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

New ads per month

1. 1

   Research & offer · Month 1

   What we do

   The first problem in this scenario is scaling ad spend, so the opening month on this smaller 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 use cart-value tiers so larger baskets earn a better offer.

   Why

   In this case study, a smaller kids brand grows monthly revenue in 6 months, from ₹1L to ₹10L (10x). Nine in ten of the accounts we measured grew more slowly than that in the same time; the case study is built on what the fastest tenth reached, and shows the gap to the agreed number honestly. The main problem in this scenario is scaling ad spend. Without layers, retargeting quietly eats the prospecting budget. A larger basket spreads the cost of each order over more revenue.

   How it works

   Retargeting sits next to prospecting and never replaces it. Tier levels are set just above the basket sizes buyers already reach.

2. 2

   Measurement & reviews · Month 1 to 6

   What we do

   We track ad-platform revenue beside store orders in a shared daily sheet. We set the path from ₹1L 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. Platform attribution over-counts, so budget decisions sit on the store-side number. A missed month shows up early instead of at the end of the case study.

   How it works

   Every budget call starts from the store's orders. 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 a dozen new ads a month by the final month, keeping carousel on a short leash because its return trails the account. We test catalogue ads state by state and city by city, with close lookalikes of past buyers. The learning month runs on a small daily budget, stepping up only once orders confirm. We commission ads in batches, and read each batch for a set window before ordering the next.

   Why

   Kids' demand varies by region and season. Spend in the learning phase pays for information. The read window keeps creative spending tied to evidence.

   How it works

   Regions that convert keep their catalogue sets; the rest are cut. The low budget stays until orders confirm the buyer. Only ads that convert inside the window keep running. 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 do

   We scale through Month 2 to Month 4 toward ₹10L as the budget rises gently while return holds, with Instagram Reels taking the largest share of spend and Facebook Feed the next. We tie every budget increase to return: we step up while it holds, and step back when it drops. We move budget in three-to-four-day windows at campaign level.

   Why

   In Month 2 to Month 4 the budget rises gently, while return on spend holds. Three of these months stop their budget step where return slips too far. Return holds through these months because each budget step stops where return starts to slip. Short windows react to category demand without resetting learning every day.

   How it works

   There is no fixed ramp; each month's budget follows the return of the last. Each window is read on purchases and cost per purchase before the next move. In the final month, Instagram Reels takes the most spend and Facebook Feed the next most. Cold audiences take most of the budget; warm audiences return more per rupee.

5. 5

   Steady state · Month 5 to 6

   What we do

   From Month 5, we protect the revenue already built and move toward ₹10L where return permits. We keep a bank of ready creatives and rotate them in as ads tire. We use WhatsApp for abandoned checkouts and for past buyers' next order.

   Why

   Growth slows from Month 5, still short of ₹10L. Budget keeps rising, more slowly than in the scaling months. A measured account showed click-through falling ahead of revenue, so tired ads are replaced early. A message to someone who nearly bought costs less than an ad.

   How it works

   The bank means a tired ad is replaced the week it tires. WhatsApp runs alongside paid retargeting, not instead of it.

1. Month 1

   First, the set-up: tracking is checked against store orders and the first ads go live on a small daily budget. The cart-value tiers are live. The account runs in layers: testing, scaling and retargeting.

   • Revenue ₹1L
   • ROAS 1.87x
   • Ad spend ₹54,636
2. Month 2

   Scaling starts: a new batch goes live after the last one is read. Only the part of the step that return supports is taken: with budget holds, return on spend holds.

   • Revenue ₹1.1L
   • ROAS 1.91x
   • Ad spend ₹59,100
3. Month 3

   Catalogue sets are kept in regions that convert and cut elsewhere. Only the part of the step that return supports is taken: with budget steps up, return on spend holds.

   • Revenue ₹1.3L
   • ROAS 1.94x
   • Ad spend ₹66,874
4. Month 4

   Repeat-order messages go to past buyers. Only the part of the step that return supports is taken: with budget holds, return on spend holds.

   • Revenue ₹1.4L
   • ROAS 1.91x
   • Ad spend ₹71,519
5. Month 5

   The case study moves into its steady phase, leaning on refreshed ads and repeat buyers.

   • Revenue ₹1.4L
   • ROAS 1.92x
   • Ad spend ₹73,902
6. Month 6

   Ads with falling click-through are swapped from the bank. Only the part of the step that return supports is taken: with 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 ₹1.4L
   • ROAS 1.86x
   • Ad spend ₹75,576

1. 1

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

2. 2

   Paused South India during Shravan and ran new creatives to the North

3. 3

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