Food & beverage case study: ₹30L to ₹52.7L monthly revenue in 6 months

New ads per month

1. 1

   Research & offer · Month 1

   What we do

   The first problem in this scenario is repeat orders, so the opening month on this established store goes there. We set up WhatsApp messages for abandoned checkouts and repeat orders from the start. Before budget rises, we close the gaps that stop a visitor buying: missing reviews, an unclear return window, no about page and no prepaid incentive.

   Why

   An established food and beverage brand grows monthly revenue in 6 months, from ₹30L to ₹1Cr (3.3x). Fewer than one in ten of our measured accounts grew that fast in the same time, so the case study follows the pace of that top tenth rather than forcing the number. The main problem was repeat orders. WhatsApp is cheaper than paid retargeting for buyers who already reached checkout. Conversion rate caps what any ad budget can return.

   How it works

   WhatsApp runs alongside paid retargeting, not instead of it. Fixes are listed and handed over early, so later budget lands on a store that converts.

2. 2

   Measurement & reviews · Month 1 to 6

   What we do

   We track ad-platform revenue beside store revenue and net sales after returns, cancellations and tax. We set the path from ₹30L to ₹1Cr as written monthly numbers, and read every review against the month so far.

   Why

   It did not report a return on ad spend, so the case study starts from what measured food and beverage stores of that size hold. Returns, cancellations and tax cut logged revenue, so the numbers are set on net sales. 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. Written monthly numbers make each scaling decision explicit.

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, keeping carousel on a short leash because its return trails the account. We run one broad video campaign of the core products, with a customer testimonial, and give it most of the budget. The learning month runs on a small daily budget, stepping up only once orders confirm. We lead with video that carries trust: creators, customer feedback and founder-led pieces.

   Why

   Broad delivery lets the algorithm find buyers for an everyday product. The first rupees are for finding the buyer, not for volume. In most accounts we measured, video that carried trust held its return.

   How it works

   The video that takes off is scaled; the tests around it are cut. Spend steps up only after orders confirm at the low budget. Low-quality UGC is pulled and founder-led video takes its place. New ads rise with the budget, most of them video, then catalogue ads.

4. 4

   Scaling · Month 2 to 4

   What we do

   Through Month 2 to Month 4, we push as far toward ₹1Cr as return allows: the budget rises gently while return holds, and Instagram Reels carries the most spend and Instagram Feed the next. 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

   In Month 2 to Month 4 the budget rises gently, while return on spend holds. Return holds through these months because each budget step stops where return starts to slip. Early-month demand is stronger for repeat consumables.

   How it works

   The monthly budget curve is weighted to the opening days. Spend shifts into each season and between regions with the calendar. Most of the final month's spend sits on Instagram Reels, then Instagram Feed. Most spend reaches people who have not bought yet; past visitors return more per rupee.

5. 5

   Steady state · Month 5 to 6

   What we do

   From Month 5, we protect the revenue already built and move toward ₹1Cr where return permits. We recover abandoned checkouts and lift repeat orders with WhatsApp messages. We build lookalikes from repeat buyers and retarget past buyers with new arrivals.

   Why

   Growth slows from Month 5, still short of ₹1Cr. Spend holds roughly steady from here. WhatsApp is cheaper than paid retargeting for buyers who already reached checkout. An order from a returning buyer costs the least.

   How it works

   Messages run beside retargeting ads. Past buyers see new arrivals before anyone else.

1. Month 1

   First, the set-up: a small daily budget carries the first ads, and store orders are matched to tracking. WhatsApp checkout recovery is switched on. Net sales are reconciled against logged revenue.

   • Revenue ₹31.9L
   • ROAS 4.85x
   • Ad spend ₹6.6L
2. Month 2

   The scaling phase opens: repeat-order messages go to past buyers. With budget holds, return on spend rises.

   • Revenue ₹33.9L
   • ROAS 5.20x
   • Ad spend ₹6.5L
3. Month 3

   Past buyers get the new arrivals ahead of prospecting. With budget steps up, return on spend holds.

   • Revenue ₹39.4L
   • ROAS 5.06x
   • Ad spend ₹7.8L
4. Month 4

   The seasonal collection campaign leads this period's spend mix.

   • Revenue ₹50.1L
   • ROAS 4.83x
   • Ad spend ₹10.4L
5. Month 5

   From here the work shifts to keeping ads fresh and bringing buyers back.

   • Revenue ₹50.9L
   • ROAS 4.41x
   • Ad spend ₹11.5L
6. Month 6

   Customer-feedback and creator videos are refreshed. With budget holds, return on spend rises. Revenue ends below ₹1Cr, the number this scenario calls for, because the case study follows what the fastest tenth of our measured accounts reached. Cost per purchase ends close to the learning phase.

   • Revenue ₹52.7L
   • ROAS 4.92x
   • Ad spend ₹10.7L

1. 1

   15 UGC videos, including regional-language cuts for the two best-selling states

2. 2

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

3. 3

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