Food & beverage case study: ₹1.25Cr to ₹2.37Cr monthly revenue in 12 months

New ads per month

1. 1

   Research & offer · Month 1

   What we do

   Before budget rises, we get the large food and beverage store ready to convert paid traffic. We start with a website audit, a creative brief and a monthly media schedule in the first week. We get the store ready for paid traffic first: reviews and trust pointers on product pages, a visible return window, an about page and a reason to pay upfront. We split the account into layers: one campaign to test creative, one to scale winners, prospecting that leaves out past buyers, and retargeting for carts.

   Why

   A large food and beverage store grows monthly revenue in 1 year, from ₹1.25Cr to ₹4.5Cr (3.6x). It is a long case study: past the eighth month our measured engagements are too few, so the pace is extended from what they showed until then. 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. No budget returns more than the store converts.

   How it works

   All three are shared with the brand's team before any budget step. Fixes are listed and handed over early, so later budget lands on a store that converts. Retargeting sits next to prospecting and never replaces it.

2. 2

   Measurement & reviews · Month 1 to 12

   What we do

   We report net sales after returns, cancellations and tax next to store revenue and platform revenue. We check the reported return on spend against store revenue before any budget moves. We set the path from ₹1.25Cr to ₹4.5Cr as written monthly numbers, and read every review against the month so far.

   Why

   The return on ad spend it reported sits below what measured stores of that size hold, so the case study starts there and rebuilds return before budget rises. The brand in this scenario also asked for a return on ad spend of 3.5x; the case study ends below that. Return gives way as spend rises, so that return and this revenue do not come together in the time. In measured accounts net sales ran below logged store revenue, so the numbers sit on the lower figure. A missed month shows up early instead of at the end of the case study.

   How it works

   Budget decisions are read off net sales, not the ad platform alone. The reported return and the store-side return are read side by side every week. Each budget step is argued against the written number.

3. 3

   Creative testing · Month 1

   What we do

   We test with video, catalogue ads and UGC and creator video first, rising to several dozen new ads a month by the final month, with carousel watched closely since it returns less than the rest. We brief creators for a steady run of UGC video, with regional-language cuts of the winners. We put most of the budget behind one broad video campaign of the core products, including a customer testimonial. We commission ads in batches, and read each batch for a set window before ordering the next.

   Why

   Regular UGC keeps testing going, and a regional cut stretches a winning idea further. An everyday product sells best when the algorithm is free to find its buyers. Buying more before a batch is read means paying for guesses.

   How it works

   Winning UGC is cut into regional languages before new ideas are bought. The video that takes off is scaled; the tests around it are cut. Batches that do not convert are cut; winners get the budget. More spend buys more new ads, led by video ahead of catalogue ads.

4. 4

   Scaling · Month 2 to 8

   What we do

   Through Month 2 to Month 8, we push toward ₹4.5Cr: the budget climbs in steps and return falls, and Instagram Reels carries the most spend and Instagram Feed the next. We let return decide budget: more while it holds, less when it slips. 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

   Across Month 2 to Month 8, the budget climbs in steps, and return on spend falls as it does. Three of these months stop their budget step where return slips too far. Spend scaled in our measured accounts pushed cost per order up and return down, so no step is taken on hope. Early-month demand is stronger for repeat consumables.

   How it works

   Each month's budget is set by the return the last one earned. The monthly budget curve is weighted to the opening days. Budget moves between regions as the calendar turns. In the final month, Instagram Reels takes the most spend and Instagram Feed the next most. Most spend reaches people who have not bought yet; past visitors return more per rupee.

5. 5

   Steady state · Month 9 to 12

   What we do

   From Month 9, we hold the gains and push toward ₹4.5Cr only as far as return allows. We refresh tired ads by mixing old and new creatives, and keep a creative bank. We hold the numbers on net sales as volume grows, since returns rise with it.

   Why

   From Month 9 growth slows while revenue is still under ₹4.5Cr. Budget stays about level over these months. In one account we measured, click-through fell before revenue did; refresh is how that is avoided. Net sales ran below logged store revenue in our measured accounts.

   How it works

   New creatives mix with proven ones rather than replacing them all at once. Each review opens with net sales against the month's number.

1. Month 1

   Learning month: a small daily budget carries the first ads, and store orders are matched to tracking. Net sales after returns are matched to logged revenue. Store fixes go live: reviews, trust pointers and the prepaid offer.

   • Revenue ₹1.25Cr
   • ROAS 2.45x
   • Ad spend ₹51L
2. Month 2

   Scaling starts: the winning UGC runs in regional-language versions. Return holds as the budget holds.

   • Revenue ₹1.39Cr
   • ROAS 2.53x
   • Ad spend ₹54.8L
3. Month 3

   The creative bank supplies this period's refresh.

   • Revenue ₹1.47Cr
   • ROAS 2.75x
   • Ad spend ₹53.7L
4. Month 4

   The creative batch is read and the winners keep the budget. Return falls as the budget steps up.

   • Revenue ₹1.72Cr
   • ROAS 2.34x
   • Ad spend ₹73.6L
5. Month 5

   A seasonal collection campaign takes a larger share of budget.

   • Revenue ₹1.96Cr
   • ROAS 2.30x
   • Ad spend ₹85.3L
6. Month 6

   Budget is reviewed against return before the next step. The budget step stops where return starts to slip: return dips as the budget steps up.

   • Revenue ₹2.18Cr
   • ROAS 2.12x
   • Ad spend ₹1.03Cr
7. Month 7

   The winning UGC runs in regional-language versions. The budget step stops where return starts to slip: return holds as the budget holds.

   • Revenue ₹2.28Cr
   • ROAS 2.16x
   • Ad spend ₹1.06Cr
8. Month 8

   The creative bank supplies this period's refresh.

   • Revenue ₹2.28Cr
   • ROAS 2.13x
   • Ad spend ₹1.07Cr
9. Month 9

   The case study moves into its steady phase, leaning on refreshed ads and repeat buyers. Return is still below the level where more budget pays, so return rises as the budget holds.

   • Revenue ₹2.34Cr
   • ROAS 2.22x
   • Ad spend ₹1.06Cr
10. Month 10

    The creative batch is read and the winners keep the budget. The budget step stops where return starts to slip: return holds as the budget holds.

    • Revenue ₹2.28Cr
    • ROAS 2.14x
    • Ad spend ₹1.07Cr
11. Month 11

    A seasonal collection campaign takes a larger share of budget.

    • Revenue ₹2.26Cr
    • ROAS 2.02x
    • Ad spend ₹1.12Cr
12. Month 12

    Each budget move is read against the return it bought. Return is still below the level where more budget pays, so return rises as the budget holds. Revenue ends below ₹4.5Cr, 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. The final return on spend is below the 3.5x this scenario calls for.

    • Revenue ₹2.37Cr
    • ROAS 2.17x
    • Ad spend ₹1.09Cr

1. 1

   Kept remarketing on add-to-cart and checkout audiences (11.2x)

2. 2

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

3. 3

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