Fashion & apparel case study: ₹5L to ₹8.8L monthly revenue in 6 months

New ads per month

1. 1

   Research & offer · Month 1

   What we do

   We start with cash-on-delivery returns and cancellations, which the brand in this scenario named first, before anything else on this mid-sized store. We tilt orders to prepaid with a prepaid discount and a cash-on-delivery charge that covers its cost. 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.

   Why

   A mid-sized fashion brand grows monthly revenue in 6 months, from ₹5L to ₹20L (4x). Fewer than one in ten of our measured accounts grew that fast in the same time, so the case study follows the pace of that top tenth, holds budget where return starts to slip, and does not force the number. The main problem was cash-on-delivery returns and cancellations. Returned cash-on-delivery orders turn attributed revenue into a loss. No budget returns more than the store converts.

   How it works

   The prepaid offer shows on product pages and at checkout. Site fixes are handed over in the first weeks, before budget rises.

2. 2

   Measurement & reviews · Month 1 to 6

   What we do

   We set the numbers on net sales after returns and cancellations, not on logged revenue. We set the path from ₹5L to ₹20L as written monthly numbers, and read every review against the month so far. We keep a shared daily sheet with the ad platform's revenue next to real store orders.

   Why

   Its reported return on ad spend is higher than measured fashion stores of that size hold, so the case study starts there and lets part of it ease as budget grows. Returns and cancellations cut into logged revenue before it reaches the bank. A missed month shows up early instead of at the end of the case study.

   How it works

   Each review opens with net sales against the month's number. The month's number is on the page at every review. The sheet is read before each budget change.

3. 3

   Creative testing · Month 1

   What we do

   We lead the testing layer with video, catalogue ads and static image, building to a few dozen new ads a month by the final month, with carousel watched closely since it returns less than the rest. The learning month runs at a low daily budget and moves up only when orders come through. We commission ads in batches, and read each batch for a set window before ordering the next. We separate the lead products into their own campaigns and review each one weekly.

   Why

   Spend in the learning phase pays for information. A fixed window stops spend chasing a creative before it has been read. Shared campaigns hide weak products; separate ones expose them fast.

   How it works

   The low budget stays until orders confirm the buyer. Batches that do not convert are cut; winners get the 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 · Month 2 to 4

   What we do

   Through Month 2 to Month 4, we push as far toward ₹20L as return allows: the budget climbs in steps and return falls, and Instagram Reels carries the most spend and Instagram Feed the next. We pause styles with high return-to-origin and test replacement styles in their own campaigns. We let return decide budget: more while it holds, less when it slips.

   Why

   Across Month 2 to Month 4, the budget climbs in steps, and return on spend falls as it does. In measured accounts, scaling spend raised cost per order and lowered return on spend, so each step waits for return to hold. Returned cash-on-delivery orders turn attributed revenue into a loss.

   How it works

   High-RTO lines are paused and replacements tested separately. There is no fixed ramp; each month's budget follows the return of the last. Instagram Reels carries the largest share of spend in the final month, with Instagram Feed next. Prospecting to new buyers takes the bulk of spend, while retargeting returns more for each rupee.

5. 5

   Steady state · Month 5 to 6

   What we do

   From Month 5, we protect the revenue already built and move toward ₹20L where return permits. We ask for a seasonal landing page, new ad formats and delivery banners ahead of the festive peak. We use WhatsApp for abandoned checkouts and for past buyers' next order.

   Why

   Growth slows from Month 5, still short of ₹20L. Budget keeps rising, more slowly than in the scaling months. Season-specific pages convert season traffic better than the default collection. WhatsApp is cheaper than paid retargeting for buyers who already reached checkout.

   How it works

   The seasonal page is requested before the season, with the catalogue campaign. Messages run beside retargeting ads.

1. Month 1

   The learning phase opens: the first ads run on a small daily budget while tracking is checked against store orders. Store orders and ad-platform revenue are checked side by side. The prepaid offer and the cash-on-delivery charge go live.

   • Revenue ₹4.7L
   • ROAS 4.04x
   • Ad spend ₹1.2L
2. Month 2

   Scaling begins: products that do not sell are paused and budget moves to the winners. Budget steps up and return on spend falls.

   • Revenue ₹5.2L
   • ROAS 3.49x
   • Ad spend ₹1.5L
3. Month 3

   Styles with high return-to-origin are paused.

   • Revenue ₹6.1L
   • ROAS 3.06x
   • Ad spend ₹2L
4. Month 4

   Past buyers get a WhatsApp nudge for their next order.

   • Revenue ₹7.6L
   • ROAS 2.57x
   • Ad spend ₹3L
5. Month 5

   Steady phase begins: creative refresh and repeat orders take on more of the work. The budget step stops where return starts to slip: budget steps up and return on spend holds.

   • Revenue ₹8.7L
   • ROAS 2.50x
   • Ad spend ₹3.5L
6. Month 6

   The seasonal landing page is briefed ahead of the peak. The budget step stops where return starts to slip: budget holds and return on spend dips. Revenue ends below ₹20L, the number this scenario calls for, because budget stops rising where return starts to slip. Each order costs more by the end than it did while learning.

   • Revenue ₹8.8L
   • ROAS 2.34x
   • Ad spend ₹3.8L

1. 1

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

2. 2

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

3. 3

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