Fashion & apparel case study: ₹5L to ₹11.3L 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 return on ad spend, so the opening month on this mid-sized store goes there. 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 run short, dated bundle sales with an awareness lead-in instead of permanent discounts.

   Why

   A mid-sized fashion brand grows monthly revenue in 6 months, from ₹5L to ₹50L (10x). 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 was return on ad spend. Conversion rate caps what any ad budget can return. A dated offer concentrates demand without training buyers to wait for a sale.

   How it works

   Fixes are listed and handed over early, so later budget lands on a store that converts. Awareness ads run ahead of each short sale window.

2. 2

   Measurement & reviews · Month 1 to 6

   What we do

   We log store orders every day beside what the ad platform claims. We agree a written number for every month on the way from ₹5L to ₹50L, and start each review with the month-to-date figure against it. We set the numbers on net sales after returns and cancellations, not on logged revenue.

   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. A shortfall is caught in the month 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. Each review opens with net sales against the month's number.

3. 3

   Creative testing · Month 1

   What we do

   We test with video, catalogue ads and static image first, rising to a few dozen new ads a month by the final month, keeping carousel on a short leash because its return trails the account. We run every lead product in a campaign of its own, read every week. The learning month runs on a small daily budget, stepping up only once orders confirm. We run static images next to the video ads.

   Why

   A product nobody buys is visible within a week when it has its own campaign. Spend in the learning phase pays for information. In measured fashion accounts, video reached the top creative tier most often.

   How it works

   Losing products are paused within a week and budget moves to the winners. Only confirmed orders at the low budget unlock the next step. Statics are added after a video wins. New ads rise with the budget, most of them video, then catalogue ads.

4. 4

   Scaling · Month 2 to 4

   What we do

   We scale through Month 2 to Month 4 toward ₹50L as the budget climbs in steps and return falls, with Instagram Feed taking the largest share of spend and Instagram Reels the next. We tie every budget increase to return: we step up while it holds, and step back when it drops. We test cost caps, bid caps and CBO against ABO side by side before each budget step.

   Why

   In Month 2 to Month 4 the budget climbs in steps, and return on spend falls as it does. In two of these months the step is trimmed to the size return can hold. Spend scaled in our measured accounts pushed cost per order up and return down, so no step is taken on hope. Parallel controls reveal which setup keeps cost per purchase down as spend grows.

   How it works

   Budget follows return month to month instead of a fixed ramp. The version that keeps cost per purchase lowest stays. In the final month, Instagram Feed takes the most spend and Instagram Reels the next most. 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 ₹50L where return permits. We hold budget where return peaks instead of pushing past it. We hold a creative bank and swap tired ads out before click-through falls.

   Why

   Growth slows from Month 5, still short of ₹50L. Spend still grows, at a slower pace than during scaling. Most of our engagements saw return fall back from its best month. Falling click-through preceded a revenue drop in a measured account, so creative refresh is not optional.

   How it works

   Budget stays at the level of the best return and is trimmed when it slips. Refreshes are gradual: a few new ads at a time.

1. Month 1

   First, the set-up: the first ads run on a small daily budget while tracking is checked against store orders. Store orders and platform revenue are reconciled in the shared sheet. Reviews, trust pointers and the prepaid incentive are now on the store.

   • Revenue ₹5L
   • ROAS 3.48x
   • Ad spend ₹1.4L
2. Month 2

   Scaling begins: the weekly product read pauses the products that are not selling. Budget steps up sharply and return on spend falls.

   • Revenue ₹7.2L
   • ROAS 2.93x
   • Ad spend ₹2.5L
3. Month 3

   Tired ads are refreshed from the creative bank. Only the part of the step that return supports is taken: budget steps up sharply and return on spend steps up sharply.

   • Revenue ₹10.7L
   • ROAS 2.39x
   • Ad spend ₹4.5L
4. Month 4

   The creative bank supplies this period's refresh. Only the part of the step that return supports is taken: budget holds and return on spend holds.

   • Revenue ₹11.5L
   • ROAS 2.48x
   • Ad spend ₹4.6L
5. Month 5

   The case study moves into its steady phase, leaning on refreshed ads and repeat buyers.

   • Revenue ₹11.4L
   • ROAS 2.40x
   • Ad spend ₹4.8L
6. Month 6

   The budget decision is taken on the return the last step earned. Only the part of the step that return supports is taken: budget holds and return on spend dips. ₹50L is not reached in the time, because budget stops rising where return starts to slip. Each order costs more by the end than it did while learning.

   • Revenue ₹11.3L
   • ROAS 2.29x
   • Ad spend ₹5L

1. 1

   Launched a wedding-season catalogue campaign and a dedicated scaling campaign

2. 2

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

3. 3

   Test bidding controls (cost caps, bid caps, CBO against ABO) side by side before scaling.