Find brands by storefront,
stack and momentum.
Search online retail brands by the platform and apps detected on their store, by the campaigns they are running, by what their customers complain about publicly, by the monthly traffic their site pulls. Retriever combines 30+ connected APIs with the live web. Each brand carries the store detail or complaint that qualified it and a named contact.
Brands on a given platform, 10 to 100 staff, running active Meta campaigns│
What you can search for in online retail
- Brands whose store was translated into a new language
- Brands named in Reddit threads complaining about delivery times
- Brands with more than 50,000 Instagram followers and no reviews on site
- Brands whose store runs an app you would replace
- Brands hiring in logistics or customer service this quarter
- Brands whose monthly traffic has been climbing for two quarters
- Brands that added a loyalty programme this year
See it qualify e-commerce brands
Store stack and apps, meta and Google campaigns, customer complaints. One signal per tab, and every row carries the sentence that qualified it.
brands on a platform
Platform detected, campaigns running
Brands on a given platform, 10 to 100 staff, running active Meta campaigns
Describe the leads to search for...
Brands on the platform, advertising
| Score | Company | Domain | What qualified it | Decision maker | Country | People |
|---|---|---|---|---|---|---|
| Searching | ||||||
Illustrative example, fictional e-commerce brands. A real run shows where store stack and apps was read, and names a contact you can write to.
Which signals qualify e-commerce brands?
| Signal | What it tells you | Where it is read |
|---|---|---|
| Store stack and apps | Platform, installed apps, analytics, loyalty and review tools, all detected on the store itself | The store site and its detected stack |
| Meta and Google campaigns | The creatives running, the markets targeted, the intensity of acquisition | Google and Meta ad libraries |
| Customer complaints | Delivery, service, quality. The exact pain, in their customers own words, quotable in a first message | Public threads, comments and reviews |
| Site audience | Monthly visits and traffic history. The real size of a store, invisible in headcount. Best effort, not on every row | Public web traffic estimates |
| Instagram and creators | Followers, posting rhythm, and the creators in their niche for influence programmes | Public profiles and posts |
| Site reading | Catalogue size, delivery promise, about page, loyalty programme, markets and currencies offered | The store site, page by page |
| Hiring and growth | Online retail, logistics and customer service roles. Separates an established brand from an opportunistic store | Job posts and team size over time |
| Markets and languages | Store versions by language, a signal of internationalisation under way | The store site, page by page |
What a qualified lead looks like here
A brand on the platform you integrate with, running active Meta campaigns, whose customers complain publicly about the exact problem you solve. Three signals crossed on the same brand, each one quoted from where it was read.
Why most brand lists are wrong
Dropshipping stores carry the same technical signature as a real brand. Headcount, hiring and domain age separate an established brand from an opportunistic store, and Retriever reads all three before keeping the company.
Who you get on every row
The founder under fifty people, the online retail or operations lead above that. Several candidates are ranked and the best one is kept, with the reason.
- The brand, its domain and its monthly traffic where available
- The quote that qualified it, with the thread or page it came from
- The decision maker, with verified email and LinkedIn profile
- Store platform and apps, campaigns running, markets, review themes
- Any extra column you ask for, researched brand by brand
Not a database subscription. A research agent.
Retriever
- Where answers come from
- 30+ connected APIs, plus the live web at search time: the store site and its detected stack, google and Meta ad libraries
- What you can ask
- "brands whose customers complain publicly about the problem you solve", or any criterion you can phrase
- Freshness
- What each one shows today: store stack and apps, meta and Google campaigns, customer complaints
- Proof
- Every match comes with the quote and source that qualified it
Static filtering
- Where answers come from
- One dataset, refreshed on its own schedule
- What you can ask
- The fields the provider ships: industry, size, location
- Freshness
- What it looked like at the last refresh
- Proof
- You trust the filter
Questions about finding e-commerce brands
How do I find brands with the exact problem I solve?
Their customers say it publicly. Retriever reads threads, comments and reviews, keeps the brands where the complaint matches what you fix, and puts the quote on the row so your first message writes itself.
Can I search brands by the apps running on their store?
Yes. Platform, installed apps, analytics, loyalty and review tools are all detectable on the store itself. That is the clearest integration and replacement signal in this market.
How do I avoid dropshipping stores?
They carry the same technical signature as a real brand. Headcount, hiring and domain age separate them, and all three are on the row.
What does Retriever return for each brand?
The brand with its store platform and apps, its monthly traffic where available, the campaigns it runs, the markets it sells in, the complaints from its customers, and a decision maker with verified email.
Can I search e-commerce brands by country, region or city?
Yes, and for online brands the shipping geography matters as much as the registered office. Ask for brands selling into a given country, or brands incorporated there. Retriever reads the storefront, its shipping pages and the campaigns they run locally.
How is Retriever different from filtering a database?
Instead of filtering a static database, Retriever reads the live web for e-commerce brands: store stack and apps, meta and Google campaigns, customer complaints. That is how "brands whose customers complain publicly about the problem you solve" becomes a search, and why every row arrives with the line that proves it.