Beauty & skincare case study: plan for ₹7L–₹8L to ₹14.3L monthly revenue in 2–3 months

New ads per month

1. 1

   Research & offer · Month 1

   What we'd do

   Start with return on ad spend, which the booking named first, before anything else on this mid-sized store. Use cart-value tiers so larger baskets earn a better offer. Open with three documents: a website audit, a creative brief and a media plan by month.

   Why

   A mid-sized beauty and skincare brand came to us to grow monthly revenue in 2–3 months, from ₹7L–₹8L to ₹30L–₹40L (4.7x). Nine in ten of the accounts we measured grew more slowly than that in the same time; the plan aims at the fastest tenth's pace, holds budget where return would slip, and shows the gap to the target honestly. The main problem named at booking was return on ad spend, followed by a clear strategy. A larger basket spreads the cost of each order over more revenue. A written brief gives every later budget decision a reference point.

   How it works

   The tiers follow real order values, not round numbers. The brief is agreed first; spend follows it.

2. 2

   Measurement & targets · Month 1 to 3

   What we'd do

   Log store orders every day beside what the ad platform claims. Write month-by-month targets with the brand's team that climb from ₹7L–₹8L to ₹30L–₹40L, and open every review with the month-to-date number against them. Set targets on net sales after returns and cancellations, not on logged revenue.

   Why

   Its reported return on ad spend is under what measured stores of that size hold; the plan begins from it and rebuilds return first. The ad platform's own count runs high, so the store's count is the one that moves budget. A missed month shows up early instead of at the end of the plan.

   How it works

   Every budget call starts from the store's orders. The target for the month is on the page at every review. Each review opens with net sales against the target.

3. 3

   Creative testing · Month 1

   What we'd do

   Test with video, static image and catalogue ads first, rising to several dozen new ads a month by the final month, with carousel watched closely since it returns less than the rest. Separate the lead products into their own campaigns and review each one weekly. Lead with video that carries trust: creators, customer feedback and founder-led pieces. The learning month runs at a low daily budget and moves up only when orders come through.

   Why

   Products that do not sell show up inside a week, not after a month of shared budget. In most accounts we measured, video that carried trust held its return. The first rupees are for finding the buyer, not for volume.

   How it works

   Losing products are paused within a week and budget moves to the winners. UGC that underperforms is replaced by founder-led video, not given more budget. Only confirmed orders at the low budget unlock the next step. 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'd do

   Through Month 2 to Month 3, push as far toward ₹30L–₹40L as return allows: the budget climbs in steps while return holds, and Instagram Reels carries the most spend and Instagram Feed the next. Raise budget only while return on spend holds, and cut it when return drops. Run cost caps, bid caps, CBO and ABO as parallel versions before budget steps up.

   Why

   Across Month 2 to Month 3, the modelled budget climbs in steps, while return on spend holds. In one of these months the step is trimmed to the size return can hold. Each budget step here is sized so that return stays close to where it was. Controls show which setup holds cost per purchase as spend rises.

   How it works

   There is no fixed ramp; each month's budget follows the return of the last. The version that keeps cost per purchase lowest stays. Instagram Reels carries the largest share of spend in the final month, with Instagram Feed next. Prospecting to new buyers takes the bulk of spend, while retargeting returns more for each rupee.

1. Month 1

   First, the set-up: 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 media plan and creative brief are signed off.

   • Projected revenue ₹7.7L
   • Projected ROAS 1.94x
   • Planned ad spend ₹4L
2. Month 2

   The scaling phase opens: budget is reviewed against return before the next step. Return holds as the budget steps up.

   • Projected revenue ₹11.5L
   • Projected ROAS 1.96x
   • Planned ad spend ₹5.9L
3. Month 3

   Bid-cap and cost-cap versions run beside open bidding. Budget is raised only as far as return allows: return holds as the budget steps up. ₹30L–₹40L is not reached in the time, because budget stops rising where return would slip. Each order costs about what it did while learning.

   • Projected revenue ₹14.3L
   • Projected ROAS 1.97x
   • Planned ad spend ₹7.3L

1. 01

   Test Static image alongside the main format: it reached the top creative tier most often in measured accounts across all industries.

2. 02

   Catalogue ads tested state-wise and city-wise, 1% lookalikes, Diwali retargeting

3. 03

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