Jewellery case study: ₹3L to ₹5.2L monthly revenue in 45 days

New ads per month

1. 1

   Research & offer · Week 1 to 2

   What we do

   The first problem in this scenario is return on ad spend, so the opening week on this smaller store goes there. We fix the store before scaling: trust pointers, reviews, a clear return window, an about page and a prepaid incentive. We audit the competitors buyers are already comparing, and agree the case study before spending.

   Why

   In this case study, a smaller jewellery brand grows monthly revenue in 45 days, from ₹3L to ₹20L (6.7x). Nine in ten of the accounts we measured grew more slowly than that in the same time; the case study is built on what the fastest tenth reached, and shows the gap to the agreed number honestly. The main problem was return on ad spend. Conversion rate caps what any ad budget can return. The audit positions the brand in this scenario against the alternatives buyers are weighing.

   How it works

   Site fixes are handed over in the first weeks, before budget rises. The audit sets the creative and site work for the first weeks.

2. 2

   Measurement & reviews · Week 1 to 7

   What we do

   We log store orders every day beside what the ad platform claims. We agree a written number for every week on the way from ₹3L to ₹20L, and start each review with the week-to-date figure against it. We set a written rule: no budget step in a week where return falls too far to pay for it.

   Why

   Its reported return on ad spend is higher than measured jewellery stores of that size hold, so the case study starts there and lets part of it ease as budget grows. Platform attribution over-counts, so budget decisions sit on the store-side number. A shortfall is caught in the week it happens, not at the end.

   How it works

   The sheet is read before each budget change. The week's number is on the page at every review. A week whose return starts to slip past that point keeps its budget instead.

3. 3

   Creative testing · Week 1 to 4

   What we do

   We test with video, catalogue ads and static image first, rising to a few dozen new ads a month by the last four weeks, keeping carousel on a short leash because its return trails the account. We show the piece: product-only singles and carousels, swapped the moment they stop converting. We lead with video that carries trust: creators, customer feedback and founder-led pieces. We work in creative batches with a fixed read window each.

   Why

   Jewellery buyers decide on the piece, and fatigue sets in fast. In most accounts we measured, video that carried trust held its return. A fixed window stops spend chasing a creative before it has been read.

   How it works

   Creatives are rotated on conversion, not on a calendar. Weak UGC is swapped for founder-led video rather than scaled. Only ads that convert inside the window keep running. The number of new ads grows with spend; video makes up the largest part and catalogue ads the next.

4. 4

   Scaling · Week 5 to 7

   What we do

   Through Week 5 to Week 7, we push toward ₹20L: the budget climbs in steps and return falls, and Instagram Reels carries the most spend and Instagram Feed the next. We tie every budget increase to return: we step up while it holds, and step back when it drops. We scale into the festive and wedding calendar with seasonal collection campaigns.

   Why

   Across Week 5 to Week 7, the budget climbs in steps, and return on spend falls as it does. In two of these weeks budget goes up only as far as return allows, so revenue grows more slowly than the agreed number needs. In measured accounts, scaling spend raised cost per order and lowered return on spend, so each step waits for return to hold. Demand is seasonal and regional, so spend moves with the calendar.

   How it works

   There is no fixed ramp; each week's budget follows the return of the last. Spend shifts into each season and between regions with the calendar. In the last four weeks, Instagram Reels takes the most spend and Instagram Feed the next most. Most spend reaches people who have not bought yet; past visitors return more per rupee.

1. Week 1

   First, the set-up: the first ads run on a small daily budget while tracking is checked against store orders. Store orders and ad-platform revenue are checked side by side. The competitor audit is shared and the creative brief agreed.

   • Revenue ₹67,755
   • ROAS 2.52x
   • Ad spend ₹26,916
2. Week 2

   The first read of the ads is in, and the ones that do not convert stop. Spend holds, and return holds.

   • Revenue ₹70,980
   • ROAS 2.49x
   • Ad spend ₹28,508
3. Week 3

   Store fixes and offers go live while orders confirm.

   • Revenue ₹70,933
   • ROAS 2.44x
   • Ad spend ₹29,065
4. Week 4

   By the end of learning, the buyer is known and one ad has won.

   • Revenue ₹70,848
   • ROAS 2.42x
   • Ad spend ₹29,335
5. Week 5

   Scaling begins: this batch's read is done: winners stay, the rest are cut. Spend steps up sharply, and return dips.

   • Revenue ₹1.2L
   • ROAS 2.15x
   • Ad spend ₹53,842
6. Week 6

   Product-only creatives that stop converting are swapped. The step is sized by what return can bear: spend steps up sharply, and return dips.

   • Revenue ₹1.7L
   • ROAS 1.94x
   • Ad spend ₹85,749
7. Week 7

   A seasonal collection campaign takes a larger share of budget. The step is sized by what return can bear: spend holds, and return holds. ₹20L is not reached in the time, because budget stops rising where return starts to slip. Each order costs more by the end than it did while learning.

   • Revenue ₹1.7L
   • ROAS 1.90x
   • Ad spend ₹90,306

1. 1

   Positioned as handcrafted and made to order; led with personalised pieces

2. 2

   Audited eight competitors and agreed a three-month case study

3. 3

   Handed over a 13-point site fix list: prepaid offer, testimonials, a three-day return window, an about page, no permanent sale prices