Beauty & skincare case study: ₹2L to ₹2.6L monthly revenue in 7 months

New ads per month

1. 1

   Research & offer · Month 1

   What we do

   We set up the base for a smaller beauty and skincare store before any budget rises. 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. We build the account in layers so each can be read on its own: testing, scaling, new-buyer prospecting and cart retargeting.

   Why

   In this case study, a smaller beauty and skincare brand grows monthly revenue in 7 months, from ₹2L to ₹6L–₹8L (3.5x). 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, holds budget where return starts to slip, and does not force the number. 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. Each extra item in a basket is revenue the ad has already paid for.

   How it works

   The audit, the brief and the media schedule are shared before spend rises. Tier levels are set just above the basket sizes buyers already reach. Retargeting sits next to prospecting and never replaces it.

2. 2

   Measurement & reviews · Month 1 to 7

   What we do

   We agree a written number for every month on the way from ₹2L to ₹6L–₹8L, and start each review with the month-to-date figure against it. We keep a shared daily sheet with the ad platform's revenue next to real store orders. We match the return the brand in this scenario reports to what the store actually took in, before touching budget.

   Why

   The return on ad spend it reported sits above what measured beauty and skincare stores of that size hold; the case study starts from it and allows for some of it to give way as spend rises. Written monthly numbers expose a slow month while there is still time to act. Platform attribution over-counts, so budget decisions sit on the store-side number.

   How it works

   Written monthly numbers make each scaling decision explicit. Every budget call starts from the store's orders. The reported return and the store-side return are read side by side every week.

3. 3

   Creative testing · Month 1

   What we do

   We test with video, static image and carousel first, rising to about two dozen new ads a month by the final month, keeping carousel on a short leash because its return trails the account. The learning month runs on a small daily budget, stepping up only once orders confirm. We buy creative in batches and give each batch a fixed read window before buying more. We lead with video that carries trust: creators, customer feedback and founder-led pieces.

   Why

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

   How it works

   Spend steps up only after orders confirm at the low budget. Batches that do not convert are cut; winners get the budget. Weak UGC is swapped for founder-led video rather than scaled. 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 5

   What we do

   We scale through Month 2 to Month 5 as far toward ₹6L–₹8L 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 let return decide budget: more while it holds, less when it slips. We recover abandoned checkouts with WhatsApp messages as traffic grows. As spend rises, we mix new creatives in with the proven ones before the old ones tire.

   Why

   In Month 2 to Month 5 the budget climbs in steps, and return on spend falls as it does. Budget is part-stepped in two of these months, taking only what return can carry. In measured accounts, scaling spend raised cost per order and lowered return on spend, so each step waits for return to hold. WhatsApp is cheaper than paid retargeting for buyers who already reached checkout.

   How it works

   There is no fixed ramp; each month's budget follows the return of the last. WhatsApp recovery runs alongside paid retargeting, not instead of it. New creatives join proven ones rather than replacing them all at once. Most of the final month's spend sits on Instagram Reels, then Instagram Feed. Prospecting to new buyers takes the bulk of spend, while retargeting returns more for each rupee.

5. 5

   Steady state · Month 6 to 7

   What we do

   From Month 6, we protect the revenue already built and move toward ₹6L–₹8L where return permits. We refresh tired ads by mixing old and new creatives, and keep a creative bank. We stop pushing budget once return has peaked.

   Why

   Growth slows from Month 6, still short of ₹6L–₹8L. Spend holds roughly steady from here. Falling click-through preceded a revenue drop in a measured account, so creative refresh is not optional. Most of our engagements saw return fall back from its best month.

   How it works

   The bank means a tired ad is replaced the week it tires. Budget is held while return is at its best and cut back when it slips.

1. Month 1

   Learning month: the first ads run on a small daily budget while tracking is checked against store orders. Store orders and ad-platform revenue are checked side by side. The media schedule and creative brief are signed off.

   • Revenue ₹2L
   • ROAS 2.55x
   • Ad spend ₹77,298
2. Month 2

   Scaling begins: fresh ads are mixed in beside the proven set. Return on spend falls while budget steps up.

   • Revenue ₹2.2L
   • ROAS 2.18x
   • Ad spend ₹1L
3. Month 3

   Each budget move is read against the return it bought.

   • Revenue ₹2.7L
   • ROAS 2.09x
   • Ad spend ₹1.3L
4. Month 4

   Tired ads are refreshed from the creative bank. Budget goes up only as far as return can carry it: return on spend dips while budget steps up.

   • Revenue ₹2.7L
   • ROAS 1.94x
   • Ad spend ₹1.4L
5. Month 5

   Customer-feedback and creator videos are refreshed. Budget goes up only as far as return can carry it: return on spend holds while budget holds.

   • Revenue ₹2.7L
   • ROAS 1.91x
   • Ad spend ₹1.4L
6. Month 6

   Steady phase begins: creative refresh and repeat orders take on more of the work.

   • Revenue ₹2.6L
   • ROAS 1.91x
   • Ad spend ₹1.4L
7. Month 7

   Budget is held at the level where return peaked. Budget goes up only as far as return can carry it: return on spend holds while budget holds. Revenue ends below ₹6L–₹8L, the number this scenario calls for, because budget stops rising where return starts to slip. Cost per purchase ends higher than in the learning phase.

   • Revenue ₹2.6L
   • ROAS 1.88x
   • Ad spend ₹1.4L

1. 1

   Instagram Reels carries the largest share of spend in measured accounts across all industries.

2. 2

   Paused South India during Shravan and ran new creatives to the North

3. 3

   Scaled into winter against written daily spend numbers