When Should You Use Customer Match vs. Lookalike Audiences?

If you’ve built up a solid base of customer data and you’re ready to take your advertising to the next level, you’re probably wondering: when do I use a customer match list and when do I switch into lookalike audiences?

The truth is, both are powerful tools, and when used at the right time, they can transform your ad campaigns.

You’ve got a list of loyal customers, you’ve got website visitors, maybe even phone numbers and email addresses collected from a loyalty program, and you want to figure out the smartest way to use that data to both retain current customers and reach new ones.

Let’s break this down, so you’re confident about using custom audience strategies with the right audience, at the right time.

Understanding Customer Match

Customer Match starts with your first-party data: email addresses, phone numbers, sometimes physical addresses, or app user IDs.

This is your actual customer list: people who have taken action, made a purchase, visited your site, and signed up for your loyalty program.

Because this is data you own, it’s a goldmine for precision.

When you upload this data to your advertising platforms, say your Google Ads account or Facebook Ads Manager, you create a custom audience built directly from your known, engaged users.

Platforms like Google describe their Customer Match offering as using information your customers have shared with you, so you can target ads to those customers and others like them. (Google for Developers)

Why use it?

Because it lets you talk directly to people who already know your brand, already interacted with you, and are therefore more likely to take the next step.

Whether it’s cross-selling, upselling, re-engaging lapsed customers, or promoting specific products to your best customers, customer match lists shine here.

And because you’re working with accurate data from your own customer base, match rates tend to be higher and conversion costs tend to be lower.

But the key is: this approach is best when you have strong first-party data and you want to connect with known users, not just random people.

If your aim is brand awareness or reaching new people, this alone won’t scale as much as you might hope.

Understanding Lookalike Audiences

Once you’ve tapped into your own customer list, it’s natural to ask: “How do I get more people like my best customers?”

That’s where lookalike audiences (or lookalike segments, depending on the platform) come in.

The concept: you feed the ad platform a seed audience (often your custom audience of current customers), and the platform uses that as a model to find “new audiences”, people who share similar characteristics with that seed.

They might behave similarly, have similar interests, or match demographic and other signals the platform considers relevant.

For example, Facebook describes a lookalike audience as a way to reach new people who are likely to be interested because they share similar characteristics to your existing customer base. (Facebook)

In recent years (2025 and beyond) this has become even more important because you cannot rely as heavily on third-party data or cookies.

Instead, you lean on your own first-party data and let algorithms work with that to find “look-alike” users. (Pixis)

What makes lookalike audiences especially valuable?

They allow you to scale.

They allow you to reach new potential customers who resemble your best current customers.

They’re terrific for acquisition, brand awareness, and when your goal is new customer growth rather than just re-engagement.

The Primary Difference

Here’s the simple breakdown:

• Customer Match = a custom audience built from your own customer data (email list, phone numbers, customer list). You’re targeting current customers or people you already know.
• Lookalike Audiences = you’re using the custom audience (or other high-value segment) as the seed, and then expanding outward to new users who share similar characteristics or behaviors.

Customer Match is about precision and known relationships.

Lookalike is about reach, expansion, and finding new people.

And it’s not just about the difference in audience source; it’s about when and why.

You use customer match when you want to deepen relationships, increase loyalty, upsell, or re-engage.

You use lookalike when you want to find new users, grow your customer base, and drive brand awareness.

When to Use Each: Real-World Scenarios

Use Customer Match when:

• You have a clean email list, phone numbers, or CRM of current customers or engaged users, and you want to turn them into repeat buyers.
• You’re promoting a specific product to high-value customers (for example, “If you bought X, you’ll love Y”).
• You’re running retargeting campaigns to those who already visited your website, signed up for your email list, or joined your loyalty program.
• You want higher conversion rates because you’re speaking to warm leads, not cold traffic.
• You want to leverage your first-party data and maintain a strong match rate (the higher the data quality, the better). For example, segmenting your email list by purchase frequency and creating a custom audience for VIPs can improve performance. (Seer Interactive)

Use Lookalike Audiences when:

• You’re looking to bring in new customers, scale your marketing efforts, build brand awareness and find high-intent prospective customers.
• You’ve already had success with your current customers and you want to replicate that success with “new people” who behave like your best users.
• You have a “seed audience” of sufficient size, many platforms suggest at least 1,000 users in the seed to create effective lookalike segments.
• You’re launching an ad campaign where the goal is acquisition, not just retention.
• You want to use the audience expansion feature of platforms like Facebook Ads Manager or Google Ads to target similar behaviors and characteristics.

A concrete example: Suppose you run an online store for high-end party dresses.

You have a strong list of customers (with emails and phone numbers) who have bought from you before.

Use that list via Customer Match to send them exclusive offers or rewards.

Once you’ve done that, build a look-alike audience based on that list to reach new women who have similar characteristics and could become your best customers.

Combining Both for Maximum Impact

You don’t need to pick one or the other.

The smartest marketing strategies use both in tandem.

First, strengthen your foundation with Customer Match, nurture your current customers.

Then use Lookalike Audiences to expand into new territory.

