Food & beverage case study: ₹1L to ₹2.2L monthly revenue in 1–2 months

New ads per month

1. 1

   Research & offer · Week 1 to 2

   What we do

   We set up the base for a smaller food and beverage store before any budget rises. We put the website audit, the creative brief and the monthly media schedule in place before spend moves. We add cart-value offers that step up at set basket sizes to lift order value.

   Why

   A smaller food and beverage brand grows monthly revenue in 1–2 months, from ₹1L to ₹40L (40x). No single problem was named; the case study works from the figures instead. Later budget calls need something written to be judged against. Higher order value lowers the share of each order that goes to ads.

   How it works

   All three are shared with the brand's team before any budget step. Tier levels are set just above the basket sizes buyers already reach.

2. 2

   Measurement & reviews · Week 1 to 9

   What we do

   We agree a written number for every week on the way from ₹1L to ₹40L, and start each review with the week-to-date figure against it. 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 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. Every budget call starts from the store's orders. 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 lead the testing layer with video, catalogue ads and static image, building to about two dozen new ads a month by the last four weeks, with carousel watched closely since it returns less than the rest. We run one broad video campaign of the core products, with a customer testimonial, and give it most of the budget. We test static images beside video. We run every lead product in a campaign of its own, read every week.

   Why

   Broad delivery lets the algorithm find buyers for an everyday product. In every industry we work in, static images were the format most often in the top creative tier. A product nobody buys is visible within a week when it has its own campaign.

   How it works

   A video that takes off gets the budget; tests that do not convert are cut. Statics join once a winning video is found. A product that does not sell is paused inside the week. The number of new ads grows with spend; video makes up the largest part and catalogue ads the next.

4. 4

   Scaling · Week 5 to 9

   What we do

   Through Week 5 to Week 9, we push toward ₹40L: the budget climbs in steps and return falls, and Instagram Reels carries the most spend and Facebook Reels the next. We make regional-language versions of the winning video for the states that buy most. We put seasonal collection campaigns in front of each festive and wedding peak.

   Why

   In Week 5 to Week 9 the budget climbs in steps, and return on spend falls as it does. In three of these weeks budget goes up only as far as return allows, so revenue grows more slowly than the final number needs. Spend stays flat for one of these weeks, waiting on return rather than on the calendar. Spend scaled in our accounts pushed cost per order up and return down, so no step is taken on hope. Buyers respond to the same idea in their own language.

   How it works

   Regional cuts run beside the original winner. Spend shifts into each season and between regions with the calendar. In the last four weeks, Instagram Reels takes the most spend and Facebook Reels the next most. Most spend reaches people who have not bought yet; past visitors return more per rupee.

1. Week 1

   First, the set-up: a small daily budget carries the first ads, and store orders are matched to tracking. The daily sheet now matches platform revenue to store orders. The media schedule and creative brief are signed off.

   • Revenue ₹24,652
   • ROAS 2.36x
   • Ad spend ₹10,427
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 ₹24,564
   • ROAS 2.41x
   • Ad spend ₹10,207
3. Week 3

   Offers and store fixes switch on as the first orders confirm.

   • Revenue ₹24,156
   • ROAS 2.29x
   • Ad spend ₹10,563
4. Week 4

   Learning phase closes: the buyer found and the winning creative picked.

   • Revenue ₹23,879
   • ROAS 2.44x
   • Ad spend ₹9,776
5. Week 5

   Scaling begins: budget shifts to the products that sold this period. Spend steps up, and return dips.

   • Revenue ₹30,883
   • ROAS 2.24x
   • Ad spend ₹13,777
6. Week 6

   The seasonal collection campaign leads this period's spend mix. Budget rises to the point where return starts to give way: spend steps up sharply, and return falls.

   • Revenue ₹45,724
   • ROAS 1.93x
   • Ad spend ₹23,640
7. Week 7

   Static images are tested beside the winning video. Budget rises to the point where return starts to give way: spend steps up, and return holds.

   • Revenue ₹54,876
   • ROAS 1.90x
   • Ad spend ₹28,864
8. Week 8

   Regional-language versions of the winner go live.

   • Revenue ₹60,164
   • ROAS 1.86x
   • Ad spend ₹32,353
9. Week 9

   Products that do not sell are paused and budget moves to the winners. The budget waits on return rather than on the calendar, so spend holds, and return holds. Revenue ends below ₹40L, the number the brand set, because budget stops rising where return starts to slip. Each order costs more by the end than it did while learning.

   • Revenue ₹60,522
   • ROAS 1.90x
   • Ad spend ₹31,864

1. 1

   Build around the festive and wedding calendar: seasonal catalogue or collection campaigns, regional audiences for regional festivals, and pausing regions during regional observances.

2. 2

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

3. 3

   Tested UGC for one product and a UGC lookalike audience, then cut both