Use case
Build a targeted list of online brands to sell to, segmented by product category, ecommerce platform, and the apps they run, with the right contact and a validated email on every row.
You sell something that only fits a certain kind of online brand: a Shopify app, a fulfillment service, a creative retainer, a subscription tool. A blanket export of "ecommerce companies" is useless to you, because most of those stores are on the wrong platform, in the wrong category, or missing the exact app that would make your pitch land. And even when you find the right brands, you are stuck emailing a generic support inbox instead of the founder or the person who owns marketing.
Start from the store, not the person. Pull a universe of brands, narrow it by category, platform, and installed tech, then resolve a named contact at each one and validate the email before you send. Every step feeds the next and exports to the same CSV.
Run a live pull of online stores in the category you sell into and export each brand with its store URL, product category, and the platform it runs on. This is your starting universe of DTC and ecommerce brands.
Query a standing database of 14M online stores instead of scraping fresh each time. Filter by category and platform and export the matches for any campaign, with unlimited queries.
Search stores by the technology they have installed: a specific Shopify app, a reviews or subscriptions widget, an email platform, a payment provider. Build a list of brands that already run something adjacent to what you sell.
Once you have the target brands, turn an Apollo.io search into a full contact list of the founders and marketing leaders at those companies, with no per-run cap on how many you export.
For any contact you have a name and domain for but no address, return a verified business email so the row is ready to send. You only pay for the ones that are found.
Sweep the finished brand list for deliverability before it ships, so bounces and spam traps never reach your sending domain.
Wire the full toolset into your AI client and build a scoped brand list from a plain-language brief, from store universe to validated contacts, in one pass.
A good brand list is built in layers. Each filter removes the stores that will never buy, so by the end you are talking only to brands that fit, using an opener that references something specific about them.
Say you sell a retention tool and your best-fit customer is a beauty brand on Shopify that already sells on subscription, so the concept needs no explaining. Here is the whole build, brief to send-ready file.
Query the ecommerce store database, or run the Store Leads Scraper ($0.0039 per lead), for beauty and skincare stores on Shopify. That gives you every fitting brand with its store URL and platform, one row each, before you narrow any further.
Run the tech-stack lookup ($4.99 per technology) to keep only the stores with a subscriptions app installed. Now every brand on the list is one that already thinks in recurring revenue, which is your entire pitch.
Feed the target companies into the Apollo Scraper ($0.0039 per lead), or query the B2B contact database by title and company, to attach the founder or the growth lead to each brand instead of a support inbox.
Where a contact has no email, run the Email Finder ($0.05 per email found (FREE if not found)) on the name and domain, then push the whole file through the Email Validator ($0.0072 per email) so only live, deliverable addresses remain.
Export one CSV: brand, store URL, platform, the app you filtered on, contact name, title, and a verified email per row. Load it straight into your sending tool, and every opener can name the exact app the brand already runs.
Every brand list on ScraperCity is built through our platform, so we can see how the sellers who get replies put their lists together.