Fashion & apparel case study: plan for ₹50,000–₹1L to ₹1.1L monthly revenue in 2–3 months

New ads per month

1. 1

   Research & offer · Month 1

   What we'd do

   Start with keeping return on spend while scaling, which the booking named first, before anything else on this smaller store. Build the account in layers so each can be read on its own: testing, scaling, new-buyer prospecting and cart retargeting. Put best-sellers on product pages and lead with the one or two categories that already sell.

   Why

   The enquiry came from a smaller fashion brand that wants to grow monthly revenue in 2–3 months, from ₹50,000–₹1L to ₹30L–₹40L (46.7x). 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 main problem named at booking was keeping return on spend while scaling, followed by scaling ad spend. Without layers, retargeting quietly eats the prospecting budget. Lead categories give prospecting ads a proven entry point.

   How it works

   Each layer keeps its own budget line. 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 ₹50,000–₹1L to ₹30L–₹40L, and open every review with the month-to-date number against them. Raise budget in a month only while return holds; where it would slip too far, hold it.

   Why

   With no return on ad spend reported, the plan begins at the level 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. 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. A month whose return would slip past that point keeps its budget instead.

3. 3

   Creative testing · Month 1

   What we'd do

   Lead the testing layer with video, catalogue ads and static image, building to about a dozen new ads a month by the final month, with every format close to the account's return. Give each lead product its own campaign and read it weekly. The learning month runs with a deliberately small daily budget until orders prove the buyer. Run creator, customer-feedback and founder-led video.

   Why

   Products that do not sell show up inside a week, not after a month of shared budget. Spend in the learning phase pays for information. In most accounts we measured, video that carried trust held its return.

   How it works

   Losing products are paused within a week and budget moves to the winners. Spend steps up only after orders confirm at the low budget. UGC that underperforms is replaced by founder-led video, not given more budget. 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'd do

   Through Month 2 to Month 3, push toward ₹30L–₹40L: the budget rises gently while return holds, and Instagram Feed carries the most spend and Instagram Reels the next. Let return decide budget: more while it holds, less when it slips. Recover abandoned checkouts with WhatsApp messages as traffic grows.

   Why

   Across Month 2 to Month 3, the modelled budget rises gently, while return on spend holds. In two of these months the step is trimmed to the size return can hold. Return holds through these months because each budget step stops where return would slip. WhatsApp is cheaper than paid retargeting for buyers who already reached checkout.

   How it works

   There is no fixed ramp; each month's budget follows the return of the last. WhatsApp recovery runs alongside paid retargeting, not instead of it. Instagram Feed carries the largest share of spend in the final month, with Instagram Reels 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. Lead categories get their own campaigns. The layered account is in place, with retargeting beside prospecting.

   • Projected revenue ₹79,176
   • Projected ROAS 1.88x
   • Planned ad spend ₹42,010
2. Month 2

   The scaling phase opens: budget is reviewed against return before the next step. Budget rises to the point where return would start to give way: budget steps up and return on spend holds.

   • Projected revenue ₹93,820
   • Projected ROAS 1.91x
   • Planned ad spend ₹48,995
3. Month 3

   Budget shifts to the products that sold this period. Budget rises to the point where return would start to give way: budget steps up and return on spend holds. ₹30L–₹40L is not reached in the time, because budget stops rising where return would slip. Cost per purchase ends close to the learning phase.

   • Projected revenue ₹1.1L
   • Projected ROAS 1.90x
   • Planned ad spend ₹57,659

1. 01

   Rebuilt the account: a new-audience campaign excluding past audiences, past-buyer retargeting, one campaign per winning product

2. 02

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

3. 03

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