Fashion & apparel case study: ₹10,000–₹15,000 to ₹30,959 monthly revenue in 3 months

New ads per month

1. 1

   Research & offer · Month 1

   What we do

   We give the first month to a clear strategy, the brand’s main problem, on a smaller base. We open with three documents: a website audit, a creative brief and a media schedule by month. We split the account into layers: one campaign to test creative, one to scale winners, prospecting that leaves out past buyers, and retargeting for carts.

   Why

   In this case study, a smaller fashion brand grows monthly revenue in 3 months, from ₹10,000–₹15,000 to ₹1.5L (12x). That is faster than nine in ten of our measured accounts grew over the same time, so the case study below is on what that fastest tenth reached and shows where it lands against the number this scenario calls for. The main problem was a clear strategy. Without a brief, each creative and budget decision starts from scratch. Without layers, retargeting quietly eats the prospecting budget.

   How it works

   All three are shared with the brand's team before any budget step. Warm layers run beside prospecting, not instead of it.

2. 2

   Measurement & reviews · Month 1 to 3

   What we do

   We agree a written number for every month on the way from ₹10,000–₹15,000 to ₹1.5L, and start each review with the month-to-date figure against it. We log store orders every day beside what the ad platform claims. We raise budget in a month only while return holds; where it slips too far, we hold it.

   Why

   No starting return on ad spend was given; the starting return is what measured fashion stores of that size hold. A missed month shows up early instead of at the end of the case study. The ad platform's own count runs high, so the store's count is the one that moves budget.

   How it works

   The month's number is on the page at every review. Every budget call starts from the store's orders. A month whose return slips past that point keeps its budget instead.

3. 3

   Creative testing · Month 1

   What we do

   We test with video, catalogue ads and static image first, rising to about a dozen new ads a month by the final month, with every format close to the account's return. We give each lead product its own campaign and read it weekly. We run static images next to the video ads. We work in creative batches with a fixed read window each.

   Why

   Products that do not sell show up inside a week, not after a month of shared budget. Among the fashion accounts we measured, video was the format most often in the top creative tier. Buying more before a batch is read means paying for guesses.

   How it works

   A product that does not sell is paused inside the week. Statics join once a winning video is found. Batches that do not convert are cut; winners get the budget. New ads rise with the budget, most of them video, then catalogue ads.

4. 4

   Scaling · Month 2 to 3

   What we do

   We scale through Month 2 to Month 3 toward ₹1.5L as the budget climbs in steps and return dips, with Instagram Reels taking the largest share of spend and Instagram Feed the next. We cut budgets during major marketplace sale events and move spend to narrower premium audiences. We raise budget only while return on spend holds, and cut it when return drops.

   Why

   Across Month 2 to Month 3, the budget climbs in steps, and return on spend dips. Budget is part-stepped in one of these months, taking only what return can carry. In one of these months budget holds, because return is below the level where more budget pays. Our measured accounts saw cost per order rise and return fall as spend scaled; that is why each step here waits on return. Marketplace sales inflate auction costs and pull price-led buyers away.

   How it works

   Spend is reduced and redirected for each event window. Budget follows return month to month instead of a fixed ramp. Most of the final month's spend sits on Instagram Reels, then Instagram Feed. Most spend reaches people who have not bought yet; past visitors return more per rupee.

1. Month 1

   First, the set-up: tracking is checked against store orders and the first ads go live on a small daily budget. Testing, scaling and retargeting now run as separate layers. Store orders and platform revenue are reconciled in the shared sheet.

   • Revenue ₹12,519
   • ROAS 2.12x
   • Ad spend ₹5,892
2. Month 2

   Scaling begins: the budget decision is taken on the return the last step earned. The budget step stops where return starts to slip: spend more than doubles, and return falls.

   • Revenue ₹30,869
   • ROAS 1.86x
   • Ad spend ₹16,576
3. Month 3

   During a marketplace sale window, spend moves to narrower premium audiences. More budget does not pay at this return, so spend holds, and return holds. ₹1.5L is not reached in the time, because budget stops rising where return starts to slip. Each order costs more by the end than it did while learning.

   • Revenue ₹30,959
   • ROAS 1.92x
   • Ad spend ₹16,113

1. 1

   Rebuilt the account: a new-audience campaign excluding past audiences, past-buyer retargeting, one campaign per winning product

2. 2

   Read Meta against Shopify every week

3. 3

   Meta in four layers: creative testing, scaling, mid-funnel and catalogue retargeting