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Health & wellness2–3 monthsCase study

Health & wellness case study: plan for ₹10L to ₹23.4L monthly revenue in 2–3 months

Monthly revenue at enquiry, self-reported₹10L
Projected for month 3, modelled₹23.4L
2.3x
Planned ad spend₹13.7L
Projected revenue₹48L
Projected blended ROAS3.5x
Projected orders2,470
Projected revenue, month 3₹23.4L
Projected ROAS, month 33.01x
Projected cost / purchase, month 3₹639
Projected avg order value, month 3₹1,921
Projected conversion, month 31.96%
Horizon3 months
Target, brand's own₹30L a month
Plan reaches78% of target

01 · Plan

Month by month

Monthly plan
MonthPhasePlanned ad spendProjected revenueProjected ROASProjected purchasesProjected cost per purchase
At enquiry, self-reported––₹10L–––
Month 1Learning₹2,22,040₹10,13,6424.57x525₹423
Month 2Scaling₹3,72,439₹14,45,7553.88x726₹513
Month 3Scaling₹7,78,759₹23,41,8893.01x1,219₹639
Total₹13,73,238₹48,01,2863.50x2,470₹556

02 · Funnel

Projected funnel, first view to purchase · month 3

  1. Impressions61,66,300
  2. Link clicks96,551
    1.57% of impressions
  3. Landing-page views62,299
    64.52% of link clicks1.01% of impressions
  4. Added to cart7,362
    11.82% of landing-page views0.119% of impressions
  5. Checkout started3,993
    54.24% of added to cart0.065% of impressions
  6. Purchases1,219
    30.53% of checkout started0.02% of impressions

0.02% of impressions became purchases

03 · Mix

Where the planned budget goes · month 3

SegmentPlanned ad spendShare of spendProjected purchasesProjected ROASProjected cost per purchase
Instagram₹4,87,65062.6%7582.99x₹643
Facebook₹2,67,86034.4%4243.04x₹632
Audience Network₹13,2371.7%213.06x₹630
WhatsApp₹10,0121.3%163.06x₹626
SegmentPlanned ad spendShare of spendProjected purchasesProjected ROASProjected cost per purchase
Instagram Reels₹2,63,33633.8%4123.00x₹639
Instagram Feed₹1,37,24417.6%2203.08x₹624
Facebook Reels₹1,28,93116.6%2093.12x₹617
Facebook Feed₹1,11,57814.3%1712.94x₹653
Instagram Stories₹87,07011.2%1262.79x₹691
Facebook Stories₹16,8972.2%273.06x₹626
Audience Network₹13,2371.7%213.06x₹630
Facebook Video₹10,4541.3%173.06x₹615
WhatsApp₹10,0121.3%163.06x₹626
SegmentPlanned ad spendShare of spendProjected purchasesProjected ROASProjected cost per purchase
Prospecting (cold audiences)₹6,81,64687.5%1,0663.00x₹639
Retargeting (warm audiences)₹46,0735.9%753.13x₹614
Lookalike audiences₹37,8524.9%572.93x₹664
Advantage+ shopping₹13,1881.7%213.02x₹628

04 · Creatives

Planned creative mix · month 3

New ads per month

Video34 a month
Static image6 a month
Catalogue (dynamic product ads)5 a month
UGC / creator video5 a month
Carousel4 a month
Moderate3.02xblended ROAS · 4 creative types₹7.6L spend
Watchlist2.54xblended ROAS · 1 creative type₹22,620 spend
Creative typeTierPlanned ad spendProjected purchasesProjected ROASProjected cost per purchase
Catalogue (dynamic product ads)Moderate₹70,3461153.15x₹612
Static imageModerate₹97,0341593.14x₹610
VideoModerate₹5,60,7308732.99x₹642
UGC / creator videoModerate₹28,029422.87x₹667
CarouselWatchlist₹22,620302.54x₹754

05 · How we'd help

How we'd help, why, and how it works

  1. Research & offer · Month 1

    What we'd do

    The booking named a clear strategy first, so the opening month on this mid-sized store goes there. Start with a website audit, a creative brief and a monthly media plan in the first week. Build the account in layers so each can be read on its own: testing, scaling, new-buyer prospecting and cart retargeting.

