Beauty & skincare case study: ₹5L to ₹11.8L monthly revenue in 3 months

New ads per month

1. 1

   Research & offer · Month 1

   What we do

   We open with set-up work on the mid-sized beauty and skincare 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 add cart-value offers that step up at set basket sizes to lift order value.

   Why

   A mid-sized beauty and skincare store grows monthly revenue in 3 months, from ₹5L to ₹30L (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 brand in this scenario named no single problem, so the case study starts from the numbers. A written brief gives every later budget decision a reference point. A larger basket spreads the cost of each order over more revenue.

   How it works

   All three are shared with the brand's team before any budget step. Tier levels are set just above the basket sizes buyers already reach.

2. 2

   Measurement & reviews · Month 1 to 3

   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 ₹5L to ₹30L as written monthly numbers, and read every review against the month so far.

   Why

   With no return on ad spend reported, the case study begins at the level measured stores of that size hold. Ad platforms claim more orders than stores record, so the store number decides budget. Written monthly numbers expose a slow month while there is still time to act.

   How it works

   Every budget call starts from the store's orders. Written monthly numbers make each scaling decision explicit.

3. 3

   Creative testing · Month 1

   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 final month, with carousel watched closely since it returns less than the rest. We buy creative in batches and give each batch a fixed read window before buying more. We make trust the subject of the video: creator reels, customer feedback and founder-led clips. The learning month runs on a small daily budget, stepping up only once orders confirm.

   Why

   A fixed window stops spend chasing a creative before it has been read. Trust-carrying video held return in most measured accounts. Early spend buys learning, not scale.

   How it works

   Batches that do not convert are cut; winners get the budget. UGC that underperforms is replaced by founder-led video, not given more budget. Spend steps up only after orders confirm at the low budget. The number of new ads grows with spend; video makes up the largest part and static image the next.

4. 4

   Scaling · Month 2 to 3

   What we do

   We scale through Month 2 to Month 3 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 test cost caps, bid caps and CBO against ABO side by side before each budget step. We tie every budget increase to return: we step up while it holds, and step back when it drops.

   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. Controls show which setup holds cost per purchase as spend rises.

   How it works

   The version that keeps cost per purchase lowest stays. Each month's budget is set by the return the last one earned. Instagram Reels carries the largest share of spend in the final month, with Instagram Feed next. Cold audiences take most of the budget; warm audiences return more per rupee.

1. Month 1

   Learning month: 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 audit, brief and media schedule are agreed with the brand's team.

   • Revenue ₹4.8L
   • ROAS 2.54x
   • Ad spend ₹1.9L
2. Month 2

   Scaling begins: cost caps and bid caps are tested against open bidding. Return falls as the budget steps up sharply.

   • Revenue ₹9L
   • ROAS 2.20x
   • Ad spend ₹4.1L
3. Month 3

   Budget is reviewed against return before the next step. Return dips as the budget steps up. The case study finishes short of ₹30L: 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 ₹11.8L
   • ROAS 2.02x
   • Ad spend ₹5.8L

1. 1

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

2. 2

   Cost per order stayed well above what a low-price consumable can carry.

3. 3

   Find the buyer on a small daily budget first, then step spend up in stages.