Why I Never Use Interest Targeting in Facebook Ads

Introduction: The Big Facebook Ads Misconception

When I first started running Facebook ads, I did what everyone else was doing. I spent hours researching interests, building detailed audience profiles, and carefully selecting every possible relevant interest category. After all, that’s what all the “gurus” were teaching, right?

Fast forward 3 years and over $2 million in ad spend later, I made a radical change – I completely stopped using interest targeting. And guess what? My results improved almost immediately.

In this comprehensive guide, I’ll explain:

• The fundamental flaws with Facebook’s interest targeting
• Why the platform’s algorithm actually works against you when using interests
• The eye-opening tests that changed my perspective forever
• Exactly what I do instead (with real campaign examples)
• When you might actually want to use interest targeting
• How to transition away from interest-based campaigns

The Hidden Problems With Facebook Interest Targeting

1.1 Outdated and Inaccurate Data

Facebook’s interest data isn’t as precise as you might think. The platform determines interests based on:

• Pages users have liked (sometimes years ago)
• Groups they’ve joined (and may no longer be active in)
• Content they’ve interacted with (even accidentally)

Real-world example: One of my clients was targeting “luxury car enthusiasts.” After analyzing the data, we discovered that:

• 42% of the audience hadn’t engaged with car content in over 18 months
• 15% were actually teenagers who just liked car pictures
• Only about 23% were genuine potential buyers

1.2 The “Interest Bubble” Problem

Facebook groups users into broad interest categories that often combine completely different types of people. For instance, people interested in “entrepreneurship” might include:

• Actual business owners (your target)
• Wantrepreneurs who never start anything
• MLM participants
• People who just like motivational quotes

1.3 The Scaling Limitation

Even when you find a good interest audience, you quickly hit a ceiling. There are only so many people in:

• “Organic gardening” (1.2M people)
• “Vegan bodybuilding” (85,000 people)
• “Minimalist parenting” (320,000 people)

Once you’ve saturated these small pools, your CPMs skyrocket and results plummet.

How Facebook’s Algorithm Actually Works

2.1 The Power of Machine Learning

Modern Facebook advertising runs on a sophisticated AI system that:

• Analyzes thousands of data points per user
• Tracks micro-behaviors (how long someone watches videos, what they click, etc.)
• Identifies patterns humans would never notice

Case study: An ecommerce client selling premium kitchen knives saw their best customers were:

• Men aged 35-54 who…
• Regularly watched BBQ content but…
• Also engaged with luxury watch ads

This was a connection we never would have made manually.

2.2 Why Narrow Targeting Hurts Performance

When you restrict Facebook’s algorithm with interest targeting, you’re:

1. Preventing it from finding unexpected high-value audiences
2. Forcing it to work with incomplete data
3. Creating artificial bottlenecks in your sales funnel

Data point: In split tests, broad audiences consistently achieve:

• 23-37% lower cost per acquisition
• 15-28% higher conversion rates
• 40-60% larger scalable audiences

My Proven Alternative Strategy

3.1 The Broad Audience Approach

Here’s exactly how I structure campaigns without interest targeting:

Step 1: Set up a broad audience

• Age range: 18-65+ (or your realistic buyer age)
• No gender restrictions
• No interest targeting
• Location: Your service areas
• Use Advantage+ audience expansion

Step 2: Layer on quality signals

• Set up conversion tracking properly
• Implement the Conversions API
• Use value optimization if applicable

Step 3: Implement smart budget pacing

• Start with at least 5x your target CPA as daily budget
• Use campaign budget optimization
• Allow at least 7 days for learning

3.2 Advanced Optimization Techniques

Once the broad audience is working, I add:

Lookalike audiences:

• 1-3% LALs from purchasers
• Exclude recent converters

Retargeting layers:

• Website visitors (30/60/90 day windows)
• Video engagers (50%+ completion)
• Lead form opens

Creative segmentation:

• Different ad sets for different messaging angles
• All still using broad targeting

Real Campaign Examples

4.1 E-commerce Store (Home Goods)

Old interest-targeted campaign:

• Interests: Home decor, interior design, DIY
• 30-day results:
  • Spend: $18,750
  • ROAS: 2.1
  • CPA: $32.50

New broad-targeted campaign:

• No interests, age 25-65, all genders
• 30-day results:
  • Spend: $24,600
  • ROAS: 3.8
  • CPA: $18.20

Key finding: The algorithm found converting audiences among working professionals who showed no explicit interest in home decor but had recent purchase behavior indicating they were setting up new homes.

4.2 B2B Software (CRM Tool)

Old approach:

• Targeted “small business owners,” “entrepreneurs,” “startups”
• Poor results (CTR under 1%, $95+ CPA)

New approach:

• Broad targeting 30-65 all genders
• Retargeting webinar attendees
• Result: CTR improved to 2.3%, CPA dropped to $42

When You Might Actually Want to Use Interest Targeting

While I generally avoid interest targeting, there are a few exceptions:

1. Market research phase:

• Use small interest-targeted tests to gather initial data
• Identify what messaging resonates
• Then switch to broad targeting

2. Extremely niche products:

• Example: Specialized medical equipment
• When the total addressable market is very small

3. Lookalike audience seed:

• Create a small custom audience based on interests
• Use it to generate a lookalike
• Then turn off the interest targeting

Making the Transition – Step by Step

If you’re currently using interest targeting, here’s how to shift:

1. Duplicate your existing campaigns
2. Remove all interest targeting
3. Expand age/gender parameters
4. Increase budgets by 30-50% (broader reach needs more fuel)
5. Monitor for 7-10 days (expect a short adjustment period)
6. Gradually phase out old campaigns as new ones stabilize

Pro tip: Run them side-by-side for 2 weeks to compare performance directly.

Conclusion: Trust the Machine

After managing millions in Facebook ad spend across dozens of clients, I’ve learned one fundamental truth: Facebook’s algorithm is smarter than we are at finding buyers. Our job isn’t to tell it who to target, but to:

1. Provide clear conversion signals
2. Create compelling offers and creatives
3. Get out of the algorithm’s way

The advertisers seeing the best results in 2024 aren’t those with the most sophisticated targeting – they’re the ones who have learned to leverage Facebook’s AI most effectively.

Ready to test this approach? Here’s your action plan:

1. Duplicate your best-performing campaign
2. Strip out all interest targeting
3. Expand your age/gender ranges
4. Set a sufficient budget
5. Let it run for at least 7 days
6. Compare results to your old approach

I’d love to hear about your experiences with broad targeting. Have you tested this approach before? What were your results? Let me know in the comments!