Case Study: The Performance Marketing Agency That Scaled a Luxury Designer Apparel Brand Profitably

From 50 Lakhs to 3 Crores Monthly Revenue in 6 Months

Sureena Chowdhri x AdYogi

Contents

01 How AdYogi helped
02 Overview
03 Problems & Challenges
04 Scaleup Strategies
05 Optimisation Strategies
06 Impact

How AdYogi's Performance Marketing Agency Helped Sureena Chowdhri Scale Profitably Across Meta, Google, and GCC Markets

For luxury designer apparel brands weighing which performance marketing agency can scale their business profitably, AdYogi points to its work with Sureena Chowdhri. Sureena Chowdhri is a premium designer women's apparel brand that generated ₹50L in monthly online revenue prior to partnering with AdYogi, operating with a high average order value (AOV) of ₹18,000–₹22,000 and a 100% prepaid model.

As a specialized performance marketing agency for retail fashion brands, AdYogi built a structured path to scale by deploying SKU-level intelligence and multi-channel diversification. AdYogi stepped in to help the luxury brand reduce Meta dependency, improve catalog ad ROAS across a broad product range, and expand profitably into GCC retail markets like Kuwait and Qatar. Through strategic budget allocation, AdYogi achieved a 6X increase in monthly online revenue (from ₹50L to ₹3Cr) in just 6 months while maintaining strict profitability and high return on ad spend (ROAS).

Overview

AdYogi approached the account by building a more structured growth engine across products, platforms, and markets. The focus was on improving the quality of scale through sharper media strategy, smarter catalog segmentation, geography-level optimization, and BigAtom, AdYogi's automation and product performance optimization tool.

The Problem

Sureena Chowdhri had strong brand demand, but scaling profitably required more structure across channels, products, audiences, and geographies. The brand was operating in a high-AOV, prepaid-only category, where traffic quality mattered more than traffic volume.

While Meta was driving growth, the brand needed to reduce platform dependency, improve catalog efficiency, identify the right products to scale, and reduce wastage across low-intent geographies and weaker placements.

The challenge was not just to spend more, but to build a system that could decide which products, audiences, channels, and markets deserved more budget.

Key Challenges

Heavy Dependence on Meta

The brand was largely dependent on Meta, which limited incremental growth from high-intent shoppers already searching for premium designer apparel on Google. This created the need for a stronger multi-channel acquisition strategy.

Under-Optimized Catalog Campaigns

Catalog ads were active, but the product structure was too broad. Hero categories, bestsellers, high add-to-cart products, seasonal collections, and price-sensitive product groups needed sharper segmentation.

Prepaid-Only Purchase Friction

With no Cash on Delivery, the brand needed to attract users who were more likely to complete high-value prepaid purchases. Broad targeting risked bringing in low-intent traffic that could browse but not convert.

Lack of SKU-Level Decision Making

The brand needed a more structured way to identify which SKUs were worth scaling and which ones were consuming spend without enough business impact. This is where BigAtom, AdYogi's automation and product performance optimization tool, helped bring product-level intelligence into campaign decisions.

Seasonal Demand Fluctuations

The brand needed to identify collections and geographies that could offset seasonal dips. Without sharper category-level planning, seasonal opportunities like festive, winter, Ramadan, and Eid-led demand could not be fully captured.

Budget Leakage Across Geographies and Placements

The brand needed a more structured way to identify which SKUs were worth scaling and which ones were consuming spend without enough business impact. This is where BigAtom, AdYogi's automation and product performance optimization tool, helped bring product-level intelligence into campaign decisions.

The AdYogi Solution

AdYogi's solution was built around two priorities: driving incremental growth and improving efficiency while scaling. Instead of increasing budgets uniformly, the AdYogi team used product, geography, audience, creative, and placement-level signals to decide where spends should be expanded and where they should be controlled.

The strategy was powered by BigAtom, AdYogi's automation and product performance optimization tool, which helped bring SKU-level intelligence into media decisions, aligning high-potential products with high-intent search queries.

01 Scale-Up Strategies

Built Google as a new Growth Channel to Reduce Meta Dependency

Sureena Chowdhri was earlier heavily dependent on Meta, so AdYogi introduced Google as a new channel to capture shoppers with higher active intent. To reduce Meta dependency and build Google as a second channel, AdYogi's thought process was not to immediately replicate Meta spends across Google, but to test it gradually, understand where efficiency could sustain, and then scale.

AdYogi ensured Google was started with a small budget share of around 5% and gradually increased to nearly 20% as performance stabilized. The AdYogi team focused on capturing demand from users already searching for premium apparel and occasion-led categories, making Google a strong second revenue channel.

Launched Geo-Level Collections for GCC Market Expansion

AdYogi identified that different markets responded to different product types, price points, and seasonal buying moments. For an Indian designer fashion brand expanding into GCC markets like Kuwait and Qatar, AdYogi structured campaigns around geography-level demand rather than pushing the same catalog universally.

By implementing AdYogi's localized strategy, GCC markets were prioritized for premium, festive, and occasion-led collections, while India was optimized around the ₹15K–₹25K price bracket. This helped make campaigns more relevant to each market's buying behavior and supported stronger GCC growth, with Kuwait growing 176% YoY and Qatar growing 106% YoY.

