Taruni already had the category logic and operational maturity for a controlled rollout.
The page should make this explicit so the proof feels honest, not inflated.
Case study
How Taruni recovered demand from out-of-stock sizes on Shopify.
Taruni is a women’s ethnicwear brand where cut-size and alteration workflows are operationally feasible. That made it a strong candidate for a controlled CutSizeGenie rollout.
Category rollout
Ops-safeSize availability board
SVirtual
MSource stock
LVirtual
XLSource stock
Influenced revenue₹10L+
Paid traffic wasteLower
Ops clarityHigher
Demand problemMissing size states on PDP
Applied logicControlled substitution rules
OutcomeStronger availability signal
The case study is strongest when it teaches merchant fit, not just outcomes.
- Use only categories where substitution is feasible.
- Protect source sizes before rollout expands.
- Keep the operational model legible to the team.
Replace this with one metrics-led visual from Taruni: before and after size availability, influenced revenue, or rollout sequence.
Asset guidance
One verified result visual is better than a gallery of generic slides.
The case study should use one clean evidence asset with one strong number, one operational context note, and one explanation of why this category was a fit.
₹10L+
monthly influenced revenue, observed
More full-size PDPs
fewer dead-end product sessions
Better ROAS directionally
less paid traffic wasted on missing sizes
Cleaner ops flow
stronger visibility for order handling
The problem
Demand existed. Size availability did not.
Like many apparel brands, Taruni often had inventory in adjacent sizes while shoppers wanted sizes that showed as unavailable. That meant product-page traffic did not fully monetize, even when the assortment still had usable inventory depth elsewhere.
What was breaking
- High-intent shoppers hit out-of-stock states on PDP.
- Marketing clicks died on missing-size pages.
- Inventory still existed, but not in the demanded size.
- Operations needed a controlled alternative, not a hack.
Why CutSizeGenie fit
Taruni’s category made it practical to map source sizes to target sizes where alteration or cut-size handling was already part of the real-world workflow.
Why a generic app would not
This was not simply a stock display issue. The business case depended on operational feasibility, safety rules, and clean order visibility.
Implementation
A controlled rollout, not a full-catalog gamble.
1
Target eligible collections
Only use categories where size substitution made operational sense.
2
Set thresholds and caps
Protect source stock before it could be overcommitted.
3
Keep order handling visible
Give operations teams the context needed for downstream processing.
Outcomes
What improved after rollout.
Revenue influence
Observed incremental sales influenced by recovered size availability reached ₹10L+ per month.
Availability
More product pages maintained a stronger visible size run instead of losing the shopper immediately.
Marketing efficiency
Paid sessions were less likely to die on a missing-size state, improving efficiency directionally.
Operations clarity
Teams had a clearer process for handling orders influenced by recovered size demand.
Important note
This is a category-specific result.
Taruni is a strong example because its product category and operations model make this workflow feasible. Results vary by assortment, process, and rollout quality.
Next step