Fashion & apparel case study: plan for ₹3L–₹4L to ₹6.5L monthly revenue in 3 months

New ads per month

1. 1

   Research & offer · Month 1

   What we'd do

   Start with a clear strategy, which the booking named first, before anything else on this smaller store. Start with a website audit, a creative brief and a monthly media plan in the first week. Layer the account: a creative-testing campaign, a scaling campaign, cold audiences that exclude past buyers, and cart retargeting.

   Why

   A smaller fashion brand came to us to grow monthly revenue in 3 months, from ₹3L–₹4L to ₹15L (4.3x). Nine in ten of the accounts we measured grew more slowly than that in the same time; the plan is built on what the fastest tenth reached, and shows the gap to the target honestly. The problem named at booking was a clear strategy. Without a brief, each creative and budget decision starts from scratch. Separate layers stop prospecting and retargeting competing for the same budget.

   How it works

   The brief is agreed first; spend follows it. Each layer keeps its own budget line.

2. 2

   Measurement & targets · Month 1 to 3

   What we'd do

   Track ad-platform revenue beside store orders in a shared daily sheet. Write month-by-month targets with the brand's team that climb from ₹3L–₹4L to ₹15L, and open every review with the month-to-date number against them.

   Why

   It did not report a return on ad spend, so the plan starts from what measured fashion stores of that size hold. 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

   Budget decisions are read off store numbers, not the ad platform alone. Written targets make each scaling decision explicit.

3. 3

   Creative testing · Month 1

   What we'd do

   Test with video, catalogue ads and carousel first, rising to about two dozen new ads a month by the final month, keeping carousel on a short leash because its return trails the account. Run every lead product in a campaign of its own, read every week. Commission ads in batches, and read each batch for a set window before ordering the next. The learning month runs with a deliberately small daily budget until orders prove the buyer.

   Why

   A product nobody buys is visible within a week when it has its own campaign. 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. Only ads that convert inside the window keep running. The low budget stays until orders confirm the buyer. New ads rise with the budget, most of them video, then catalogue ads.

4. 4

   Scaling · Month 2 to 3

   What we'd do

   Scale through Month 2 to Month 3 as far toward ₹15L as return allows as the budget climbs in steps and return dips, with Instagram Reels taking the largest share of spend and Instagram Feed the next. Raise budget only while return on spend holds, and cut it when return drops. Cut budgets during major marketplace sale events and move spend to narrower premium audiences.

   Why

   Across Month 2 to Month 3, the modelled budget climbs in steps, and return on spend dips. 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

   Budget follows return month to month instead of a fixed ramp. Spend is reduced and redirected for each event window. In the final month, Instagram Reels takes the most spend and Instagram Feed the next most. Prospecting to new buyers takes the bulk of spend, while retargeting returns more for each rupee.

1. Month 1

   First, the set-up: a small daily budget carries the first ads, and store orders are matched to tracking. The website audit, creative brief and media plan are shared. Testing, scaling and retargeting now run as separate layers.

   • Projected revenue ₹3.6L
   • Projected ROAS 3.04x
   • Planned ad spend ₹1.2L
2. Month 2

   The scaling phase opens: each budget move is read against the return it bought. With budget steps up, return on spend dips.

   • Projected revenue ₹4.7L
   • Projected ROAS 2.91x
   • Planned ad spend ₹1.6L
3. Month 3

   During a marketplace sale window, spend moves to narrower premium audiences. With budget steps up, return on spend dips. ₹15L is not reached in the time, because the plan follows what the fastest tenth of our measured accounts reached. Cost per purchase ends higher than in the learning phase.

   • Projected revenue ₹6.5L
   • Projected ROAS 2.72x
   • Planned ad spend ₹2.4L

1. 01

   Tested each colour of the lead product in its own campaign

2. 02

   Layer the account: creative testing, a scaling campaign, new audiences that exclude past buyers, and catalogue or cart retargeting.

3. 03

   Launched a wedding-season catalogue campaign and a dedicated scaling campaign