Beauty & skincare case study: ₹8L to ₹13.5L monthly revenue in 45 days

New ads per month

1. 1

   Research & offer · Week 1 to 2

   What we do

   We start with creative and content, which the brand in this scenario named first, before anything else on this mid-sized store. We set basket-size offers that reward a second and third item in the cart. Before budget rises, we close the gaps that stop a visitor buying: missing reviews, an unclear return window, no about page and no prepaid incentive.

   Why

   A mid-sized beauty and skincare brand grows monthly revenue in 45 days, from ₹8L to ₹30L (3.8x). 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 in this scenario is creative and content. Each extra item in a basket is revenue the ad has already paid for. Conversion rate caps what any ad budget can return.

   How it works

   Offers are tuned to the order values that already sell. Site fixes are handed over in the first weeks, before budget rises.

2. 2

   Measurement & reviews · Week 1 to 7

   What we do

   We keep a shared daily sheet with the ad platform's revenue next to real store orders. We set the path from ₹8L to ₹30L as written weekly numbers, and read every review against the week so far. We read results in three-to-four-day windows, since the case study runs week by week.

   Why

   Its reported return on ad spend is in line with what measured stores of that size hold, so the case study starts there. The ad platform's own count runs high, so the store's count is the one that moves budget. A shortfall is caught in the week it happens, not at the end.

   How it works

   The sheet is read before each budget change. Each budget step is argued against the written number. Each window is read on purchases and cost per purchase before the next move.

3. 3

   Creative testing · Week 1 to 4

   What we do

   We lead the testing layer with video, static image and catalogue ads, building to several dozen new ads a month by the last four weeks, keeping carousel on a short leash because its return trails the account. We run creator, customer-feedback and founder-led video. 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. Buying more before a batch is read means paying for guesses. Regular UGC keeps testing going, and a regional cut stretches a winning idea further.

   How it works

   Weak UGC is swapped for founder-led video rather than scaled. Batches that do not convert are cut; winners get the 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 static image the next.

4. 4

   Scaling · Week 5 to 7

   What we do

   We scale through Week 5 to Week 7 as far toward ₹30L as return allows as the budget climbs in steps and return falls, with Instagram Reels taking the largest share of spend and Instagram Feed the next. We refresh tired ads by mixing old and new creatives as spend rises. We run cost caps, bid caps, CBO and ABO as parallel versions before budget steps up.

   Why

   In Week 5 to Week 7 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. Frequency climbs with spend, and tired ads lose click-through first.

   How it works

   Proven ads stay while new ones are added. Controls run as parallel versions and the one that holds cost is kept. Instagram Reels carries the largest share of spend in the last four weeks, with Instagram Feed next. Cold audiences take most of the budget; warm audiences return more per rupee.

1. Week 1

   The learning phase opens: a small daily budget carries the first ads, and store orders are matched to tracking. Store fixes go live: reviews, trust pointers and the prepaid offer. The cart-value tiers are live.

   • Revenue ₹1.9L
   • ROAS 3.04x
   • Ad spend ₹61,084
2. Week 2

   First creative read: ads that do not convert are cut. Spend holds, and return holds.

   • Revenue ₹1.9L
   • ROAS 2.92x
   • Ad spend ₹63,674
3. Week 3

   Store fixes and offers go live while orders confirm.

   • Revenue ₹1.9L
   • ROAS 2.86x
   • Ad spend ₹65,777
4. Week 4

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

   • Revenue ₹1.9L
   • ROAS 2.85x
   • Ad spend ₹67,355
5. Week 5

   Scaling begins: a new batch goes live after the last one is read. Spend holds, and return rises.

   • Revenue ₹2.1L
   • ROAS 3.15x
   • Ad spend ₹67,536
6. Week 6

   The winning UGC runs in regional-language versions. Spend steps up sharply, and return dips.

   • Revenue ₹3.8L
   • ROAS 2.82x
   • Ad spend ₹1.4L
7. Week 7

   Customer-feedback and creator videos are refreshed. Spend steps up sharply, and return falls. ₹30L is not reached in the time, because the case study follows what the fastest tenth of our measured accounts reached. Cost per purchase ends close to the learning phase.

   • Revenue ₹5.6L
   • ROAS 2.46x
   • Ad spend ₹2.3L

1. 1

   Test UGC / creator video alongside the main format: it reached the top creative tier most often in this industry's measured accounts.

2. 2

   Move budget in three-to-four-day windows at campaign level, with catalogue campaigns by collection.

3. 3

   Gave each product its own campaign