Home & kitchen case study: plan for ₹15L to ₹30L monthly revenue in 3–6 months

New ads per month

1. 1

   Research & offer · Month 1

   What we'd do

   The booking named a clear strategy first, so the opening month on this mid-sized store goes there. Open with three documents: a website audit, a creative brief and a media plan by month. Build the account in layers so each can be read on its own: testing, scaling, new-buyer prospecting and cart retargeting.

   Why

   A mid-sized home and kitchen brand came to us to grow monthly revenue in 3–6 months, from ₹15L to ₹30L (2x). Only the faster-growing accounts we measured reached that pace in the same time, but they did reach it. The problem named at booking was a clear strategy. A written brief gives every later budget decision a reference point. Layers keep each budget line readable, so a weak campaign cannot hide inside a strong one.

   How it works

   All three are shared with the brand's team before any budget step. Each layer keeps its own budget line.

2. 2

   Measurement & targets · Month 1 to 6

   What we'd do

   Keep a shared daily sheet with the ad platform's revenue next to real store orders. Write month-by-month targets with the brand's team that climb from ₹15L to ₹30L, and open every review with the month-to-date number against them. Check the reported return on spend against store revenue before any budget moves.

   Why

   The return on ad spend it reported sits below what measured stores of that size hold, so the plan starts there and rebuilds return before budget rises. The ad platform's own count runs high, so the store's count is the one that moves budget. Written targets expose a slow month while there is still time to act.

   How it works

   The sheet is read before each budget change. Written targets make each scaling decision explicit. Both returns are reviewed together each week.

3. 3

   Creative testing · Month 1

   What we'd do

   Test with video, catalogue ads and static image first, rising to a few dozen new ads a month by the final month, with carousel watched closely since it returns less than the rest. Run every lead product in a campaign of its own, read every week. Stack kitchen and home interests around a creator video of the lead product. The learning month runs on a small daily budget, stepping up only once orders confirm.

   Why

   Shared campaigns hide weak products; separate ones expose them fast. A demonstration video explains a utility product faster than a static image. 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. The interest stack runs beside a broad audience, read on the same video. The low budget stays until orders confirm the buyer. New ads rise with the budget, most of them video, then catalogue ads.

4. 4

   Scaling · Month 2 to 4

   What we'd do

   Scale through Month 2 to Month 4 toward ₹30L as the budget rises gently while return holds, with Instagram Reels taking the largest share of spend and Instagram Feed the next. Run cost caps, bid caps, CBO and ABO as parallel versions before budget steps up. Raise budget only while return on spend holds, and cut it when return drops.

   Why

   In Month 2 to Month 4 the modelled budget rises gently, while return on spend holds. 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

   Controls run as parallel versions and the one that holds cost is kept. Each month's budget is set by the return the last one earned. Instagram Reels carries the largest share of spend in the final month, with Instagram Feed next. Cold audiences take most of the budget; warm audiences return more per rupee.

5. 5

   Steady state · Month 5 to 6

   What we'd do

   From Month 5, close the last stretch to ₹30L without losing return. Refresh tired ads by mixing old and new creatives, and keep a creative bank. Recover abandoned checkouts and lift repeat orders with WhatsApp messages.

   Why

   At Month 5 revenue is close to ₹30L. Budget keeps rising, more slowly than in the scaling months. In one account we measured, click-through fell before revenue did; refresh is how that is avoided. WhatsApp is cheaper than paid retargeting for buyers who already reached checkout.

   How it works

   New creatives mix with proven ones rather than replacing them all at once. WhatsApp runs alongside paid retargeting, not instead of it.

1. Month 1

   First, the set-up: the first ads run on a small daily budget while tracking is checked against store orders. Store orders and platform revenue are reconciled in the shared sheet. The account runs in layers: testing, scaling and retargeting.

   • Projected revenue ₹14.8L
   • Projected ROAS 3.53x
   • Planned ad spend ₹4.2L
2. Month 2

   The scaling phase opens: repeat-order messages go to past buyers. Return on spend rises while budget holds.

   • Projected revenue ₹16.3L
   • Projected ROAS 3.84x
   • Planned ad spend ₹4.2L
3. Month 3

   The creative bank supplies this period's refresh. Return on spend holds while budget steps up.

   • Projected revenue ₹21.2L
   • Projected ROAS 3.78x
   • Planned ad spend ₹5.6L
4. Month 4

   Cost caps and bid caps are tested against open bidding. Monthly revenue passes the halfway point between ₹15L and ₹30L.

   • Projected revenue ₹25.1L
   • Projected ROAS 3.54x
   • Planned ad spend ₹7.1L
5. Month 5

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

   • Projected revenue ₹28.7L
   • Projected ROAS 3.68x
   • Planned ad spend ₹7.8L
6. Month 6

   Each budget move is read against the return it bought. Return on spend holds while budget holds. Revenue gets to ₹30L, the level the brand asked for. Each order costs about what it did while learning.

   • Projected revenue ₹30.6L
   • Projected ROAS 3.60x
   • Planned ad spend ₹8.5L

1. 01

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

2. 02

   Track ad-platform revenue beside store revenue (and net sales) daily or weekly, and set targets on the lower number.

3. 03

   Test bidding controls (cost caps, bid caps, CBO against ABO) side by side before scaling.