1st Party Lookalike (1P LAL) modeling is revolutionising the way brands extend their audience reach. By identifying users who resemble a brand’s high-value customers, this advanced technique ensures targeted marketing that boosts conversion rates and ROI. In this blog, we will explore the 1P Lookalike feature offered by Zeotap CDP and demonstrate how it can effectively help brands extend their reach and enhance their marketing strategies.
1P Lookalike offered by Zeotap CDP
1P Lookalike modeling enhances traditional segmentation by finding users who behave similarly to your existing 1st party (1P) users. 1P lookalike is an extension for brands segmented users, where this extension provides the brands, more 1st party users that behave like the segmented 1P users.
This feature is especially interesting for companies looking to monetise their 1P data through selling ad placements on their own website. With lookalike modeling, the marketer can acquire additional customers who behave similarly to their high-value customers. For example, if one group of users frequently clicks on ads, 1P LAL identifies other users likely to do the same.
How it works
Here is how Zeotap CDP’s Lookalike 1P feature works
- Data Segmentation and Clustering: We use clustering algorithms to identify “twins” in your user base. This information is then stored in a Lookalike graph, updated weekly.
- Profile Attribute Analysis: We then evaluate all user profile attributes to calculate the closest “twins.”
- Customisation Options: You can choose between high accuracy (fewer but more precise matches) or high scale (larger volume but less precision) based on your campaign goals.
- Deployment Flexibility: Finally, you can opt to send 1P lookalike users along with the original seed set or only the extended users to your chosen channels, optimising reach and targeting.
Understanding how a leading Retailer extended their Audience Reach with 1P Lookalike
Joe, the head of performance marketing at a leading retailer, wanted to stray away from traditional marketing methods by targeting new users similar to their existing audience. Joe was looking to extend its audience from users who frequently purchase high-end fashion items to similar new users. By utilising 1P LAL, the retailer was able to identify and target new users who exhibit similar purchasing behaviours to their existing high-value customers.
In order to optimize ad spend, the retailer excluded existing customers from ad campaigns and instead target lookalike users. This strategy increases the chances of converting new users and ensures that the ad budget is used efficiently to attract potential customers.
Additionally, the retailer was able to monetise its 1P data by selling ad placements on its website, targeting users who behave like their high-value customers. This enabled the retailer to generate additional revenue from its existing customer data.
1P Lookalike modeling is a powerful tool for brands looking to maximize their marketing efforts. By leveraging this advanced technique, marketers can ensure their campaigns are more effective, compliant with privacy regulations, and capable of reaching a broader audience. For more information feel free to request a demo here. We’re excited to address any inquiries you may have.
