Fashion & apparel case study: plan for ₹5L to ₹4.5L monthly revenue in 1 month

New ads per month

1. 1

   Research & offer · Week 1 to 2

   What we'd do

   Start with results that swing from month to month, which the booking named first, before anything else on this mid-sized store. Layer the account: a creative-testing campaign, a scaling campaign, cold audiences that exclude past buyers, and cart retargeting. Map the festive and wedding calendar before spending, with seasonal collections ready in advance.

   Why

   A mid-sized fashion store asked us how to grow monthly revenue in 1 month, from ₹5L to ₹25L (5x). 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 results that swing from month to month. Separate layers stop prospecting and retargeting competing for the same budget. Buyers in this category shop around festivals and weddings.

   How it works

   Retargeting sits next to prospecting and never replaces it. Each peak has its campaign ready before it starts.

2. 2

   Measurement & targets · Week 1 to 4

   What we'd do

   Track ad-platform revenue beside store orders in a shared daily sheet. Set the path from ₹5L to ₹25L as written weekly targets, and read every review against the week so far.

   Why

   It did not report a return on ad spend, so the plan starts from what measured fashion stores of that size hold. Platform attribution over-counts, so budget decisions sit on the store-side number. Written targets expose a slow week while there is still time to act.

   How it works

   Budget decisions are read off store numbers, not the ad platform alone. The target for the week is on the page at every review.

3. 3

   Creative testing · Week 1 to 4

   What we'd do

   Test with video, catalogue ads and static image first, rising to a few dozen new ads a month by the last four weeks, keeping carousel on a short leash because its return trails the account. Commission ads in batches, and read each batch for a set window before ordering the next. The four learning weeks run at a low daily budget and moves up only when orders come through. Separate the lead products into their own campaigns and review each one weekly.

   Why

   The read window keeps creative spending tied to evidence. Early spend buys learning, not scale. Products that do not sell show up inside a week, not after a month of shared budget.

   How it works

   Only ads that convert inside the window keep running. Spend steps up only after orders confirm at the low budget. Budget follows the products that sell. The number of new ads grows with spend; video makes up the largest part and catalogue ads the next.

4. 4

   Scaling · Week 4

   What we'd do

   Through Week 4, push toward ₹25L: the budget stays close to the learning level while return holds, and Instagram Reels carries the most spend and Instagram Feed the next. Cut budgets during major marketplace sale events and move spend to narrower premium audiences. Raise budget only while return on spend holds, and cut it when return drops.

   Why

   Across Week 4, the modelled budget stays close to the learning level, while return on spend holds. Return holds through these weeks because each budget step stops where return would slip. Marketplace sales inflate auction costs and pull price-led buyers away.

   How it works

   Spend is reduced and redirected for each event window. There is no fixed ramp; each week's budget follows the return of the last. Most of the last four weeks'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.

1. Week 1

   First, the set-up: a small daily budget carries the first ads, and store orders are matched to tracking. The daily sheet now matches platform revenue to store orders. The layered account is in place, with retargeting beside prospecting.

   • Projected revenue ₹1.2L
   • Projected ROAS 2.54x
   • Planned ad spend ₹45,918
2. Week 2

   First creative read: ads that do not convert are cut. Budget holds and return on spend holds.

   • Projected revenue ₹1.1L
   • Projected ROAS 2.55x
   • Planned ad spend ₹43,866
3. Week 3

   Store fixes and offers go live while orders confirm.

   • Projected revenue ₹1.1L
   • Projected ROAS 2.55x
   • Planned ad spend ₹42,307
4. Week 4

   By the end of learning, the buyer is known and one ad has won. Budget holds and return on spend holds. The plan finishes short of ₹25L: budget stops rising where return would slip. Cost per purchase ends close to the learning phase.

   • Projected revenue ₹1.1L
   • Projected ROAS 2.53x
   • Planned ad spend ₹44,768

1. 01

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

2. 02

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

3. 03

   Best-sellers on product pages, trousers and co-ords as lead categories, a monthly creative bank