Food & beverage case study: ₹25,000 to ₹30,300 monthly revenue in 7 months

New ads per month

1. 1

   Research & offer · Month 1

   What we do

   Before budget rises, we get the smaller food and beverage store ready to convert paid traffic. We open with three documents: a website audit, a creative brief and a media schedule by month. We set basket-size offers that reward a second and third item in the cart. We fix the store before scaling: trust pointers, reviews, a clear return window, an about page and a prepaid incentive.

   Why

   In this case study, a smaller food and beverage brand grows monthly revenue in 7 months, from ₹25,000 to ₹10L (40x). Nine in ten of the accounts we measured grew more slowly than that in the same time; the case study is built on what the fastest tenth reached, and shows the gap to the agreed number honestly. The brand in this scenario named no single problem, so the case study starts from the numbers. Without a brief, each creative and budget decision starts from scratch. Each extra item in a basket is revenue the ad has already paid for.

   How it works

   The brief is agreed first; spend follows it. The tiers follow real order values, not round numbers. Fixes are listed and handed over early, so later budget lands on a store that converts.

2. 2

   Measurement & reviews · Month 1 to 7

   What we do

   We keep a shared daily sheet with the ad platform's revenue next to real store orders. We write month-by-month revenue numbers with the brand's team that climb from ₹25,000 to ₹10L, and open every review with the month-to-date number against them. We raise budget in a month only while return holds; where it slips too far, we hold it.

   Why

   With no return on ad spend reported, the case study begins at the level measured food and beverage stores of that size hold. The ad platform's own count runs high, so the store's count is the one that moves budget. A missed month shows up early instead of at the end of the case study.

   How it works

   Budget decisions are read off store numbers, not the ad platform alone. Each budget step is argued against the written number. 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 catalogue ads, video and static image, building to a handful of new ads a month by the final month, with no format far behind the account's return. The learning month runs at a low daily budget and moves up only when orders come through. We run one broad video campaign of the core products, with a customer testimonial, and give it most of the budget. We make trust the subject of the video: creator reels, customer feedback and founder-led clips.

   Why

   Spend in the learning phase pays for information. Broad delivery lets the algorithm find buyers for an everyday product. Video built on trust was the format that held return in most measured accounts.

   How it works

   Only confirmed orders at the low budget unlock the next step. The video that takes off is scaled; the tests around it are cut. Weak UGC is swapped for founder-led video rather than scaled. More spend buys more new ads, led by catalogue ads ahead of video.

4. 4

   Scaling · Month 2 to 5

   What we do

   We scale through Month 2 to Month 5 toward ₹10L as the budget rises gently while return holds, with Instagram Reels taking the largest share of spend and Facebook Reels the next. We front-load about a third of each month's budget into the first week. We make regional-language versions of the winning video for the states that buy most. We raise budget only while return on spend holds, and cut it when return drops.

   Why

   Across Month 2 to Month 5, the budget rises gently, while return on spend holds. Budget is part-stepped in four of these months, taking only what return will carry. Each budget step here is sized so that return stays close to where it was. Early-month demand is stronger for repeat consumables.

   How it works

   The monthly budget curve is weighted to the opening days. Regional cuts run beside the original winner. Each month's budget is set by the return the last one earned. Most of the final month's spend sits on Instagram Reels, then Facebook Reels. Most spend reaches people who have not bought yet; past visitors return more per rupee.

5. 5

   Steady state · Month 6 to 7

   What we do

   From Month 6, we hold the gains and push toward ₹10L only as far as return allows. We hold a creative bank and swap tired ads out before click-through falls. We recover abandoned checkouts and lift repeat orders with WhatsApp messages.

   Why

   Growth slows from Month 6, still short of ₹10L. Spend holds roughly steady from here. Falling click-through preceded a revenue drop in a measured account, so creative refresh is not optional. A message to someone who nearly bought costs less than an ad.

   How it works

   Refreshes are gradual: a few new ads at a time. 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. The audit, brief and media schedule are agreed with the brand's team. Reviews, trust pointers and the prepaid incentive are now on the store.

   • Revenue ₹25,302
   • ROAS 1.91x
   • Ad spend ₹13,268
2. Month 2

   Scaling starts: budget is reviewed against return before the next step. Budget goes up only as far as return can carry it: return on spend holds while budget holds.

   • Revenue ₹26,927
   • ROAS 1.95x
   • Ad spend ₹13,843
3. Month 3

   Past buyers get a WhatsApp nudge for their next order.

   • Revenue ₹28,881
   • ROAS 1.90x
   • Ad spend ₹15,179
4. Month 4

   Tired ads are refreshed from the creative bank.

   • Revenue ₹29,386
   • ROAS 1.90x
   • Ad spend ₹15,494
5. Month 5

   The winner now also runs in regional languages.

   • Revenue ₹30,139
   • ROAS 1.92x
   • Ad spend ₹15,673
6. Month 6

   From here the work shifts to keeping ads fresh and bringing buyers back.

   • Revenue ₹30,277
   • ROAS 1.90x
   • Ad spend ₹15,943
7. Month 7

   New creator and customer-feedback videos join the account. Budget goes up only as far as return can carry it: return on spend holds while budget holds. The case study finishes short of ₹10L: budget stops rising where return starts to slip. Cost per purchase ends close to the learning phase.

   • Revenue ₹30,300
   • ROAS 1.96x
   • Ad spend ₹15,449

1. 1

   Refreshed tired ads by mixing old and new creatives; one product ad returned to 24.8x

2. 2

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

3. 3

   Tracked Meta and Shopify side by side, day by day, in a shared sheet