    Why

    A mid-sized health and wellness store asked us how to grow monthly revenue in 2–3 months, from ₹10L to ₹30L (3x). That is faster than nine in ten of our measured accounts grew over the same time, so the plan below is modelled on what that fastest tenth reached and shows where it lands against the target. At booking, the brand named a clear strategy as its main problem. A written brief gives every later budget decision a reference point. Layers keep each budget line readable, so a weak campaign cannot hide inside a strong one.

    How it works

    The brief is agreed first; spend follows it. Warm layers run beside prospecting, not instead of it.

  2. Measurement & targets · Month 1 to 3

    What we'd do

    Log store orders every day beside what the ad platform claims. Agree a written target for every month on the way from ₹10L to ₹30L, and start each review with the month-to-date figure against it.

    Why

    No return on ad spend was given at booking; the starting return is what measured stores of that size hold. The ad platform's own count runs high, so the store's count is the one that moves budget. A shortfall is caught in the month it happens, not at the end.

    How it works

    Every budget call starts from the store's orders. The target for the month is on the page at every review.

  3. Creative testing · Month 1

    What we'd do

    Test with video, static image and catalogue ads first, rising to a few dozen new ads a month by the final month, keeping carousel on a short leash because its return trails the account. Keep creators producing UGC video on a steady schedule, and cut the winners into regional languages. Give each lead product its own campaign and read it weekly. The learning month runs with a deliberately small daily budget until orders prove the buyer.

    Why

    A steady supply keeps the testing layer fed, and regional cuts reach more buyers with the same idea. Shared campaigns hide weak products; separate ones expose them fast. Early spend buys learning, not scale.

    How it works

    Regional cuts of a winner come before new ideas. A product that does not sell is paused inside the week. The low budget stays until orders confirm the buyer. The number of new ads grows with spend; video makes up the largest part and static image the next.

  4. Scaling · Month 2 to 3

    What we'd do

    Scale through Month 2 to Month 3 as far toward ₹30L as return allows as the budget climbs in steps and return falls, with Instagram Reels taking the largest share of spend and Instagram Feed the next. Run cost caps, bid caps, CBO and ABO as parallel versions before budget steps up. Let return decide budget: more while it holds, less when it slips.

    Why

    In Month 2 to Month 3 the modelled budget climbs in steps, and return on spend falls as it does. In measured accounts, scaling spend raised cost per order and lowered return on spend, so each step waits for return to hold. Parallel controls reveal which setup keeps cost per purchase down as spend grows.

    How it works

    The version that keeps cost per purchase lowest stays. Budget follows return month to month instead of a fixed ramp. In the final month, Instagram Reels takes the most spend and Instagram Feed the next most. Cold audiences take most of the budget; warm audiences return more per rupee.

06 · Milestones

Projected milestones by month

  1. Month 1

    The learning phase opens: a small daily budget carries the first ads, and store orders are matched to tracking. The website audit, creative brief and media plan are shared. The account runs in layers: testing, scaling and retargeting.

    • Projected revenue ₹10.1L
    • Projected ROAS 4.57x
    • Planned ad spend ₹2.2L
  2. Month 2

    The scaling phase opens: the winning UGC runs in regional-language versions. With budget steps up sharply, return on spend falls.

    • Projected revenue ₹14.5L
    • Projected ROAS 3.88x
    • Planned ad spend ₹3.7L
  3. Month 3

    The budget decision is taken on the return the last step earned. With budget steps up sharply, return on spend falls. Monthly revenue passes the halfway point between ₹10L and ₹30L. ₹30L is not reached in the time, because the plan follows what the fastest tenth of our measured accounts reached. Cost per purchase ends higher than in the learning phase.

    • Projected revenue ₹23.4L
    • Projected ROAS 3.01x
    • Planned ad spend ₹7.8L

07 · Learnings

Learnings from Health & wellness brands we measured

  1. Relaunched campaigns on a new pixel the moment hostile comments appeared

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

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

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