Investment
Source and screen e-commerce acquisition targets
For Aggregators, private equity and M&A advisors
The problem
Proprietary deal flow in e-commerce means finding businesses that are not for sale yet. Brokered listings are competitive by definition and priced accordingly.
How the data solves it
Screen the population on the characteristics of a good target: an established domain, a substantial catalogue, a professional technology stack, international reach, and no signals of decline.
The filter set this maps to
Every field below exists in the shop schema. This is the query, not an illustration.
- Domain age
- > 3 years
- Products
- 100–5,000
- Shop active
- yes
- Status
- live
Build it
Four steps to this list
Every column named here exists in the schema, and the request below runs as written.
- 1Set age >= 3 for an established domain.
- 2Add products between 100 and 5,000 for a real but acquirable catalogue.
- 3Add shop_active = yes and recently_down = no to exclude dead and unstable storefronts.
- 4Export theme, apps and lh_perf as first-pass technical due diligence.
The same query through the API
POST this to /api/v1/search for a count, or /api/v1/rows for the shops themselves.
{
"filters": [
{
"kind": "numeric",
"col": "age",
"op": "gte",
"min": 3
},
{
"kind": "numeric",
"col": "products",
"op": "between",
"min": 100,
"max": 5000
},
{
"kind": "dropdown",
"col": "shop_active",
"values": [
"yes"
]
},
{
"kind": "dropdown",
"col": "recently_down",
"values": [
"no"
]
}
]
}Playbook
What to do once you have the list
A list is not a campaign. These are the three things that decide whether it converts.
Screen the population, not a listing
Brokered deals are competitive by definition. Screening 8.9 million shops on consistent criteria gives you targets before anyone lists them.
Liveness is a real filter
shop_active and recently_down separate trading businesses from abandoned domains — indistinguishable in a plain domain list, and the difference between a target and a waste of a week.
Technical debt is visible early
Theme age, app sprawl and a poor performance score are diligence findings you can see at sourcing stage rather than in week six.
Outcome
What you end up with
Proprietary target lists built before anything is listed
Consistent screening criteria applied across the whole population
Technical due-diligence signals available at sourcing stage
Questions
Investment: frequently asked
Can I see whether a shop is still trading?
Yes. Shop status classifies storefronts as live, down, password-locked or coming soon, a status-reason field records why a failing shop failed, and a tri-state active flag sits alongside them. That is what separates a working shop from an abandoned domain, which look identical in a plain domain list.
Is revenue data available?
No, and no honest source has it for private shops. Catalogue size, technology investment, international reach and performance are observable proxies; we do not publish revenue estimates dressed up as fact.
What can this tell me that a broker listing cannot?
It tells you about shops that are not for sale. A listing is a shop that has already decided to sell, priced accordingly and shown to everyone. Querying the population lets you build a thesis first, by category, country, catalogue size and trading age, and then approach owners directly before anything is listed.
Which fields help me judge whether a shop is a real business?
Domain age and registration date show how long it has traded, shop active and status confirm the storefront is live rather than abandoned, catalogue depth shows the operation behind it, and international shipping and languages show reach. Performance and SEO scores then tell you how much unrealised improvement sits in the asset.
Does the dataset include revenue or traffic?
No, and no dataset built from public storefronts honestly can. It describes what a shop is and how it is built, not what it earns. Use it to build and qualify a target list, then get financials from the owner in diligence. The value here is finding the right conversations, not pricing them.
Start finding better e-commerce leads today
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