Health & wellness case study: ₹1L to ₹1.3L monthly revenue in 3 months

New ads per month

1. 1

   Research & offer · Month 1

   What we do

   The first problem in this scenario is reaching new buyers, so the opening month on this smaller store goes there. We build audiences on the buyer's life and profession, not on health-condition interests. We add cart-value offers that step up at set basket sizes to lift order value.

   Why

   In this case study, a smaller health and wellness brand grows monthly revenue in 3 months, from ₹1L to ₹10L (10x). 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 in this scenario is reaching new buyers. Condition-based audience setting is restricted and reaches the wrong buyer. Higher order value lowers the share of each order that goes to ads.

   How it works

   Lifestyle audiences replace condition interests from the first campaign. The tiers follow real order values, not round numbers.

2. 2

   Measurement & reviews · Month 1 to 3

   What we do

   We log store orders every day beside what the ad platform claims. We write month-by-month revenue numbers with the brand's team that climb from ₹1L to ₹10L, and open every review with the month-to-date number against them. We raise budget in a month only while return holds; where it slips too far, we hold it.

   Why

   It did not report a return on ad spend, so the case study starts from what measured health and wellness stores of that size hold. 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. 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, static image and UGC and creator video, building to about two dozen new ads a month by the final month, with carousel watched closely since it returns less than the rest. The learning month runs with a deliberately small daily budget until orders prove the buyer. We run every lead product in a campaign of its own, read every week. We commission ads in batches, and read each batch for a set window before ordering the next.

   Why

   The first rupees are for finding the buyer, not for volume. Shared campaigns hide weak products; separate ones expose them fast. Buying more before a batch is read means paying for guesses.

   How it works

   The low budget stays until orders confirm the buyer. A product that does not sell is paused inside the week. Only ads that convert inside the window keep running. New ads rise with the budget, most of them video, then static image.

4. 4

   Scaling · Month 2 to 3

   What we do

   Through Month 2 to Month 3, we push toward ₹10L: the budget rises gently and return dips, and Instagram Reels carries the most spend and Facebook Reels the next. We cut regional-language versions of the winning video for the best-selling states. Once purchases are steady, we add lookalikes of past buyers next to broad prospecting.

   Why

   In Month 2 to Month 3 the budget rises gently, and return on spend dips. Two of these months stop their budget step where return slips too far. In measured accounts, scaling spend raised cost per order and lowered return on spend, so each step waits for return to hold. Buyers respond to the same idea in their own language.

   How it works

   Regional cuts run beside the original winner. Lookalike and broad audiences run the same ads, so they can be compared. Most of the final month's spend sits on Instagram Reels, then Facebook Reels. Prospecting to new buyers takes the bulk of spend, while retargeting returns more for each rupee.

1. Month 1

   First, the set-up: tracking is checked against store orders and the first ads go live on a small daily budget. Store orders and platform revenue are reconciled in the shared sheet. Lifestyle audiences replace condition interests.

   • Revenue ₹98,591
   • ROAS 2.19x
   • Ad spend ₹44,998
2. Month 2

   Scaling starts: the winner now also runs in regional languages. Only the part of the step that return supports is taken: budget steps up and return on spend falls.

   • Revenue ₹1.2L
   • ROAS 1.90x
   • Ad spend ₹65,495
3. Month 3

   The creative batch is read and the winners keep the budget. Only the part of the step that return supports is taken: budget holds and return on spend holds. The case study finishes short of ₹10L: budget stops rising where return starts to slip. Each order costs more by the end than it did while learning.

   • Revenue ₹1.3L
   • ROAS 1.94x
   • Ad spend ₹67,842

1. 1

   Rebuilt creative around the two services that convert, plus a founder-led ad

2. 2

   Add static images beside video once a winning video is found.

3. 3

   Retargeted video viewers and unfinished form fills; built lookalikes from converted leads