices, and links without touching the setup again. Simple and very practical.
Dorian B.Content & SEO SpecialistI use Thunderbit's Field AI Prompts to clean and tag scraped blog content. It extracts titles, authors, and even suggests categories. Works great across dynamic sites and subpages—perfect for building structured SEO datasets.
Lina K.Marketplace Operations LeadWe track SKUs from niche stores using Thunderbit. Cloud Scraping handles 50 pages at a time, and for login-required sites, we switch to browser mode. It’s fast, flexible, and doesn’t need ongoing maintenance or manual edits.
Jorge F.Inbound Sales ManagerThunderbit’s AI Autofill is a lifesaver. After scraping contact info, I use it to fill lead forms directly in my browser. I just select the tab, and it fills everything using the scraped row. No manual input needed.
Alina D.Freelance ResearcherI rely on Thunderbit for extracting data from PDFs, image-based sites, and infinite scroll pages. It handles messy formats with AI and delivers ready-to-export tables I can send to Google Sheets or Airtable in seconds.
Taryn W.Growth Strategist@Thunderbit changed how I run competitor research. I click 'AI Suggest Fields,' and it builds a clean table across paginated results—no coding, no CSS. Huge time-saver when analyzing product data from long-tail marketplaces.
Miles T.Sales Development ConsultantI use Thunderbit to grab emails and phone numbers from directories. It extracts clean contact info in one click, and exporting to Sheets or Notion takes seconds. No extra setup, no coding—just usable data ready to work with.
Rhea C.E-commerce AnalystThunderbit helps me monitor SKU data across multiple pages. I scrape the listings, then use Subpage Scraping to pull full product specs, pricing, reviews, and stock. The AI organizes everything into columns I define.
Cassian B.Real Estate AdvisorThunderbit's Scheduled Scraper makes real estate tracking easier. I describe the interval in plain English, and it automatically pulls updated listings, prices, and links without touching the setup again. Simple and very practical.
Dorian B.Content & SEO SpecialistI use Thunderbit's Field AI Prompts to clean and tag scraped blog content. It extracts titles, authors, and even suggests categories. Works great across dynamic sites and subpages—perfect for building structured SEO datasets.
Lina K.Marketplace Operations LeadWe track SKUs from niche stores using Thunderbit. Cloud Scraping handles 50 pages at a time, and for login-required sites, we switch to browser mode. It’s fast, flexible, and doesn’t need ongoing maintenance or manual edits.
Jorge F.Inbound Sales ManagerThunderbit’s AI Autofill is a lifesaver. After scraping contact info, I use it to fill lead forms directly in my browser. I just select the tab, and it fills everything using the scraped row. No manual input needed.
Alina D.Freelance ResearcherI rely on Thunderbit for extracting data from PDFs, image-based sites, and infinite scroll pages. It handles messy formats with AI and delivers ready-to-export tables I can send to Google Sheets or Airtable in seconds.
Frequently Asked Questions
Extract Data using AI
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