Fashion & apparel case study: plan for ₹75,000 to ₹81,226 monthly revenue in 90 days

New ads per month

1. 1

   Research & offer · Month 1

   What we'd do

   Open with set-up work on the smaller fashion store, since the booking gave no single problem. Put the website audit, the creative brief and the monthly media plan in place before spend moves. Put best-sellers on product pages and lead with the one or two categories that already sell.

   Why

   A smaller fashion store asked us how to grow monthly revenue in 90 days, from ₹75,000 to ₹5L (6.7x). That is faster than nine in ten of our measured accounts grew over the same time, so the plan aims at that fastest tenth's pace, holds budget where return would slip, and shows where it lands against the target. The booking gave no single problem, so the plan starts from the numbers. Without a brief, each creative and budget decision starts from scratch. Lead categories give prospecting ads a proven entry point.

   How it works

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

2. 2

   Measurement & targets · Month 1 to 3

   What we'd do

   Keep a shared daily sheet with the ad platform's revenue next to real store orders. Write month-by-month targets with the brand's team that climb from ₹75,000 to ₹5L, and open every review with the month-to-date number against them. Set a written rule: no budget step in a month where return would fall too far to pay for it.

   Why

   With no return on ad spend reported, the plan begins at the level measured fashion stores of that size hold. Ad platforms claim more orders than stores record, so the store number decides budget. Written targets expose a slow month while there is still time to act.

   How it works

   Budget decisions are read off store numbers, not the ad platform alone. Each budget step is argued against the written target. Where return would slip too far, the month keeps last month's budget.

3. 3

   Creative testing · Month 1

   What we'd do

   Test with video, catalogue ads and static image first, rising to about a dozen new ads a month by the final month, with carousel watched closely since it returns less than the rest. Commission ads in batches, and read each batch for a set window before ordering the next. Make trust the subject of the video: creator reels, customer feedback and founder-led clips. Separate the lead products into their own campaigns and review each one weekly.

   Why

   The read window keeps creative spending tied to evidence. Video built on trust was the format that held return in most measured accounts. Shared campaigns hide weak products; separate ones expose them fast.

   How it works

   Losing batches stop; winning ads take their budget. Weak UGC is swapped for founder-led video rather than scaled. A product that does not sell is paused inside the week. 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 ₹5L as return allows as the budget rises gently while return holds, with Instagram Reels taking the largest share of spend and Instagram Feed the next. Tie every budget increase to return: step up while it holds, step back when it drops. Put seasonal collection campaigns in front of each festive and wedding peak.

   Why

   In Month 2 to Month 3 the modelled 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 target needs. Return holds through these months because each budget step stops where return would slip. Demand is seasonal and regional, so spend moves with the calendar.

   How it works

   There is no fixed ramp; each month's budget follows the return of the last. Spend shifts into each season and between regions with the calendar. 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

   The learning phase opens: the first ads run on a small daily budget while tracking is checked against store orders. The media plan and creative brief are signed off. Store orders and ad-platform revenue are checked side by side.

   • Projected revenue ₹69,432
   • Projected ROAS 1.90x
   • Planned ad spend ₹36,545
2. Month 2

   Scaling starts: products that do not sell are paused and budget moves to the winners. The budget step stops where return would slip: return on spend holds while budget steps up.

   • Projected revenue ₹78,053
   • Projected ROAS 1.89x
   • Planned ad spend ₹41,385
3. Month 3

   Customer-feedback and creator videos are refreshed. The budget step stops where return would slip: return on spend holds while budget holds. ₹5L is not reached in the time, because budget stops rising where return would slip. Each order costs about what it did while learning.

   • Projected revenue ₹81,226
   • Projected ROAS 1.88x
   • Planned ad spend ₹43,196

1. 01

   Run Google Search and Shopping beside Meta, and use Google's demand data to shape Meta.

2. 02

   Put best-sellers on product pages, lead with the one or two categories that sell, and keep a monthly creative bank.

3. 03

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