Fashion & apparel case study: ₹50,000 to ₹67,842 monthly revenue in 3 months

New ads per month

1. 1

   Research & offer · Month 1

   What we do

   We start with scaling ad spend, which the brand in this scenario named first, before anything else on this smaller store. We layer the account: a creative-testing campaign, a scaling campaign, cold audiences that exclude past buyers, and cart remarketing. 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 ₹50,000 to ₹10L (20x). 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. The main problem in this scenario is scaling ad spend, with a clear strategy close behind. Without layers, retargeting quietly eats the prospecting budget. Lead categories give prospecting ads a proven entry point.

   How it works

   Warm layers run beside prospecting, not instead of it. Lead categories carry the first scaling months.

2. 2

   Measurement & reviews · Month 1 to 3

   What we do

   We track ad-platform revenue beside store orders in a shared daily sheet. We write month-by-month revenue numbers with the brand's team that climb from ₹50,000 to ₹10L, and open every review with the month-to-date number against them. We raise budget in a month only while return holds; where it slips too far, we hold it.

   Why

   It did not report a return on ad spend, so the case study starts from what measured fashion stores of that size hold. The ad platform's own count runs high, so the store's count is the one that moves budget. Written monthly numbers expose a slow month while there is still time to act.

   How it works

   The sheet is read before each budget change. The month's number is on the page at every review. Where return slips too far, the month keeps last month's budget.

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 no format far behind the account's return. We separate the lead products into their own campaigns and review each one weekly. We commission ads in batches, and read each batch for a set window before ordering the next. The learning month runs at a low daily budget and moves up only when orders come through.

   Why

   Shared campaigns hide weak products; separate ones expose them fast. Buying more before a batch is read means paying for guesses. 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

   We scale through Month 2 to Month 3 toward ₹10L as the budget rises gently while return holds, with Instagram Reels taking the largest share of spend and Facebook Feed the next. We let return decide budget: more while it holds, less when it slips. We cut budgets during major marketplace sale events and move spend to narrower premium audiences.

   Why

   Across Month 2 to Month 3, the budget rises gently, while return on spend holds. In two of these months budget goes up only as far as return allows, so revenue grows more slowly than the brand's number needs. Each budget step here is sized so that return stays close to where it was. 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. 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

   Learning month: a small daily budget carries the first ads, and store orders are matched to tracking. The layered account is in place, with retargeting beside prospecting. Lead categories get their own campaigns.

   • Revenue ₹50,097
   • ROAS 1.98x
   • Ad spend ₹25,282
2. Month 2

   Scaling begins: budget shifts to the products that sold this period. Budget goes up only as far as return can carry it: budget steps up and return on spend holds.

   • Revenue ₹59,930
   • ROAS 1.95x
   • Ad spend ₹30,785
3. Month 3

   The budget decision is taken on the return the last step earned. Budget goes up only as far as return can carry it: budget steps up and return on spend holds. Revenue ends below ₹10L, the number this scenario calls for, because budget stops rising where return starts to slip. Each order costs about what it did while learning.

   • Revenue ₹67,842
   • ROAS 1.99x
   • Ad spend ₹34,007

1. 1

   Tracked Meta spend, revenue and Shopify orders daily in a shared sheet

2. 2

   Tested each colour of the lead product in its own campaign

3. 3

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