Fashion & apparel case study: ₹3L to ₹6.3L monthly revenue in 10 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 smaller 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 put best-sellers on product pages and lead with the one or two categories that already sell. We run short, dated bundle sales with an awareness lead-in instead of permanent discounts.

   Why

   In this case study, a smaller fashion brand grows monthly revenue in 10 months, from ₹3L to ₹10L (3.3x). 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 creative and content, followed by scaling ad spend. Layers keep each budget line readable, so a weak campaign cannot hide inside a strong one. Lead categories give prospecting ads a proven entry point.

   How it works

   Retargeting sits next to prospecting and never replaces it. Lead categories carry the first scaling months. Awareness ads run ahead of each short sale window.

2. 2

   Measurement & reviews · Month 1 to 10

   What we do

   We write month-by-month revenue numbers with the brand's team that climb from ₹3L to ₹10L, and open every review with the month-to-date number against them. We keep a shared daily sheet with the ad platform's revenue next to real store orders. We match the return the brand in this scenario reports to what the store actually took in, before touching budget.

   Why

   Its reported return on ad spend is in line with what measured fashion stores of that size hold, so the case study starts there. Written monthly numbers expose a slow month while there is still time to act. Ad platforms claim more orders than stores record, so the store number decides budget.

   How it works

   Written monthly numbers make each scaling decision explicit. Budget decisions are read off store numbers, not the ad platform alone. Both returns are reviewed together each week.

3. 3

   Creative testing · Month 1

   What we do

   We test with video, catalogue ads and static image first, rising to about two dozen new ads a month by the final month, with carousel watched closely since it returns less than the rest. 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 keep creators producing UGC video on a steady schedule, and cut the winners into regional languages.

   Why

   In most accounts we measured, video that carried trust held its return. The read window keeps creative spending tied to evidence. 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. Batches that do not convert are cut; winners get the budget. Winning UGC is cut into regional languages before new ideas are bought. More spend buys more new ads, led by video ahead of catalogue ads.

4. 4

   Scaling · Month 2 to 7

   What we do

   Through Month 2 to Month 7, 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 let return decide budget: more while it holds, less when it slips. We scale into the festive and wedding calendar with seasonal collection campaigns. We pause styles with high return-to-origin and test replacement styles in their own campaigns.

   Why

   In Month 2 to Month 7 the budget climbs in steps, and return on spend falls as it does. Spend scaled in our measured accounts pushed cost per order up and return down, so no step is taken on hope. Seasonal demand moves by region, so the spend does too.

   How it works

   Each month's budget is set by the return the last one earned. Budget moves between regions as the calendar turns. High-RTO lines are paused and replacements tested separately. In the final month, Instagram Reels takes the most spend and Instagram Feed the next most. Cold audiences take most of the budget; warm audiences return more per rupee.

5. 5

   Steady state · Month 8 to 10

   What we do

   From Month 8, we hold the gains and push toward ₹10L only as far as return allows. We keep a bank of ready creatives and rotate them in as ads tire. We recover abandoned checkouts and lift repeat orders with WhatsApp messages.

   Why

   From Month 8 growth slows while revenue is still under ₹10L. Spend still grows, at a slower pace than during scaling. A measured account showed click-through falling ahead of revenue, so tired ads are replaced early. A message to someone who nearly bought costs less than an ad.

   How it works

   Refreshes are gradual: a few new ads at a time. Messages run beside retargeting ads.

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 platform revenue are reconciled in the shared sheet. The reported return is checked against the store-side return.

   • Revenue ₹2.9L
   • ROAS 2.54x
   • Ad spend ₹1.1L
2. Month 2

   The scaling phase opens: the winning UGC runs in regional-language versions. Return on spend dips while budget steps up.

   • Revenue ₹3.1L
   • ROAS 2.30x
   • Ad spend ₹1.3L
3. Month 3

   This batch's read is done: winners stay, the rest are cut.

   • Revenue ₹3.4L
   • ROAS 2.24x
   • Ad spend ₹1.5L
4. Month 4

   Styles with high return-to-origin are paused. Return on spend holds while budget holds.

   • Revenue ₹3.5L
   • ROAS 2.25x
   • Ad spend ₹1.6L
5. Month 5

   Tired ads are refreshed from the creative bank. Return on spend rises while budget steps up.

   • Revenue ₹4.1L
   • ROAS 2.36x
   • Ad spend ₹1.7L
6. Month 6

   Budget is reviewed against return before the next step.

   • Revenue ₹4.5L
   • ROAS 2.24x
   • Ad spend ₹2L
7. Month 7

   Repeat-order messages go to past buyers.

   • Revenue ₹5.4L
   • ROAS 2.09x
   • Ad spend ₹2.6L
8. Month 8

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

   • Revenue ₹5.8L
   • ROAS 2.10x
   • Ad spend ₹2.8L
9. Month 9

   A fresh round of creator and customer-feedback video goes live.

   • Revenue ₹6.3L
   • ROAS 2.13x
   • Ad spend ₹3L
10. Month 10

    A seasonal collection campaign takes a larger share of budget. Return on spend rises while budget holds. The case study finishes short of ₹10L: the case study follows what the fastest tenth of our measured accounts reached. Each order costs more by the end than it did while learning.

    • Revenue ₹6.3L
    • ROAS 2.24x
    • Ad spend ₹2.8L

1. 1

   Meta in four layers: creative testing, scaling, mid-funnel and catalogue retargeting

2. 2

   Rebuilt the account: a new-audience campaign excluding past audiences, past-buyer retargeting, one campaign per winning product

3. 3

   Store revenue per rupee of ad spend fell from 8.2x to 5.5x as monthly spend nearly doubled