Work · The Pink Moon
Case №003 · The Pink Moon · Store + online

₹16 lakh to ₹85 lakh+ in monthly sales

A premium fashion brand stuck at roughly ₹16 lakh a month, with an incumbent agency and a return that collapsed every time spend rose. Five times the monthly sales later, more than half of it comes from customers who came back.

5xMonthly sales, first month to best month
~5xBlended return, held while spend scaled ~3.5x
32xROI on the WhatsApp retention engine
Image · The Pink Moon

Before

Around ₹16 lakh a month in online revenue, growth stalled. A previous agency on the account, and every attempt to scale spend killed the return. No lifecycle program, and a flagship store that nobody was measuring.

The moves

A planning-first performance engine. Monthly plans across Meta and Google built around collections, drops and sale moments, with budgets paced daily against the plan rather than left to the algorithm.

Creative velocity. Thirty or more new creatives tested every month, with AI folded into production so testing never waits on design bandwidth. Winners scale, losers die in days.

A WhatsApp retention engine. Abandoned-cart nudges at two and eight hours, a 30-day repurchase nudge, dormant win-backs, and campaign sends segmented by recency, spend tier and city.

The store measured like a channel. Walk-in tracking tying footfall and billed sales back to campaigns.

What it produced

Monthly sales grew more than five times, from ₹16 lakh to an ₹85 lakh+ best month, 45% up year over year. The blended return held near 5x while spend scaled about three and a half times. The WhatsApp engine returned 32x on its cost and reached about a fifth of monthly revenue within two months of launch. In-store, 400+ tracked walk-ins billed ₹16 lakh+, and store shoppers spend 35 to 70% more per bill than online.

For every ₹1 in ads, about ₹5 came back in sales, and it held while monthly sales grew five times over.

On the record
"Extremely seamless. Super-approachable, on the ball and very prompt. They have an eye for detail and help pick what is most relevant to the brand."
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