Jewellery case study: ₹50,000 to ₹52,191 monthly revenue in 2 months

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 get the store ready for paid traffic first: reviews and trust pointers on product pages, a visible return window, an about page and a reason to pay upfront. We lead with craft: handcrafted or made-to-order positioning, with personalised pieces up front.

   Why

   In this case study, a smaller jewellery brand grows monthly revenue in 2 months, from ₹50,000 to ₹30L (60x). 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 in this scenario is return on ad spend. Every rupee of ads is capped by how well the store turns visits into orders. Jewellery buyers decide on the piece and the story behind it.

   How it works

   Fixes are listed and handed over early, so later budget lands on a store that converts. Personalised pieces open the prospecting ads.

2. 2

   Measurement & reviews · Week 1 to 9

   What we do

   We keep a shared daily sheet with the ad platform's revenue next to real store orders. We set the path from ₹50,000 to ₹30L as written weekly numbers, and read every review against the week so far. We raise budget in a week only while return holds; where it starts to slip too far, we hold it.

   Why

   No starting return on ad spend was given; the starting return is what measured jewellery stores of that size hold. Platform attribution over-counts, so budget decisions sit on the store-side number. A missed week shows up early instead of at the end of the case study.

   How it works

   Every budget call starts from the store's orders. 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 about a dozen new ads a month by the last four weeks, with no format far behind the account's return. We show the piece: product-only singles and carousels, swapped the moment they stop converting. The four learning weeks run on a small daily budget, stepping up only once orders confirm. We work in creative batches with a fixed read window each.

   Why

   Jewellery buyers decide on the piece, and fatigue sets in fast. Early spend buys learning, not scale. Buying more before a batch is read means paying for guesses.

   How it works

   Creatives are rotated on conversion, not on a calendar. The low budget stays until orders confirm the buyer. Losing batches stop; winning ads take their budget. 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 9

   What we do

   We scale through Week 5 to Week 9 toward ₹30L as the budget rises gently and return dips, with Instagram Reels taking the largest share of spend and Instagram Feed the next. We let return decide budget: more while it holds, less when it slips. We put seasonal collection campaigns in front of each festive and wedding peak.

   Why

   Across Week 5 to Week 9, the budget rises gently, and return on spend dips. In several of these weeks budget goes up only as far as return allows, so revenue grows more slowly than the final number needs. Our measured accounts saw cost per order rise and return fall as spend scaled; that is why each step here waits on return. Seasonal demand moves by region, so the spend does too.

   How it works

   Budget follows return week to week instead of a fixed ramp. 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

   The learning phase opens: 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. Reviews, trust pointers and the prepaid incentive are now on the store.

   • Revenue ₹12,173
   • ROAS 1.93x
   • Ad spend ₹6,308
2. Week 2

   First creative read: ads that do not convert are cut. Spend holds, and return holds.

   • Revenue ₹11,491
   • ROAS 1.90x
   • Ad spend ₹6,036
3. Week 3

   Store fixes and offers go live while orders confirm.

   • Revenue ₹11,925
   • ROAS 1.90x
   • Ad spend ₹6,282
4. Week 4

   The learning phase ends with a buyer identified and a winning ad chosen.

   • Revenue ₹11,815
   • ROAS 1.97x
   • Ad spend ₹5,991
5. Week 5

   Scaling begins: product-only creatives that stop converting are swapped. Budget rises to the point where return starts to give way: spend holds, and return holds.

   • Revenue ₹12,659
   • ROAS 1.93x
   • Ad spend ₹6,567
6. Week 6

   The creative batch is read and the winners keep the budget.

   • Revenue ₹12,695
   • ROAS 1.91x
   • Ad spend ₹6,630
7. Week 7

   The seasonal collection campaign leads this period's spend mix.

   • Revenue ₹13,050
   • ROAS 1.94x
   • Ad spend ₹6,724
8. Week 8

   Budget is reviewed against return before the next step.

   • Revenue ₹13,232
   • ROAS 1.92x
   • Ad spend ₹6,899
9. Week 9

   Product-only creatives that stop converting are swapped. Budget rises to the point where return starts to give way: spend holds, and return holds. ₹30L is not reached in the time, because budget stops rising where return starts to slip. Cost per purchase ends close to the learning phase.

   • Revenue ₹13,214
   • ROAS 1.88x
   • Ad spend ₹7,039

1. 1

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

2. 2

   New product pieces and post-Diwali product tests from fresh creative

3. 3

   Audited eight competitors and agreed a three-month case study