Food & beverage case study: ₹4L–₹5L to ₹11.4L monthly revenue in 6 months

New ads per month

1. 1

   Research & offer · Month 1

   What we do

   We start with a clear strategy, which the brand in this scenario named first, before anything else on this smaller store. We open with three documents: a website audit, a creative brief and a media schedule by month. We build the account in layers so each can be read on its own: testing, scaling, new-buyer prospecting and cart retargeting.

   Why

   In this case study, a smaller food and beverage brand grows monthly revenue in 6 months, from ₹4L–₹5L to ₹20L–₹25L (5x). That is faster than nine in ten of our measured accounts grew over the same time, so the case study below is on what that fastest tenth reached and shows where it lands against the number this scenario calls for. The main problem in this scenario is a clear strategy. Later budget calls need something written to be judged against. Layers keep each budget line readable, so a weak campaign cannot hide inside a strong one.

   How it works

   The audit, the brief and the media schedule are shared before spend rises. Warm layers run beside prospecting, not instead of it.

2. 2

   Measurement & reviews · Month 1 to 6

   What we do

   We agree a written number for every month on the way from ₹4L–₹5L to ₹20L–₹25L, and start each review with the month-to-date figure against it. We keep a shared daily sheet with the ad platform's revenue next to real store orders. 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. A shortfall is caught in the month it happens, not at the end. Ad platforms claim more orders than stores record, so the store number decides budget.

   How it works

   Written monthly numbers make each scaling decision explicit. Budget decisions are read off store numbers, not the ad platform alone. A month whose return slips past that point keeps its budget instead.

3. 3

   Creative testing · Month 1

   What we do

   We test with video, catalogue ads and UGC and creator video first, rising to a few dozen new ads a month by the final month, keeping carousel on a short leash because its return trails the account. We put most of the budget behind one broad video campaign of the core products, including a customer testimonial. We lead with video that carries trust: creators, customer feedback and founder-led pieces. The learning month runs on a small daily budget, stepping up only once orders confirm.

   Why

   Broad delivery lets the algorithm find buyers for an everyday product. In most accounts we measured, video that carried trust held its return. Early spend buys learning, not scale.

   How it works

   The video that takes off is scaled; the tests around it are cut. Weak UGC is swapped for founder-led video rather than scaled. Spend steps up only after orders confirm at the low budget. More spend buys more new ads, led by video ahead of catalogue ads.

4. 4

   Scaling · Month 2 to 4

   What we do

   Through Month 2 to Month 4, we push as far toward ₹20L–₹25L as return allows: the budget climbs in steps and return falls, and Instagram Reels carries the most spend and Instagram Feed the next. We tie every budget increase to return: we step up while it holds, and step back when it drops. We front-load about a third of each month's budget into the first week.

   Why

   Across Month 2 to Month 4, the budget climbs in steps, and return on spend falls as it does. 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

   There is no fixed ramp; each month's budget follows the return of the last. The monthly budget curve is weighted to the opening days. Instagram Reels carries the largest share of spend in the final month, with Instagram Feed next. Cold audiences take most of the budget; warm audiences return more per rupee.

5. 5

   Steady state · Month 5 to 6

   What we do

   From Month 5, we hold the gains and push toward ₹20L–₹25L only as far as return allows. We keep a bank of ready creatives and rotate them in as ads tire. We use WhatsApp for abandoned checkouts and for past buyers' next order.

   Why

   Growth slows from Month 5, still short of ₹20L–₹25L. Spend still grows, at a slower pace than during scaling. A measured account showed click-through falling ahead of revenue, so tired ads are replaced early. 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. Messages run beside retargeting ads.

1. Month 1

   First, the set-up: tracking is checked against store orders and the first ads go live on a small daily budget. The media schedule and creative brief are signed off. Store orders and ad-platform revenue are checked side by side.

   • Revenue ₹4.4L
   • ROAS 3.10x
   • Ad spend ₹1.4L
2. Month 2

   Scaling starts: repeat-order messages go to past buyers. Return holds as the budget steps up.

   • Revenue ₹4.9L
   • ROAS 3.07x
   • Ad spend ₹1.6L
3. Month 3

   Tired ads are refreshed from the creative bank.

   • Revenue ₹6.5L
   • ROAS 2.79x
   • Ad spend ₹2.3L
4. Month 4

   New creator and customer-feedback videos join the account.

   • Revenue ₹8.8L
   • ROAS 2.53x
   • Ad spend ₹3.5L
5. Month 5

   The case study moves into its steady phase, leaning on refreshed ads and repeat buyers.

   • Revenue ₹11.3L
   • ROAS 2.38x
   • Ad spend ₹4.7L
6. Month 6

   Each budget move is read against the return it bought. Budget rises to the point where return starts to give way: return holds as the budget holds. Revenue ends below ₹20L–₹25L, the number this scenario calls for, because the case study follows what the fastest tenth of our measured accounts reached. Cost per purchase ends higher than in the learning phase.

   • Revenue ₹11.4L
   • ROAS 2.32x
   • Ad spend ₹4.9L

1. 1

   Front-loaded 30–35% of each month's budget into the first eight days

2. 2

   Put 95% of the Meta budget behind videos of the core products, including a customer testimonial

3. 3

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