Fashion & apparel case study: ₹3L to ₹3L–₹6L monthly revenue in 3 months

New ads per month

1. 1

   Research & offer · Month 1

   What we do

   We give the first month to return on ad spend, the brand’s main problem, on a smaller base. Before budget rises, we close the gaps that stop a visitor buying: missing reviews, an unclear return window, no about page and no prepaid incentive. 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

   A smaller fashion store grows monthly revenue in 3 months, from ₹3L to ₹3L–₹6L (+50%). One in four of the accounts we measured grew at least that fast in the same time. The main problem in this scenario is return on ad spend. Conversion rate caps what any ad budget can return. Without layers, retargeting quietly eats the prospecting budget.

   How it works

   The fix list goes to the brand's team in the opening weeks, ahead of any budget step. Retargeting sits next to prospecting and never replaces it.

2. 2

   Measurement & reviews · Month 1 to 3

   What we do

   We set the path from ₹3L to ₹3L–₹6L as written monthly numbers, and read every review against the month so far. We log store orders every day beside what the ad platform claims.

   Why

   With no return on ad spend reported, the case study begins at the level measured fashion stores of that size hold. A missed month shows up early instead of at the end of the case study. Ad platforms claim more orders than stores record, so the store number decides budget.

   How it works

   Each budget step is argued against the written number. Every budget call starts from the store's orders.

3. 3

   Creative testing · Month 1

   What we do

   We test with video, catalogue ads and carousel first, rising to about two dozen new ads a month by the final month, with carousel watched closely since it returns less than the rest. We give each lead product its own campaign and read it weekly. We commission ads in batches, and read each batch for a set window before ordering the next. The learning month runs on a small daily budget, stepping up only once orders confirm.

   Why

   Shared campaigns hide weak products; separate ones expose them fast. The read window keeps creative spending tied to evidence. Early spend buys learning, not scale.

   How it works

   Losing products are paused within a week and budget moves to the winners. Batches that do not convert are cut; winners get the budget. Only confirmed orders at the low budget unlock the next step. More spend buys more new ads, led by video ahead of catalogue ads.

4. 4

   Scaling · Month 2 to 3

   What we do

   Through Month 2 to Month 3, we push toward ₹3L–₹6L: the budget climbs in steps and return falls, and Instagram Reels carries the most spend and Instagram Feed the next. We tie every budget increase to return: we step up while it holds, and step back when it drops. We cut budgets during major marketplace sale events and move spend to narrower premium audiences.

   Why

   Across Month 2 to Month 3, the budget climbs in steps, and return on spend falls as it does. Spend scaled in our measured accounts pushed cost per order up and return down, so no step is taken on hope. Marketplace sales inflate auction costs and pull price-led buyers away.

   How it works

   Each month's budget is set by the return the last one earned. Spend is reduced and redirected for each event window. Most of the final month's spend sits on Instagram Reels, then Instagram Feed. Prospecting to new buyers takes the bulk of spend, while retargeting returns more for each rupee.

1. Month 1

   First, the set-up: the first ads run on a small daily budget while tracking is checked against store orders. Store orders and ad-platform revenue are checked side by side. Reviews, trust pointers and the prepaid incentive are now on the store.

   • Revenue ₹3.1L
   • ROAS 2.83x
   • Ad spend ₹1.1L
2. Month 2

   Scaling begins: the weekly product read pauses the products that are not selling. Budget steps up and return on spend dips.

   • Revenue ₹3.6L
   • ROAS 2.53x
   • Ad spend ₹1.4L
3. Month 3

   During a marketplace sale window, spend moves to narrower premium audiences. Budget steps up and return on spend dips. The case study reaches ₹3L–₹6L a month. Each order costs more by the end than it did while learning.

   • Revenue ₹4.7L
   • ROAS 2.25x
   • Ad spend ₹2.1L

1. 1

   We cut budgets during major marketplace sale events and move spend to narrower premium audiences.

2. 2

   Raise budget only while return on spend holds; cut it when return drops.

3. 3

   Give each product (or colour) its own campaign, read weekly, and move budget to the winner.