Electronics case study: ₹50,000 to ₹60,788 monthly revenue in 4 months

New ads per month

1. 1

   Research & offer · Month 1

   What we do

   The first problem in this scenario is reaching new buyers, so the opening month on this smaller store goes there. We set basket-size offers that reward a second and third item in the cart. We ask for a product-level stock count so spend follows what can ship.

   Why

   In this case study, a smaller electronics brand grows monthly revenue in 4 months, from ₹50,000 to ₹5L (10x). That is faster than nine in ten of our measured accounts grew over the same time, so the case study below is on what that fastest tenth reached and shows where it lands against the number this scenario calls for. The main problem in this scenario is reaching new buyers, with marketing and social presence close behind. A larger basket spreads the cost of each order over more revenue. Scaling ads on a product that sells out wastes the peak.

   How it works

   The tiers follow real order values, not round numbers. Spend is set against stock by product.

2. 2

   Measurement & reviews · Month 1 to 4

   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 ₹50,000 to ₹5L 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

   It did not report a return on ad spend, so the case study starts from what measured electronics stores of that size hold. The ad platform's own count runs high, so the store's count is the one that moves budget. Written monthly numbers expose a slow month while there is still time to act.

   How it works

   Every budget call starts from the store's orders. 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 test with video, static image and carousel first, rising 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 several interest clusters against a broad audience, with video and catalogue ads. The learning month runs at a low daily budget and moves up only when orders come through. We give each lead product its own campaign and read it weekly.

   Why

   Buyers split by use case, so clusters show which one buys before budget is committed. Early spend buys learning, not scale. Shared campaigns hide weak products; separate ones expose them fast.

   How it works

   Clusters are read against broad before the scaling budget is set. Spend steps up only after orders confirm at the low budget. Budget follows the products that sell. New ads rise with the budget, most of them video, then static image.

4. 4

   Scaling · Month 2 to 3

   What we do

   We scale through Month 2 to Month 3 toward ₹5L as the budget rises gently while return holds, with Instagram Reels taking the largest share of spend and Facebook Feed the next. Once purchases are steady, we add lookalikes of past buyers next to broad prospecting. We raise budget only while return on spend holds, and cut it when return drops.

   Why

   Across Month 2 to Month 3, the budget rises gently, while return on spend holds. Two of these months stop their budget step where return slips too far. Each budget step here is sized so that return stays close to where it was. The people who already bought describe the next buyer best.

   How it works

   Lookalikes are read against broad on the same creative. Budget follows return month to month instead of a fixed ramp. Instagram Reels carries the largest share of spend in the final month, with Facebook Feed next. Cold audiences take most of the budget; warm audiences return more per rupee.

5. 5

   Steady state · Month 4

   What we do

   From Month 4, we hold the gains and push toward ₹5L only as far as return allows. We build lookalikes from repeat buyers and retarget past buyers with new arrivals. We hold a creative bank and swap tired ads out before click-through falls.

   Why

   Growth slows from Month 4, still short of ₹5L. Budget stays about level over these months. Repeat buyers are the cheapest orders an account gets. A measured account showed click-through falling ahead of revenue, so tired ads are replaced early.

   How it works

   Past buyers see new arrivals before anyone else. New creatives mix with proven ones rather than replacing them all at once.

1. Month 1

   Learning month: the first ads run on a small daily budget while tracking is checked against store orders. Store orders and ad-platform revenue are checked side by side. The cart-value tiers are live.

   • Revenue ₹51,310
   • ROAS 1.91x
   • Ad spend ₹26,922
2. Month 2

   Scaling starts: tired ads are refreshed from the creative bank. Budget rises to the point where return starts to give way: budget holds and return on spend holds.

   • Revenue ₹56,041
   • ROAS 1.91x
   • Ad spend ₹29,370
3. Month 3

   Past buyers get the new arrivals ahead of prospecting.

   • Revenue ₹59,704
   • ROAS 1.98x
   • Ad spend ₹30,138
4. Month 4

   Steady phase begins: creative refresh and repeat orders take on more of the work. Budget rises to the point where return starts to give way: budget holds and return on spend holds. ₹5L is not reached in the time, because budget stops rising where return starts to slip. Each order costs about what it did while learning.

   • Revenue ₹60,788
   • ROAS 1.98x
   • Ad spend ₹30,685

1. 1

   Six interest clusters, from tech and gaming to fashion, plus a broad audience, with video and catalogue ads

2. 2

   Run several interest clusters plus a broad audience with video and catalogue ads, then a bundle offer and a cost-control campaign to scale.

3. 3

   Scaling built on video creative, bundle offers and a cost-control campaign