Fashion & apparel case study: ₹1L to ₹1.2L monthly revenue in 3 months

New ads per month

1. 1

   Research & offer · Month 1

   What we do

   We set up the base for a smaller fashion store before any budget rises. We put the website audit, the creative brief and the monthly media schedule in place before spend moves. We put best-sellers on product pages and lead with the one or two categories that already sell.

   Why

   In this case study, a smaller fashion brand grows monthly revenue in 3 months, from ₹1L to ₹30L (30x). Fewer than one in ten of our measured accounts grew that fast in the same time, so the case study follows the pace of that top tenth rather than forcing the number. No single problem was named; the case study works from the figures instead. Later budget calls need something written to be judged against. Lead categories give prospecting ads a proven entry point.

   How it works

   The audit, the brief and the media schedule are shared before spend rises. Lead categories carry the first scaling months.

2. 2

   Measurement & reviews · Month 1 to 3

   What we do

   We keep a shared daily sheet with the ad platform's revenue next to real store orders. We agree a written number for every month on the way from ₹1L to ₹30L, and start each review with the month-to-date figure against it. We raise budget in a month only while return holds; where it slips too far, we hold it.

   Why

   Its reported return on ad spend is too low for more budget to pay, so the first months lift return before any budget step. Ad platforms claim more orders than stores record, so the store number decides budget. A shortfall is caught in the month it happens, not at the end.

   How it works

   Every budget call starts from the store's orders. Each budget step is argued against the written number. 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 two dozen new ads a month by the final month, with carousel watched closely since it returns less than the rest. The learning month runs with a deliberately small daily budget until orders prove the buyer. We run every lead product in a campaign of its own, read every week. We lead with video that carries trust: creators, customer feedback and founder-led pieces.

   Why

   Early spend buys learning, not scale. Shared campaigns hide weak products; separate ones expose them fast. Trust-carrying video held return in most measured accounts.

   How it works

   Spend steps up only after orders confirm at the low budget. Budget follows the products that sell. Low-quality UGC is pulled and founder-led video takes its place. The number of new ads grows with spend; video makes up the largest part and catalogue ads the next.

4. 4

   Scaling · Month 2 to 3

   What we do

   We scale through Month 2 to Month 3 toward ₹30L as the budget rises gently while return holds, with Instagram Reels taking the largest share of spend and Facebook Feed the next. We put seasonal collection campaigns in front of each festive and wedding peak. We let return decide budget: more while it holds, less when it slips.

   Why

   Across Month 2 to Month 3, the budget rises gently, while return on spend holds. Two of these months stop their budget step where return slips too far. Return holds through these months because each budget step stops where return starts to slip. Seasonal demand moves by region, so the spend does too.

   How it works

   Budget moves between regions as the calendar turns. Budget follows return month to month instead of a fixed ramp. Instagram Reels carries the largest share of spend in the final month, with Facebook Feed next. 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. The daily sheet now matches platform revenue to store orders. Lead categories get their own campaigns.

   • Revenue ₹1L
   • ROAS 1.92x
   • Ad spend ₹52,141
2. Month 2

   Scaling begins: budget is reviewed against return before the next step. The step is sized by what return can bear: as budget holds, return on spend holds.

   • Revenue ₹1.1L
   • ROAS 1.95x
   • Ad spend ₹56,737
3. Month 3

   The weekly product read pauses the products that are not selling. The step is sized by what return can bear: as budget steps up, return on spend holds. The case study finishes short of ₹30L: budget stops rising where return starts to slip. Each order costs about what it did while learning.

   • Revenue ₹1.2L
   • ROAS 1.88x
   • Ad spend ₹64,972

1. 1

   Ran CBO and ABO versions side by side to see which held cost

2. 2

   Scaling spend raised cost per order and lowered return on spend.

3. 3

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