Health & wellness case study: ₹1L to ₹1.3L monthly revenue in 2–3 months

New ads per month

1. 1

   Research & offer · Month 1

   What we do

   The first problem in this scenario is scaling ad spend, so the opening month on this smaller store goes there. We layer the account: a creative-testing campaign, a scaling campaign, cold audiences that exclude past buyers, and cart remarketing. 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 2–3 months, from ₹1L to ₹8L (8x). 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 in this scenario is scaling ad spend. Separate layers stop prospecting and retargeting competing for the same budget. Higher order value lowers the share of each order that goes to ads.

   How it works

   Warm layers run beside prospecting, not instead of it. Tier levels are set just above the basket sizes buyers already reach.

2. 2

   Measurement & reviews · Month 1 to 3

   What we do

   We log store orders every day beside what the ad platform claims. We set the path from ₹1L to ₹8L as written monthly numbers, and read every review against the month so far. 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 health and wellness 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. 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 test with video, carousel and catalogue ads 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 lead with video that carries trust: creators, customer feedback and founder-led pieces. We build creative around the buyer's everyday routine rather than a condition.

   Why

   A product nobody buys is visible within a week when it has its own campaign. In most accounts we measured, video that carried trust held its return. Condition claims are restricted and reach the wrong buyer.

   How it works

   Budget follows the products that sell. UGC that underperforms is replaced by founder-led video, not given more budget. Everyday-routine creative is read against the lifestyle audiences. The number of new ads grows with spend; video makes up the largest part and carousel the next.

4. 4

   Scaling · Month 2 to 3

   What we do

   We scale through Month 2 to Month 3 toward ₹8L as the budget rises gently and return dips, with Instagram Reels taking the largest share of spend and Instagram Feed the next. We raise budget only while return on spend holds, and cut it when return drops. We make regional-language versions of the winning video for the states that buy most.

   Why

   Across Month 2 to Month 3, the budget rises gently, and return on spend dips. In two of these months the step is trimmed to the size return can hold. 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

   There is no fixed ramp; each month's budget follows the return of the last. Regional cuts run beside the original winner. Instagram Reels carries the largest share of spend in the final month, with Instagram Feed next. Cold audiences take most of the budget; warm audiences return more per 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. The cart-value tiers are live. Store orders and platform revenue are reconciled in the shared sheet.

   • Revenue ₹1L
   • ROAS 2.01x
   • Ad spend ₹50,983
2. Month 2

   Scaling begins: budget shifts to the products that sold this period. Budget goes up only as far as return can carry it: with budget steps up, return on spend steps up.

   • Revenue ₹1.1L
   • ROAS 1.91x
   • Ad spend ₹58,213
3. Month 3

   Regional-language versions of the winner go live. Budget goes up only as far as return can carry it: with budget steps up, return on spend steps up. Revenue ends below ₹8L, the number this scenario calls for, because budget stops rising where return starts to slip. Each order costs more by the end than it did while learning.

   • Revenue ₹1.3L
   • ROAS 1.87x
   • Ad spend ₹69,155

1. 1

   Audiences built on the buyer's life and profession rather than health-condition interests

2. 2

   Scaling spend raised cost per order and lowered return on spend.

3. 3

   Build audiences on the buyer's life and profession rather than health-condition interests.