Sign UpSign In
Sign InSign Up

Lookalike Modeling: What You Need to Know

Lookalike modeling: What you need to know


In today's digital landscape, lookalike modeling has emerged as a powerful tool for marketers seeking to optimize their targeting strategies. By leveraging the potential of data-driven insights, businesses can identify audiences similar to their existing customers, leading to improved customer acquisition, engagement, and overall business growth.


Understanding Lookalike Modeling

Lookalike modeling is a technique that involves identifying and targeting audiences who share similar attributes and characteristics to your current customer base. By analyzing data, such as demographics, purchase behavior, and interests, businesses can uncover valuable insights and create audience segments that closely resemble their best customers. Lookalike models help marketers increase reach by creating larger audiences that “look like” a smaller audience. Typically the smaller audience has known, deterministic attributes based on 1st party data or trusted 3rd party data. The larger look-alike audience has similar attributes but the known confidence level of those attributes is typically less than the smaller audience. 


The Process of Lookalike Modeling

1. Data Collection: To initiate the lookalike modeling process, businesses gather relevant data points about their existing customers, such as age, location, interests, and purchasing history. Best practices for creating look-alike models start with a trusted data set, typically first party CRM data a marketer knows. Skydeo uses a variety of deterministic attributes to create high value seed audiences which can then be expanded by look-alike modeling. Attributes include: apps owned, locations history, age, gender, income, purchase history and device information.

2. Data Analysis: Statistical algorithms analyze the collected data to identify patterns and similarities among customers, allowing businesses to uncover key attributes.

3. Audience Segmentation: Based on the identified attributes, businesses segment their audience into groups with shared characteristics, forming the foundation for lookalike modeling.

4. Lookalike Model Creation: Using advanced machine learning algorithms, businesses build lookalike models that match the attributes of their ideal customers, enabling targeted outreach to similar audiences.

5. Targeting and Outreach: Armed with the lookalike model, businesses can effectively target and engage with audiences that exhibit traits similar to their existing customers, maximizing the chances of conversions and engagement.


Benefits of Lookalike Modeling

Increased Reach: Lookalike modeling expands the target audience beyond existing customers, diving into untapped potential and reaching new prospects.

Higher Conversion Rates: By focusing on audiences similar to the best customers, businesses can optimize their marketing efforts and increase the likelihood of conversions.

Cost Efficiency: Lookalike modeling ensures that marketing spend is directed towards audiences with a higher probability of conversion, maximizing the return on investment.

Improved Personalization: By tailoring marketing messages to specific customer segments identified through lookalike modeling, businesses can enhance personalization and relevance, resonating with their target audience.

Lookalike Modeling in Action:

For example, a marketer may want to target people who use the McDonalds mobile app or who have visited a McDonalds in the last 30 days. That audience in Skydeo yields a finite number of approximately 2.3 million people. We can expand reach by creating a look-alike model based on apps and places with high affinity to the original McDonald’s audience to 7-8 million people. This would offer a higher degree of accurate targeting than just targeting all fast food buyers. By loosening the targeting criteria a marketer can expand the scale and reach of their campaigns intelligently.


The issue with look-alike modeling is that the desire for increased reach sacrifices targeting. Look-alike modeling, specifically in Facebook, can be over used to the extent the campaign isn’t really targeted at all. In the case of Facebook, marketers don’t really know which attributes are being used to expand the look-alike model. Skydeo enables marketers to have similar functionality to Facebook look-alike modeling but for use anywhere they want to advertise. Skydeo’s use of deterministic attributes enables marketers to create exact-alike audiences based on similar apps installed, competitive apps or places visited as well as the standard age, gender and income metrics.

You can use Skydeo’s deterministic mobile data attributes, machine learning and either your 1st Party data or Skydeo seeds to drive exact-alike prospect lists for activation. 


Lookalike modeling revolutionizes the way businesses target their audience, enabling them to unlock new growth opportunities and maximize their marketing efforts. By leveraging the power of data-driven insights and partnering with Skydeo, businesses can harness the potential of lookalike modeling to drive customer acquisition, improve engagement, and achieve tangible business results.


For more information about lookalike modeling, check out this resource  or our blog "3 Ways to Target Your Audience Better As a Retailer" And if you’re ready to take your campaigns to the next level with precise ad targeting, contact us today or request a free quote on any audience segments


Follow us on all your favorite platforms to stay updated with the latest news and events!





And don’t forget to subscribe to our monthly segment release to get the latest info on audience segments that should be on your radar each month!



Get Started Today

Supercharge your campaigns with targeted segments