Adidas, Uber, Airbnb, Walmart and Sephora have achieved growth in customer base and spike in ad effectiveness with lookalike audience targeting. The process lets a brand dissect its customers to spot common characteristics and reel-in previously unreachable high-quality customers.
Airbnb, the leading online marketplace for short-term homestays, collects a wide range of user data, including travel history, search history, and social media activity. This data lets the company identify what its most valuable guests have in common; for instance, figures like age, gender, location, and travel preferences.
This targeting method used in digital advertising to reach new potential customers sharing identical behaviours with an existing customer base is known as Lookalike Audience.
Using advertising platforms like Facebook and Google, Airbnb can utilise this data to create a lookalike audience. This lets the company increase the likelihood that these people will book a stay on their platform.
For example, if Airbnb’s data analysis shows that their most valuable guests tend to be females aged 25-34 who frequently travel to major cities, they can create a lookalike audience of females in the same age bracket who have shown an interest in city travel. This audience is more likely to engage with Airbnb’s advertising and book a stay on their platform than a general audience that is not targeted similarly.
How does this work?
The idea is to have a group of customers who are highly engaged with the brand or have a high lifetime value, and use their characteristics to find other people likely to have similar behaviours and interests.
First, a company identifies a group of customers meeting certain criteria, such as making frequent purchases or spending a certain amount of time on the website. This data is then used for analysis techniques like machine learning algorithms to identify the common characteristics of these customers, such as demographic data, behavioural patterns, or interests.
Next, the company uses these characteristics to find people similar to the original group of customers. This is typically done through a third-party platform, such as Facebook or Google, which uses its data and algorithms to match the characteristics of the original group of customers to a larger population of potential customers.
The resulting “lookalike” audience is a group of people who share characteristics similar to the original group of customers and are, therefore, more likely to engage with the company’s marketing efforts or become customers themselves.
Gains For Brands
Some of the bigger brands are using the tool to add new customers. Uber, the ride-hailing company, uses lookalike audience targeting to find people similar to its existing riders. By targeting these people with personalised ads and promotions, Uber has attracted new customers and increased its market share. Others include the following:
- Sephora, the beauty retailer, uses lookalike audience targeting to find identical customers with respect to purchasing behaviour and interests. By targeting these people with relevant ads and promotions, Sephora has been able to increase its sales and drive customer loyalty.
- Adidas checks shared interests and demographics. The brand has increased its market share and brand awareness by targeting these people with personalised ads.
- Walmart, the retail giant, uses purchasing behaviour and interests to spot its lookalike audience and consequently hike sales and customer loyalty.
Lookalike audience targeting is a powerful tool that can help marketers achieve several key goals in their advertising campaigns. It helps marketers expand their reach beyond their existing customer base. By finding new people who share similar characteristics and behaviours with their current customers, they can reach a wider audience and attract new potential customers.
When marketers get a set of people similar to their existing customers, they are more likely to find people interested in their products or services. This can increase engagement and ultimately lead to more conversions and sales.
By targeting people who are more likely to be interested in their products or services, they can increase click-through rates, decrease bounce rates, improve the performance of their ads, and ultimately improve the overall effectiveness of their campaigns.
The targeting also allows marketers to create highly personalised and relevant ads that speak directly to their audience’s interests and needs. This increases the effectiveness of their advertising campaigns and improves the likelihood of conversions. Overall, they can identify common customer patterns and traits using data-driven analysis and modelling techniques and then find new people who match those characteristics in the wider population.
When you create your Lookalike Audience, you can use a percentage range to choose how closely you want your new audience to match your source audience. The size you choose depends on your goals. Smaller percentages more closely match your source audience, but larger percentages create a bigger, broader audience.
- You can create up to 500 Lookalike Audiences from a single source audience.
- Your source audience must contain at least 100 people from a single country to use it as the basis for a Lookalike Audience.
- Lookalike Audiences use your ad set locations and only include people from those locations.