Food & beverage case study: plan for ₹3L to ₹4.1L monthly revenue in 6 months

New ads per month

1. 1

   Research & offer · Month 1

   What we'd do

   Start with return on ad spend, which the booking named first, before anything else on this smaller store. Add cart-value offers that step up at set basket sizes to lift order value. Before budget rises, close the gaps that stop a visitor buying: missing reviews, an unclear return window, no about page and no prepaid incentive.

   Why

   The enquiry came from a smaller food and beverage brand that wants to grow monthly revenue in 6 months, from ₹3L to ₹10L (3.3x). That is faster than nine in ten of our measured accounts grew over the same time, so the plan aims at that fastest tenth's pace, holds budget where return would slip, and shows where it lands against the target. The main problem named at booking was return on ad spend, followed by reaching new buyers. Each extra item in a basket is revenue the ad has already paid for. Every rupee of ads is capped by how well the store turns visits into orders.

   How it works

   Tier levels are set just above the basket sizes buyers already reach. The fix list goes to the brand's team in the opening weeks, ahead of any budget step.

2. 2

   Measurement & targets · Month 1 to 6

   What we'd do

   Track ad-platform revenue beside store orders in a shared daily sheet. Write month-by-month targets with the brand's team that climb from ₹3L to ₹10L, and open every review with the month-to-date number against them. Set targets on net sales after returns and cancellations, not on logged revenue.

   Why

   It did not report a return on ad spend, so the plan starts from what 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

   Budget decisions are read off store numbers, not the ad platform alone. Each budget step is argued against the written target. Each review opens with net sales against the target.

3. 3

   Creative testing · Month 1

   What we'd do

   Lead the testing layer with video, catalogue ads and UGC and creator video, building to a few dozen new ads a month by the final month, keeping carousel on a short leash because its return trails the account. Separate the lead products into their own campaigns and review each one weekly. Run one broad video campaign of the core products, with a customer testimonial, and give it most of the budget. Test static images beside video.

   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. In every industry we measured, static images were the format most often in the top creative tier.

   How it works

   A product that does not sell is paused inside the week. The video that takes off is scaled; the tests around it are cut. Statics are added after a video wins. More spend buys more new ads, led by video ahead of catalogue ads.

4. 4

   Scaling · Month 2 to 4

   What we'd do

   Through Month 2 to Month 4, push as far toward ₹10L as return allows: the budget rises gently while return holds, and Instagram Reels carries the most spend and Facebook Reels the next. Let return decide budget: more while it holds, less when it slips. Front-load about a third of each month's budget into the first week.

   Why

   Across Month 2 to Month 4, the modelled budget rises gently, while return on spend holds. In two of these months the step is trimmed to the size return can hold. 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

   Budget follows return month to month instead of a fixed ramp. The monthly budget curve is weighted to the opening days. Instagram Reels carries the largest share of spend in the final month, with Facebook Reels next. Prospecting to new buyers takes the bulk of spend, while retargeting returns more for each rupee.

5. 5

   Steady state · Month 5 to 6

   What we'd do

   From Month 5, hold the gains and push toward ₹10L only as far as return allows. Hold budget where return peaks instead of pushing past it. Hold a creative bank and swap tired ads out before click-through falls.

   Why

   Growth slows from Month 5, still short of ₹10L. Budget stays about level over these months. Most of our engagements saw return fall back from its best month. In one account we measured, click-through fell before revenue did; refresh is how that is avoided.

   How it works

   Budget is held while return is at its best and cut back when it slips. The bank means a tired ad is replaced the week it tires.

1. Month 1

   Learning month: 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 ₹3.2L
   • Projected ROAS 1.89x
   • Planned ad spend ₹1.7L
2. Month 2

   Scaling starts: products that do not sell are paused and budget moves to the winners. With budget holds, return on spend holds.

   • Projected revenue ₹3.4L
   • Projected ROAS 1.90x
   • Planned ad spend ₹1.8L
3. Month 3

   Tired ads are refreshed from the creative bank. The step is sized by what return will bear: with budget steps up, return on spend holds.

   • Projected revenue ₹3.8L
   • Projected ROAS 1.92x
   • Planned ad spend ₹2L
4. Month 4

   Static images are tested beside the winning video. The step is sized by what return will bear: with budget holds, return on spend holds.

   • Projected revenue ₹4L
   • Projected ROAS 1.93x
   • Planned ad spend ₹2.1L
5. Month 5

   Steady phase begins: creative refresh and repeat orders take on more of the work.

   • Projected revenue ₹4.1L
   • Projected ROAS 1.88x
   • Planned ad spend ₹2.2L
6. Month 6

   Budget is reviewed against return before the next step. With return short of where a budget step pays, with budget holds, return on spend holds. Revenue ends below ₹10L, the target set at enquiry, because budget stops rising where return would slip. Cost per purchase ends close to the learning phase.

   • Projected revenue ₹4.1L
   • Projected ROAS 1.93x
   • Planned ad spend ₹2.1L

1. 01

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

2. 02

   Put most of the budget behind one broad video campaign of the core products, and scale a video that takes off.

3. 03

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