Pets case study: ₹1.8L to ₹3.6L monthly revenue in 6 months

New ads per month

1. 1

   Research & offer · Month 1

   What we do

   We start with reaching new buyers, which the brand in this scenario named first, before anything else on this smaller store. We set basket-size offers that reward a second and third item in the cart. We set up WhatsApp messages for abandoned checkouts and repeat orders from the start.

   Why

   In this case study, a smaller pet brand grows monthly revenue in 6 months, from ₹1.8L to ₹6L (3.3x). Fewer than one in ten of our measured accounts grew that fast in the same time, so the case study follows the pace of that top tenth, holds budget where return starts to slip, and does not force the number. The main problem in this scenario is reaching new buyers, with repeat orders close behind. Each extra item in a basket is revenue the ad has already paid for. WhatsApp is cheaper than paid retargeting for buyers who already reached checkout.

   How it works

   Tier levels are set just above the basket sizes buyers already reach. WhatsApp runs alongside paid retargeting, not instead of it.

2. 2

   Measurement & reviews · Month 1 to 6

   What we do

   We keep a shared daily sheet with the ad platform's revenue next to real store orders. We set the path from ₹1.8L to ₹6L as written monthly numbers, and read every review against the month so far. We raise budget in a month only while return holds; where it slips too far, we hold it.

   Why

   Its reported return on ad spend is too low for more budget to pay, so the first months lift return before any budget step. Ad platforms claim more orders than stores record, so the store number decides budget. Written monthly numbers expose a slow month while there is still time to act.

   How it works

   Budget decisions are read off store numbers, not the ad platform alone. Written monthly numbers make each scaling decision explicit. A month whose return slips past that point keeps its budget instead.

3. 3

   Creative testing · Month 1

   What we do

   We lead the testing layer with video, catalogue ads and carousel, building to about two dozen new ads a month by the final month, with carousel watched closely since it returns less than the rest. We give each lead product its own campaign and read it weekly. The learning month runs at a low daily budget and moves up only when orders come through. We buy creative in batches and give each batch a fixed read window before buying more.

   Why

   A product nobody buys is visible within a week when it has its own campaign. The first rupees are for finding the buyer, not for volume. Buying more before a batch is read means paying for guesses.

   How it works

   Losing products are paused within a week and budget moves to the winners. The low budget stays until orders confirm the buyer. Losing batches stop; winning ads take their budget. 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

   Through Month 2 to Month 4, we push as far toward ₹6L as return allows: the budget rises gently while return holds, and Instagram Reels carries the most spend and Instagram Feed the next. Once purchases are steady, we add lookalikes of past buyers next to broad prospecting. As spend rises, we mix new creatives in with the proven ones before the old ones tire.

   Why

   Across Month 2 to Month 4, the budget rises gently, while return on spend holds. Budget is part-stepped in one of these months, taking only what return can carry. Return holds through these months because each budget step stops where return starts to slip. Past buyers are the clearest signal of who buys next.

   How it works

   Lookalike and broad audiences run the same ads, so they can be compared. Proven ads stay while new ones are added. 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 do

   From Month 5, we hold the gains and push toward ₹6L only as far as return allows. We show new arrivals to past buyers first, and build lookalikes from the ones who came back. We recover abandoned checkouts and lift repeat orders with WhatsApp messages.

   Why

   Growth slows from Month 5, still short of ₹6L. Budget keeps rising, more slowly than in the scaling months. An order from a returning buyer costs the least. A message to someone who nearly bought costs less than an ad.

   How it works

   New arrivals go to past buyers first, before broad prospecting. WhatsApp runs alongside paid retargeting, not instead of it.

1. Month 1

   The learning phase opens: a small daily budget carries the first ads, and store orders are matched to tracking. WhatsApp checkout recovery is switched on. Store orders and ad-platform revenue are checked side by side.

   • Revenue ₹1.8L
   • ROAS 1.87x
   • Ad spend ₹98,777
2. Month 2

   Scaling begins: repeat-order messages go to past buyers. With budget holds, return on spend holds.

   • Revenue ₹2L
   • ROAS 1.89x
   • Ad spend ₹1.1L
3. Month 3

   This batch's read is done: winners stay, the rest are cut. With budget steps up, return on spend holds.

   • Revenue ₹2.6L
   • ROAS 1.89x
   • Ad spend ₹1.4L
4. Month 4

   New arrivals go to past buyers first. Only the part of the step that return supports is taken: with budget steps up, return on spend holds.

   • Revenue ₹3.1L
   • ROAS 1.90x
   • Ad spend ₹1.6L
5. Month 5

   Steady phase begins: creative refresh and repeat orders take on more of the work. Only the part of the step that return supports is taken: with budget holds, return on spend holds.

   • Revenue ₹3.4L
   • ROAS 1.96x
   • Ad spend ₹1.7L
6. Month 6

   New creatives join the proven ones. Only the part of the step that return supports is taken: with budget holds, return on spend holds. Revenue ends below ₹6L, the number this scenario calls for, because budget stops rising where return starts to slip. Each order costs about what it did while learning.

   • Revenue ₹3.6L
   • ROAS 1.94x
   • Ad spend ₹1.8L

1. 1

   Falling click-through preceded a revenue drop; creative refresh is not optional.

2. 2

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

3. 3

   Test Static image alongside the main format: it reached the top creative tier most often in this industry's measured accounts.