Fashion & apparel case study: ₹20,000 to ₹23,777 monthly revenue in 6 months

New ads per month

1. 1

   Research & offer · Month 1

   What we do

   The first problem in this scenario is reaching new buyers, so the opening month on this smaller store goes there. We run short, dated bundle sales with an awareness lead-in instead of permanent discounts. We map the festive and wedding calendar before spending, with seasonal collections ready in advance.

   Why

   In this case study, a smaller fashion brand grows monthly revenue in 6 months, from ₹20,000 to ₹20L (100x). 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 reaching new buyers. A dated offer concentrates demand without training buyers to wait for a sale. Buyers in this category shop around festivals and weddings.

   How it works

   Awareness ads run ahead of each short sale window. Seasonal campaigns are prepared ahead of each peak.

2. 2

   Measurement & reviews · Month 1 to 6

   What we do

   We log store orders every day beside what the ad platform claims. We set the path from ₹20,000 to ₹20L as written monthly numbers, and read every review against the month so far. We set a written rule: no budget step in a month where return falls too far to pay for it.

   Why

   No starting return on ad spend was given; the starting return is 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. The month's number is on the page at every review. A month whose return slips past that point keeps its budget instead.

3. 3

   Creative testing · Month 1

   What we do

   We test with catalogue ads, video and static image first, rising to a handful of new ads a month by the final month, 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 run static images next to the video ads.

   Why

   Products that do not sell show up inside a week, not after a month of shared budget. In most accounts we measured, video that carried trust held its return. Among the fashion accounts we measured, video was the format most often in the top creative tier.

   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. Statics join once a winning video is found. New ads rise with the budget, most of them catalogue ads, then video.

4. 4

   Scaling · Month 2 to 4

   What we do

   We scale through Month 2 to Month 4 toward ₹20L as the budget rises gently and return dips, with Instagram Reels taking the largest share of spend and Instagram Feed the next. Once purchases are steady, we add lookalikes of past buyers next to broad prospecting. We put seasonal collection campaigns in front of each festive and wedding peak.

   Why

   Across Month 2 to Month 4, the budget rises gently, and return on spend dips. In three of these months the step is trimmed to the size return can hold. Our measured accounts saw cost per order rise and return fall as spend scaled; that is why each step here waits on return. Past buyers are the clearest signal of who buys next.

   How it works

   Lookalikes are read against broad on the same creative. Budget moves between regions as the calendar turns. Most of the final month's spend sits on Instagram Reels, then Instagram Feed. Most spend reaches people who have not bought yet; past visitors return more per rupee.

5. 5

   Steady state · Month 5 to 6

   What we do

   From Month 5, we hold the gains and push toward ₹20L only as far as return allows. We ask for a seasonal landing page, new ad formats and delivery banners ahead of the festive peak. We show new arrivals to past buyers first, and build lookalikes from the ones who came back.

   Why

   From Month 5 growth slows while revenue is still under ₹20L. Spend holds roughly steady from here. Season-specific pages convert season traffic better than the default collection. Repeat buyers are the cheapest orders an account gets.

   How it works

   The seasonal page is requested before the season, with the catalogue campaign. Past buyers see new arrivals before anyone else.

1. Month 1

   The learning phase opens: the first ads run on a small daily budget while tracking is checked against store orders. The next festive collection is briefed and ready. Awareness ads open ahead of a short bundle sale.

   • Revenue ₹19,369
   • ROAS 1.99x
   • Ad spend ₹9,729
2. Month 2

   Scaling starts: the seasonal collection campaign leads this period's spend mix. Budget rises to the point where return starts to give way: spend steps up, and return holds.

   • Revenue ₹22,433
   • ROAS 1.92x
   • Ad spend ₹11,679
3. Month 3

   The seasonal landing page is briefed ahead of the peak. Budget rises to the point where return starts to give way: spend holds, and return holds.

   • Revenue ₹23,453
   • ROAS 1.94x
   • Ad spend ₹12,082
4. Month 4

   Budget shifts to the products that sold this period.

   • Revenue ₹23,526
   • ROAS 1.91x
   • Ad spend ₹12,330
5. Month 5

   From here the work shifts to keeping ads fresh and bringing buyers back.

   • Revenue ₹23,596
   • ROAS 1.91x
   • Ad spend ₹12,343
6. Month 6

   New arrivals go to past buyers first. Budget rises to the point where return starts to give way: spend holds, and return holds. Revenue ends below ₹20L, the number this scenario calls for, because budget stops rising where return starts to slip. Cost per purchase ends close to the learning phase.

   • Revenue ₹23,777
   • ROAS 1.90x
   • Ad spend ₹12,506

1. 1

   We pause styles with high return-to-origin and test replacement styles in their own campaigns.

2. 2

   Read Meta against Shopify every week

3. 3

   Net sales ran below logged store revenue after returns, cancellations and tax.