How Adil Qadri Got a Precision Roadmap to ₹30L/Day on Meta

The Challenge

Adil Qadri — the fragrance brand behind My Dream Store — had built a meaningful Meta Ads presence. With over ₹20 Lakhs in daily GMV, the account was generating real revenue. But growth had stalled. The ₹30L/day target felt close in theory and distant in practice.

The surface-level metrics weren't the problem. Headline ROAS across the account looked respectable: 2.3–2.7x. Campaign managers could point to numbers and declare the account healthy. But underneath the aggregate, a different story was forming.

A large and growing portion of that ROAS was being driven by repeat buyers — existing customers who would have purchased anyway, now being aggressively retargeted at high frequency. Two campaigns in particular were serving their "Existing" audience segment at frequencies of 5.1 and 6.0 — burning budget reaching the same customers over and over while barely outperforming blended ROAS by 1.11x. The high numbers weren't proof the ads were working; they were proof the account was milking its existing customer base.

Meanwhile, the ads genuinely driving new customer acquisition — the ones with 70–93% fresh audience rates — weren't getting proportionally more budget. The scoring system the account was implicitly using (ROAS alone) couldn't distinguish between a campaign that was earning revenue and one that was harvesting it.

What We Did

1. Segment-Aware Attribution: The Scale Score Formula

The first and most important step was replacing headline ROAS with a composite scoring engine built around what actually matters for growth: incremental purchases from new and first-time customers.

We designed a four-factor Scale Score that weighted Growth Incremental Purchases (Prospecting + Engaged segments) at 55% — the single largest input — then Budget Capacity at 30%, ROAS Sanity at 15%, and an Attribution Quality Multiplier based on click-vs-view attribution share.

The critical design decision: purchases from the Existing (repeat) segment are deliberately excluded from the scaling reward. Scaling budget toward repeat buyers doesn't grow the business — it just looks like it does on the dashboard. This formula redirected the optimization signal toward campaigns that were genuinely expanding the customer base.

An offer cap (0.80x multiplier for discovery/offer units) ensured that cheap-traffic offer campaigns couldn't game the score. Click-share across the account was uniformly high at 83–87%, which validated that most spend was genuinely click-driven — with the formula correctly demoting the few view-heavy outliers.

2. Ad-Level Kill List: Stopping the Bleeding First

Before injecting a single rupee of new budget, we ran a full ad-level audit to identify underperforming ads dragging down their parent ad sets.

Three ads surfaced immediately:

• AQ_Sales_ALLPERFUME_TheStory_AB1605_Mall — ₹6.33L spent at 1.59x ROAS, pulling the entire AllPerfume_TheStory ad set below profitability.
• AQ_Sales_AsrarSeries_D&D1 - Copy — ₹4.78L at 1.48x ROAS. High spend, sub-breakeven acquisition.
• AQ_Sales_AsrarSeries_amiirahmad — 0.86x ROAS. Burning money with majority repeat spend.

Combined, these three ads had consumed over ₹11.14L in 30 days at returns that made scaling their parent ad sets impossible. They were paused immediately — a necessary cleanup that freed both budget and optimization headroom for the campaigns that were working.

3. Audience Split Strategy: Separating Growth from Retention

The scoring data identified two campaigns that had crossed a critical threshold: they were over-serving repeat buyers at such high frequency that their ROAS was a mirage — subsidized by existing customer demand rather than earned through new acquisition.

UBAU_AQ_Sales_TheStoryPerfume — 47% of spend going to repeat buyers at a frequency of 6.0. The campaign's ROAS looked strong, but nearly half its revenue was coming from customers who would have likely purchased directly.

UBAU_AQ_Sales_Value_Perfumes — 38% repeat spend at 5.1 frequency, with repeat ROAS only 1.11x above blended. It wasn't earning a premium for serving repeat customers — it was just serving them compulsively.

The split verdict: carve the "Existing" audience into a dedicated retention campaign, restrict the original to Prospecting only. This doesn't reduce revenue — it makes the P&L honest, and it allows the retention budget to be managed deliberately at a cost-effective frequency rather than blended into the acquisition budget where it inflates the headline and obscures the truth.

4. Precision Budget Reallocation: +₹1,20,000/Day

With the kill list cleared and the split candidates isolated, we allocated ₹1,20,000/day in incremental budget exclusively to the highest-scoring growth units — campaigns and ad sets with proven capacity to absorb budget while driving new customer acquisition.

At the CBO level, the Box_Attar campaign received the largest increase (₹39,000/day) — the account's strongest growth engine with 8,548 incremental purchases in 30 days, a 53% prospecting spend share, and multiple ad sets running at strong frequency-to-purchase ratios. AsraSeries received ₹11,000/day.

At the ABO ad set level, six sets received targeted increases: Perfume Discovery Set Pack of 10 (+₹27K/day), TraditionalFragrance (+₹11K/day), AsrarSeries_Influencer (+₹10K/day), ShanayaAttar (+₹8K/day), NewGiftSet (+₹9K/day), and AllPerfume (+₹5K/day). Each increase was applied at the controlling budget unit — campaign level for CBOs, ad set level for ABOs — following Meta's budget architecture strictly to avoid disrupting delivery.

A 3-day monitoring protocol was built into the plan: track Outbound Clicks and CTR as leading indicators. If CPM and Frequency rise without matching lift in Incremental Purchases, the audience is saturating and a New/Repeat split is triggered for the next round.

5. Creative Hierarchy: What to Scale and What to Cap

The 30-day ad-level data ranked every creative by scalability: Fresh % (new + warm buyers), click attribution, ROAS, and frequency. The top creative — AQ_Sales_Perfume_Discovery_Set_Collab_PC — had a 93% fresh audience rate on ₹18.86L of spend at 2.15x ROAS. This is the blueprint for new creatives: founder-driven, discovery-first, low-frequency, click-attributed.

The audit also surfaced the "CAP — Repeat-Dependent" creatives: the influencer retargeting and DPA (dynamic product ads) running at frequencies of 5.0+ with 40–48% repeat audiences. These don't need to be paused — they belong in a deliberate retention strategy. What they must not do is compete for acquisition budget, which they were.

The Results

The 30-day analysis cracked open a problem that blended ROAS had been concealing: an account that looked like it was performing at scale was partly harvesting demand it had already built. Two campaigns were serving past buyers at high frequency and counting the revenue as acquisition wins. Eleven-plus lakhs in monthly spend was flowing into ads operating below breakeven.

By rebuilding the optimization signal around segment-aware attribution — rewarding only purchases from new and warm-first-time customers — the account got its first honest view of where budget was compounding and where it was decaying. The ₹1,20,000/day incremental was allocated not to the campaigns with the best-looking dashboards, but to the ones with the strongest growth incremental scores: proven budget absorbers with high fresh rates and click-driven attribution.

The path from ₹20L to ₹30L/day GMV had been there all along. It required a measurement framework that could see past the headline.