Fashion & apparel case study: ₹38L to ₹59.8L monthly revenue in 12 months

New ads per month

1. 1

   Research & offer · Month 1

   What we do

   The first problem in this scenario is creative and content, so the opening month on this established store goes there. We split the account into layers: one campaign to test creative, one to scale winners, prospecting that leaves out past buyers, and retargeting for carts. 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

   An established fashion brand grows monthly revenue in 12 months, from ₹38L to ₹1Cr (2.6x). 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 was creative and content, followed by competition. Separate layers stop prospecting and retargeting competing for the same budget. Conversion rate caps what any ad budget can return.

   How it works

   Retargeting sits next to prospecting and never replaces it. The fix list goes to the brand's team in the opening weeks, ahead of any budget step. Awareness ads run ahead of each short sale window.

2. 2

   Measurement & reviews · Month 1 to 12

   What we do

   We agree a written number for every month on the way from ₹38L to ₹1Cr, and start each review with the month-to-date figure against it. We track ad-platform revenue beside store revenue and net sales after returns, cancellations and tax. We reconcile the return on spend the brand in this scenario reports with store revenue before the first budget change.

   Why

   Its reported return on ad spend is under what measured fashion stores of that size hold; the case study begins from it and rebuilds return first. A shortfall is caught in the month it happens, not at the end. In measured accounts net sales ran below logged store revenue, so the numbers sit on the lower figure.

   How it works

   Each budget step is argued against the written number. Budget decisions are read off net sales, not the ad platform alone. The reported return and the store-side return are read side by side every week.

3. 3

   Creative testing · Month 1

   What we do

   We lead the testing layer with video, catalogue ads and static image, building to several dozen new ads a month by the final month, with carousel watched closely since it returns less than the rest. We make trust the subject of the video: creator reels, customer feedback and founder-led clips. We commission ads in batches, and read each batch for a set window before ordering the next. We brief creators for a steady run of UGC video, with regional-language cuts of the winners.

   Why

   In most accounts we measured, video that carried trust held its return. Buying more before a batch is read means paying for guesses. A steady supply keeps the testing layer fed, and regional cuts reach more buyers with the same idea.

   How it works

   Weak UGC is swapped for founder-led video rather than scaled. Losing batches stop; winning ads take their budget. Winning UGC is cut into regional languages before new ideas are bought. 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 9

   What we do

   We scale through Month 2 to Month 9 as far toward ₹1Cr as return allows as the budget rises gently and return dips, with Instagram Reels taking the largest share of spend and Instagram Feed the next. We cut budgets during major marketplace sale events and move spend to narrower premium audiences. We raise budget only while return on spend holds, and cut it when return drops. We run cost caps, bid caps, CBO and ABO as parallel versions before budget steps up.

   Why

   Across Month 2 to Month 9, the budget rises gently, and return on spend dips. Spend scaled in our measured accounts pushed cost per order up and return down, so no step is taken on hope. Marketplace sales inflate auction costs and pull price-led buyers away.

   How it works

   Spend is reduced and redirected for each event window. There is no fixed ramp; each month's budget follows the return of the last. Controls run as parallel versions and the one that holds cost is kept. In the final month, Instagram Reels takes the most spend and Instagram Feed the next most. Prospecting to new buyers takes the bulk of spend, while retargeting returns more for each rupee.

5. 5

   Steady state · Month 10 to 12

   What we do

   From Month 10, we protect the revenue already built and move toward ₹1Cr where return permits. We ask for a seasonal landing page, new ad formats and delivery banners ahead of the festive peak. We refresh tired ads by mixing old and new creatives, and keep a creative bank.

   Why

   From Month 10 growth slows while revenue is still under ₹1Cr. Spend holds roughly steady from here. Season-specific pages convert season traffic better than the default collection. Falling click-through preceded a revenue drop in a measured account, so creative refresh is not optional.

   How it works

   The seasonal page is requested before the season, with the catalogue campaign. New creatives mix with proven ones rather than replacing them all at once.

1. Month 1

   The learning phase opens: a small daily budget carries the first ads, and store orders are matched to tracking. Net sales are reconciled against logged revenue. Store fixes go live: reviews, trust pointers and the prepaid offer.

   • Revenue ₹38.2L
   • ROAS 2.72x
   • Ad spend ₹14.1L
2. Month 2

   Scaling starts: the creative batch is read and the winners keep the budget. Return on spend rises while budget holds.

   • Revenue ₹39.1L
   • ROAS 2.88x
   • Ad spend ₹13.6L
3. Month 3

   Bid-cap and cost-cap versions run beside open bidding.

   • Revenue ₹39.3L
   • ROAS 2.94x
   • Ad spend ₹13.4L
4. Month 4

   Regional-language cuts of the winning UGC go live.

   • Revenue ₹40.8L
   • ROAS 3.06x
   • Ad spend ₹13.3L
5. Month 5

   During a marketplace sale window, spend moves to narrower premium audiences. Return on spend dips while budget steps up.

   • Revenue ₹44.6L
   • ROAS 2.89x
   • Ad spend ₹15.4L
6. Month 6

   Ads with falling click-through are swapped from the bank. Return on spend rises while budget holds.

   • Revenue ₹44.9L
   • ROAS 3.02x
   • Ad spend ₹14.9L
7. Month 7

   New creator and customer-feedback videos join the account. Return on spend dips while budget steps up.

   • Revenue ₹49.1L
   • ROAS 2.87x
   • Ad spend ₹17.1L
8. Month 8

   The seasonal landing page is briefed ahead of the peak. Return on spend holds while budget holds.

   • Revenue ₹51.9L
   • ROAS 2.76x
   • Ad spend ₹18.8L
9. Month 9

   The budget decision is taken on the return the last step earned. Return on spend dips while budget steps up.

   • Revenue ₹56.1L
   • ROAS 2.53x
   • Ad spend ₹22.2L
10. Month 10

    From here the work shifts to keeping ads fresh and bringing buyers back. Return on spend holds while budget holds.

    • Revenue ₹58.6L
    • ROAS 2.57x
    • Ad spend ₹22.8L
11. Month 11

    The creative batch is read and the winners keep the budget.

    • Revenue ₹59.1L
    • ROAS 2.61x
    • Ad spend ₹22.6L
12. Month 12

    Bid-cap and cost-cap versions run beside open bidding. Return on spend holds while budget holds. Revenue ends below ₹1Cr, the number this scenario calls for, because the case study follows what the fastest tenth of our measured accounts reached. Cost per purchase ends close to the learning phase.

    • Revenue ₹59.8L
    • ROAS 2.59x
    • Ad spend ₹23.1L

1. 1

   Run Google Search and Shopping beside Meta, and use Google's demand data to shape Meta.

2. 2

   Run short bundle sales with an awareness lead-in rather than permanent discounts.

3. 3

   We cut budgets during major marketplace sale events and move spend to narrower premium audiences.