Fashion & apparel case study: ₹5L to ₹8.8L monthly revenue in 3 months

New ads per month

1. 1

   Research & offer · Month 1

   What we do

   We point the first month at creative and content, 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 3 months, from ₹5L to ₹10L (2x). 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 rather than forcing the number. The main problem in this scenario is creative and content. No budget returns more than the store converts. Lead categories give prospecting ads a proven entry point.

   How it works

   Site fixes are handed over in the first weeks, before budget rises. Lead categories carry the first scaling months.

2. 2

   Measurement & reviews · Month 1 to 3

   What we do

   We agree a written number for every month on the way from ₹5L to ₹10L, and start each review with the month-to-date figure against it. We track ad-platform revenue beside store orders in a shared daily sheet. We check the reported return on spend against store revenue before any budget moves.

   Why

   The return on ad spend it reported sits close to what measured fashion stores of that size hold, and the case study starts from it. A shortfall is caught in the month it happens, not at the end. Ad platforms claim more orders than stores record, so the store number decides budget.

   How it works

   Each budget step is argued against the written number. Budget decisions are read off store numbers, not the ad platform alone. The store-side return becomes the number every review uses.

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 lead with video that carries trust: creators, customer feedback and founder-led pieces. We work in creative batches with a fixed read window each. We brief creators for a steady run of UGC video, with regional-language cuts of the winners.

   Why

   Trust-carrying video held return in most measured accounts. A fixed window stops spend chasing a creative before it has been read. A steady supply keeps the testing layer fed, and regional cuts reach more buyers with the same idea.

   How it works

   Low-quality UGC is pulled and founder-led video takes its place. Losing batches stop; winning ads take their budget. Winning UGC is cut into regional languages before new ideas are bought. New ads rise with the budget, most of them video, then catalogue ads.

4. 4

   Scaling · Month 2 to 3

   What we do

   Through Month 2 to Month 3, we push as far toward ₹10L as return allows: the budget climbs in steps and return falls, and Instagram Reels carries the most spend and Instagram Feed the next. We test cost caps, bid caps and CBO against ABO side by side before each budget step. We recover abandoned checkouts with WhatsApp messages as traffic grows.

   Why

   In Month 2 to Month 3 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. Parallel controls reveal which setup keeps cost per purchase down as spend grows.

   How it works

   Controls run as parallel versions and the one that holds cost is kept. WhatsApp recovery runs alongside paid retargeting, not instead of it. Most of the final month's spend sits on Instagram Reels, then Instagram Feed. Cold audiences take most of the budget; warm audiences return more per rupee.

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 ad-platform revenue are checked side by side. Lead categories get their own campaigns.

   • Revenue ₹5.1L
   • ROAS 2.94x
   • Ad spend ₹1.7L
2. Month 2

   The scaling phase opens: the creative batch is read and the winners keep the budget. With budget steps up, return on spend dips.

   • Revenue ₹6.7L
   • ROAS 2.68x
   • Ad spend ₹2.5L
3. Month 3

   Bid-cap and cost-cap versions run beside open bidding. With budget steps up sharply, return on spend falls. Halfway from ₹5L to ₹10L is passed. Revenue ends below ₹10L, the number this scenario calls for, because the case study follows what the fastest tenth of our measured accounts reached. Cost per purchase ends higher than in the learning phase.

   • Revenue ₹8.8L
   • ROAS 2.27x
   • Ad spend ₹3.9L

1. 1

   Put best-sellers on product pages, lead with the one or two categories that sell, and keep a monthly creative bank.

2. 2

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

3. 3

   Run creator, customer-feedback and founder-led video; replace low-quality UGC with founder-led video when sales soften.