Case Study #882 • D2C Engineering

THE ARCHITECTURE
OF AGGRESSIVE SCALE.

How we bypassed the "Scaling Tax" to take a lifestyle brand from stagnant 6-figure days to a consistent 4.22X ROAS at ₹5.7L+ daily volume.

Validated Peak Daily Revenue

₹5,77,412
SYSTEM CALIBRATED

Efficiency

4.22X ROAS

Growth

+477.4%

AOV Strength

₹2,257

Net CAC

₹240.12

01. The "Death Loop"

The client was trapped in Interest-Based Overlap. Every time they pushed spend past ₹20k, Meta's algorithm bid against itself, skyrocketing CPMs and tanking ROAS to 0.8x. They were fighting the algorithm instead of fueling it.

02. Creative Liquidity

We eliminated all restrictive targeting. By using Broad Targeting (Age/Gender only), we forced the algorithm to use the ad creative as the targeting tool. This allowed the machine to find buyers in "Blue Ocean" pockets the competitors couldn't reach.

03. The Hook Engine

Scaling isn't about bidding; it's about Creative Retention. We deployed 15+ variations per week via DCT (Dynamic Creative Testing), isolating "Winner Hooks" that held attention for more than 3 seconds, significantly dropping our CPCs by 40%.

PERFORMANCE BENCHMARKS

DAILY AD SPEND
₹30,000 (Max)
₹1,40,000+
HIGH LIQUIDITY
ROAS VOLATILITY
± 1.5 Variation
± 0.2 Deviation
STABILIZED
CONV. RATE (CVR)
2.1% (Standard)
4.8% (Optimized)
LP OVERHAUL
AD FATIGUE CYCLE
3-4 Days
24 Days Average
WINNER DCT

The Austivo Technical Protocol

We implemented a Post-Purchase Upsell (PPU) funnel that immediately boosted AOV by 18% without increasing ad spend. Simultaneously, we migrated the Meta tracking to CAPI (Conversions API) via server-side tagging. This reduced the "Data Gap" by 25%, giving the Meta AI cleaner signals to optimize for high-value customers rather than just "clickers." The result was a scaling engine that actually got cheaper as we spent more.

WANT THESE NUMBERS?

We are looking for 2 brands to scale for Q4.

Apply For A Growth Audit

Requirement: Minimum ₹15k Daily Current Ad Spend