When you’re running push notification campaigns — especially with a sizeable budget — there’s one golden rule: never go all-in without testing first.
This is where split testing becomes a game changer. It’s not just a “good practice,” it’s the difference between burning thousands of dollars and creating a consistent profit machine.
In this case study, I’ll walk you through how I approached A/B testing for push ads with a large campaign budget, what variables I tested, and the results I got.
When you’re working with big spend potential, it might be tempting to throw the entire budget behind what you “think” will work. The problem? What you think will work and what actually works are often two different things.
Split testing allows you to allocate a small fraction of your budget to compare different versions of your ad setups — what I call “connections” (creative + targeting + landing page combination). The winner gets the full budget. The loser gets eliminated before it can drain your funds.
In simple terms, split testing (or A/B testing) is the process of running two or more variations of the same campaign at the same time, but with specific, controlled differences. One group of users sees Version A, the other sees Version B. You compare performance metrics like CTR, conversion rate, and ultimately, ROI.
The goal? To identify the exact elements that drive higher conversions. Once you know that, scaling becomes much less risky.
Over the course of my testing, here are the variables I focused on:
Through disciplined split testing, I was able to cut my CPA by more than half in certain campaigns and boost overall ROI. The best part? I had clear, data-backed insights on which creatives, flows, and targeting options performed best — allowing me to scale with confidence.
The key takeaway here is simple: Split testing isn’t an optional extra — it’s your insurance policy against budget burn.
The next time you’re tempted to push your entire budget into a single campaign setup, remember this: a few small, controlled tests can save you thousands and make scaling far more predictable.
This is where split testing becomes a game changer. It’s not just a “good practice,” it’s the difference between burning thousands of dollars and creating a consistent profit machine.
In this case study, I’ll walk you through how I approached A/B testing for push ads with a large campaign budget, what variables I tested, and the results I got.
Why Split Testing is Essential for Large Budgets
When you’re working with big spend potential, it might be tempting to throw the entire budget behind what you “think” will work. The problem? What you think will work and what actually works are often two different things.
Split testing allows you to allocate a small fraction of your budget to compare different versions of your ad setups — what I call “connections” (creative + targeting + landing page combination). The winner gets the full budget. The loser gets eliminated before it can drain your funds.
What Exactly is Split Testing?
In simple terms, split testing (or A/B testing) is the process of running two or more variations of the same campaign at the same time, but with specific, controlled differences. One group of users sees Version A, the other sees Version B. You compare performance metrics like CTR, conversion rate, and ultimately, ROI.
The goal? To identify the exact elements that drive higher conversions. Once you know that, scaling becomes much less risky.
Key Elements to Test in Push Campaigns
Over the course of my testing, here are the variables I focused on:
- Notification Texts & Landing Page Copy
Your copy is often the first point of persuasion. I tested different headline styles, emotional triggers, and calls-to-action in both the push notifications and landing pages. Subtle changes in tone and urgency had surprisingly big effects on CTR. - Creatives & Visuals
In push ads, your image can make or break the campaign. I swapped out multiple visuals — some more product-focused, others more lifestyle-driven. The CTR variations between them were significant enough to justify deep testing. - Pre-Landing Pages vs. Direct Landing
I experimented with using pre-landers for warming up the user before sending them to the main offer page. Testing variations of pre-landers also helped reveal which flow led to higher conversions. - Buttons & CTAs
The difference between “Download Now” and “Get Started” might seem small — but testing proved otherwise. Even small tweaks to button color, size, and text impacted results. - Targeting Parameters
Testing GEO-specific targeting, device types, and user activity levels helped me weed out underperforming segments. Cutting low-value audiences saved a substantial chunk of budget.
Rules I Follow for Reliable Testing
- Change One Thing at a Time: If you tweak too many elements at once, you’ll never know what actually caused the change in performance.
- Gather Enough Data: Don’t make decisions after 10 clicks — let both versions get statistically significant traffic.
- Run Tests Simultaneously: Testing at different times introduces biases from timing, competition, and even day-of-week behavior.
- Test on the Same GEO: Audiences vary drastically from one country to another. Keep GEO constant for accuracy.
Results & Takeaways
Through disciplined split testing, I was able to cut my CPA by more than half in certain campaigns and boost overall ROI. The best part? I had clear, data-backed insights on which creatives, flows, and targeting options performed best — allowing me to scale with confidence.
The key takeaway here is simple: Split testing isn’t an optional extra — it’s your insurance policy against budget burn.
The next time you’re tempted to push your entire budget into a single campaign setup, remember this: a few small, controlled tests can save you thousands and make scaling far more predictable.