Three tools come up almost every time a team describes how they prospect into e-commerce. A store directory like StoreLeads. A technology lookup like BuiltWith. A general B2B database like Apollo. Each is good at the slice it was built for. None of them was built for the whole job, which is why so many teams pay for two or three of them and still start Monday in a spreadsheet.
ShopLeads comes from the team behind 1,000+ interested D2C replies, and that work kept coming back to the same three questions, in the same sitting:
- Which of these stores actually sell their own products?
- Who decides there, and will the email land?
- Why would they care this week?
Hold those three up against each tool and the gaps are easy to see. None of what follows is a knock on the tools.
A store directory answers half of the first question
A store directory tells you which domains run a store, on what platform and with which apps. That is a real head start.
Two things are usually missing: a name and a date. Contact data at the store level tends to mean a public inbox, and info@ is a triage queue read by whoever is on it that morning. And a directory of storefronts is wider than your market. Industrial suppliers, resellers and other businesses that are not D2C brands sit in the same export, so deciding which rows are brands you can sell to is a human afternoon, every time. We wrote the row-by-row version of this on ShopLeads vs StoreLeads.
A technology lookup answers a question of evidence
A technology lookup tells you what a site is running. If your pitch depends on a platform or an app, that evidence is genuinely useful.
The trouble starts when a stack is used to qualify a company. Agencies run their clients' stacks. Resellers, marketplaces, suppliers and half-finished test stores all show up with the same detections as the brands you want. And an install is not an event: a tool that has been in place for three years is not a reason to write today.
So after the export you still have four jobs. Qualify the store. Find the person who runs email, ads or operations. Check that the mailbox accepts mail. Find something dated worth mentioning. That is the week, every week. The comparison is on ShopLeads vs BuiltWith.
A general database is the opposite trade
A general B2B database is built around people, which is the right shape for question two, and it covers every market. Covering every market is exactly why it struggles with this one.
"Retail" and "consumer goods" hold the brand you want, the marketplace that resells it, the dropshipper that copies it and the supplier behind it. An industry or platform filter cannot separate them, because the thing that separates them is whether the store sells its own products, which you only learn by reading the store. Title filters have the same problem: a filter tuned to a 400-person company does not describe a 12-person brand where the founder decides on email, ads and fulfilment. More on ShopLeads vs Apollo.
The stitched setup, and what it really costs
Put those three gaps together and you get the setup we hear described most often: stores from one tool, people from a second, a verifier for the third. Three bills, three exports, a join on domain in a spreadsheet, and a list that is weeks old before anyone writes to it.
The subscriptions are not the expensive part. The expensive part is that no two tools agree on what a qualified store is, so that definition ends up living in the head of whoever built the sheet. When they are on holiday, the list stops.
Three things, one search
That is what we built instead. ShopLeads runs one pipeline: we start from e-commerce platform data, scan each store's own website, check every store with rules and an AI check, then find and verify the people through several contact data providers.
- Stores that sell their own products. Marketplaces, resellers, dropship and print-on-demand stores are filtered out by rules and an AI check, so that work is done before you see the list.
- The people who decide. With a work email and LinkedIn, plus store inboxes and phones. Every email gets a mailbox test, and the status shows next to it: verified, or unconfirmed when the mail server accepts any address or the check could not confirm it.
- A reason to write this week. Signals are dated events: Meta and Google ads, hiring, new leaders, funding, app and tech changes, and product launches. Every event shows its real date, and standing facts are never shown as new. Signals are open on every plan, priced in credits: 10 credits a store on a plan, 20 on the free trial. Pro and Scale include signal unlocks every month.
- The words to write with. Each profiled store comes with a plain-text context block: company story, what it sells, who buys, where it sells, size, tech stack, recent changes and key people.
The pricing follows the same idea. Search, filters and export are free, and credits are spent only when you open a contact. A work email with LinkedIn is 2 credits, a phone with the email and LinkedIn is 5, a store inbox or phone is 1, and you are charged once per person and kind, so a contact you already opened stays open at no charge. The plans and the full credit table are on pricing.
What this does not do
Being the one search for three jobs means being narrow about all three.
- We only cover e-commerce stores that sell their own products. If your buyers are marketplaces, resellers, dropshippers or print-on-demand stores, we filter out exactly who you need.
- We do not report technology market share or cover sites outside e-commerce, so a technology lookup is still the right tool for research questions.
- ShopLeads does not send your email and does not run sequences. Export is free, and there is a REST API and an MCP server, so the contacts land in the tool you already send with.
- Signals are open on every plan and priced in credits: 10 credits a store on a plan, 20 on the free trial. Pro and Scale include signal unlocks every month. Every plan gets the stores, the people and the verified contacts.
- We do not publish other companies' prices or feature lists on these pages, because they change. Check their own sites.
How to test any of this in an afternoon
Every new account starts with a 7-day trial and 500 free credits. A card is needed, nothing is charged until the trial ends, you can cancel before then, and unused free credits end with the trial.
Because search and filters are free, the useful test is not how big the list looks. Build one segment you already sell into, put it next to the list your current tools produce, and then spend the free credits only on people you would genuinely write to. At 2 credits for a work email with LinkedIn, 500 credits is around 250 verified emails.
If what you need is the stores and people in bulk, or a custom data set built to your own fields, that part is not self-serve: enterprise data is priced on what you need, with volume pricing per contact. Book a call.