Case Study: How a D2C Fashion Brand Increased ROAS by 300%

A niche D2C fashion brand was stuck at 1-2 orders per day with a dismal 0.5x ROAS despite testing every Meta Ads campaign structure. By digging into deep market research, adjusting their pricing to meet customer expectations, and revamping their creative approach, they achieved a 300% ROAS lift in just two weeks.

• Identify why broad audience testing fails when product pricing is misaligned.
• Learn how to read dashboard signals like high CPMs and dropping active time.
• Discover the impact of a data-backed price drop on overall profitability.
• Automate your creative testing pipeline using EngageReel.

How does a fashion brand break out of a 0.5x ROAS slump when every ad strategy seems to fail? The answer usually isn't just another Meta Ads campaign hack; it requires fundamental market alignment. In this case study, we examine how a niche Korean-inspired D2C fashion brand went from bleeding cash to consistently generating 10 orders a day by looking beyond the ads manager and fixing their core offer.

The challenge: Hitting a growth ceiling at 0.5x ROAS

The brand, specializing in K-pop and K-drama designs, launched with high hopes but quickly hit a wall. Despite testing Bid Caps, Cost Caps, Broad targeting, Interest-Based clusters, and Lookalike audiences, sales remained stagnant. They were maxing out at 1 to 2 orders per day, and their Return on Ad Spend (ROAS) was frozen at an unprofitable 0.5x for months.

Market research indicates that testing new creatives and audiences is futile if the underlying product-market fit or pricing strategy is fundamentally disconnected from consumer expectations. The brand had limited SKUs across only two categories, making it difficult to justify premium pricing to a cold audience.

Why ignoring competitor pricing destroys ad efficiency

Deeper market research revealed the fatal flaw: extreme price sensitivity. General competitors in the Korean fashion space were selling similar apparel for ₹400 to ₹1000. This brand was priced at ₹900 to ₹1200. This massive pricing gap meant that even when the ads reached the right audience, the sticker shock prevented conversions.

Metric	Before Pricing Adjustment	After Pricing Adjustment
Product Price	₹1,000	₹700
Orders per Day	1 - 2	10+
Platform ROAS	0.5x	1.5x

Reading the hidden signals in your Meta Ads dashboard

The brand's dashboard data confirmed the pricing mismatch. Unique reach was decreasing, while impressions skyrocketed, meaning the same non-converting users were seeing the ads repeatedly. CPMs were artificially high because the algorithm couldn't find buyers, and active time on the website was dropping rapidly.

When engagement is poor but impressions are high, it indicates that the creative might be catching the eye, but the landing page experience—specifically the price—is acting as a hard barrier. The campaign structure and creatives weren't reaching new, high-intent audiences.

How a strategic price drop triggered a 300% ROAS increase

The team executed two major changes. First, they restructured their campaign and creative strategy to force the algorithm to seek net-new audiences. Second, they dropped the price of their core t-shirt from ₹1,000 to ₹700, presenting it in a value-driven, psychological manner.

The results were immediate. By understanding their customers deeply and making data-backed decisions rather than guessing, orders jumped to 10 per day. The ROAS tripled, moving from 0.5x to 1.5x in just two weeks, proving that sometimes the best advertising optimization happens outside the ad account.

EngageReel automates creative testing and spend allocation

Finding the right combination of creative hook and price point requires rapid, continuous testing. EngageReel—an AI ad performance and creative platform for fashion eCommerce—watches every creative you run, learns what converts, and optimizes Meta, Google, and TikTok spend 24/7.

Instead of manually monitoring dropping reach and rising CPMs, EngageReel shifts budget automatically to winning variations. This allows D2C fashion founders to focus on core business economics—like pricing and inventory—while the AI handles the heavy lifting of customer acquisition.