Food & beverage case study: ₹3Cr to ₹7.54Cr monthly revenue in 12 months

New ads per month

1. 1

   Research & offer · Month 1

   What we do

   The first problem in this scenario is a clear strategy, so the opening month on this large store goes there. We open with three documents: a website audit, a creative brief and a media schedule by month. 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. 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.

   Why

   A large food and beverage brand grows monthly revenue in 1 year, from ₹3Cr to ₹12Cr (4x). The timeframe runs past the point our measured engagements cover, so the later months extend the pace they showed up to month eight. The main problem was a clear strategy. A written brief gives every later budget decision a reference point. 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. Retargeting sits next to prospecting and never replaces it. Fixes are listed and handed over early, so later budget lands on a store that converts.

2. 2

   Measurement & reviews · Month 1 to 12

   What we do

   We track ad-platform revenue beside store revenue and net sales after returns, cancellations and tax. We agree a written number for every month on the way from ₹3Cr to ₹12Cr, 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 stores of that size hold. Returns, cancellations and tax cut logged revenue, so the numbers are set on net sales. Written monthly numbers expose a slow month while there is still time to act.

   How it works

   Net sales, not platform revenue, decide each budget step. 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 lead the testing layer with video, catalogue ads and UGC and creator video, building to well over a hundred new ads a month by the final month, with carousel watched closely since it returns less than the rest. We give each lead product its own campaign and read it weekly. The learning month runs at a low daily budget and moves up only when orders come through. We put most of the budget behind one broad video campaign of the core products, including a customer testimonial.

   Why

   Shared campaigns hide weak products; separate ones expose them fast. The first rupees are for finding the buyer, not for volume. An everyday product sells best when the algorithm is free to find its buyers.

   How it works

   Budget follows the products that sell. The low budget stays until orders confirm the buyer. The video that takes off is scaled; the tests around it are cut. 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 9

   What we do

   We scale through Month 2 to Month 9 toward ₹12Cr as the budget climbs in steps and return falls, with Instagram Reels taking the largest share of spend and Instagram Feed the next. We let return decide budget: more while it holds, less when it slips. We make regional-language versions of the winning video for the states that buy most. We front-load about a third of each month's budget into the first week.

   Why

   In Month 2 to Month 9 the budget climbs in steps, and return on spend falls as it does. In one of these months budget goes up only as far as return allows, so revenue grows more slowly than the number this scenario calls for. Spend stays flat for one of these months, waiting on return rather than on the calendar. Spend scaled in our measured accounts pushed cost per order up and return down, so no step is taken on hope. The same winning idea reaches more buyers in their own language.

   How it works

   There is no fixed ramp; each month's budget follows the return of the last. The regional versions run next to the original. The monthly budget curve is weighted to the opening days. In the final month, Instagram Reels takes the most spend and Instagram Feed the next most. Cold audiences take most of the budget; warm audiences return more per rupee.

5. 5

   Steady state · Month 10 to 12

   What we do

   From Month 10, we protect the revenue already built and move toward ₹12Cr where return permits. We keep a bank of ready creatives and rotate them in as ads tire. We hold the numbers on net sales as volume grows, since returns rise with it.

   Why

   From Month 10 growth slows while revenue is still under ₹12Cr. Spend holds roughly steady from here. A measured account showed click-through falling ahead of revenue, so tired ads are replaced early. Net sales ran below logged store revenue in our measured accounts.

   How it works

   Refreshes are gradual: a few new ads at a time. Each review opens with net sales against the month's number.

1. Month 1

   First, the set-up: the first ads run on a small daily budget while tracking is checked against store orders. The account runs in layers: testing, scaling and retargeting. The store fix list is live, with reviews on product pages and a prepaid offer.

   • Revenue ₹2.83Cr
   • ROAS 3.52x
   • Ad spend ₹80.5L
2. Month 2

   Scaling starts: the budget decision is taken on the return the last step earned. Return on spend holds while budget holds.

   • Revenue ₹2.96Cr
   • ROAS 3.65x
   • Ad spend ₹81.1L
3. Month 3

   Tired ads are refreshed from the creative bank. Return on spend dips while budget steps up.

   • Revenue ₹3.15Cr
   • ROAS 3.43x
   • Ad spend ₹91.9L
4. Month 4

   Budget shifts to the products that sold this period.

   • Revenue ₹3.61Cr
   • ROAS 3.07x
   • Ad spend ₹1.18Cr
5. Month 5

   The winner now also runs in regional languages.

   • Revenue ₹4.29Cr
   • ROAS 3.20x
   • Ad spend ₹1.34Cr
6. Month 6

   Each budget move is read against the return it bought.

   • Revenue ₹5.25Cr
   • ROAS 3.08x
   • Ad spend ₹1.7Cr
7. Month 7

   The creative bank supplies this period's refresh.

   • Revenue ₹6.5Cr
   • ROAS 2.59x
   • Ad spend ₹2.51Cr
8. Month 8

   Products that do not sell are paused and budget moves to the winners. Budget rises to the point where return starts to give way: return on spend holds while budget steps up.

   • Revenue ₹7.3Cr
   • ROAS 2.52x
   • Ad spend ₹2.9Cr
9. Month 9

   Regional-language versions of the winner go live. Return is still below the level where more budget pays, so return on spend holds while budget holds.

   • Revenue ₹7.35Cr
   • ROAS 2.57x
   • Ad spend ₹2.85Cr
10. Month 10

    Steady phase begins: creative refresh and repeat orders take on more of the work. Budget rises to the point where return starts to give way: return on spend holds while budget holds.

    • Revenue ₹7.25Cr
    • ROAS 2.50x
    • Ad spend ₹2.9Cr
11. Month 11

    Each budget move is read against the return it bought. Return is still below the level where more budget pays, so return on spend holds while budget holds.

    • Revenue ₹7.45Cr
    • ROAS 2.60x
    • Ad spend ₹2.87Cr
12. Month 12

    Ads with falling click-through are swapped from the bank. Return is still below the level where more budget pays, so return on spend holds while budget holds. Revenue is now past halfway from ₹3Cr to ₹12Cr. The case study finishes short of ₹12Cr: budget stops rising where return starts to slip. Each order costs more by the end than it did while learning.

    • Revenue ₹7.54Cr
    • ROAS 2.64x
    • Ad spend ₹2.85Cr

1. 1

   Monthly review calls that start with what has not worked

2. 2

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

3. 3

   Run by region for regional festivals, and pan-India for Dasara and Diwali