Food & beverage case study: Under ₹1L to ₹1.3L monthly revenue in 12 months

New ads per month

1. 1

   Research & offer · Month 1

   What we do

   We give the first month to a clear strategy, the brand’s main problem, on a smaller base. We start with a website audit, a creative brief and a monthly media schedule in the first week. We layer the account: a creative-testing campaign, a scaling campaign, cold audiences that exclude past buyers, and cart remarketing. We set basket-size offers that reward a second and third item in the cart.

   Why

   In this case study, a smaller food and beverage brand grows monthly revenue in 1 year, from Under ₹1L to ₹40L–₹50L (45x). 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 was a clear strategy. A written brief gives every later budget decision a reference point. Without layers, retargeting quietly eats the prospecting budget.

   How it works

   All three are shared with the brand's team before any budget step. Warm layers run beside prospecting, not instead of it. The tiers follow real order values, not round numbers.

2. 2

   Measurement & reviews · Month 1 to 12

   What we do

   We track ad-platform revenue beside store orders in a shared daily sheet. We agree a written number for every month on the way from Under ₹1L to ₹40L–₹50L, and start each review with the month-to-date figure against it. We raise budget in a month only while return holds; where it slips too far, we hold it.

   Why

   No starting return on ad spend was given; the starting return is what measured food and beverage stores of that size hold. Platform attribution over-counts, so budget decisions sit on the store-side number. Written monthly numbers expose a slow month while there is still time to act.

   How it works

   The sheet is read before each budget change. The month's number is on the page at every review. 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 about two dozen 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. We run one broad video campaign of the core products, with a customer testimonial, and give it most of the budget. We run static images next to the video ads.

   Why

   A product nobody buys is visible within a week when it has its own campaign. Broad delivery lets the algorithm find buyers for an everyday product. Across measured accounts in all industries, static images reached the top creative tier most often.

   How it works

   Budget follows the products that sell. A video that takes off gets the budget; tests that do not convert are cut. Statics join once a winning video is found. More spend buys more new ads, led by video ahead of catalogue ads.

4. 4

   Scaling · Month 2 to 9

   What we do

   Through Month 2 to Month 9, we push toward ₹40L–₹50L: the budget rises gently and return dips, and Instagram Reels carries the most spend and Facebook 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. We make regional-language versions of the winning video for the states that buy most.

   Why

   In Month 2 to Month 9 the budget rises gently, and return on spend dips. In several of these months budget goes up only as far as return allows, so revenue grows more slowly than the final number needs. In one of these months budget holds, because return is below the level where more budget pays. 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

   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. Regional cuts run beside the original winner. 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.

5. 5

   Steady state · Month 10 to 12

   What we do

   From Month 10, we hold the gains and push toward ₹40L–₹50L 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 10, still short of ₹40L–₹50L. Spend holds roughly steady from here. In one account we measured, click-through fell before revenue did; refresh is how that is avoided. WhatsApp is cheaper than paid retargeting for buyers who already reached checkout.

   How it works

   The bank means a tired ad is replaced the week it tires. Messages run beside retargeting ads.

1. Month 1

   The learning phase opens: a small daily budget carries the first ads, and store orders are matched to tracking. Store orders and platform revenue are reconciled in the shared sheet. Cart-value offers go live at checkout.

   • Revenue ₹96,256
   • ROAS 2.12x
   • Ad spend ₹45,365
2. Month 2

   The scaling phase opens: regional-language versions of the winner go live. Return on spend holds while budget steps up.

   • Revenue ₹1.1L
   • ROAS 2.08x
   • Ad spend ₹54,647
3. Month 3

   Products that do not sell are paused and budget moves to the winners. Budget is raised only as far as return allows: return on spend dips while budget steps up.

   • Revenue ₹1.2L
   • ROAS 1.90x
   • Ad spend ₹65,030
4. Month 4

   Tired ads are refreshed from the creative bank. Budget is raised only as far as return allows: return on spend holds while budget holds.

   • Revenue ₹1.3L
   • ROAS 1.90x
   • Ad spend ₹67,900
5. Month 5

   Past buyers get a WhatsApp nudge for their next order.

   • Revenue ₹1.3L
   • ROAS 1.86x
   • Ad spend ₹71,416
6. Month 6

   Statics go live next to the winning video.

   • Revenue ₹1.3L
   • ROAS 1.87x
   • Ad spend ₹71,022
7. Month 7

   The budget decision is taken on the return the last step earned.

   • Revenue ₹1.3L
   • ROAS 1.95x
   • Ad spend ₹68,314
8. Month 8

   Regional-language versions of the winner go live.

   • Revenue ₹1.3L
   • ROAS 1.90x
   • Ad spend ₹70,135
9. Month 9

   Products that do not sell are paused and budget moves to the winners. More budget does not pay at this return, so return on spend holds while budget holds.

   • Revenue ₹1.3L
   • ROAS 1.95x
   • Ad spend ₹68,439
10. Month 10

    The case study moves into its steady phase, leaning on refreshed ads and repeat buyers. Budget is raised only as far as return allows: return on spend holds while budget holds.

    • Revenue ₹1.3L
    • ROAS 1.94x
    • Ad spend ₹68,072
11. Month 11

    The creative bank supplies this period's refresh.

    • Revenue ₹1.3L
    • ROAS 1.87x
    • Ad spend ₹70,023
12. Month 12

    Past buyers get a WhatsApp nudge for their next order. Budget is raised only as far as return allows: return on spend holds while budget holds. ₹40L–₹50L is not reached in the time, because budget stops rising where return starts to slip. Cost per purchase ends higher than in the learning phase.

    • Revenue ₹1.3L
    • ROAS 1.90x
    • Ad spend ₹69,282

1. 1

   Layer the account: creative testing, a scaling campaign, new audiences that exclude past buyers, and catalogue or cart retargeting.

2. 2

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

3. 3

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