For ecommerce tools

GTM infrastructure for ecommerce tool startups

Everything you need to qualify an ecommerce brand is on their storefront. The build is a scraping problem, and that is the part most stacks outsource badly.

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The quickest way to waste a month in this market is to buy a list of online stores. Most of them sell nothing. The signal that a brand is worth contacting is operational: how deep the catalog runs, which apps are installed, whether reviews still arrive.

All of that is public and all of it can be read. A table with one row per store, a crawl column for the site, an extraction column for the numbers you care about, then contact lookup on the rows that survived. Each step keeps the page it read.

Who this is for
Seed to Series A companies selling software to ecommerce brands: retention, logistics, merchandising, reviews, subscriptions, or analytics. Four to fifty people.
What it looks like today
Brand lists are sold by the million and are mostly dead stores, dropshippers, and hobby shops. What separates a real brand from noise, catalog depth, installed apps, review volume, is on the storefront and in nobody's database.
What changes
The storefront becomes the qualifier. A crawl reads the platform, the app stack, and the catalog, those numbers become columns, and enrichment runs only after a store proved it is a working business.

Example searches

Ask for it the way you'd say it

Each example is a request in plain words, with what it returns underneath.

  • Real brands, not dead stores

    find stores on this cart platform with more than 500 products and recent reviews

    Catalog depth and review recency land as columns, so an abandoned store is filtered out before you spend on contacts.

  • App stack on the storefront

    which of these brands already run a subscription app and a loyalty app

    A yes or no column per app reads the crawled storefront, so a stack combination is a filter rather than a per store investigation.

  • The person who runs ecommerce

    find the founder or head of ecommerce at each of these brands with a work email

    Small brands answer from the founder's own address, so one accurate contact per store beats 3 generic ones. A managed finder bills on a hit. Email checks bill even on a miss, including guessed addresses on rows without a LinkedIn URL.

Plays

Three motions you can run this week

Each one is a chain of OXYGEN primitives: the same hosted objects your workspace already has, composed.

  • Storefront qualification

    A list where every store proved it is an operating business first.

    1. Tables
    2. Workflows
    3. Records
    1. 1Crawl each storefront and extract catalog size, installed apps, and review activity.
    2. 2Filter down to the operating brands, then promote them into accounts.
    oxygen tools run

  • Catch an app install early

    Brands whose storefront started carrying an app you compete with, caught on the next crawl.

    1. Tables
    2. Workflows
    3. Records
    1. 1Put the crawl column on a weekly full refresh so every target store is read again on the same cadence.
    2. 2Read each store's crawl cell history and work only the brands whose app stack moved.
    oxygen tables schedule set

  • One brand, one thread

    Founder, ecommerce lead, and agency replies all on one account.

    1. Sequences
    2. Messages
    3. Records
    1. 1Enroll the named contacts and let a reply from any of them stop the rest.
    2. 2Label the answers in the shared inbox, then log the outcome on the brand.
    oxygen inbox tag

Capabilities

What you get

  • The storefront as your database

    Crawling and extraction are first class columns, so the facts that qualify a brand come from the store itself rather than from a resold list.

  • Detection plus crawl

    Platform and app detection narrows the market, and a crawl of the store fills in the operating numbers detection cannot see from outside.

  • Spend only on survivors

    Contact lookups run after the filter, so the expensive step only touches brands that already proved they are worth an email.

  • Free tables, metered crawling

    Tables, workflows, and sequence drafts cost nothing to set up. Crawling runs and contact lookups draw credits, and each run you start carries a credit ceiling.

Instead of

The stack this replaces

Native, on one contract and one credit balance, not another tab wired to the last one.

Data sources

Data sources and CRM connections

  • LeadMagic

    Scans a store's website for its cart platform, such as Shopify or WooCommerce, and the marketing and chat tools it loads.

  • Firecrawl

    Site crawling and page extraction for catalog depth, policies, app widgets, and the numbers a store publishes itself.

  • Blitz API

    Finds the founder or ecommerce lead behind a brand rather than a support address.

Use managed credits where available, or connect a supported provider key on an eligible paid plan. Your provider bills its calls; OXYGEN adds a per-call platform fee. Signed-in CRM connections such as HubSpot have no per-call fee. Connected sending accounts reserve monthly credits. See pricing and supported integrations.

Limits

Where this stops

  • Detection and crawling see the public storefront only. A headless build or a custom stack can hide what a store runs, so an empty app column means unknown rather than absent.

FAQ

Questions people ask first

How do we filter out dead stores?
With operating evidence rather than a flag. Catalog size, recent reviews, and an active app stack together separate a working brand from a page that was launched and abandoned two years ago.
Is scraping reliable enough to build a list on?
It is when the runs are inspectable. Each crawl is a durable run with its pages, outputs, and failures recorded, so a row that came back empty is visible instead of silently wrong.
Can we track when a brand installs a competitor app?
Yes, by crawling the storefront again rather than waiting on a feed. A weekly full refresh of the crawl column re-reads each target store, the old value stays visible in that cell's change history, and only the brands whose app stack moved need a human. The cadence you choose is the resolution you get.
Who do we actually email at a small brand?
The founder, most of the time, and a head of ecommerce or retention once the brand is larger. The lookup asks for the owner of the decision and records the title it resolved.
Do agencies count as accounts here?
They can, and they behave differently, so keep them in their own table. One agency conversation can carry twenty brands, which is worth tracking as a relationship rather than as a single row.
What does a crawl of ten thousand stores cost?
Preview it before it runs. Crawling is metered per page read, every run you start carries a credit ceiling, and sampling 100 stores is the sensible way to size the rest of the job.

Put your GTM motion on one stack

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