Kids case study: plan for ₹1L to ₹1.4L monthly revenue in 6 months

New ads per month

1. 1

   Research & offer · Month 1

   What we'd do

   Start with reaching new buyers, which the booking named first, before anything else on this smaller store. Map the festive and wedding calendar before spending, with seasonal collections ready in advance. Pick the hero categories to lead with, and check the pixel against store orders.

   Why

   A smaller kids store asked us how to grow monthly revenue in 6 months, from ₹1L to ₹15L (15x). Nine in ten of the accounts we measured grew more slowly than that in the same time; the plan is built on what the fastest tenth reached, and shows the gap to the target honestly. The problem named at booking was reaching new buyers. Buyers in this category shop around festivals and weddings. A broken pixel and diffuse categories both starve the algorithm of signal.

   How it works

   Seasonal campaigns are prepared ahead of each peak. Hero categories get their own campaigns from the first week.

2. 2

   Measurement & targets · Month 1 to 6

   What we'd do

   Log store orders every day beside what the ad platform claims. Raise budget in a month only while return holds; where it would slip too far, hold it. Agree a written target for every month on the way from ₹1L to ₹15L, and start each review with the month-to-date figure against it.

   Why

   No return on ad spend was given at booking; the starting return is what measured kids stores of that size hold. The ad platform's own count runs high, so the store's count is the one that moves budget. In the store accounts we measured, one budget step-up in four lost about a quarter of its return or more, so a step is taken only while return holds.

   How it works

   The sheet is read before each budget change. A month whose return would slip past that point keeps its budget instead. Written targets make each scaling decision explicit.

3. 3

   Creative testing · Month 1

   What we'd do

   Lead the testing layer with video, catalogue ads and static image, building to about two dozen new ads a month by the final month, keeping carousel on a short leash because its return trails the account. Test catalogue ads state by state and city by city, with close lookalikes of past buyers. Commission ads in batches, and read each batch for a set window before ordering the next. The learning month runs on a small daily budget, stepping up only once orders confirm.

   Why

   Kids' demand varies by region and season. Buying more before a batch is read means paying for guesses. Spend in the learning phase pays for information.

   How it works

   Regions that convert keep their catalogue sets; the rest are cut. Only ads that convert inside the window keep running. The low budget stays until orders confirm the buyer. More spend buys more new ads, led by video ahead of catalogue ads.

4. 4

   Scaling · Month 2 to 4

   What we'd do

   Through Month 2 to Month 4, push toward ₹15L: the budget rises gently while return holds, and Instagram Reels carries the most spend and Instagram Feed the next. Cut regional-language versions of the winning video for the best-selling states. Put seasonal collection campaigns in front of each festive and wedding peak.

   Why

   Across Month 2 to Month 4, the modelled budget rises gently, while return on spend holds. Budget is part-stepped in three of these months, taking only what return will carry. 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

   The regional versions run next to the original. Spend shifts into each season and between regions with the calendar. Most of the final month's spend sits on Instagram Reels, then Instagram Feed. 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, hold the gains and push toward ₹15L only as far as return allows. Build lookalikes from repeat buyers and retarget past buyers with new arrivals. Refresh tired ads by mixing old and new creatives, and keep a creative bank.

   Why

   Growth slows from Month 5, still short of ₹15L. Spend still grows, at a slower pace than during scaling. Repeat buyers are the cheapest orders an account gets. In one account we measured, click-through fell before revenue did; refresh is how that is avoided.

   How it works

   New arrivals go to past buyers first, before broad prospecting. Refreshes are gradual: a few new ads at a time.

1. Month 1

   First, the set-up: the first ads run on a small daily budget while tracking is checked against store orders. The daily sheet now matches platform revenue to store orders. Seasonal collections are prepared for the next peak.

   • Projected revenue ₹1L
   • Projected ROAS 1.91x
   • Planned ad spend ₹53,823
2. Month 2

   Scaling starts: tired ads are refreshed from the creative bank. Budget goes up only as far as return can carry it: return on spend holds while budget holds.

   • Projected revenue ₹1.1L
   • Projected ROAS 1.93x
   • Planned ad spend ₹57,822
3. Month 3

   Regional-language versions of the winner go live. Budget goes up only as far as return can carry it: return on spend holds while budget steps up.

   • Projected revenue ₹1.2L
   • Projected ROAS 1.93x
   • Planned ad spend ₹63,733
4. Month 4

   A seasonal collection campaign takes a larger share of budget. Budget goes up only as far as return can carry it: return on spend holds while budget holds.

   • Projected revenue ₹1.3L
   • Projected ROAS 1.93x
   • Planned ad spend ₹65,705
5. Month 5

   From here the work shifts to keeping ads fresh and bringing buyers back.

   • Projected revenue ₹1.3L
   • Projected ROAS 1.93x
   • Planned ad spend ₹69,352
6. Month 6

   New arrivals go to past buyers first. Budget goes up only as far as return can carry it: return on spend holds while budget holds. ₹15L 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 ₹1.4L
   • Projected ROAS 1.98x
   • Planned ad spend ₹68,402

1. 01

   Ran catalogue campaigns by collection, with best sellers and video for key categories

2. 02

   After the spring fall: hero categories, a pixel fix and festive influencer content

3. 03

   Test catalogue ads state-wise and city-wise, with 1% lookalikes and festive retargeting.