Digital Marketing
How to Use Data for Meta Ads Audience Segmentation
Enhance your Meta Ads performance with data-driven audience segmentation strategies for better targeting and higher conversions.
By Mason Boroff
Mar 21, 2025
To get the best results from your Meta Ads, focus on data-driven audience segmentation. This means dividing your target audience into smaller groups based on shared traits or behaviors. Here's why it matters:
Better targeting: Reach the right people with the right message.
Lower costs: Spend your budget more effectively.
Higher conversions: Personalize ads to boost results.
Scalable campaigns: Use insights to grow your reach.
Use tools like first-party data, Meta Pixel, and CRM data to create precise audience segments. Follow these steps:
Collect data: Use customer purchase history, email engagement, website activity, and survey feedback.
Build Custom Audiences: Upload clean customer lists and refine them using behavior and demographics.
Test and optimize: Compare audience segments by tracking metrics like CTR, CPA, and ROAS.
Expand with Lookalike Audiences: Target people similar to your best customers.
Track performance regularly and adjust your strategy to maximize results. By leveraging these techniques, you can create campaigns that drive higher ROAS and better engagement.
Data Types for Meta Ads Audiences
Understanding the right data categories is key to precise targeting and better campaign results. Here’s a breakdown of the main types you should focus on:
First-Party Data
This is the data you collect directly from your customers, such as:
Purchase history from your website or store
Email engagement metrics, including open rates and clicks
Website activity, like page views and time spent on your site
Customer service interactions, such as support tickets
Account registration details and user profiles
This type of data gives you valuable insight into customer preferences and behaviors, making it an essential resource for building targeted audience segments.
Meta Pixel Data
The Meta Pixel tracks user actions on your website, helping you understand how visitors interact with your content. It collects data like:
Page views and navigation patterns
Product views and shopping cart activity
Form submissions and lead captures
Purchase confirmations and transaction values
Custom events tailored to your business goals
To get the most out of Meta Pixel, place it on key pages of your site and set up custom events that align with your conversion objectives. Pair this data with your first-party insights for even sharper targeting.
Other Useful Data Sources
Expand your audience insights by incorporating:
CRM Data: Segment customers based on purchase frequency, total lifetime value, service history, or account status.
Email Marketing Lists: Use details like engagement levels, content preferences, how long they’ve been subscribed, and response rates.
Survey and Feedback Data: Create segments using customer input on:
Product preferences
Brand perception
Buying intentions
Satisfaction scores
Building Custom Audiences: Step by Step
Upload and Manage First-Party Data
Start by preparing a CSV file containing key customer details like emails, phone numbers, or IDs. Make sure it aligns with Meta's formatting and privacy guidelines.
Go to Audiences in Meta Ads Manager.
Click on Create a Custom Audience.
Select Customer List as your source.
Upload your CSV file.
Match your data fields to Meta’s categories.
Tip: Clean your data beforehand by removing duplicates and outdated entries. This helps improve match rates and ensures more accurate targeting.
After uploading, fine-tune your audience by applying filters based on behavior and demographics.
Set Up Behavior and Demographic Targeting
Once your customer list is ready, enhance your audience segments with specific filters.
Behavioral Targeting:
Track website activity patterns.
Analyze purchase frequency and average order value.
Consider time since their last purchase.
Look at engagement with particular product categories.
Demographic Filters:
Define age ranges.
Target specific locations (cities, states, or regions).
Use income levels or education as criteria.
Include job titles or industries if relevant.
For example, you can create a premium group by isolating high-value customers who spent over $500 in the last 90 days.
Test and Improve Audience Groups
Systematic testing can help you optimize audience performance. Here’s how:
Create 3–4 audience segments to compare.
Track key metrics like:
Cost per acquisition (CPA)
Click-through rate (CTR)
Conversion rate
Return on ad spend (ROAS)
Review results every 2–3 weeks. Adjust or remove segments that underperform.
This process ensures your audience groups are consistently optimized for better results.
Using Lookalike Audiences
Lookalike audiences help you reach people who resemble your best customers, expanding your potential audience based on existing insights.