Here’s how you combine them:

1. Upload your customer list (your email list, phone numbers, key high-value customers) and create a custom audience.
2. Segment that list by behaviour, maybe by customer lifetime value, purchase frequency, or product interest. Use this to build your best-performing seed audience.
3. Create your lookalike audience based on that seed. Choose the size carefully: narrower sizes (e.g., 1%) tend to be more accurate; larger sizes reach more people but may reduce similarity.
4. Then run separate campaigns: one retargeting the custom audience, another reaching out to the lookalike audience. Monitor performance, compare conversion rates, customer acquisition costs, and refine accordingly.
5. Make sure you exclude current customers from your acquisition-focused lookalike campaigns. Otherwise you risk paying to fish in a pond where a lot of your current customers already live.

By doing this, you cover both ends of the funnel: re-engaging the right people (customer match) and finding the right new people (lookalike).

That gives you both retention and growth.

Best Practices You Should Follow

To get the best results, here are some time-tested best practices:

• Keep your data clean. Your customer list should have accurate email addresses, phone numbers (if you’re uploading phone numbers), and reflect real users. Better data equals higher match rates.
• Use first-party data wherever possible. This reduces dependence on third-party data (which is increasingly restricted) and aligns with data privacy regulations.
• Segment your data. Don’t just upload a big generic list of “everyone who ever bought.” Break it down by high-value customers, recent purchasers, or frequent buyers. That helps build a stronger seed audience.
• Choose your audience size carefully for lookalike. Smaller percentages (1–2%) will mirror your best customers more closely, but reach fewer people; larger percentages reach more people but may dilute similarity.
• Exclude current customers from acquisition campaigns. If you’re trying to reach new users, make sure your “new prospective audiences” campaign isn’t overlapping with your current customers.
• Update your lists regularly. Stale customer data leads to low match rates and poor performance. Some platforms note that lists older than 540 days need refreshing.
• Use your website visitors and custom segments too. For example, create audiences of recent website visitors using your facebook pixel or analytics tracking, then use them either as custom audiences or seeds for lookalikes.
• Monitor performance metrics: audience size, match rate, conversion rate, customer acquisition cost, customer lifetime value (CLV). These help you determine if your audiences are hitting the mark.
• Respect data privacy and user consent. Whenever you’re uploading email addresses, phone numbers or other user data, ensure you’ve collected it in compliance with privacy laws and platform policies.

Finding the Right Time to Use Each

So how do you know when it’s the “right time” to use customer match vs lookalike?

Here are some cues to guide you:

• If your priority is deepening relationships and increasing value from your current customers → use Customer Match.
• If you have a product for high-value customers and want to replicate that success with new users → build a seed of your high-value customers and create a Lookalike Audience.
• If you’re launching a new marketing effort and you don’t yet have a large list of engaged customers, you may need to build your customer data (via website traffic, email list growth, loyalty program) before lookalikes perform well.
• If you’re seeing performance stagnate in acquisition campaigns, switching to Lookalike Audiences can help you reach new users with similar behaviors to your best customers.
• If your list of current customers is growing and you want to pick up more high-intent prospective customers, now’s a good time to layer both: custom + lookalike.
• If your match rates are low (customer list isn’t matching well), it might be worth focusing first on cleaning your data and improving the custom audience before building a lookalike.

Why Data Quality and Platform Choice Matter

At the heart of this whole discussion lies data.

Whether you’re uploading email addresses, phone numbers, or tracking website visitors via your Facebook pixel or Google Analytics, the quality of your user data determines the quality of your targeting.

If you have incomplete data, mismatched formatting, or no segmentation, your match rates drop and your results suffer.

The ad platforms you’re using matter too.

For example, on Google Ads, “Similar Audiences” (the older term) has been deprecated and replaced by manually-created “Lookalike Segments” for Demand Gen campaigns.

Meanwhile, on Facebook Ads Manager, lookalike audiences remain one of the most powerful ways to reach new customers.

Selecting the right platform, ensuring your tracking (pixel, analytics) is properly configured, and regularly refreshing and segmenting your audience lists are all key to getting the best results.

Putting It All Together

When you think about your marketing efforts, here’s one way to frame it: you have your foundation, your current customers, your email list, your website visitors.

Use that foundation with Customer Match to nurture and engage.

Then you have your expansion strategy, looking for new users who behave like your best customers. That’s when you use lookalike audiences.

Your goal at Brimar Online Marketing is to help you allocate ad spend wisely.

By using these tools at the right moments, you both reduce waste and increase relevance.

You show the right message to the right audience, and you keep moving forward.

So the next time you ask whether to use a customer match list or a lookalike audience, ask yourself:

• Who am I trying to reach? Current customers or new ones?
• What data do I already have? Is it clean, segmented, high-quality?
• What’s the size of my audience list? Do I have enough seed users for a lookalike?
• What’s my goal: retention, upsell, or acquisition and expansion?

Answering these questions will tell you which tool is the right one, and when to switch from one to the other.

At Brimar Online Marketing, we’re here to help you build that connection between your data and your growth.

Whether you’re working on building out your first custom audience or ready to scale with lookalikes, we’ll help you find the right audience, at the right time, with the right strategy.

When you’re ready, let’s dive in, clean up your data, build the segments, and start reaching the people who matter most.

You’ve done the hard work of gathering the customer data, now it’s time to use it to grow.