Beauty & skincare case study: ₹10,000–₹15,000 to ₹21,869 monthly revenue in 6 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 add cart-value offers that step up at set basket sizes to lift order value. We fix the store before scaling: trust pointers, reviews, a clear return window, an about page and a prepaid incentive.

   Why

   In this case study, a smaller beauty and skincare brand grows monthly revenue in 6 months, from ₹10,000–₹15,000 to ₹10L (80x). 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 main problem was creative and content. Higher order value lowers the share of each order that goes to ads. Every rupee of ads is capped by how well the store turns visits into orders.

   How it works

   Tier levels are set just above the basket sizes buyers already reach. Fixes are listed and handed over early, so later budget lands on a store that converts.

2. 2

   Measurement & reviews · Month 1 to 6

   What we do

   We track ad-platform revenue beside store orders in a shared daily sheet. We write month-by-month revenue numbers with the brand's team that climb from ₹10,000–₹15,000 to ₹10L, and open every review with the month-to-date number against them. We set a written rule: no budget step in a month 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 beauty and skincare stores of that size hold. Platform attribution over-counts, so budget decisions sit on the store-side number. A shortfall is caught in the month it happens, not at the end.

   How it works

   Budget decisions are read off store numbers, not the ad platform alone. The month's number is on the page at every review. A month whose return slips past that point keeps its budget instead.

3. 3

   Creative testing · Month 1

   What we do

   We lead the testing layer with carousel, catalogue ads and static image, building to a handful of new ads a month by the final month, 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 brief creators for a steady run of UGC video, with regional-language cuts of the winners.

   Why

   Video built on trust was the format that held return in most measured accounts. A fixed window stops spend chasing a creative before it has been read. Regular UGC keeps testing going, and a regional cut stretches a winning idea further.

   How it works

   UGC that underperforms is replaced by founder-led video, not given more budget. Only ads that convert inside the window keep running. Winning UGC is cut into regional languages before new ideas are bought. More spend buys more new ads, led by carousel ahead of catalogue ads.

4. 4

   Scaling · Month 2 to 4

   What we do

   We scale through Month 2 to Month 4 toward ₹10L as the budget rises gently while return holds, with Instagram Reels taking the largest share of spend and Facebook Feed the next. We refresh tired ads by mixing old and new creatives as spend rises. We cut regional-language versions of the winning video for the best-selling states.

   Why

   Across Month 2 to Month 4, the budget rises gently, while return on spend holds. Budget is part-stepped in three of these months, taking only what return can carry. Return holds through these months because each budget step stops where return starts to slip. Frequency climbs with spend, and tired ads lose click-through first.

   How it works

   Proven ads stay while new ones are added. The regional versions run next to the original. Instagram Reels carries the largest share of spend in the final month, with Facebook Feed next. Cold audiences take most of the budget; warm audiences return more per rupee.

5. 5

   Steady state · Month 5 to 6

   What we do

   From Month 5, we protect the revenue already built and move toward ₹10L where return permits. We refresh tired ads by mixing old and new creatives, and keep a creative bank. We build lookalikes from repeat buyers and retarget past buyers with new arrivals.

   Why

   Growth slows from Month 5, still short of ₹10L. Spend still grows, at a slower pace than during scaling. Falling click-through preceded a revenue drop in a measured account, so creative refresh is not optional. Repeat buyers are the cheapest orders an account gets.

   How it works

   Refreshes are gradual: a few new ads at a time. New arrivals go to past buyers first, before broad prospecting.

1. Month 1

   First, the set-up: the first ads run on a small daily budget while tracking is checked against store orders. The cart-value tiers are live. Reviews, trust pointers and the prepaid incentive are now on the store.

   • Revenue ₹12,189
   • ROAS 1.87x
   • Ad spend ₹6,521
2. Month 2

   The scaling phase opens: fresh ads are mixed in beside the proven set. Only the part of the step that return supports is taken: return on spend holds while budget steps up.

   • Revenue ₹16,544
   • ROAS 1.94x
   • Ad spend ₹8,534
3. Month 3

   Tired ads are refreshed from the creative bank.

   • Revenue ₹19,045
   • ROAS 1.89x
   • Ad spend ₹10,058
4. Month 4

   Regional-language versions of the winner go live. Only the part of the step that return supports is taken: return on spend holds while budget holds.

   • Revenue ₹20,357
   • ROAS 1.93x
   • Ad spend ₹10,523
5. Month 5

   From here the work shifts to keeping ads fresh and bringing buyers back.

   • Revenue ₹21,450
   • ROAS 1.89x
   • Ad spend ₹11,354
6. Month 6

   A new batch goes live after the last one is read. Only the part of the step that return supports is taken: return on spend holds while budget holds. ₹10L 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 ₹21,869
   • ROAS 1.89x
   • Ad spend ₹11,558

1. 1

   A low average order value limited how far spend could scale.

2. 2

   Moved budget in three-to-four-day windows at campaign level

3. 3

   Put 95% of the Meta budget behind videos of the core products, including a customer testimonial