How to Use Customer Lists to Scale Your Art Store with Meta Ads

Most artists think of their email list as something you use for email marketing. Send a newsletter, announce a new drop, maybe run a sale. That's it.

But your email list - especially your customer list - is also one of the most valuable targeting assets you can feed into Meta ads. When you upload a list of real buyers to Meta, you can suppress them from prospecting campaigns, retarget them with repeat-purchase offers, and most importantly, build Lookalike Audiences that reach people who look just like your best customers.

Here's how to do it, from export to upload to the campaigns you can run.

What You Can Actually Do with a Customer List on Meta

There are two main uses:

Custom Audience from Customer List. Upload your customer emails (and optionally phone numbers, names, and other identifiers). Meta matches them to Facebook and Instagram accounts. The resulting audience can be used directly - to retarget past buyers, exclude existing customers from prospecting, or run win-back campaigns.

Source for Lookalike Audiences. This is the more powerful use. Once Meta has your customer list as a Custom Audience, you can tell Meta: "Find me more people who look like these buyers." That Lookalike Audience goes into your prospecting campaigns, finding cold traffic that shares characteristics with your real customers.

Exporting Your Customer List from Shopify

If your store is on Shopify, exporting customers who've actually purchased is straightforward.

1. Go to Orders in your Shopify admin
2. Click Export (top right)
3. Choose "All orders" or filter by date range
4. Open the CSV in a spreadsheet
5. You want the Email column at minimum. Phone number helps Meta match more accounts

For best results, clean the list before uploading: remove duplicates, strip any rows with missing emails, and make sure there's a clear header row labeled "Email."

If you're using Klaviyo, you can also export segments directly - more on that below.

Uploading to Meta Ads Manager

1. Go to Meta Ads Manager
2. Open the Audiences section (top navigation, under "Tools")
3. Click Create Audience > Custom Audience
4. Choose Customer List
5. Skip the "customer value" column for now (you can add it later for value-based Lookalikes)
6. Upload your CSV
7. Map your columns - Meta will ask which column is email, which is phone, etc.
8. Agree to Meta's data terms and submit

Meta will process the list over the next few hours.

Match Rates: What to Expect

Meta will tell you the match rate after processing - the percentage of emails it was able to connect to a Facebook or Instagram account.

A match rate of 30-60% is normal. This means if you upload 1,000 emails, Meta might match 350-600 of them. That sounds low, but it's enough to work with. People use different emails for shopping than for Facebook; some have deactivated accounts; others have privacy settings that limit matching.

To improve match rates:

• Include phone numbers alongside emails when available
• Include first name, last name, and country (Meta uses all signals together)
• Export from Klaviyo profiles rather than just email addresses - Klaviyo stores more identifiers

Building a Value-Based Customer List

A standard customer list Lookalike treats every buyer equally. A value-based list tells Meta which customers spent the most - and asks it to find more people like your high-spenders.

To build this, add a third column to your CSV: a "Value" column with each customer's lifetime spend. Your top 25% of spenders become a premium seed audience for a high-quality Lookalike.

This takes a bit more work to set up in Shopify (you'll need to filter and sort by total order value), but Artvertise clients who've set this up typically see better Lookalike performance than from flat customer lists. The signal is richer.

Using Klaviyo Segments Instead of a Full Export

If you're running Klaviyo for email, you can export specific segments rather than your full customer list. This lets you get strategic about which audience you're feeding into Meta.

Useful segments to try:

• High-value customers (top 25% by spend)
• Repeat buyers (ordered more than once)
• Engaged subscribers who haven't purchased yet (for a different kind of Lookalike - people who are warm but not yet buyers)

Each of these makes a distinct seed audience, and each Lookalike built from them will behave differently in your campaigns.

Refresh Your List Monthly

Customer lists are static - they don't automatically update when someone makes a new purchase. Set a reminder to re-export and re-upload monthly. This keeps your Custom Audience current and makes sure new buyers are included in your Lookalike seed data.

In Meta, you can update an existing Customer List audience rather than creating a new one each time.

GDPR and Data Privacy Considerations

Before uploading any customer data to Meta, you need to be confident you have appropriate consent. In practice this means:

• Your customers agreed to your privacy policy at checkout, which should disclose that their data may be shared with advertising partners
• You're not uploading data for people who've opted out of marketing communications
• You're using Meta's hashing feature (which anonymises emails before upload) - Meta does this automatically

Meta requires you to agree to their Custom Audience Terms of Service before creating these audiences. Read them. Don't upload data from purchased lists or third parties - only your own customer data from people who've transacted with your store.

The Lookalike Audience to Build First

If you only have time to do one thing from this article: export your full customer list from Shopify, upload it to Meta, and build a 1% Lookalike Audience from it.

This 1% Lookalike is Meta finding the people most similar to your buyers, out of the entire Meta user population. Put it in a prospecting campaign with your best creative, let it run for 7-14 days, and compare its ROAS to your interest-based campaigns.

In our experience, a Lookalike built from a customer list of 500+ real buyers will usually outperform interest targeting once the campaign has enough data to optimise.

Not sure whether your targeting setup is getting the most from your customer data? Artvertise's free audit looks at your full account - audiences, creative, campaign structure, and pixel health - and tells you where the gaps are. Book your free audit here.