Who Are Lookalike Audiences? A Beginner-Friendly Guide to Who Uses and Benefits from Them

Who they are

Lookalike audiences are not individual people with a label, but rather algorithmically identified groups of users who resemble a chosen seed audience. The seed audience might be a list of past purchasers, newsletter subscribers, website visitors, or any set of users a business uses to define its ideal customer profile. Advertising platforms analyze attributes and behaviors from the seed, then locate other users who exhibit similar signals.

Who creates them

Marketers and media buyers typically create lookalike audiences using tools provided by ad platforms such as Meta (Facebook), Google, LinkedIn, TikTok and others. Creation can be done directly within the ad platform’s interface or by integrating customer data via a CRM, data management platform, or pixel tracking. Agencies, consultants, and in-house digital teams all have a role in building the right seed audiences and configuring lookalikes.

Who uses them

• Small and medium businesses looking to scale acquisition cost-effectively, such as an online retailer expanding beyond repeat buyers.
• Enterprise marketers aiming to broaden reach for top-of-funnel campaigns while retaining quality leads.
• Ecommerce, SaaS, subscription services, and B2B companies seeking new customers similar to their best existing customers.
• Agencies and performance marketers optimizing media buys across platforms.

Who benefits

Companies that have a clear, high-quality seed audience benefit most. For example, an e-commerce brand with a verified list of repeat purchasers or high-lifetime-value customers can use lookalikes to find similar shoppers, increasing conversion rates while lowering acquisition costs. Non-profits and political campaigns also use lookalikes to reach supporters who mirror existing donors or volunteers.

Who should be cautious

Businesses without enough seed data or with poor-quality customer lists may see limited results. Similarly, industries with small niche audiences or those subject to strict privacy regulations need to be careful in how they prepare and upload data. In some cases, legal teams should vet customer lists before using them for lookalike modeling.

Real-world example

A boutique furniture retailer has 3,000 repeat customers who spend above $300 per order. The marketing team uploads a hashed customer list to an ad platform, selects that list as the seed, and creates a lookalike audience set to 1% similarity within their country. The campaign reaches people with similar online behaviors and purchase likelihoods, producing a higher return on ad spend than broad targeting.

Practical tips on who should handle lookalikes

• Assign a marketer or analyst to own data hygiene—ensure emails and IDs are clean and normalized.
• Let a performance marketer or media buyer configure audience sizes and campaign tests.
• Involve privacy and compliance teams when uploading customer data, especially in regions with GDPR or CCPA rules.

Common mistakes by people creating lookalikes

• Using a seed audience that is too small or unrepresentative (results in poor matches).
• Uploading unclean or outdated data (hashed emails that don’t match platform requirements).
• Failing to segment seeds by value—mixing one-time buyers with high-LTV customers can dilute results.

Summary

Lookalike audiences are a tool created and used by marketers, agencies, and platforms to find new prospects who resemble an existing valuable customer group. They work best when owned by cross-functional teams that combine clean data, thoughtful segmentation, and media buying expertise. For beginners, the most important 'who' decisions are: who owns your seed data, who will create the lookalike on the platform, and who measures the campaign performance.