Pick one of 4,000+ technologies. See every online store and popular website running it, with country, niche, size, age and authority on each row. Filter it down, then export.
Technology lookup tools usually stop at a domain list. Every row here carries the context you need to decide whether to call.
Every store and popular site in the database that runs the technology you typed.
Who they are, what they sell, how big they are and what else they run.
Export the filtered list and load it where your team works.
The whole flow happens in one screen of the dashboard. There is nothing to install and no code to write, and the same steps work for every one of the 4,000+ technologies.
Start typing and pick from 4,000+ suggestions.
The full list of sites using it appears in a table.
Country, vertical, price, products, age, authority, language.
By popularity, catalog size, price or authority.
CSV, Excel or PDF, up to your plan's row limit.
Popular tools have very large install bases. These filters cut them to the slice you can actually sell to.
| Filter | Use it to | Example |
|---|---|---|
| Country | Match your sales territory or language | Only US and Canada |
| Vertical / category | Focus on industries you know | Home & Garden |
| Subcategory | Get very specific | Outdoor furniture |
| Average price | Target premium or budget stores | Above $100 per item |
| Number of products | Pick a store size that fits your pricing | 100 to 2,000 products |
| Domain age | Find new stores or established ones | Under 5 years |
| Authority | Prioritize stores with strong link profiles | Top quartile |
| Popularity rank | Focus on high-traffic sites | Top 200,000 |
| Language | Match your sales team's languages | German, French |
| Keyword | Combine technology with a product word | "coffee" |
Add filters until the list is small enough that a person would read every row. That is usually the right list to send.
The same search answers very different business questions depending on who runs it.
Every site with that chat widget.
Stores collecting product reviews.
Stores investing in retention.
Sites earning from display ads.
Sites on a given server stack.
Sites built with a specific builder.
Stores offering financing at checkout.
Sites watching user behavior closely.
Some technologies live mostly on stores. Others live everywhere. Choose the pool that matches your buyer.
The ecommerce pool, with store-specific fields.
The wider web, classified into 440 IAB categories.
Before you build a list, you can read the install base as a market report.
The total row count is the tool's reach in the database.
Filter country by country to see where a tool is strong.
Category ratios show where a tool over-indexes.
The domain-age profile shows if new sites still adopt it.
The technology market analytics page shows ratio charts, age profiles and popularity tiers.
People respond when you show you understand their setup. The row already tells you most of what you need.
The AI cold email generator writes a first message for any row, using the site and your product description.
Every technology family has one filter that cuts noise fastest. Start with it, then add the rest.
| Technology family | Pair it with | Why |
|---|---|---|
| Email and SMS marketing | Number of products | Bigger catalogs send more campaigns and pay for higher tiers. |
| Reviews and UGC | Category | Reviews matter most in fashion, beauty and home. |
| Live chat and helpdesk | Average price | High-ticket shoppers ask more questions before they buy. |
| Subscriptions | Category | Consumables like food, pet and beauty dominate. |
| Pay-later and financing | Average price | Financing only matters above a certain basket size. |
| Shipping and returns | Country | Carriers and rules are local. |
| Translation and currency | Language | Shows which stores sell across borders. |
| Analytics and testing | Popularity rank | Testing only pays off with enough traffic. |
| Ad pixels and tag managers | Domain age | Young stores rely heavily on paid traffic. |
| Ad monetization scripts | Category | Ad rates vary sharply by niche. |
| Page builders and themes | Domain age | Older sites are due for a redesign. |
| Servers and hosting | Popularity rank | Infrastructure needs scale with traffic. |
Illustrative scenarios showing how different teams turn one lookup into a campaign. Notice that each one uses a different sort order. The sort decides who gets contacted first, so it matters as much as the filters.
Wants mid-size stores that already handle a lot of support.
Wants stores due for a rebuild in home and garden.
Wants high-ticket stores on a rival financing option.
An exported list splits cleanly by the fields already on each row. No more arguments about who owns which account.
The right list at the wrong time still fails. These moments lift reply rates.
Stores buy tools two to three months ahead of their busiest weeks.
Users re-evaluate when their bill goes up.
New stores are still choosing their stack.
Growing catalogs outgrow starter tools.
A store that just added a complementary tool is in buying mode.
New languages or currencies mean new needs.
We see the same mistakes across new accounts every month. All six are easy to avoid once you know them, and fixing them usually doubles the useful share of a list.
The biggest list is rarely the best one. Filter first, export second.
Users who just installed a rival will not move for months. Look at older domains first.
Your pricing fits a band of store sizes. Stay inside it.
Switch, integrate and add-on lists each need their own opener.
Install bases change monthly. Schedule a refresh.
Users of complementary tools are often warmer than users of rivals.
Each one uses the install base for a different job. The search is identical; what changes is which filters they add and what they do with the export afterwards.
Rival users for displacement and partner users for integration-led selling.
Stores on the platform and apps your product extends.
Sites on the platforms you build for, in the verticals you know.
Publishers on a given ad network, ready for yield conversations.
Sites on a server or CDN you can beat on price or speed.
Install bases as a proxy for vendor traction and market share.
Browser extensions answer "what does this one site run". A database answers "who runs this". Most teams use both: the extension while browsing, the database when building a campaign.
| Need | Browser extension | LeadsQuantum |
|---|---|---|
| Stack of one site | Yes | Yes |
| All sites using a tool | No | Yes, across 6M+ sites |
| Filter by country and vertical | No | Yes |
| Store size and price level | No | Yes |
| Likely next tool | No | Yes, with the reason |
| Export a list | No | CSV, Excel, PDF |
Technology lookups are part of both plans, Advanced and Enterprise.
For one-off exports above your plan limit, write to [email protected] with the technology and filters.
Type the technology name in the search box and pick it from the suggestions. The table fills with every site running it.
More than 4,000, from store platforms and apps to analytics, advertising and server software.
Yes. The five million most popular domains are included alongside more than a million stores.
Yes, along with vertical, price level, product count, domain age, authority, popularity and language.
Store records include public contact information where available, and it is included in exports.
Either plan. Both include technology lookups.
Run one lookup per technology and merge the exports. For market comparisons, the analytics view puts several tools on one chart.
A lookup shows current users of a tool. The recommender shows sites likely to adopt it next.
Yes. Expand any row to see its full stack and the tools it is likely to add.
Write to [email protected] with the name and website of the technology.
Outreach rules differ by country. Follow the email and privacy laws that apply to you and to each recipient.
Re-run the same technology and filters any time. Most teams refresh monthly and work new rows first.
Export both lookups and match the domains in Excel. The overlap is often your warmest segment.
Search the leading products in the category one by one, then combine. The recommender also works at the level of your own product's category.
Results appear in the table within seconds. Each lookup and each page of results counts as a search on your plan.
Start with the filtered row count. Plan for the share your team can personally research and contact in a month.
For most small teams that is a few hundred rows, refreshed monthly, rather than thousands at once.
No. Lookups use a search box, dropdown filters and an export button. If you can use a spreadsheet, you can use the platform.
Technology lookups, the AI recommender and AI cold email are included in both plans, from $999 per year.