Home & kitchen case study: ₹30L to ₹27L monthly revenue in 15–30 days

New ads per month

1. 1

   Research & offer · Week 1 to 2

   What we do

   The first problem in this scenario is scaling ad spend, so the opening week on this established store goes there. We split the account into layers: one campaign to test creative, one to scale winners, prospecting that leaves out past buyers, and retargeting for carts. We open with three documents: a website audit, a creative brief and a media schedule by month.

   Why

   An established home and kitchen store grows monthly revenue in 15–30 days, from ₹30L to ₹60L (2x). 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 in this scenario is scaling ad spend, with marketing and social presence close behind. Without layers, retargeting quietly eats the prospecting budget. Later budget calls need something written to be judged against.

   How it works

   Retargeting sits next to prospecting and never replaces it. All three are shared with the brand's team before any budget step.

2. 2

   Measurement & reviews · Week 1 to 4

   What we do

   We report net sales after returns, cancellations and tax next to store revenue and platform revenue. We agree a written number for every week on the way from ₹30L to ₹60L, and start each review with the week-to-date figure against it.

   Why

   With no return on ad spend reported, the case study begins at the level measured stores of that size hold. In measured accounts net sales ran below logged store revenue, so the numbers sit on the lower figure. A missed week shows up early instead of at the end of the case study.

   How it works

   Budget decisions are read off net sales, not the ad platform alone. Each budget step is argued against the written number.

3. 3

   Creative testing · Week 1 to 4

   What we do

   We lead the testing layer with video, catalogue ads and static image, building to a few dozen new ads a month by the last four weeks, keeping carousel on a short leash because its return trails the account. We separate the lead products into their own campaigns and review each one weekly. We stack kitchen and home interests around a creator video of the lead product. We keep creators producing UGC video on a steady schedule, and cut the winners into regional languages.

   Why

   Shared campaigns hide weak products; separate ones expose them fast. A demonstration video explains a utility product faster than a static image. Regular UGC keeps testing going, and a regional cut stretches a winning idea further.

   How it works

   Budget follows the products that sell. The interest stack runs beside a broad audience, read on the same video. Regional cuts of a winner come before new ideas. New ads rise with the budget, most of them video, then catalogue ads.

4. 4

   Scaling · Week 4

   What we do

   Through Week 4, we push toward ₹60L: the budget stays close to the learning level while return holds, and Instagram Reels carries the most spend and Instagram Feed the next. We run cost caps, bid caps, CBO and ABO as parallel versions before budget steps up. We let return decide budget: more while it holds, less when it slips.

   Why

   In Week 4 the budget stays close to the learning level, while return on spend holds. Each budget step here is sized so that return stays close to where it was. Parallel controls reveal which setup keeps cost per purchase down as spend grows.

   How it works

   Controls run as parallel versions and the one that holds cost is kept. There is no fixed ramp; each week's budget follows the return of the last. Most of the last four weeks'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.

1. Week 1

   First, the set-up: a small daily budget carries the first ads, and store orders are matched to tracking. Net sales are reconciled against logged revenue. The website audit, creative brief and media schedule are shared.

   • Revenue ₹6.9L
   • ROAS 4.69x
   • Ad spend ₹1.5L
2. Week 2

   First creative read: ads that do not convert are cut. Budget holds and return on spend holds.

   • Revenue ₹6.5L
   • ROAS 4.72x
   • Ad spend ₹1.4L
3. Week 3

   Store fixes and offers go live while orders confirm.

   • Revenue ₹6.7L
   • ROAS 4.64x
   • Ad spend ₹1.4L
4. Week 4

   By the end of learning, the buyer is known and one ad has won. Budget holds and return on spend holds. ₹60L 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 ₹6.9L
   • ROAS 4.50x
   • Ad spend ₹1.5L

1. 1

   Ran kitchen and home-brand interest stacks around an influencer video

2. 2

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

3. 3

   Tested cost caps and bid caps against open bidding