Fashion & apparel case study: ₹1L to ₹1.6L monthly revenue in 4–5 months

New ads per month

1. 1

   Research & offer · Month 1

   What we do

   We point the first month at reaching new buyers, the brand’s main problem, on a smaller base. We run short, dated bundle sales with an awareness lead-in instead of permanent discounts. We mark the festive and wedding dates first and have seasonal collections ready ahead of them.

   Why

   In this case study, a smaller fashion brand grows monthly revenue in 4–5 months, from ₹1L to ₹3L (3x). That is faster than nine in ten of our measured accounts grew over the same time, so the case study below is on what that fastest tenth reached and shows where it lands against the number this scenario calls for. The main problem in this scenario is reaching new buyers. A dated offer concentrates demand without training buyers to wait for a sale. Demand in this category rises and falls with the festive calendar.

   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 5

   What we do

   We log store orders every day beside what the ad platform claims. We set the path from ₹1L to ₹3L 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. The ad platform's own count runs high, so the store's count is the one that moves budget. Written monthly numbers expose a slow month while there is still time to act.

   How it works

   The sheet is read before each budget change. 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 lead the testing layer with video, catalogue ads and carousel, building to about two dozen new ads a month by the final month, with carousel watched closely since it returns less than the rest. We separate the lead products into their own campaigns and review each one weekly. We test static images beside video. The learning month runs on a small daily budget, stepping up only once orders confirm.

   Why

   Products that do not sell show up inside a week, not after a month of shared budget. In measured fashion accounts, video reached the top creative tier most often. The first rupees are for finding the buyer, not for volume.

   How it works

   A product that does not sell is paused inside the week. Statics are added after a video wins. Only confirmed orders at the low budget unlock the next step. More spend buys more new ads, led by video ahead of catalogue ads.

4. 4

   Scaling · Month 2 to 3

   What we do

   We scale through Month 2 to Month 3 as far toward ₹3L 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. We scale into the festive and wedding calendar with seasonal collection campaigns. Once purchases are steady, we add lookalikes of past buyers next to broad prospecting.

   Why

   Across Month 2 to Month 3, the budget rises gently, while return on spend holds. Return holds through these months because each budget step stops where return starts to slip. Demand is seasonal and regional, so spend moves with the calendar.

   How it works

   Budget moves between regions as the calendar turns. Lookalikes are read against broad on the same creative. 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 4 to 5

   What we do

   From Month 4, we hold the gains and push toward ₹3L 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 4 growth slows while revenue is still under ₹3L. Spend still grows, at a slower pace than during scaling. Season-specific pages convert season traffic better than the default collection. An order from a returning buyer costs the least.

   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: tracking is checked against store orders and the first ads go live on a small daily budget. Store orders and platform revenue are reconciled in the shared sheet. The next festive collection is briefed and ready.

   • Revenue ₹99,972
   • ROAS 1.93x
   • Ad spend ₹51,877
2. Month 2

   The scaling phase opens: a past-buyer lookalike audience joins broad prospecting. Spend holds, and return holds.

   • Revenue ₹1.1L
   • ROAS 1.99x
   • Ad spend ₹54,463
3. Month 3

   The seasonal landing page is briefed ahead of the peak. Spend steps up, and return holds.

   • Revenue ₹1.5L
   • ROAS 1.97x
   • Ad spend ₹75,088
4. Month 4

   The case study moves into its steady phase, leaning on refreshed ads and repeat buyers. The step is sized by what return can bear: spend holds, and return holds.

   • Revenue ₹1.5L
   • ROAS 1.90x
   • Ad spend ₹81,456
5. Month 5

   Statics go live next to the winning video. The step is sized by what return can bear: spend holds, and return holds. Revenue ends below ₹3L, 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 ₹1.6L
   • ROAS 1.87x
   • Ad spend ₹86,515

1. 1

   Find the buyer on a small daily budget first, then step spend up in stages.

2. 2

   Build around the festive and wedding calendar: seasonal catalogue or collection campaigns, regional audiences for regional festivals, and pausing regions during regional observances.

3. 3

   Read Meta against Shopify every week