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How PPOP scaled ad spend from ₹3K to ₹64K with creative testing
At a glance
- Client
- PPOP
- Category
- Intimate wellness · D2C
- Engagement
- Meta Ads creative testing and structured scaling
- Starting point
- Approximately ₹3,000 ad spend at around 1.14X ROAS
- Testing pace
- Approximately 25 creatives tested in 25–30 days
The account needed more creative volume before it could scale with confidence
PPOP is a modern intimate wellness brand built around the idea of helping customers feel more confident, connected and excited about their experience. When we started working on the account, the biggest constraint was not simply budget. It was creative testing capacity.
Traditional creator-led content was difficult to produce consistently because not every creator was comfortable appearing in product videos. At the same time, the brand needed to test aggressively enough to discover which creative ideas could actually convert.
Before scaling
- Approximately ₹3,000 in ad spend
- Around 1.14X ROAS
- No clearly established winning creative
- Limited traditional creator-led video options
What the account needed
- A larger testing pool
- More creative formats and messaging angles
- Clear winner identification
- Controlled budget increases behind proven ads
We built the scaling process around creative testing instead of one “hero” ad
Instead of depending on a few standard ads, we increased the volume and variety of creative experiments. In roughly 25–30 days, around 25 creatives were tested.
Expand the creative pool
Testing covered AI-generated videos, graphic creatives, product-led visuals, different messaging angles, video-and-graphic combinations and multiple concepts around individual products.
Use AI video where creator production was limited
Because conventional creator-led content was harder to produce consistently in this category, AI-generated video became one part of the testing system rather than a replacement for performance data.
Finding the winning combinations
The first phase was not about immediate aggressive scaling. It was about testing enough ideas to identify the few that had earned more budget.
After the testing pool became large enough, clearer winners started to emerge. One of the stronger combinations came from mixing graphic creative with an AI-generated video.
The account did not scale because one format was assumed to work. It scaled after enough formats were tested to show which ads deserved more budget.
Spend increased by more than 20X while ROAS improved
The starting point was approximately ₹3,000 in ad spend at 1.14X ROAS. After the testing phase identified stronger creatives and more budget was moved toward those winners, spend increased to approximately ₹64,000 while ROAS improved to about 1.5X.
Instead of increasing spend blindly, the account used testing to understand what was working first. Budget followed evidence.
The real improvement was creative-led scaling under a difficult production constraint
The biggest win was not simply the higher spend. It was the ability to increase spend by more than 20X while also improving ROAS, despite having fewer traditional creator-led content options than many other D2C categories.
₹3K spend → 1.14X ROAS became approximately ₹64K spend → 1.5X ROAS after a larger creative testing pool produced clearer winners.
What other performance teams can steal from the PPOP testing system
The 4 moves behind the creative-led scaling process:
Testing volume matters.
Around 25 creatives gave the account enough variation to identify stronger patterns instead of making decisions from a tiny sample.
Do not depend on one content format.
AI-generated video, graphics and product-focused concepts kept testing moving when creator-led production was constrained.
Find winners before adding budget.
The goal of the first phase was learning. Larger budgets came after performance data made the stronger creatives easier to identify.
Let the category shape the creative system.
Difficult production constraints require a different process, not a pause in experimentation.
The campaign created a repeatable way to keep testing even when content production was difficult
The main takeaway from the PPOP campaign was not simply moving from 1.14X to 1.5X ROAS. It was building a repeatable creative testing system for a category where content production itself was one of the biggest constraints.
Within approximately 25–30 days, the team tested around 25 creatives, identified stronger combinations and increased ad spend from roughly ₹3,000 to ₹64,000 while improving ROAS.
When traditional content options are limited, growth does not have to stop. A disciplined mix of creative testing, AI-led production, graphics and performance data can keep the learning loop active until winners become clear.
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