Choose Your Base Audience
The foundation of effective lookalike audiences is solid source data from your top-performing customers. Start by identifying a base audience that reflects your goals.
Here are some examples:
High-value customers: People who spent over $1,000 in the last six months.
Frequent buyers: Customers who made three or more purchases in 90 days.
Engaged website visitors: Users who viewed five or more pages and spent over three minutes on your site.
For best results, aim for a source audience of 1,000 to 50,000 users. Smaller groups may limit reach, while overly large ones could reduce precision.
Tips for selecting your base audience:
Use recent data (ideally from the last 180 days).
Exclude inactive customers.
Focus on users who match your target market.
Include conversion data when possible.
Prioritize consistent purchase behaviors.
With a well-chosen base, you can create lookalike audiences that deliver better targeting and performance.
Improve Lookalike Results
To get the most out of your lookalike audiences, adjust their size and test different ranges. Platforms like Meta allow you to create lookalikes on a 1-10% scale, where 1% represents the closest match to your source audience.
Here’s how to structure your testing:
1. Start with a narrow focus
Begin with a 1% lookalike audience. This group is the most similar to your top customers, which often results in higher conversion rates, though with a smaller reach.
2. Add targeting layers
Refine your audience by incorporating filters such as:
Location
Age range
Interests
Device type
3. Expand carefully
Once you’ve tested the 1% group, try broader audiences (2–3%) and monitor metrics like cost per acquisition (CPA) and return on ad spend (ROAS).
You can also create multiple lookalike audiences based on metrics like customer lifetime value, average order value, or purchase frequency. Regularly review and adjust these segments to keep them aligned with your overall strategy.
Track and Improve Campaign Results
Keep a close eye on your Meta Ads and make adjustments to boost ROAS and overall performance.
Key Metrics to Watch
Focus on these metrics to evaluate how well your audience segments are performing:
Click-Through Rate (CTR)
Cost Per Acquisition (CPA)
Return on Ad Spend (ROAS)
Audience Overlap
Frequency
Experiment with Audience Groups
Use A/B testing to fine-tune your audience targeting:
1. Set up controlled tests
Create ad sets that are identical except for the audience you're targeting. This ensures you're isolating the impact of the audience variable.
2. Track performance metrics
Let your tests run for 2-3 weeks and keep an eye on these key indicators:
Conversion rates for each audience
Cost differences across segments
Engagement trends
Purchase behavior patterns
3. Log your results
Document which audience characteristics deliver the best outcomes. Use this data to sharpen your future campaigns and stay responsive to market changes.
Schedule Regular Updates
Organize your optimization process with a structured review schedule:
1. Weekly checks: Review basic metrics like CTR, CPA, and ROAS. Adjust bids and budgets as needed.
2. Monthly deep dives: Analyze audience behavior and segment performance in detail. Look at:
Best-performing times of day
Device usage trends
Geographic response variations
Demographic engagement levels
3. Quarterly strategy updates: Use the data you've collected to rethink your approach to segmentation. Consider:
Seasonal patterns
Shifts in the customer lifecycle
New product launches
Changes in market conditions
Conclusion
Getting the most out of your Meta Ads segmentation requires a well-organized and regularly refined strategy. By tapping into first-party data, Meta Pixel insights, and custom audience tools, you can create campaigns that are both targeted and easy to measure.
Here are some key actions to focus on:
Track performance metrics like CTR, CPA, and ROAS consistently.
Run structured tests to see what works best for your audience.
Ensure accurate tracking to avoid missing important data.
Leverage attribution tools for a deeper understanding of campaign impact.
This approach keeps your campaigns flexible and results-focused. Dancing Chicken specializes in using data to fine-tune audience segmentation and optimize campaigns. With over $30 million in ad spend under their management, their team delivers solutions like advanced Meta account setups, pixel integration, and strategies designed to maximize ROAS.
"My mission is to empower businesses to scale effortlessly using data-driven advertising frameworks and automation." - Mason Boroff, Founder & CEO of Dancing Chicken