Home & kitchen case study: ₹2L to ₹2.3L 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 smaller home and kitchen 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 set basket-size offers that reward a second and third item in the cart.

   Why

   In this case study, a smaller home and kitchen brand grows monthly revenue in 3 months, from ₹2L to ₹10L (5x). Nine in ten of the accounts we measured grew more slowly than that in the same time; the case study follows the fastest tenth's pace, holds budget where return starts to slip, and shows the gap to the brand's number honestly. The brand in this scenario named no single problem, so the case study starts from the numbers. Later budget calls need something written to be judged against. Higher order value lowers the share of each order that goes to ads.

   How it works

   The audit, the brief and the media schedule are shared before spend rises. The tiers follow real order values, not round numbers.

2. 2

   Measurement & reviews · Month 1 to 3

   What we do

   We log store orders every day beside what the ad platform claims. We set the path from ₹2L to ₹10L as written monthly numbers, and read every review against the month so far. We reconcile the return on spend the brand in this scenario reports with store revenue before the first budget change.

   Why

   The return on ad spend it reported is below the level where raising budget pays for a store of that size, so budget does not rise until return climbs. The ad platform's own count runs high, so the store's count is the one that moves budget. Written monthly numbers expose a slow month while there is still time to act.

   How it works

   The sheet is read before each budget change. Written monthly numbers make each scaling decision explicit. The store-side return becomes the number every review uses.

3. 3

   Creative testing · Month 1

   What we do

   We lead the testing layer with video, catalogue ads and static image, building to about two dozen new ads a month by the final month, with carousel watched closely since it returns less than the rest. We stack kitchen and home interests around a creator video of the lead product. The learning month runs at a low daily budget and moves up only when orders come through. We give each lead product its own campaign and read it weekly.

   Why

   A demonstration video explains a utility product faster than a static image. Early spend buys learning, not scale. Products that do not sell show up inside a week, not after a month of shared budget.

   How it works

   The interest stack runs beside a broad audience, read on the same video. Spend steps up only after orders confirm at the low budget. A product that does not sell is paused inside the week. New ads rise with the budget, most of them video, then catalogue ads.

4. 4

   Scaling · Month 2 to 3

   What we do

   Through Month 2 to Month 3, we push as far toward ₹10L as return allows: the budget rises gently while return holds, and Instagram Reels carries the most spend and Instagram Feed the next. We let return decide budget: more while it holds, less when it slips. We make regional-language versions of the winning video for the states that buy most.

   Why

   In Month 2 to Month 3 the budget rises gently, while return on spend holds. In two of these months budget goes up only as far as return allows, so revenue grows more slowly than the brand's number needs. Each budget step here is sized so that return stays close to where it was. Buyers respond to the same idea in their own language.

   How it works

   Each month's budget is set by the return the last one earned. The regional versions run next to the original. 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: the first ads run on a small daily budget while tracking is checked against store orders. The website audit, creative brief and media schedule are shared. The store-side return is now the one budget follows.

   • Revenue ₹2L
   • ROAS 1.87x
   • Ad spend ₹1.1L
2. Month 2

   Scaling begins: the budget decision is taken on the return the last step earned. The budget step stops where return starts to slip: while budget holds, return on spend holds.

   • Revenue ₹2.2L
   • ROAS 1.94x
   • Ad spend ₹1.1L
3. Month 3

   Products that do not sell are paused and budget moves to the winners. The budget step stops where return starts to slip: while budget holds, return on spend 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 ₹2.3L
   • ROAS 1.91x
   • Ad spend ₹1.2L

1. 1

   Tested cost caps and bid caps against open bidding

2. 2

   Ran regional-language versions of the winning creative (6.9x)

3. 3

   We stack kitchen and home interests around a creator video of the lead product.