Food & beverage case study: ₹30,000 to ₹33,153 monthly revenue in 2 months

New ads per month

1. 1

   Research & offer · Week 1 to 2

   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 mark the festive and wedding dates first and have seasonal collections ready ahead of them. We use cart-value tiers so larger baskets earn a better offer.

   Why

   In this case study, a smaller food and beverage brand grows monthly revenue in 2 months, from ₹30,000 to ₹1L (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 was reaching new buyers. Demand in this category rises and falls with the festive calendar. Higher order value lowers the share of each order that goes to ads.

   How it works

   Seasonal campaigns are prepared ahead of each peak. Tier levels are set just above the basket sizes buyers already reach.

2. 2

   Measurement & reviews · Week 1 to 9

   What we do

   We set the path from ₹30,000 to ₹1L as written weekly numbers, and read every review against the week so far. We log store orders every day beside what the ad platform claims. We read results in three-to-four-day windows, since the case study runs week by week.

   Why

   With no return on ad spend reported, the case study begins at the level measured food and beverage stores of that size hold. Written monthly numbers expose a slow week while there is still time to act. The ad platform's own count runs high, so the store's count is the one that moves budget.

   How it works

   Written monthly numbers make each scaling decision explicit. Budget decisions are read off store numbers, not the ad platform alone. Each window is read on purchases and cost per purchase before the next move.

3. 3

   Creative testing · Week 1 to 4

   What we do

   We test with catalogue ads, video and static image first, rising to a handful of new ads a month by the last four weeks, with no format far behind the account's return. We run one broad video campaign of the core products, with a customer testimonial, and give it most of the budget. We give each lead product its own campaign and read it weekly. The four learning weeks run at a low daily budget that moves up only when orders come through.

   Why

   An everyday product sells best when the algorithm is free to find its buyers. Products that do not sell show up inside a week, not after a month of shared budget. The first rupees are for finding the buyer, not for volume.

   How it works

   A video that takes off gets the budget; tests that do not convert are cut. Losing products are paused within a week and budget moves to the winners. Spend steps up only after orders confirm at the low budget. The number of new ads grows with spend; catalogue ads makes up the largest part and video the next.

4. 4

   Scaling · Week 5 to 9

   What we do

   Through Week 5 to Week 9, we push as far toward ₹1L as return allows: the budget rises gently while return holds, and Instagram Reels carries the most spend and Facebook Feed the next. Once purchases are steady, we add lookalikes of past buyers next to broad prospecting. We scale into the festive and wedding calendar with seasonal collection campaigns.

   Why

   In Week 5 to Week 9 the budget rises gently, while return on spend holds. Three of these weeks stop their budget step before return slips too far. Spend stays flat for one of these weeks, waiting on return rather than on the calendar. 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. Spend shifts into each season and between regions with the calendar. Instagram Reels carries the largest share of spend in the last four weeks, with Facebook Feed next. Prospecting to new buyers takes the bulk of spend, while retargeting returns more for each rupee.

1. Week 1

   First, the set-up: tracking is checked against store orders and the first ads go live on a small daily budget. Store orders and ad-platform revenue are checked side by side. Basket-size offers switch on at checkout.

   • Revenue ₹7,196
   • ROAS 1.91x
   • Ad spend ₹3,776
2. Week 2

   The first read of the ads is in, and the ones that do not convert stop. Spend holds, and return holds.

   • Revenue ₹7,113
   • ROAS 1.96x
   • Ad spend ₹3,626
3. Week 3

   Store fixes and offers go live while orders confirm.

   • Revenue ₹7,366
   • ROAS 1.87x
   • Ad spend ₹3,934
4. Week 4

   By the end of learning, the buyer is known and one ad has won.

   • Revenue ₹6,996
   • ROAS 1.91x
   • Ad spend ₹3,672
5. Week 5

   Scaling begins: the seasonal collection campaign leads this period's spend mix. Spend holds, and return rises.

   • Revenue ₹7,298
   • ROAS 1.99x
   • Ad spend ₹3,669
6. Week 6

   A past-buyer lookalike audience joins broad prospecting. The budget step stops where return starts to slip: spend steps up, and return dips.

   • Revenue ₹7,943
   • ROAS 1.90x
   • Ad spend ₹4,173
7. Week 7

   Products that do not sell are paused and budget moves to the winners. The budget step stops where return starts to slip: spend holds, and return holds.

   • Revenue ₹8,261
   • ROAS 1.94x
   • Ad spend ₹4,265
8. Week 8

   The seasonal collection campaign leads this period's spend mix.

   • Revenue ₹8,418
   • ROAS 1.88x
   • Ad spend ₹4,466
9. Week 9

   A past-buyer lookalike audience joins broad prospecting. Return is still below the level where more budget pays, so spend holds, and return rises. Revenue ends below ₹1L, the number this scenario calls for, because budget stops rising where return starts to slip. Cost per purchase ends close to the learning phase.

   • Revenue ₹8,531
   • ROAS 1.96x
   • Ad spend ₹4,342

1. 1

   Cost per order stayed well above what a low-price consumable can carry.

2. 2

   15 UGC videos, including regional-language cuts for the two best-selling states

3. 3

   Run by region for regional festivals, and pan-India for Dasara and Diwali