Interest-based targeting used to be Meta’s bread and butter. For years, advertisers built entire strategies around categories like“ fitness,” “clean beauty,” or “gut health.” But in 2025, those interests aren’t just less effective, they’re actively dragging down performance.
Meta’s ad platform has changed. Privacy updates, deprecation of sensitive categories, and algorithmic shifts have turned once-reliable audiences into overbroad, expensive pools. If you’re still leaning on interest-based targeting to fill your prospecting funnel, you’re likely wasting spend, chasing the wrong clicks, and missing the buyers who are actually in-market.
Let’s unpack why.
Interest categories are based on historical behavior and platform activity, not real-time buying intent. Someone might follow a few wellness brands, engage with a fitness meme, or click on a skincare reel six months ago. That doesn’t mean they’re shopping for your product today.
This gap between passive interests and commercial intent is why advertisers are seeing:
It’s not that your ads are bad. It’s that your audiences are stale.
In2025, Meta removed or deprecated many of the interest categories brands used most, including PCOS, ADHD, semaglutide, gut health, and other sensitive health topics. Even for non-sensitive niches, Meta’s algorithm has deprioritized interest data in favor of conversion-based signals.
That means if you’re building lookalikes off of interest pools, or launching broad prospecting ads using “clean skincare” or “weight loss” tags, you’re feeding the machine weak inputs. And Meta’s optimization system can only work with what you give it.
Here’s the uncomfortable truth: many interest-based audiences are full of people who would never buy from you.
They might be curious. They might have liked a post. They might have been interested… a while ago. But curiosity doesn’t convert.
And if you’re paying $12–$30 CPMs to reach these users, the waste adds up fast.
Now multiply that by 3–5 ad sets. Add in lookalikes based on those same interests. Layer retargeting on top. Suddenly, you’ve spent $10K+ and have no clue which audience is actually in-market.
Intent targeting flips the model. Instead of relying on past likes and assumed interests, it starts with present-tense behavior. What are people searching, comparing, reading, and clicking right now?
We explain more in how intent data works, but here’s the short version:
When someone’s normal browsing behavior changes like suddenly spending more time comparing product pages, clicking through competitor guides, or searching specific solution keywords, we classify that as high intent. It’s not about hitting a magic number of actions. It’s about detecting a shift in engagement that signals they’re moving into a decision-making phase. Then we verify that person’s profile and push it into your Meta campaign as a custom audience via Lift.
It’s precise. It’s timely. And it performs.
Whether you’re selling a hair supplement or running a B2B SaaS campaign, the difference is clear:
Interest-Based Targeting
Lift Intent Audience
That’s not hypothetical. Brands using Lift have consistently seen 20–45% lower cost per purchase within 14 days of switching.
One of the biggest issues with interest audiences is that they don’t age well. You could be targeting someone based on a click they made in 2022.
Lift updates your audience list daily. That means the people in your campaign have shown commercial behavior in the last 7 days, not 7 months ago.
This recency drives better click-throughs, stronger learning phase signals, and more profitable scaling.
Here’s another way interest targeting costs you: bad lookalikes.
If your seed audience is based on a vague interest or a stale customer list, your lookalike will be equally diluted.
Instead, you can use Lift to seed high-intent custom audiences based on verified behavioral data. This gives Meta a stronger starting point to find more buyers.
It’snot about reaching more people. It’s about reaching the right ones.
For brands running geo-targeted or retail campaigns, Zone lets you apply the same high-intent model to ZIP-code level targeting. This is ideal for:
Zone shows you which ZIPs are seeing the biggest spike in high-intent behaviors. Then you can run Meta campaigns just to those areas.
Combine that with Lift audiences, and you get both intent and location precision, without relying on unreliable interest categories.
Interest targeting had a good run. But the game has changed.
If you’re still seeing inconsistent Meta performance, rising CPAs, and weak prospecting ROAS, your audience strategy is likely the culprit.
Switching from interest-based to intent-based targeting doesn’t require changing your funnel, your creative, or your team. You just need better data.
Lift gives Meta advertisers real-time intent audiences that outperform broad and interest-based targeting. It’s simple to activate and proven to scale.
Let the rest of the market keep guessing. You’ve got better signals now.
