Fashion & apparel case study: ₹1L to ₹93,946 monthly revenue in 10 days

New ads per month

1. 1

   Research & offer · Week 1 to 2

   What we do

   We start with turning visits into orders, which the brand in this scenario named first, before anything else on this smaller store. We get the store ready for paid traffic first: reviews and trust pointers on product pages, a visible return window, an about page and a reason to pay upfront. We put best-sellers on product pages and lead with the one or two categories that already sell.

   Why

   In this case study, a smaller fashion brand grows monthly revenue in 10 days, from ₹1L to ₹10L (10x). Nine in ten of the accounts we measured grew more slowly than that in the same time; the case study is built on what the fastest tenth reached, and shows the gap to the agreed number honestly. The main problem was turning visits into orders. Conversion rate caps what any ad budget can return. Lead categories give prospecting ads a proven entry point.

   How it works

   The fix list goes to the brand's team in the opening weeks, ahead of any budget step. Lead categories carry the first scaling months.

2. 2

   Measurement & reviews · Week 1 to 4

   What we do

   We keep a shared daily sheet with the ad platform's revenue next to real store orders. We set the path from ₹1L to ₹10L as written weekly numbers, and read every review against the week so far.

   Why

   No starting return on ad spend was given; the starting return is what measured fashion stores of that size hold. Platform attribution over-counts, so budget decisions sit on the store-side number. A shortfall is caught in the week it happens, not at the end.

   How it works

   The sheet is read before each budget change. Written monthly numbers make each scaling decision explicit.

3. 3

   Creative testing · Week 1 to 4

   What we do

   We test with video, catalogue ads and static image first, rising to about two dozen new ads a month by the last four weeks, with no format far behind the account's return. We give each lead product its own campaign and read it weekly. We lead with video that carries trust: creators, customer feedback and founder-led pieces. We work in creative batches with a fixed read window each.

   Why

   A product nobody buys is visible within a week when it has its own campaign. Trust-carrying video held return in most measured accounts. Buying more before a batch is read means paying for guesses.

   How it works

   Losing products are paused within a week and budget moves to the winners. Weak UGC is swapped for founder-led video rather than scaled. Batches that do not convert are cut; winners get the budget. More spend buys more new ads, led by video ahead of catalogue ads.

4. 4

   Scaling · Week 4

   What we do

   Through Week 4, we push toward ₹10L: the budget stays close to the learning level while return holds, and Instagram Reels carries the most spend and Instagram Feed the next. We recover abandoned checkouts with WhatsApp messages as traffic grows. We tie every budget increase to return: we step up while it holds, and step back when it drops.

   Why

   Across Week 4, the budget stays close to the learning level, while return on spend holds. Each budget step here is sized so that return stays close to where it was. WhatsApp is cheaper than paid retargeting for buyers who already reached checkout.

   How it works

   WhatsApp recovery runs alongside paid retargeting, not instead of it. There is no fixed ramp; each week's budget follows the return of the last. Instagram Reels carries the largest share of spend in the last four weeks, with Instagram Feed next. Cold audiences take most of the budget; warm audiences return more per rupee.

1. Week 1

   First, the set-up: the first ads run on a small daily budget while tracking is checked against store orders. Lead categories get their own campaigns. Store orders and platform revenue are reconciled in the shared sheet.

   • Revenue ₹23,916
   • ROAS 1.92x
   • Ad spend ₹12,473
2. Week 2

   The first read of the ads is in, and the ones that do not convert stop. Return holds as the budget holds.

   • Revenue ₹23,216
   • ROAS 1.90x
   • Ad spend ₹12,212
3. Week 3

   Store fixes and offers go live while orders confirm.

   • Revenue ₹23,502
   • ROAS 1.93x
   • Ad spend ₹12,163
4. Week 4

   The learning phase ends with a buyer identified and a winning ad chosen. Return holds as the budget holds. Revenue ends below ₹10L, the number this scenario calls for, because budget stops rising where return starts to slip. Each order costs about what it did while learning.

   • Revenue ₹23,312
   • ROAS 1.97x
   • Ad spend ₹11,816

1. 1

   Run creator, customer-feedback and founder-led video; replace low-quality UGC with founder-led video when sales soften.

2. 2

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

3. 3

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