All work

Ethnicwear · Inventory Analysis · Growth Strategy

₹12.33 crore sitting in out-of-stock products. We found it before the competition did.

Period

Dec 2024 – Dec 2025

Scope

9,745 SKUs · 365-day analysis

Company

Conversion Lab

The numbers

₹8.96 Cr

Revenue actually captured

₹12.33 Cr

Revenue lost to stockouts

141 days

Avg OOS for top 300 SKUs

Context

The campaigns were fine. The problem was elsewhere.

While managing paid media for this ethnicwear brand, I kept running into the same wall. Campaigns were performing — traffic was coming in, intent was there — but conversion was not following. The usual suspects checked out: creative was solid, targeting was refined, landing pages were clean.

The problem was upstream. The products people were clicking on were not available.

I commissioned a full 365-day inventory analysis across the brand's entire catalog — 9,745 SKUs — to quantify what we were actually dealing with.

What the data showed

Best-selling products. Worst availability.

The brand had generated ₹8.96 crore in revenue over the year. That sounds reasonable until you look at availability.

The top 300 SKUs — the ones driving the bulk of actual revenue — were out of stock for an average of 141 days. That is 39% of the year. 41% of those top-performing SKUs were unavailable for more than 180 days.

The pattern that stood out most: the brand's best products suffered the most. Top 50–200 SKUs had the highest OOS rates (130–152 days average). The slow-moving bottom 5,000 SKUs were better stocked than the products customers actually wanted. Only 40 of the top 300 SKUs — 13% — maintained full availability across the year.

41%

Of top 300 SKUs out of stock 180+ days

13%

Of top 300 SKUs fully available all year

₹1.03L

Avg daily revenue lost to stockouts

By product line

Where the revenue was locked.

Mirror Work

1,121 SKUs · 165 days avg OOS

₹6.87 Cr

lost revenue

Hand Embroidered

6 SKUs · 286 days avg OOS

₹35.72 L

lost revenue

Pure Cotton Hand Embroidered

6 SKUs · 296 days avg OOS

₹30.61 L

lost revenue

Mirror Work Cotton Kurta

6 SKUs · 276 days avg OOS

₹25.02 L

lost revenue

Mirror Work alone — 1,121 SKUs generating ₹2.46 Cr — had ₹6.87 Cr sitting unrealised.

What this meant for paid media

Stockouts don't announce themselves in the ad account.

They show up as unexplained dips in ROAS, lower-than-expected conversion rates, and a widening gap between traffic quality and outcomes — all of which point you toward the wrong problems. You optimise bids, refresh creative, tighten audiences. The number still does not move. The ceiling is not in the campaign. It is in the warehouse.

Attribution made this invisible. Conversions looked low, so the instinct was to fix targeting or test new creatives. The actual lever was inventory. This is why performance marketing has to extend beyond the ad account.

The opportunity

Revenue projections by OOS target.

Modelled on current sales velocity during in-stock periods. ROI on fixing inventory: ₹2.54 returned for every ₹1 invested in restocking.

OOS reduced to 30 days

₹16.56 Cr

+196%

OOS reduced to 60 days

₹15.23 Cr

+172%

OOS reduced to 90 days

₹13.93 Cr

+149%

100% stock availability

₹17.92 Cr

+220%

Recommended actions

A 90-day path to capturing lost revenue.

01

Priority restock: 124 critical SKUs

SKUs with 180+ OOS days representing ₹92L+ in demand. These are known performers — the demand is already proven.

02

Inventory rebalancing

Shift investment from the bottom 5,000 SKUs (contributing 10% of revenue) toward the top 500 (36.5%). The long tail is being overstocked relative to its contribution.

03

90-day safety stock on Mirror Work and Hand Embroidered lines

These product lines have the highest demand and the worst availability. They need a structural buffer, not just reactive restocking.

04

Demand forecasting and automated reorder triggers

Manual restocking at this catalog size will always lag. The top 500 SKUs need automated reorder points based on sales velocity.

What this shows

Performance marketing does not start and end at the ad account. If the product is not available, the campaign cannot convert — and the data will point you toward the wrong problems. This analysis came from spending enough time with the business to ask why campaigns were not converting the way they should have been.

Growth problems are rarely where they first appear.