Beauty & skincare case study: ₹1L to ₹1.7L monthly revenue in 3 months

New ads per month

1. 1

   Research & offer · Month 1

   What we do

   The first problem in this scenario is reaching new buyers, so the opening month on this smaller store goes there. We set basket-size offers that reward a second and third item in the cart. We get the store ready for paid traffic first: reviews and trust pointers on product pages, a visible return window, an about page and a reason to pay upfront.

   Why

   In this case study, a smaller beauty and skincare brand grows monthly revenue in 3 months, from ₹1L to ₹25L (25x). 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 reaching new buyers, followed by marketing and social presence. 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

   The tiers follow real order values, not round numbers. Fixes are listed and handed over early, so later budget lands on a store that converts.

2. 2

   Measurement & reviews · Month 1 to 3

   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 ₹1L to ₹25L, and open every review with the month-to-date number against them. We raise budget in a month only while return holds; where it slips too far, we hold it.

   Why

   With no return on ad spend reported, the case study begins at the level measured beauty and skincare 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. 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 video, static image and carousel, building to about two dozen new ads a month by the final month, with carousel watched closely since it returns less than the rest. The learning month runs at a low daily budget and moves up only when orders come through. We brief creators for a steady run of UGC video, with regional-language cuts of the winners. We give each lead product its own campaign and read it weekly.

   Why

   The first rupees are for finding the buyer, not for volume. Regular UGC keeps testing going, and a regional cut stretches a winning idea further. A product nobody buys is visible within a week when it has its own campaign.

   How it works

   The low budget stays until orders confirm the buyer. Winning UGC is cut into regional languages before new ideas are bought. Losing products are paused within a week and budget moves to the winners. More spend buys more new ads, led by video ahead of static image.

4. 4

   Scaling · Month 2 to 3

   What we do

   We scale through Month 2 to Month 3 toward ₹25L as the budget rises gently while return holds, with Instagram Reels taking the largest share of spend and Instagram Feed the next. We cut regional-language versions of the winning video for the best-selling states. We build lookalikes from past buyers once purchases are steady, beside broad prospecting.

   Why

   Across Month 2 to Month 3, the budget rises gently, while return on spend holds. In two of these months the step is trimmed to the size return can hold. Return holds through these months because each budget step stops where return starts to slip. Buyers respond to the same idea in their own language.

   How it works

   Regional cuts run beside the original winner. Lookalike and broad audiences run the same ads, so they can be compared. 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.

1. Month 1

   Learning month: a small daily budget carries the first ads, and store orders are matched to tracking. Basket-size offers switch on at checkout. Reviews, trust pointers and the prepaid incentive are now on the store.

   • Revenue ₹1L
   • ROAS 1.90x
   • Ad spend ₹54,391
2. Month 2

   Scaling begins: products that do not sell are paused and budget moves to the winners. Only the part of the step that return supports is taken: budget steps up and return on spend holds.

   • Revenue ₹1.4L
   • ROAS 1.90x
   • Ad spend ₹73,532
3. Month 3

   A past-buyer lookalike audience joins broad prospecting. Only the part of the step that return supports is taken: budget steps up and return on spend holds. ₹25L is not reached in the time, because budget stops rising where return starts to slip. Each order costs about what it did while learning.

   • Revenue ₹1.7L
   • ROAS 1.92x
   • Ad spend ₹87,249

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

   Video carries most creative spend in measured accounts across all industries.

3. 3

   Kept remarketing on add-to-cart and checkout audiences (11.2x)