Other case study: ₹1L to ₹1.8L monthly revenue in 2 months

New ads per month

1. 1

   Research & offer · Week 1 to 2

   What we do

   We open with set-up work on the smaller store, since the brand in this scenario named no single problem. We put the website audit, the creative brief and the monthly media schedule in place before spend moves. We fix the store before scaling: trust pointers, reviews, a clear return window, an about page and a prepaid incentive.

   Why

   A smaller store grows monthly revenue in 2 months, from ₹1L to ₹6L–₹8L (7x). Nine in ten of the accounts we measured grew more slowly than that in the same time; the case study is built on what the fastest tenth reached, and shows the gap to the agreed number honestly. The brand in this scenario named no single problem, so the case study starts from the numbers. Without a brief, each creative and budget decision starts from scratch. Conversion rate caps what any ad budget can return.

   How it works

   All three are shared with the brand's team before any budget step. Fixes are listed and handed over early, so later budget lands on a store that converts.

2. 2

   Measurement & reviews · Week 1 to 9

   What we do

   We track ad-platform revenue beside store orders in a shared daily sheet. We set the path from ₹1L to ₹6L–₹8L as written weekly numbers, and read every review against the week so far. We set a written rule: no budget step in a week where return falls too far to pay for it.

   Why

   It did not report a return on ad spend, so the case study starts from what measured stores of that size hold. Platform attribution over-counts, so budget decisions sit on the store-side number. A shortfall is caught in the week it happens, not at the end.

   How it works

   Budget decisions are read off store numbers, not the ad platform alone. Written monthly numbers make each scaling decision explicit. A week whose return starts to slip past that point keeps its budget instead.

3. 3

   Creative testing · Week 1 to 4

   What we do

   We lead the testing layer with video, catalogue ads and carousel, building to about two dozen new ads a month by the last four weeks, keeping carousel on a short leash because its return trails the account. The four learning weeks run on a small daily budget, stepping up only once orders confirm. We make trust the subject of the video: creator reels, customer feedback and founder-led clips. We work in creative batches with a fixed read window each.

   Why

   Early spend buys learning, not scale. In most accounts we measured, video that carried trust held its return. A fixed window stops spend chasing a creative before it has been read.

   How it works

   The low budget stays until orders confirm the buyer. UGC that underperforms is replaced by founder-led video, not given more budget. Batches that do not convert are cut; winners get the budget. The number of new ads grows with spend; video makes up the largest part and catalogue ads the next.

4. 4

   Scaling · Week 5 to 9

   What we do

   Through Week 5 to Week 9, we push toward ₹6L–₹8L: the budget climbs in steps while return holds, and Instagram Reels carries the most spend and Instagram Feed the next. We tie every budget increase to return: we step up while it holds, and step back when it drops. Once purchases are steady, we add lookalikes of past buyers next to broad prospecting.

   Why

   Across Week 5 to Week 9, the budget climbs in steps, while return on spend holds. Four of these weeks stop their budget step where return starts to slip too far. Each budget step here is sized so that return stays close to where it was. Past buyers are the clearest signal of who buys next.

   How it works

   Budget follows return week to week instead of a fixed ramp. Lookalikes are read against broad on the same creative. Most of the last four weeks's spend sits on Instagram Reels, then Instagram Feed. Cold audiences take most of the budget; warm audiences return more per rupee.

1. Week 1

   The learning phase opens: tracking is checked against store orders and the first ads go live on a small daily budget. The daily sheet now matches platform revenue to store orders. The website audit, creative brief and media schedule are shared.

   • Revenue ₹24,063
   • ROAS 1.95x
   • Ad spend ₹12,310
2. Week 2

   First creative read: ads that do not convert are cut. Return dips as the budget holds.

   • Revenue ₹23,697
   • ROAS 1.86x
   • Ad spend ₹12,750
3. Week 3

   Store fixes and offers go live while orders confirm.

   • Revenue ₹24,618
   • ROAS 1.86x
   • Ad spend ₹13,252
4. Week 4

   Learning phase closes: the buyer found and the winning creative picked.

   • Revenue ₹24,378
   • ROAS 1.91x
   • Ad spend ₹12,735
5. Week 5

   Scaling starts: the budget decision is taken on the return the last step earned. Return holds as the budget steps up.

   • Revenue ₹28,357
   • ROAS 1.93x
   • Ad spend ₹14,676
6. Week 6

   A past-buyer lookalike audience joins broad prospecting. Only the part of the step that return supports is taken: return holds as the budget steps up.

   • Revenue ₹41,072
   • ROAS 1.89x
   • Ad spend ₹21,743
7. Week 7

   This batch's read is done: winners stay, the rest are cut. Only the part of the step that return supports is taken: return rises as the budget holds.

   • Revenue ₹44,230
   • ROAS 1.98x
   • Ad spend ₹22,389
8. Week 8

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

   • Revenue ₹44,610
   • ROAS 1.90x
   • Ad spend ₹23,437
9. Week 9

   Each budget move is read against the return it bought. Only the part of the step that return supports is taken: return holds as the budget holds. ₹6L–₹8L is not reached in the time, because budget stops rising where return starts to slip. Cost per purchase ends close to the learning phase.

   • Revenue ₹47,498
   • ROAS 1.88x
   • Ad spend ₹25,266

1. 1

   Video carries most creative spend in this industry's measured accounts.

2. 2

   Add static images beside video once a winning video is found.

3. 3

   Audited eight competitors and agreed a three-month case study