Reebok x Adyogi Case Study

Overview

To drive GMV growth while improving ROI without a proportional increase in ad spend on Flipkart, footwear and sportswear brands must transition from reactive ad management to dynamic, inventory-aware advertising strategies. Improving ROAS and conversion rates on a marketplace requires a holistic approach that aligns ad budgets with real-time stock availability (Quantity on Hand) and product listing quality.

This case study explores how Reebok, a leading sportswear brand, partnered with AdYogi to re-engineer its Flipkart advertising strategy to achieve profitability and scale. AdYogi identified core structural constraints limiting performance: siloed budget allocation disconnected from real-time stock availability, underutilization of browse and discovery placements to capture demand beyond search, and inconsistent top-position visibility on high-volume generic keywords.

Instead of scaling paid search budgets blindly, the AdYogi strategy focused on inventory-led budget allocation using real-time stock signals, securing impression share in discovery placements, and executing performance-led bidding for generic keywords. This strategic realignment by AdYogi translated into measurable business impact: 10.74x ROAS, 9.31% ACOS, a 39% improvement in conversion rate, and Reebok's highest-ever monthly GMV on Flipkart.

Contents

1. Context
2. Challenges
3. Solutions

Where the Brand was?

At the time of onboarding, Reebok had established brand presence and consistent sales momentum on Flipkart, supported by a strong assortment and steady consumer demand. However, advertising performance was not fully aligned with the brand's scale potential. The account operated predominantly through a search-led structure, with budget allocation not systematically linked to live inventory depth or SKU-level prioritization.

Three core gaps were identified. First, ad spend was not aligned with real-time stock availability, resulting in inefficiencies. Second, browse and discovery placements were under-leveraged, limiting reach beyond high-intent search traffic. Third, visibility on high-volume generic keywords remained inconsistent despite the presence of well-rated, high-performing bestselling SKUs.

While the brand had strong commercial fundamentals, the campaign framework lacked structural integration across inventory management, placement strategy, and keyword visibility, creating a clear opportunity for strategic realignment.

Challenges

01. Inventory-Advertising Misalignment

Pre-transformation performance trends indicated volatility across revenue and efficiency metrics, particularly during mid-year trading months. One underlying structural driver was the disconnect between advertising investments and real-time inventory depth.

Budget allocation operated independently of stock availability, leading to inconsistent SKU prioritization. Low-inventory products continued receiving media exposure despite limited fulfillment capacity, while high-QOH SKUs with scaling potential were under-leveraged.

This misalignment constrained performance stability. Demand was being generated without structured supply backing, creating efficiency fluctuations and limiting sustained promotional momentum during high-traffic periods.

02. Limited Customer Journey Coverage

Campaign performance showed dependence on bottom-funnel demand capture, with the majority of investment concentrated in search placements. While this supported high-intent conversion, overall conversion rates remained within a narrow baseline band prior to transformation.

Browse and discovery environments were underutilized, despite clear category behavior indicating product comparison and switching before purchase. Without structured browse coverage, Reebok was capturing existing demand rather than expanding it.

This restricted reach diversification and increased vulnerability to competitive bidding pressure within search-heavy auctions.

03. Inconsistent Generic Keyword Visibility

CTR and efficiency trends suggested opportunity for stronger presence on high volume, non-branded category keywords. Despite having well-rated bestsellers, impression share on generic discovery searches was not consistently secured.

In competitive auction environments, cautious bidding patterns limited sustained top-position visibility. As a result, the brand was not fully capitalizing on category-level traffic where purchase decisions are influenced before brand preference is formed.

04. Efficiency Plateau & Siloed Campaign Structure

Pre-strategy metrics reflected a performance ceiling, steady but incremental improvements rather than step-change growth. Conversion rates and ROI showed fluctuation rather than compounding gains, while ACOS remained within a predictable band.

A key reason was structural fragmentation. Campaigns were optimized independently across placements and keywords without unified integration between:

• Inventory depth
• SKU performance tiers
• Placement strategy
• Visibility objectives

Without an integrated ecosystem, scaling budgets risked linear returns instead of multiplicative impact.

Solutions Outside the Box

QOH* First Campaign Prioritization

Inventory-Led Budget Allocation
To align marketplace ad budgets with real-time stock availability, campaign budgets were aligned with real-time QOH* levels, ensuring high-stock SKUs received proportionate investment while low-stock products were deprioritized.

Dynamic Budget Adjustments
AdYogi's dynamic inventory reviews triggered structured budget recalibration, scaling campaigns up when stock was replenished and reducing exposure as inventory declined.

Inventory-Gated Activation
AdYogi's predefined stock thresholds determined campaign eligibility, preventing promotion of near-stockout items and protecting spend efficiency.

Strategic Outcome
By embedding inventory into media decisioning, Reebok and AdYogi aligned demand generation with supply readiness, enabling sustained promotional intensity and scalable, efficient growth.

Browse Placement Campaigns (ROB/TOB)

• Strategic SKU Selection: AdYogi's browse campaigns were structured around lower AOV footwear products to reduce purchase barriers during the exploration phase and drive stronger engagement within discovery environments.
• Inventory-Backed Scaling: Within AdYogi's strategy, high-QOH SKUs were prioritized to ensure consistent availability while capturing product-switching behavior during browsing sessions, especially during high-traffic sale periods.
• Visibility-First Optimization: Campaigns were optimized for impression share rather than immediate click efficiency, strengthening brand presence across browse placements where consideration and comparison occur.
• Strategic Outcome: During the sale period, this structured browse expansion outperformed baseline trends, contributing meaningfully to incremental demand capture and enhancing overall performance beyond search-led traffic.

Bestseller-Led Visibility on High-Volume Keywords

• Strict SKU Qualification: Only products meeting defined performance benchmarks (strong ratings of 4+ stars, proven conversion history, and sufficient inventory depth) were shortlisted for visibility-led campaigns.
• Strategic Keyword Selection: Focus was placed on high-intent, non-branded generic searches where traffic volume justified sustained investment and competitive positioning.
• Performance-Led Bidding Approach: Bestselling SKUs were structurally differentiated within the bidding strategy, strengthening quality signals and improving auction competitiveness without overspending on exploratory phases.
• Strategic Outcome: This approach by AdYogi drove engagement rates above category benchmarks while improving cost efficiency through quality score gains, enabling sustained top-position visibility during high-traffic periods.

Grow Your Brand With AdYogi Across Channels

• D2C: Meta Business Partner, Google Partner (Premier 2024), Snapchat
• Marketplace: Amazon, Myntra, Flipkart
• Quick Commerce: Instamart, Zepto, Blinkit

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