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What Is Lookalike Targeting?

Lookalike Targeting (sometimes referred to as Lookalike Audiences) is a advertising strategy that aims to identify and target individuals or audiences who are similar to a brand’s existing or ideal customers. This technique leverages data analysis and algorithms to find potential leads or new customers, who share similar characteristics, behaviors, interests, or preferences with the brand’s current customer base.

How Does Lookalike Targeting Work In Combination With Other Ad Targeting Strategies?

Where demographic targeting focuses on specific traits such as age, location, or gender, and psychographic targeting delves into deeper aspects like values and lifestyle choices, lookalike targeting considers everything in combination. It goes beyond the surface-level characteristics of a group to focus on what makes them similar rather than what makes them different.

For example, it’s reasonable to assume that a skincare brand’s ideal audience is primarily women between the ages of 25-40. However, with lookalike audience, the focus of custom audience would not just be on gender and age but also on other factors such similar characteristics such as income level, shopping habits, interests in self-care or beauty products, and so on. This allows the brand to expand its reach and potentially find a new audience that may not have been identified through traditional, broad demographic targeting.

Lookalike Audience Percentages Explained

Lookalike audiences are often defined by their similarity percentage, which refers to the level of resemblance between the existing customers and the targeted lookalike audience. This percentage can range from 1% to 10%, with a higher percentage indicating a closer match between the existing customer data and target lookalike audiences.

For example, if a brand has an existing customer base of mostly millennial females aged 25-34 who are interested in fashion and beauty, a 1% lookalike audience would include individuals who share the majority of those characteristics. A 5% lookalike+ audience size would include a wider pool of individuals with some similarities but not as many as the 1% lookalike audiences audience. And a 10% lookalike+ audience size would include an even larger pool of individuals with fewer similarities.

How Does Lookalike Targeting Work?

Lookalike audiences uses a data-driven approach to identify potential new customers who share similar traits as the brand’s current customer data or ideal customer base. The process involves three main steps:

1. Building a Seed Audience

In this step, the brand first needs to define its seed audience, which is typically its existing customers or those individuals who have already shown interest in the brand’s products or services. For example, if the brand is a beauty company, its seed audience could be its current customers who have purchased skincare products in the past. Or, it could also include individuals or fans who have visited the brand’s website or social media pages.

In any case, the more comprehensive a seed audience is, the better. It will be used as a reference point to identify similar traits in other users and potential customers.

2. Conducting Data Analysis

Once the seed audience is determined, the next step involves the source audience and analyzing their data to identify common characteristics, behaviors, and interests. This process can include factors such as demographics (age, gender), location, purchase history, or browsing behavior. Businesses source information on custom audience for analysis from various platforms, such as CRM databases, social media insights, and website visitors’ analytics.

It’s recommended to use a combination of quantitative and qualitative data to connect to the custom audience and get a well-rounded view of the seed audience. Quantitative data, such as website traffic, visitors and sales figures, can provide concrete numbers and trends. Qualitative data from surveys or focus groups can provide insights into the reasoning behind customer behavior.

3. Finding Similar Individuals

Using the power of data analysis and algorithms, lookalike targeting tools search for potential customers, visitors and users who match the identified traits of the seed audience. These individuals are then grouped into segments based on their level of similarity to the seed audience, with the top segment being the closest match to source audience.

The top-matching audience isn’t always necessarily the best target audience for a business. Lookalike audiences can just as easily be used as metrics to contrast against the seed audience, helping businesses understand where their current audience may be lacking and what areas they could potentially expand into.


What Are the Benefits of Lookalike Targeting?

Lookalike targeting delivers value to advertising campaigns in more ways than one. See a breakdown of the three biggest benefits that come with using this strategy below.

Increased Targeting Efficiency

One advantage of lookalike targeting is its efficiency – instead of spending time and resources on broad targeting, brands can focus their efforts and budget on a specific group of potential new customers, users who are more likely to convert.

Time Savings

The cost and time-savings aspect plays into another advantage, which is scalability. As data and algorithms improve, it becomes easier to identify ideal customers and create lookalike campaigns for larger audiences, that are larger and more accurate. This allows brands to reach a wider audience without sacrificing personalization.

Economized Spending and Higher ROI

It should go without saying that better-focused ad spending and increased efficiency have the potential to create and ultimately lead to a higher return on investment (ROI). By targeting ads to potential customers larger audiences who are more likely to convert, brands can see a higher conversion rate and potentially lower cost per acquisition (CPA) compared to broad targeting methods.

What to Know Before Trying Lookalike Targeting

With the above data points and potential benefits being stated, it’s important for brands to keep in mind that lookalike targeting is not foolproof. Note the following data points for potential drawbacks and limitations before using this strategy in your own campaign.

There’s No Guarantee of Accuracy

The tools used to create and execute lookalike strategy rely on data and algorithms, which means that there is always a chance for error. Furthermore, different platforms have different methods of sourcing information to create them for lookalike demographics and audiences. This variation in data sources can lead to differences in the accuracy of targeting across platforms.

Customer Behavior Can Change

Changes in customer behavior or preferences may also affect the effectiveness and cost of lookalike targeting. For example, if a brand’s ideal customer shifts to a different demographic or platform, advertising goals for the previously effective lookalike target audience may no longer be relevant.

Potential for Overexposure

Another potential limitation is oversaturation and fatigue among the targeted ad or audience. If a lookalike ad or audience is constantly bombarded with ads from multiple brands, it may become less responsive and more likely to tune out ad, or ignore those ads.



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