So I’ve been playing around with different targeting setups lately, and something that keeps popping up in discussions is lookalike audiences for casino ads. I always assumed they were just another one of those “sounds great on paper” features that don’t actually move the needle much. But after messing with them for a bit, I realized there’s more going on here than I expected.
At first, I honestly didn’t think much about how audience modeling could impact my CTR. I mean, with casino traffic, you can get clicks easily—what’s hard is finding actual players who don’t bounce in 3 seconds. So improving CTR never felt like my biggest problem. But then my usual targeting started getting a little stale. My campaigns weren’t tanking or anything, but I could see engagement slowly slipping. And since most of us know how brutal ad fatigue can be in this vertical, I figured it might be worth testing something new.
The first pain point I ran into was not knowing what size or source audience would work best. Some people say you need at least 5k high-quality users, others swear they’ve made it work with just a few hundred. I was somewhere in the middle, and honestly, I didn’t feel confident that the platform would “learn” the right signals. Casino players aren’t exactly predictable—some deposit on day one, some float around for weeks. So I wasn’t sure if lookalikes would even pick up the right characteristics.
Eventually, curiosity won, and I set up a 1%, 3%, and 5% lookalike based on my recent depositors. Nothing fancy. I didn’t even change the creatives. I just wanted to see if the targeting alone made any difference. And to my surprise, the click-through rate jumped a lot faster than I expected. It wasn’t dramatic right away, but I could tell the traffic quality felt better. The clicks didn’t seem as random, and my bounce rate dropped a bit too.
What really caught my attention was that the 1% lookalike brought in fewer impressions but much higher engagement. It made me wonder if the CTR boost people talk about (around 20% or so) is actually legit. I’m not going to say that everyone will see the same results, but in my case, it wasn’t far off.
Something I did notice, though, is that lookalike audiences seem to work better when the creative is clear about the value proposition. I know “value proposition” sounds like some marketing buzzword, but I mean simple things like mentions of welcome bonuses, fast registration, or a specific game people like. When the ads were vague, even the best audiences didn’t respond well. So the targeting helps, but it doesn’t magically fix weak creatives.
Another small learning: expanding beyond the 1% too early didn’t help me. The 3% was okay, but the 5% lookalike started drifting into “too broad” territory pretty quickly. Maybe it works for bigger budgets, but for me it felt like the audience stopped resembling my real players at that point. So if anyone else is testing, I’d say start small and scale outward only when the early signs look promising.
One more thing—I came across this simple breakdown that explains how lookalikes actually work and why they tend to boost CTR, especially in niches like ours. It helped me understand why my campaigns reacted the way they did. If anyone wants to dig into the reasoning instead of just testing blindly like I did, here’s the link I found useful: improve CTR with casino lookalike audiences
I’m not saying lookalikes are some magic solution. They’re definitely not plug-and-play. But they’re a nice break from generic broad targeting, especially if your regular audiences are burning out. And if you’ve already collected at least some decent first-party data—email lists, depositors, returning players—it’s worth experimenting. Worst case, you learn what doesn’t work. Best case, you get that little CTR jump we all keep chasing.
For now, I’m still testing different audience sizes and creative angles, but the early results were good enough that I’m keeping them in my rotation. If anyone else here has tried lookalikes for casino ads, I’d love to hear what kind of results you got. I’m curious if my experience was just luck, or if this is something most people are seeing too.
At first, I honestly didn’t think much about how audience modeling could impact my CTR. I mean, with casino traffic, you can get clicks easily—what’s hard is finding actual players who don’t bounce in 3 seconds. So improving CTR never felt like my biggest problem. But then my usual targeting started getting a little stale. My campaigns weren’t tanking or anything, but I could see engagement slowly slipping. And since most of us know how brutal ad fatigue can be in this vertical, I figured it might be worth testing something new.
The first pain point I ran into was not knowing what size or source audience would work best. Some people say you need at least 5k high-quality users, others swear they’ve made it work with just a few hundred. I was somewhere in the middle, and honestly, I didn’t feel confident that the platform would “learn” the right signals. Casino players aren’t exactly predictable—some deposit on day one, some float around for weeks. So I wasn’t sure if lookalikes would even pick up the right characteristics.
Eventually, curiosity won, and I set up a 1%, 3%, and 5% lookalike based on my recent depositors. Nothing fancy. I didn’t even change the creatives. I just wanted to see if the targeting alone made any difference. And to my surprise, the click-through rate jumped a lot faster than I expected. It wasn’t dramatic right away, but I could tell the traffic quality felt better. The clicks didn’t seem as random, and my bounce rate dropped a bit too.
What really caught my attention was that the 1% lookalike brought in fewer impressions but much higher engagement. It made me wonder if the CTR boost people talk about (around 20% or so) is actually legit. I’m not going to say that everyone will see the same results, but in my case, it wasn’t far off.
Something I did notice, though, is that lookalike audiences seem to work better when the creative is clear about the value proposition. I know “value proposition” sounds like some marketing buzzword, but I mean simple things like mentions of welcome bonuses, fast registration, or a specific game people like. When the ads were vague, even the best audiences didn’t respond well. So the targeting helps, but it doesn’t magically fix weak creatives.
Another small learning: expanding beyond the 1% too early didn’t help me. The 3% was okay, but the 5% lookalike started drifting into “too broad” territory pretty quickly. Maybe it works for bigger budgets, but for me it felt like the audience stopped resembling my real players at that point. So if anyone else is testing, I’d say start small and scale outward only when the early signs look promising.
One more thing—I came across this simple breakdown that explains how lookalikes actually work and why they tend to boost CTR, especially in niches like ours. It helped me understand why my campaigns reacted the way they did. If anyone wants to dig into the reasoning instead of just testing blindly like I did, here’s the link I found useful: improve CTR with casino lookalike audiences
I’m not saying lookalikes are some magic solution. They’re definitely not plug-and-play. But they’re a nice break from generic broad targeting, especially if your regular audiences are burning out. And if you’ve already collected at least some decent first-party data—email lists, depositors, returning players—it’s worth experimenting. Worst case, you learn what doesn’t work. Best case, you get that little CTR jump we all keep chasing.
For now, I’m still testing different audience sizes and creative angles, but the early results were good enough that I’m keeping them in my rotation. If anyone else here has tried lookalikes for casino ads, I’d love to hear what kind of results you got. I’m curious if my experience was just luck, or if this is something most people are seeing too.