Electronics case study: plan for ₹1.3Cr to ₹4Cr monthly revenue in 1 year

New ads per month

1. 1

   Research & offer · Month 1

   What we'd do

   Aim the first month at keeping return on spend while scaling, the problem named at booking, on a large base. Build the account in layers so each can be read on its own: testing, scaling, new-buyer prospecting and cart retargeting. Fix the store before scaling: trust pointers, reviews, a clear return window, an about page and a prepaid incentive. Ask for a product-level stock forecast so spend follows what can ship.

   Why

   A large electronics store asked us how to grow monthly revenue in 1 year, from ₹1.3Cr to ₹4Cr (3.1x). The timeframe runs past the point our measured engagements cover, so the later months extend the pace they showed up to month eight. At booking, the brand named keeping return on spend while scaling as its main problem, with return on ad spend close behind. Separate layers stop prospecting and retargeting competing for the same budget. Every rupee of ads is capped by how well the store turns visits into orders.

   How it works

   Each layer keeps its own budget line. Site fixes are handed over in the first weeks, before budget rises. Spend is planned against stock by product.

2. 2

   Measurement & targets · Month 1 to 12

   What we'd do

   Agree a written target for every month on the way from ₹1.3Cr to ₹4Cr, and start each review with the month-to-date figure against it. Report net sales after returns, cancellations and tax next to store revenue and platform revenue.

   Why

   It did not report a return on ad spend, so the plan starts from what measured stores of that size hold. A shortfall is caught in the month it happens, not at the end. Returns, cancellations and tax cut logged revenue, so targets are set on net sales.

   How it works

   Written targets make each scaling decision explicit. Budget decisions are read off net sales, not the ad platform alone.

3. 3

   Creative testing · Month 1

   What we'd do

   Test with video, static image and catalogue ads first, rising to well over a hundred new ads a month by the final month, keeping carousel on a short leash because its return trails the account. Give each lead product its own campaign and read it weekly. Commission ads in batches, and read each batch for a set window before ordering the next. Test several interest clusters against a broad audience, with video and catalogue ads.

   Why

   A product nobody buys is visible within a week when it has its own campaign. A fixed window stops spend chasing a creative before it has been read. Buyers split by use case, so clusters show which one buys before budget is committed.

   How it works

   Budget follows the products that sell. Losing batches stop; winning ads take their budget. Clusters are read against broad before the scaling plan is set. More spend buys more new ads, led by video ahead of static image.

4. 4

   Scaling · Month 2 to 9

   What we'd do

   Through Month 2 to Month 9, push toward ₹4Cr: the budget climbs in steps and return falls, and Instagram Reels carries the most spend and Instagram Feed the next. Tie every budget increase to return: step up while it holds, step back when it drops. Run cost caps, bid caps, CBO and ABO as parallel versions before budget steps up. Plan spend against stock with a product-level forecast, and scale with bundle offers and a cost-control campaign.

   Why

   Across Month 2 to Month 9, 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. Controls show which setup holds cost per purchase as spend rises.

   How it works

   Budget follows return month to month instead of a fixed ramp. Controls run as parallel versions and the one that holds cost is kept. Spend is planned against stock by product. 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 10 to 12

   What we'd do

   From Month 10, close the last stretch to ₹4Cr without losing return. Hold budget where return peaks instead of pushing past it. Hold targets on net sales as volume grows, since returns rise with it.

   Why

   At Month 10 revenue is close to ₹4Cr. Budget keeps rising, more slowly than in the scaling months. Most of our engagements saw return fall back from its best month. Net sales ran below logged store revenue in our measured accounts.

   How it works

   Budget is held while return is at its best and cut back when it slips. Each review opens with net sales against the target.

1. Month 1

   First, the set-up: the first ads run on a small daily budget while tracking is checked against store orders. Net sales are reconciled against logged revenue. Store fixes go live: reviews, trust pointers and the prepaid offer.

   • Projected revenue ₹1.28Cr
   • Projected ROAS 3.44x
   • Planned ad spend ₹37.2L
2. Month 2

   Scaling starts: bid-cap and cost-cap versions run beside open bidding. Return on spend holds while budget holds.

   • Projected revenue ₹1.33Cr
   • Projected ROAS 3.44x
   • Planned ad spend ₹38.7L
3. Month 3

   The budget decision is taken on the return the last step earned.

   • Projected revenue ₹1.39Cr
   • Projected ROAS 3.31x
   • Planned ad spend ₹41.9L
4. Month 4

   Products that do not sell are paused and budget moves to the winners. Return on spend holds while budget steps up.

   • Projected revenue ₹1.53Cr
   • Projected ROAS 3.26x
   • Planned ad spend ₹47L
5. Month 5

   Bundle offers run with a cost-control campaign.

   • Projected revenue ₹1.75Cr
   • Projected ROAS 3.07x
   • Planned ad spend ₹57.1L
6. Month 6

   This batch's read is done: winners stay, the rest are cut.

   • Projected revenue ₹2.19Cr
   • Projected ROAS 2.99x
   • Planned ad spend ₹73.3L
7. Month 7

   Bid-cap and cost-cap versions run beside open bidding.

   • Projected revenue ₹2.63Cr
   • Projected ROAS 2.82x
   • Planned ad spend ₹93L
8. Month 8

   Bid-cap and cost-cap versions run beside open bidding. Return on spend rises while budget holds. Monthly revenue passes the halfway point between ₹1.3Cr and ₹4Cr.

   • Projected revenue ₹2.97Cr
   • Projected ROAS 2.96x
   • Planned ad spend ₹1.01Cr
9. Month 9

   Budget shifts to the products that sold this period. Return on spend holds while budget steps up.

   • Projected revenue ₹3.54Cr
   • Projected ROAS 2.93x
   • Planned ad spend ₹1.21Cr
10. Month 10

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

    • Projected revenue ₹3.73Cr
    • Projected ROAS 2.72x
    • Planned ad spend ₹1.37Cr
11. Month 11

    Budget shifts to the products that sold this period. Return on spend holds while budget holds.

    • Projected revenue ₹3.8Cr
    • Projected ROAS 2.74x
    • Planned ad spend ₹1.39Cr
12. Month 12

    This batch's read is done: winners stay, the rest are cut. Return on spend dips while budget steps up. The plan projects reaching the ₹4Cr target. Each order costs more by the end than it did while learning.

    • Projected revenue ₹4.08Cr
    • Projected ROAS 2.63x
    • Planned ad spend ₹1.55Cr

1. 01

   Ask for a product-level festive forecast so spend follows stock.

2. 02

   Kept a creatives bank and 4–8 social posts a month

3. 03

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