Home & kitchen case study: plan for ₹30L–₹35L to ₹73.2L monthly revenue in 6 months

New ads per month

1. 1

   Research & offer · Month 1

   What we'd do

   Aim the first month at creative and content, the problem named at booking, on a established base. 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

   An established home and kitchen store asked us how to grow monthly revenue in 6 months, from ₹30L–₹35L to ₹1Cr (3.1x). That is faster than nine in ten of our measured accounts grew over the same time, so the plan below is modelled on what that fastest tenth reached and shows where it lands against the target. The main problem named at booking was creative and content, followed by a clear strategy. Later budget calls need something written to be judged against. Without layers, retargeting quietly eats the prospecting budget.

   How it works

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

2. 2

   Measurement & targets · Month 1 to 6

   What we'd do

   Report net sales after returns, cancellations and tax next to store revenue and platform revenue. Write month-by-month targets with the brand's team that climb from ₹30L–₹35L to ₹1Cr, and open every review with the month-to-date number against them.

   Why

   With no return on ad spend reported, the plan begins at the level measured stores of that size hold. In measured accounts net sales ran below logged store revenue, so targets sit on the lower number. Written targets expose a slow month while there is still time to act.

   How it works

   Budget decisions are read off net sales, not the ad platform alone. The target for the month is on the page at every review.

3. 3

   Creative testing · Month 1

   What we'd do

   Lead the testing layer with video, catalogue ads and static image, building to several dozen new ads a month by the final month, keeping carousel on a short leash because its return trails the account. Buy creative in batches and give each batch a fixed read window before buying more. Make trust the subject of the video: creator reels, customer feedback and founder-led clips. Run static images next to the video ads.

   Why

   The read window keeps creative spending tied to evidence. Trust-carrying video held return in most measured accounts. In every industry we measured, static images were the format most often in the top creative tier.

   How it works

   Only ads that convert inside the window keep running. Low-quality UGC is pulled and founder-led video takes its place. Statics join once a winning video is found. The number of new ads grows with spend; video makes up the largest part and catalogue ads the next.

4. 4

   Scaling · Month 2 to 4

   What we'd do

   Scale through Month 2 to Month 4 as far toward ₹1Cr 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. Make regional-language versions of the winning video for the states that buy most. Run cost caps, bid caps, CBO and ABO as parallel versions before budget steps up.

   Why

   Across Month 2 to Month 4, the modelled budget climbs in steps, and return on spend falls as it does. In measured accounts, scaling spend raised cost per order and lowered return on spend, so each step waits for return to hold. Buyers respond to the same idea in their own language.

   How it works

   Regional cuts run beside the original winner. Controls run as parallel versions and the one that holds cost is kept. 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.

5. 5

   Steady state · Month 5 to 6

   What we'd do

   From Month 5, hold the gains and push toward ₹1Cr only as far as return allows. Refresh tired ads by mixing old and new creatives, and keep a creative bank. Hold targets on net sales as volume grows, since returns rise with it.

   Why

   Growth slows from Month 5, still short of ₹1Cr. Spend still grows, at a slower pace than during scaling. Falling click-through preceded a revenue drop in a measured account, so creative refresh is not optional. Net sales ran below logged store revenue in our measured accounts.

   How it works

   Refreshes are gradual: a few new ads at a time. Each review opens with net sales against the target.

1. Month 1

   The learning phase opens: tracking is checked against store orders and the first ads go live on a small daily budget. The account runs in layers: testing, scaling and retargeting. The audit, brief and media plan are agreed with the brand's team.

   • Projected revenue ₹33L
   • Projected ROAS 3.58x
   • Planned ad spend ₹9.2L
2. Month 2

   Scaling starts: bid-cap and cost-cap versions run beside open bidding. Budget steps up and return on spend dips.

   • Projected revenue ₹37.5L
   • Projected ROAS 3.35x
   • Planned ad spend ₹11.2L
3. Month 3

   A fresh round of creator and customer-feedback video goes live.

   • Projected revenue ₹47.1L
   • Projected ROAS 3.16x
   • Planned ad spend ₹14.9L
4. Month 4

   Tired ads are refreshed from the creative bank.

   • Projected revenue ₹60.3L
   • Projected ROAS 2.91x
   • Planned ad spend ₹20.7L
5. Month 5

   Steady phase begins: creative refresh and repeat orders take on more of the work. Halfway from ₹30L–₹35L to ₹1Cr is passed.

   • Projected revenue ₹69.7L
   • Projected ROAS 3.05x
   • Planned ad spend ₹22.9L
6. Month 6

   The winner now also runs in regional languages. Budget holds and return on spend holds. The plan finishes short of ₹1Cr: the plan follows what the fastest tenth of our measured accounts reached. Each order costs more by the end than it did while learning.

   • Projected revenue ₹73.2L
   • Projected ROAS 2.93x
   • Planned ad spend ₹25L

1. 01

   Tested cost caps and bid caps against open bidding

2. 02

   Gave each product its own campaign

3. 03

   Ran each product as its own campaign and read results weekly