Food & beverage case study: ₹50,000 to ₹64,516 monthly revenue in 6 months

New ads per month

1. 1

   Research & offer · Month 1

   What we do

   We start with scaling ad spend, which the brand in this scenario named first, before anything else on this smaller store. 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 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 6 months, from ₹50,000 to ₹1Cr (200x). 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 scaling ad spend. Without layers, retargeting quietly eats the prospecting budget. Each extra item in a basket is revenue the ad has already paid for.

   How it works

   Retargeting sits next to prospecting and never replaces it. Offers are tuned to the order values that already sell.

2. 2

   Measurement & reviews · Month 1 to 6

   What we do

   We keep a shared daily sheet with the ad platform's revenue next to real store orders. We write month-by-month revenue numbers with the brand's team that climb from ₹50,000 to ₹1Cr, and open every review with the month-to-date number against them. We check the reported return on spend against store revenue before any budget moves.

   Why

   The return on ad spend it reported sits above what measured food and beverage stores of that size hold; the case study starts from it and allows for some of it to give way as spend rises. The ad platform's own count runs high, so the store's count is the one that moves budget. 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. The reported return and the store-side return are read side by side every week.

3. 3

   Creative testing · Month 1

   What we do

   We test with video, catalogue ads and static image first, rising to about a dozen new ads a month by the final month, keeping carousel on a short leash because its return trails the account. We run every lead product in a campaign of its own, read every week. We work in creative batches with a fixed read window each. We put most of the budget behind one broad video campaign of the core products, including a customer testimonial.

   Why

   A product nobody buys is visible within a week when it has its own campaign. The read window keeps creative spending tied to evidence. Broad delivery lets the algorithm find buyers for an everyday product.

   How it works

   Budget follows the products that sell. Losing batches stop; winning ads take their budget. The video that takes off is scaled; the tests around it are cut. New ads rise with the budget, most of them video, then catalogue ads.

4. 4

   Scaling · Month 2 to 4

   What we do

   We scale through Month 2 to Month 4 toward ₹1Cr as the budget rises gently and return falls, with Instagram Reels taking the largest share of spend and Facebook Feed the next. We front-load about a third of each month's budget into the first week. We raise budget only while return on spend holds, and cut it when return drops.

   Why

   In Month 2 to Month 4 the budget rises gently, and return on spend falls as it does. In three of these months the step is trimmed to the size return can hold. 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

   The monthly budget curve is weighted to the opening days. There is no fixed ramp; each month's budget follows the return of the last. Most of the final month's spend sits on Instagram Reels, then Facebook Feed. 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 ₹1Cr only as far as return allows. We use WhatsApp for abandoned checkouts and for past buyers' next order. We refresh tired ads by mixing old and new creatives, and keep a creative bank.

   Why

   Growth slows from Month 5, still short of ₹1Cr. Budget stays about level over these months. WhatsApp is cheaper than paid retargeting for buyers who already reached checkout. A measured account showed click-through falling ahead of revenue, so tired ads are replaced early.

   How it works

   WhatsApp runs alongside paid retargeting, not instead of it. The bank means a tired ad is replaced the week it tires.

1. Month 1

   The learning phase opens: tracking is checked against store orders and the first ads go live on a small daily budget. Cart-value offers go live at checkout. The account runs in layers: testing, scaling and retargeting.

   • Revenue ₹52,016
   • ROAS 2.47x
   • Ad spend ₹21,043
2. Month 2

   The scaling phase opens: ads with falling click-through are swapped from the bank. Budget rises to the point where return starts to give way: as budget steps up sharply, return on spend steps up sharply.

   • Revenue ₹69,745
   • ROAS 2.02x
   • Ad spend ₹34,536
3. Month 3

   The weekly product read pauses the products that are not selling. Budget rises to the point where return starts to give way: as budget holds, return on spend holds.

   • Revenue ₹73,178
   • ROAS 1.94x
   • Ad spend ₹37,715
4. Month 4

   Repeat-order messages go to past buyers.

   • Revenue ₹69,834
   • ROAS 2.00x
   • Ad spend ₹34,989
5. Month 5

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

   • Revenue ₹67,335
   • ROAS 1.96x
   • Ad spend ₹34,388
6. Month 6

   Budget is reviewed against return before the next step. Budget rises to the point where return starts to give way: as budget holds, return on spend holds. ₹1Cr 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 ₹64,516
   • ROAS 1.90x
   • Ad spend ₹33,937

1. 1

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

2. 2

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

3. 3

   Monthly review calls that start with what has not worked