Health & wellness case study: ₹40L to ₹67.9L 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 creative and content, so the opening month on this established store goes there. 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. We layer the account: a creative-testing campaign, a scaling campaign, cold audiences that exclude past buyers, and cart remarketing.

   Why

   An established health and wellness store grows monthly revenue in 3 months, from ₹40L to ₹80L (2x). 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 creative and content, followed by marketing and social presence. No budget returns more than the store converts. Separate layers stop prospecting and retargeting competing for the same budget.

   How it works

   The fix list goes to the brand's team in the opening weeks, ahead of any budget step. Each layer keeps its own budget line.

2. 2

   Measurement & reviews · Month 1 to 3

   What we do

   We write month-by-month revenue numbers with the brand's team that climb from ₹40L to ₹80L, and open every review with the month-to-date number against them. We track ad-platform revenue beside store revenue and net sales after returns, cancellations and tax.

   Why

   It did not report a return on ad spend, so the case study starts from what measured stores of that size hold. A shortfall is caught in the month it happens, not at the end. Returns, cancellations and tax cut logged revenue, so the numbers are set on net sales.

   How it works

   Each budget step is argued against the written number. Net sales, not platform revenue, decide each budget step.

3. 3

   Creative testing · Month 1

   What we do

   We test with video, static image 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 make trust the subject of the video: creator reels, customer feedback and founder-led clips. We brief creators for a steady run of UGC video, with regional-language cuts of the winners. We commission ads in batches, and read each batch for a set window before ordering the next.

   Why

   Trust-carrying video held return in most measured accounts. A steady supply keeps the testing layer fed, and regional cuts reach more buyers with the same idea. A fixed window stops spend chasing a creative before it has been read.

   How it works

   Weak UGC is swapped for founder-led video rather than scaled. Regional cuts of a winner come before new ideas. Losing batches stop; winning ads take their budget. More spend buys more new ads, led by video ahead of static image.

4. 4

   Scaling · Month 2 to 3

   What we do

   Through Month 2 to Month 3, we push as far toward ₹80L as return allows: the budget climbs in steps and return falls, and Instagram Reels carries the most spend and Facebook Reels the next. We refresh tired ads by mixing old and new creatives as spend rises. We make regional-language versions of the winning video for the states that buy most.

   Why

   Across Month 2 to Month 3, the budget climbs in steps, and return on spend falls as it does. Spend scaled in our measured accounts pushed cost per order up and return down, so no step is taken on hope. More spend means the same people see an ad more often, and click-through fades.

   How it works

   Proven ads stay while new ones are added. The regional versions run next to the original. Instagram Reels carries the largest share of spend in the final month, with Facebook Reels next. Cold audiences take most of the budget; warm audiences return more per rupee.

1. Month 1

   The learning phase opens: the first ads run on a small daily budget while tracking is checked against store orders. Net sales are reconciled against logged revenue. The account runs in layers: testing, scaling and retargeting.

   • Revenue ₹40.6L
   • ROAS 4.54x
   • Ad spend ₹9L
2. Month 2

   Scaling begins: fresh ads are mixed in beside the proven set. Budget steps up sharply and return on spend falls.

   • Revenue ₹54.5L
   • ROAS 3.73x
   • Ad spend ₹14.6L
3. Month 3

   The winner now also runs in regional languages. Budget steps up and return on spend dips. Halfway from ₹40L to ₹80L is passed. The case study finishes short of ₹80L: the case study follows what the fastest tenth of our measured accounts reached. Cost per purchase ends higher than in the learning phase.

   • Revenue ₹67.9L
   • ROAS 3.54x
   • Ad spend ₹19.2L

1. 1

   Ran dated creative versions (V1 to V3) in separate campaigns

2. 2

   Relaunched campaigns on a new pixel the moment hostile comments appeared

3. 3

   Opened a month-to-date table against the cap on every weekly call