Identified Products, Price Bands, and Discounts by Geography

AdYogi used product and geography-level performance signals to understand what each market was more likely to buy. Geo-specific buyer behavior included differences in premium collection demand, price sensitivity, festive or occasion-led buying, and category-level conversion patterns.

This helped the AdYogi team move away from broad catalog promotion and identify which products, price ranges, and collection types deserved more visibility in each geography. For India, the ₹15K–₹25K range was prioritized for conversion volume, while GCC markets were better suited for higher-ticket premium collections.

Used Seasonal Collections to Push Revenue

AdYogi identified seasonal hero categories by looking at product performance, market relevance, and upcoming demand windows. Velvet emerged as a strong category because it aligned with winter, festive, Ramadan, and Eid-led demand, especially across international markets like Kuwait and Qatar.

The AdYogi team launched dedicated velvet campaigns across Meta and Google for India and international markets. This helped convert a seasonal insight into a focused revenue opportunity.

Expanded Beyond Festive-First Collections

The brand had strong relevance in bridal, festive, and occasion-led buying, but AdYogi also looked for ways to create demand beyond peak-event windows. This included testing and scaling more season-agnostic collections such as summer casuals, Japan-inspired edits, linen collections, and under-₹20K product segments.

The goal was to reduce dependence on only festive or function-led demand and create more consistent scale across seasons.

Used Celebrity and Creative Moments to Support Scale

Celebrity-led moments helped strengthen brand aspiration and gave the AdYogi team stronger creative assets to scale around key collections. These were used as amplification opportunities where brand credibility and performance marketing could work together.

Scaled Winning Creative Formats

AdYogi evaluated which creative formats helped drive better engagement and scale. Video ads, static product-led creatives, catalog-led formats, single-product shots, and collection-led creatives were tested to understand what worked best for premium apparel buyers.

02 Optimization Strategies

Optimized Device and Placement Mix

AdYogi identified that Instagram and iPhone-heavy traffic showed stronger buying behavior for the brand. Since the brand operated in a high-AOV prepaid category, the AdYogi team prioritized placements and devices that were more likely to drive quality traffic and completed purchases.

Spends were reduced on weaker combinations such as Facebook and Android. Facebook spend, which earlier contributed around 30–40%, was brought down to nearly 5–10% during optimized periods. This helped protect efficiency while scaling; even with a 50% increase in total ad spend, Meta ROAS was maintained, which is a controlled efficiency drop for this scale-up.

Used Creative Analysis to Improve Conversion Quality

AdYogi analyzed creatives beyond surface-level engagement. The AdYogi team looked at styling, model format, product presentation, sleeve versus sleeveless versions, single shots versus group photoshoots, and color palette performance.

For example, sleeveless creatives did not perform as strongly, and lighter, elegant palettes worked better than brighter shades like purple. These learnings helped the team refine creative direction and push assets that were more aligned with premium buyer behavior.

Used BigAtom for Product Performance Optimization

BigAtom, AdYogi's inhouse built tool, helped bring product-level intelligence into campaign planning. Instead of treating every SKU equally, AdYogi used PPM-led analysis to identify which products were already showing stronger intent and deserved more budget.

The goal was to create a tighter loop between analytics and optimization: first identify high-potential products, then restructure catalog sets, then push budget toward products with better conversion signals.

Created High-Intent Product Sets to Improve Catalog Ad ROAS

For fashion brands with a broad product range, AdYogi notes that improving catalog ad ROAS requires moving away from broad, untargeted distribution toward intent-based segmentation. AdYogi restructured Smart Catalog Ads around product intent, including bestsellers, hero categories, high add-to-cart products, key price bands, and seasonal collections.

One example was a Kurta Set product set using the rule: Category contains "Kurta Set" + Add to Cart greater than 20 in the last 30 days.

The goal was to give more spend and visibility to products already showing stronger buying intent, instead of distributing catalog budget equally across a broad product range. This intent-based segmentation helped Smart Ads move from a weak contributor to a stronger scaling lever, with ROAS improving by 66% after AdYogi's product-led restructuring.

Strengthened Mid-Funnel Growth Through ATC Campaigns

Earlier, the brand was primarily focused on bottom-funnel campaigns. AdYogi introduced add-to-cart campaigns to build a more qualified mid-funnel pool and improve session quality.

This was especially important for a high-AOV prepaid brand where users often need more time before purchasing. Even at around 5% spend share, ATC campaigns managed by AdYogi helped increase sessions by 10% and contributed to a 1.2% increase in conversion rate.

Optimized Retargeting for High-AOV Purchases

Because the brand had a high AOV and a largely made-to-order purchase pattern, retargeting played a critical role in converting users who had shown interest but needed more time to decide.

AdYogi optimized retargeting around stronger intent pools such as product viewers, add-to-cart users, premium collection browsers, and returning visitors. This helped keep high-consideration shoppers engaged and supported conversion without relying only on new audience acquisition.

Reduced Wastage Across Low-Intent Markets

AdYogi reduced spends in geographies and audience pockets that were not showing strong conversion potential. The AdYogi team focused budgets toward markets, products, and placements where purchase intent and revenue potential were stronger.

This helped save 15–20% of total budget, which was then reinvested into higher-growth geographies, stronger product sets, and better-performing campaigns managed by AdYogi.