Fashion & apparel case study: ₹3L to ₹4.4L monthly revenue in 3–4 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. We start with a website audit, a creative brief and a monthly media schedule in the first week. 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.

   Why

   In this case study, a smaller fashion brand grows monthly revenue in 3–4 months, from ₹3L to ₹50L (16.7x). 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 return on ad spend, with a clear strategy close behind. Without a brief, each creative and budget decision starts from scratch. Conversion rate caps what any ad budget can return.

   How it works

   All three are shared with the brand's team before any budget step. Fixes are listed and handed over early, so later budget lands on a store that converts.

2. 2

   Measurement & reviews · Month 1 to 4

   What we do

   We track ad-platform revenue beside store orders in a shared daily sheet. We agree a written number for every month on the way from ₹3L to ₹50L, and start each review with the month-to-date figure against it. We reconcile the return on spend the brand in this scenario reports with store revenue before the first budget change.

   Why

   The return on ad spend it reported sits close to what measured fashion stores of that size hold, and the case study starts from it. Platform attribution over-counts, so budget decisions sit on the store-side number. A shortfall is caught in the month it happens, not at the end.

   How it works

   Budget decisions are read off store numbers, not the ad platform alone. The month's number is on the page at every review. Both returns are reviewed together each week.

3. 3

   Creative testing · Month 1

   What we do

   We lead the testing layer with video, catalogue ads and carousel, building to a few dozen new ads a month by the final month, with carousel watched closely since it returns less than the rest. We separate the lead products into their own campaigns and review each one weekly. The learning month runs on a small daily budget, stepping up only once orders confirm. We brief creators for a steady run of UGC video, with regional-language cuts of the winners.

   Why

   Shared campaigns hide weak products; separate ones expose them fast. Early spend buys learning, not scale. Regular UGC keeps testing going, and a regional cut stretches a winning idea further.

   How it works

   Budget follows the products that sell. The low budget stays until orders confirm the buyer. Regional cuts of a winner come before new ideas. 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 ₹50L: the budget rises gently and return dips, and Instagram Reels carries the most spend and Instagram 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, and return on spend dips. Two of these months stop their budget step where return slips too far. 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

   There is no fixed ramp; each month's budget follows the return of the last. 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.

5. 5

   Steady state · Month 4

   What we do

   From Month 4, we protect the revenue already built and move toward ₹50L where return permits. We refresh tired ads by mixing old and new creatives, and keep a creative bank. We hold budget where return peaks instead of pushing past it.

   Why

   From Month 4 growth slows while revenue is still under ₹50L. Spend still grows, at a slower pace than during scaling. A measured account showed click-through falling ahead of revenue, so tired ads are replaced early. Return on spend fell from its peak month in most of our engagements; peaks do not hold.

   How it works

   New creatives mix with proven ones rather than replacing them all at once. Budget is held while return is at its best and cut back when it slips.

1. Month 1

   First, the set-up: a small daily budget carries the first ads, and store orders are matched to tracking. Reported and store-side returns are reconciled. The audit, brief and media schedule are agreed with the brand's team.

   • Revenue ₹2.9L
   • ROAS 2.18x
   • Ad spend ₹1.3L
2. Month 2

   Scaling begins: during a marketplace sale window, spend moves to narrower premium audiences. The budget step stops where return starts to slip: return dips as the budget steps up.

   • Revenue ₹3.7L
   • ROAS 2.00x
   • Ad spend ₹1.9L
3. Month 3

   The creative bank supplies this period's refresh.

   • Revenue ₹4.3L
   • ROAS 1.92x
   • Ad spend ₹2.3L
4. Month 4

   The case study moves into its steady phase, leaning on refreshed ads and repeat buyers. The budget step stops where return starts to slip: return holds as the budget holds. ₹50L is not reached in the time, because budget stops rising where return starts to slip. Cost per purchase ends higher than in the learning phase.

   • Revenue ₹4.4L
   • ROAS 1.92x
   • Ad spend ₹2.3L

1. 1

   Tracked net sales beside Shopify revenue and set the numbers on the lower figure

2. 2

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

3. 3

   We ask for a seasonal landing page, new ad formats and delivery banners ahead of the festive peak.