Food & beverage case study: plan for ₹1L to ₹1.1L monthly revenue in 3 months

New ads per month

1. 1

   Research & offer · Month 1

   What we'd do

   Start with creative and content, which the booking named first, before anything else on this smaller store. Use cart-value tiers so larger baskets earn a better offer. Layer the account: a creative-testing campaign, a scaling campaign, cold audiences that exclude past buyers, and cart retargeting.

   Why

   The enquiry came from a smaller food and beverage brand that wants to grow monthly revenue in 3 months, from ₹1L to ₹5L (5x). Nine in ten of the accounts we measured grew more slowly than that in the same time; the plan aims at the fastest tenth's pace, holds budget where return would slip, and shows the gap to the target honestly. At booking, the brand named creative and content as its main problem. Higher order value lowers the share of each order that goes to ads. Separate layers stop prospecting and retargeting competing for the same budget.

   How it works

   Tier levels are set just above the basket sizes buyers already reach. Retargeting sits next to prospecting and never replaces it.

2. 2

   Measurement & targets · Month 1 to 3

   What we'd do

   Track ad-platform revenue beside store orders in a shared daily sheet. Set the path from ₹1L to ₹5L as written monthly targets, and read every review against the month so far. Raise budget in a month only while return holds; where it would slip too far, hold it.

   Why

   With no return on ad spend reported, the plan begins at the level measured food and beverage stores of that size hold. Ad platforms claim more orders than stores record, so the store number decides budget. Written targets expose a slow month while there is still time to act.

   How it works

   The sheet is read before each budget change. Each budget step is argued against the written target. Where return would slip too far, the month keeps last month's budget.

3. 3

   Creative testing · Month 1

   What we'd do

   Test with video, catalogue ads and static image first, rising to about a dozen new ads a month by the final month, with carousel watched closely since it returns less than the rest. Run one broad video campaign of the core products, with a customer testimonial, and give it most of the budget. Lead with video that carries trust: creators, customer feedback and founder-led pieces. Work in creative batches with a fixed read window each.

   Why

   An everyday product sells best when the algorithm is free to find its buyers. In most accounts we measured, video that carried trust held its return. Buying more before a batch is read means paying for guesses.

   How it works

   A video that takes off gets the budget; tests that do not convert are cut. Low-quality UGC is pulled and founder-led video takes its place. Batches that do not convert are cut; winners get the budget. New ads rise with the budget, most of them video, then catalogue ads.

4. 4

   Scaling · Month 2 to 3

   What we'd do

   Through Month 2 to Month 3, push as far toward ₹5L as return allows: the budget rises gently while return holds, and Instagram Reels carries the most spend and Facebook Feed the next. Make regional-language versions of the winning video for the states that buy most. Front-load about a third of each month's budget into the first week.

   Why

   In Month 2 to Month 3 the modelled budget rises gently, while return on spend holds. Budget is part-stepped in two of these months, taking only what return will carry. Each budget step here is sized so that return stays close to where it was. The same winning idea reaches more buyers in their own language.

   How it works

   The regional versions run next to the original. The monthly budget curve is weighted to the opening days. Most of the final month's spend sits on Instagram Reels, then Facebook Feed. Prospecting to new buyers takes the bulk of spend, while retargeting returns more for each rupee.

1. Month 1

   The learning phase opens: the first ads run on a small daily budget while tracking is checked against store orders. Cart-value offers go live at checkout. Store orders and platform revenue are reconciled in the shared sheet.

   • Projected revenue ₹95,261
   • Projected ROAS 1.89x
   • Planned ad spend ₹50,371
2. Month 2

   Scaling begins: this batch's read is done: winners stay, the rest are cut. The step is sized by what return will bear: with budget holds, return on spend rises.

   • Projected revenue ₹1L
   • Projected ROAS 1.97x
   • Planned ad spend ₹51,864
3. Month 3

   New creator and customer-feedback videos join the account. The step is sized by what return will bear: with budget steps up, return on spend dips. ₹5L is not reached in the time, because budget stops rising where return would slip. Cost per purchase ends close to the learning phase.

   • Projected revenue ₹1.1L
   • Projected ROAS 1.87x
   • Planned ad spend ₹58,703

1. 01

   Cut regional-language versions of the winning creative for the best-selling states.

2. 02

   Buy creative in batches, give each batch a fixed read window, and refresh tired ads by mixing old and new.

3. 03

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