Fashion & apparel case study: ₹10L+ to ₹19.3L monthly revenue in 6 months

New ads per month

1. 1

   Research & offer · Month 1

   What we do

   We focus the first month on turning visits into orders, the brand’s main problem, on a mid-sized base. We fix the store before scaling: trust pointers, reviews, a clear return window, an about page and a prepaid incentive. We put best-sellers on product pages and lead with the one or two categories that already sell.

   Why

   A mid-sized fashion brand grows monthly revenue in 6 months, from ₹10L+ to ₹30L+ (3x). The main problem is turning visits into orders, with marketing and social presence close behind. 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 · Month 1 to 6

   What we do

   We track ad-platform revenue beside store orders in a shared daily sheet. We set the path from ₹10L+ to ₹30L+ as written monthly numbers, and read every review against the month so far.

   Why

   It did not report a return on ad spend, so the case study starts from what 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

   Every budget call starts from the store's orders. Written monthly numbers make each scaling decision explicit.

3. 3

   Creative testing · Month 1

   What we do

   We test with video, catalogue ads and static image first, rising to several dozen new ads a month by the final month, keeping carousel on a short leash because its return trails the account. We separate the lead products into their own campaigns and review each one weekly. We make trust the subject of the video: creator reels, customer feedback and founder-led clips. We test static images beside video.

   Why

   Shared campaigns hide weak products; separate ones expose them fast. Video built on trust was the format that held return in most of our accounts. In our fashion accounts, video reached the top creative tier most often.

   How it works

   A product that does not sell is paused inside the week. Low-quality UGC is pulled and founder-led video takes its place. 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

   Through Month 2 to Month 4, we push as far toward ₹30L+ as return allows: the budget rises gently and return falls, and Instagram Reels carries the most spend and Instagram Feed the next. We recover abandoned checkouts with WhatsApp messages as traffic grows. We test cost caps, bid caps and CBO against ABO side by side before each budget step.

   Why

   Across Month 2 to Month 4, the budget rises gently, and return on spend falls as it does. Our accounts saw cost per order rise and return fall as spend scaled; that is why each step here waits on return. 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. The version that keeps cost per purchase lowest stays. 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 ₹30L+ 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 use WhatsApp for abandoned checkouts and for past buyers' next order.

   Why

   From Month 5 growth slows while revenue is still under ₹30L+. Spend still grows, at a slower pace than during scaling. Season-specific pages convert season traffic better than the default collection. A message to someone who nearly bought costs less than an ad.

   How it works

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

1. Month 1

   Learning month: a small daily budget carries the first ads, and store orders are matched to tracking. Store orders and ad-platform revenue are checked side by side. Lead categories get their own campaigns.

   • Revenue ₹10.7L
   • ROAS 3.84x
   • Ad spend ₹2.8L
2. Month 2

   The scaling phase opens: a fresh round of creator and customer-feedback video goes live. Return holds as the budget holds.

   • Revenue ₹10.8L
   • ROAS 3.73x
   • Ad spend ₹2.9L
3. Month 3

   The seasonal landing page is briefed ahead of the peak. Return dips as the budget steps up.

   • Revenue ₹12.6L
   • ROAS 3.45x
   • Ad spend ₹3.7L
4. Month 4

   Repeat-order messages go to past buyers.

   • Revenue ₹15.9L
   • ROAS 3.37x
   • Ad spend ₹4.7L
5. Month 5

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

   • Revenue ₹18.7L
   • ROAS 3.00x
   • Ad spend ₹6.2L
6. Month 6

   Abandoned checkouts get WhatsApp follow-ups. Return rises as the budget holds. Revenue ends below ₹30L+, the number the brand set. Each order costs more by the end than it did while learning.

   • Revenue ₹19.3L
   • ROAS 3.18x
   • Ad spend ₹6.1L

1. 1

   Tested each colour of the lead product in its own campaign

2. 2

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

3. 3

   SEO alongside: product titles, collection copy, feed and technical audit