Users similar to existing customers.
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A lookalike audience is a group of potential customers identified by an advertising platform because their characteristics or behavior resemble those of an existing audience, such as previous customers or website visitors. Advertisers use lookalike audiences to reach new people who may be interested in their products or services.
Lookalike audiences are commonly associated with platforms such as Meta Ads, although similar audience-expansion features are available on other advertising platforms under different names.
How Does a Lookalike Audience Work?
Choose a source audience: Use existing customers, purchasers, app users, or other eligible audience data.
Analyze patterns: The advertising platform identifies useful similarities within the source audience.
Find similar people: The platform uses those patterns and available signals to identify potential customers.
Run advertising campaigns: Advertisers show relevant ads to the newly identified audience.
Measure performance: Track conversions, cost per acquisition (CPA), and return on ad spend (ROAS).
Benefits of Lookalike Audiences
Helps businesses reach potential new customers.
Expands campaigns beyond existing customers.
Can improve audience relevance and targeting efficiency.
Supports customer acquisition and brand awareness.
Helps advertisers scale successful campaigns.
Example in Ecommerce
A Shopify jewellery store has 5,000 existing customers who have purchased gold-plated necklaces and earrings. The store creates a source audience from eligible customer data and uses a lookalike audience feature to find new people with similar characteristics.
The store then runs ads promoting its jewellery collections and measures how many new customers purchase.
Lookalike Audience vs. Retargeting
Lookalike audience: Targets new people who resemble an existing audience.
Retargeting: Targets people who have already interacted with a business, such as visiting its website or viewing products.
In short: A lookalike audience helps advertisers find new potential customers who resemble their existing customers, making it useful for expanding paid advertising campaigns. Results are not guaranteed, so performance should be measured and customer-data privacy requirements followed.