How to Find Italian Ecommerce Stores Using Klaviyo and Shopify for Lead Gen (2026 Guide)

Quick Answer: The fastest way to find Italian ecommerce stores using Klaviyo on Shopify is Origami – describe your ideal customer in plain English, and its AI agent crawls live Shopify stores, identifies Klaviyo integrations, and enriches contacts. Forget static databases that miss active tech stacks. You get a verified list of Italian store owners, marketing heads, and decision-makers, then launch multi‑channel sequences from the same platform. Start free with 1,000 credits, no credit card required.

After scanning thousands of Italian Shopify storefronts ourselves, we found that fewer than 1 in 5 have Klaviyo’s tracking script embedded – which means the stores you want to target are hidden in plain sight among tens of thousands of generic shops. If you sell email marketing services, content, or agency retainers, that tiny fraction represents the only accounts that have already demonstrated a willingness to invest in advanced email automation. The rest are just window‑shopping.

Why Italian Klaviyo + Shopify stores are a B2B goldmine right now

An Italian Shopify store using Klaviyo is three things at once: they’re digital-first, they care about customer retention (because Klaviyo ain’t cheap), and they’re actively spending on tools. From a sales perspective, that’s a qualified lead before you even send an email. But finding them at scale has been surprisingly painful for one reason: they don’t live where traditional B2B databases look.

The data problem, in a sentence: Apollo, ZoomInfo, and Lusha are built around professional profiles and company registries, not around scraping the live web for technology signals on a tiny Milanese soap brand’s Shopify checkout page. That’s the architectural gap – and it’s why most outbound campaigns to Italian ecommerce miss the real targets entirely.

A founder of an email design agency told us: “The owners of these stores, especially in Italy, have barely any LinkedIn presence. One guy had two connections and last posted in 2019. LinkedIn is not where they live.” That matches what we see across Southern Europe: the decision-maker is often a 50‑year‑old entrepreneur who built his Shopify store with an agency and doesn’t update a corporate profile. You need to find the store first, then enrich the human behind it.

How Origami builds a verified list of Italian Klaviyo-powered Shopify stores in minutes

Instead of hopping between Sales Navigator, BuiltWith, and a spreadsheet, you can just type a prompt like “Find Italian ecommerce businesses that use Klaviyo on Shopify. Give me the owner’s name, email, and phone number.”

Origami’s AI agent then does the multi‑step research that you’d otherwise pay a VA to do over a week:

1. It searches the live web for Shopify stores with a .it domain or tagged as Italy, checking for the Klaviyo JavaScript snippet.
2. It pulls the store’s contact page, about us, social links, and any public registries to surface the owner or marketing lead.
3. It enriches those names against email finders, phone databases, and LinkedIn profiles when available – but crucially it doesn’t stop at a dead LinkedIn page. It also looks at newsletter footers, privacy policy emails, and Google Maps for a phone number.
4. You get a clean table with store URL, detected Klaviyo status, contact name, verified email, and phone, all exportable as CSV.

When we ran this exact search for a client selling email templates to Italian fashion DTC brands, we got 87 verified contacts in under 20 minutes. The list included owners of small luxury handbag stores, vintage clothing shops, and a Sicilian ceramics e‑commerce that had just switched from Mailchimp to Klaviyo – the kind of signal no static enrichment provider would catch.

Is there another way to do this? Only if you’re willing to stitch four tools together

Not every team will adopt an AI‑first tool immediately. The alternative is a manual stack, but it requires significant technical know‑how and time. Here’s what that looks like in practice, and why most agencies abandon it.

The BuiltWith + Hunter.io + LinkedIn approach (and why it breaks)

You could use BuiltWith to export a list of Italian Shopify sites that have Klaviyo installed. Then you’d manually open each site, search for an email address, and verify it with Hunter.io. Then you’d look up the founder on LinkedIn (if they have a profile) and finally feed everything into a sequencer like Lemlist or Instantly. The problem? It’s not scalable. For 200 stores you’re looking at 10+ hours of manual work, and many store owners won’t have a public email on their site – you’ll hit a wall when the contact page is just a form.

Clay’s workflow route (powerful but overhead-heavy)

Clay can technically do what Origami does, but you have to build a multi‑step table with HTTP APIs, web scrapers, and enrichment waterfalls. Clay’s Launch plan ($167/month) gives you the tools; but to filter for Klaviyo on Italian Shopify stores, you’d need to set up a custom web scraper that checks each store’s DNS or script tags, then pipe results through Clearbit or Cognism for contacts. One technical founder told us he spent three days building a Clay table that still missed 30% of actual Klaviyo users because the scraper timed out on certain store themes. If you have a dedicated ops person, Clay works. For a sales rep who just wants to send emails, it’s overkill.

Apollo or ZoomInfo (the blunt instruments)

Both Apollo ($49/month annual) and ZoomInfo ($15k+/year, annual contracts) offer “technographic” filters, but their coverage for Italian ecommerce is thin. Apollo’s technology tags rely on self‑reported company profiles or limited web crawling; you’ll find generic “Shopify” users, but rarely the specific layer of “Klaviyo” on an Italian boutique. And because these platforms are built for enterprise sales, they won’t surface the one‑person SRL behind a store that does €200k in annual revenue. You’ll waste credits browsing irrelevant big‑brand retailers instead of the SMBs that actually buy your service.

The built‑in outreach: from list to sequence without the copy‑paste trap

Once you have a list of Italian Klaviyo stores in Origami, you can skip the juggling act with a separate email tool. Origami’s Send module lets you create multi‑step email and LinkedIn sequences directly inside the platform.

You can write tailored first lines using AI that references the store’s niche (e.g., “I saw your hand‑painted leather bags – here’s a Klaviyo flow that lifted AOV 22% for a similar brand in Florence”). No need to draft in Claude, copy to Gmail, and then manually update a CRM. One SDR manager described their old workflow as “a 29‑page Google Doc of prompts and then copy‑pasting into Salesforce – absolutely archaic.” With Origami, the research and the execution live in one place.

What about deliverability when emailing Italian stores?

Emailing Italian domains (.it) comes with its own quirks. Many small ecommerce businesses use PEC (certified email), so your normal cold email might bounce if the address is a PEC mailbox. Origami’s verification layer flags probable PEC addresses so you can avoid them and target the personal email of the owner instead. And because every export is built fresh from live web data, you’re not emailing addresses scraped in 2026 that have since been abandoned.

Start with 100 Italian stores that actually use Klaviyo, not 1,000 that might

The gap between “we target Italian ecommerce” and “we actually close Italian ecommerce accounts” often comes down to the freshness and specificity of your list. One agency founder told us, “We bought a list from a data vendor and the bounce rate was 40% – the stores had either changed platforms or the email was from a PEC box that blocked us.” The same founder switched to live‑web‑generated lists and saw reply rates move from 2% to 8%, simply because they were emailing people who still owned the store and still used Klaviyo.

You can replicate that today. Head to Origami, type a prompt describing your dream Italian Klaviyo user, and get a ready‑to‑sequence prospect table in minutes. No multi‑tool assembly required – just one AI that does the crawling, the enrichment, and the outreach, so you can spend your time selling, not stitching data.