Food & beverage case study: ₹20,000 to ₹22,906 monthly revenue in 3 months

New ads per month

1. 1

   Research & offer · Month 1

   What we do

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

   Why

   In this case study, a smaller food and beverage brand grows monthly revenue in 3 months, from ₹20,000 to ₹12L (60x). 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 rather than forcing the number. The brand in this scenario named no single problem, so the case study starts from the numbers. Later budget calls need something written to be judged against. Each extra item in a basket is revenue the ad has already paid for.

   How it works

   All three are shared with the brand's team before any budget step. The tiers follow real order values, not round numbers.

2. 2

   Measurement & reviews · Month 1 to 3

   What we do

   We track ad-platform revenue beside store orders in a shared daily sheet. We agree a written number for every month on the way from ₹20,000 to ₹12L, and start each review with the month-to-date figure against it. We set a written rule: no budget step in a month where return falls too far to pay for it.

   Why

   It did not report a return on ad spend, so the case study starts from what measured food and beverage stores of that size hold. Platform attribution over-counts, so budget decisions sit on the store-side number. 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. Where return slips too far, the month keeps last month's budget.

3. 3

   Creative testing · Month 1

   What we do

   We test with video, catalogue ads and UGC and creator video first, rising to about a dozen new ads a month by the final month, with no format far behind the account's return. We run every lead product in a campaign of its own, read every week. We put most of the budget behind one broad video campaign of the core products, including a customer testimonial. The learning month runs with a deliberately small daily budget until orders prove the buyer.

   Why

   Products that do not sell show up inside a week, not after a month of shared budget. Broad delivery lets the algorithm find buyers for an everyday product. Spend in the learning phase pays for information.

   How it works

   Budget follows the products that sell. A video that takes off gets the budget; tests that do not convert are cut. Only confirmed orders at the low budget unlock the next step. The number of new ads grows with spend; video makes up the largest part and catalogue ads the next.

4. 4

   Scaling · Month 2 to 3

   What we do

   Through Month 2 to Month 3, we push toward ₹12L: the budget rises gently and return dips, and Instagram Reels carries the most spend and Facebook Reels the next. We front-load about a third of each month's budget into the first week. We put seasonal collection campaigns in front of each festive and wedding peak.

   Why

   In Month 2 to Month 3 the budget rises gently, and return on spend dips. In two of these months budget goes up only as far as return allows, so revenue grows more slowly than the brand's number needs. Our measured accounts saw cost per order rise and return fall as spend scaled; that is why each step here waits on return. Early-month demand is stronger for repeat consumables.

   How it works

   The monthly budget curve is weighted to the opening days. Spend shifts into each season and between regions with the calendar. In the final month, 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. Month 1

   Learning month: tracking is checked against store orders and the first ads go live on a small daily budget. The audit, brief and media schedule are agreed with the brand's team. The daily sheet now matches platform revenue to store orders.

   • Revenue ₹21,175
   • ROAS 1.98x
   • Ad spend ₹10,681
2. Month 2

   Scaling starts: a seasonal collection campaign takes a larger share of budget. Only the part of the step that return supports is taken: with budget holds, return on spend dips.

   • Revenue ₹22,240
   • ROAS 1.89x
   • Ad spend ₹11,744
3. Month 3

   Products that do not sell are paused and budget moves to the winners. Only the part of the step that return supports is taken: with budget holds, return on spend holds. Revenue ends below ₹12L, the number this scenario calls for, because budget stops rising where return starts to slip. Cost per purchase ends higher than in the learning phase.

   • Revenue ₹22,906
   • ROAS 1.89x
   • Ad spend ₹12,121

1. 1

   We front-load about a third of each month's budget into the first week.

2. 2

   Track ad-platform revenue beside store revenue (and net sales) daily or weekly, and set the numbers on the lower figure.

3. 3

   Monthly review calls that start with what has not worked