CutSizeGenie is a Shopify app for fashion and apparel e-commerce brands that unlocks revenue from out-of-stock sizes using virtual inventory and size mapping. It improves size availability on Shopify product pages without theme edits.
Case study

Taruni × CutSizeGenie: recovering demand from out-of-stock sizes on Shopify.

Taruni is a women’s ethnicwear brand where tailoring/cut-size flows are operationally feasible. Like many fashion brands, Taruni often had inventory in jump sizes (M/XL) while high-intent demand came for S/L — and PDPs showed “Out of stock”. CutSizeGenie helped keep size-led availability stronger using controlled size mapping + safety thresholds.

Women’s ethnicwear Alteration-friendly Shopify inventory Ops logs
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Note: Outcomes depend on catalog, traffic quality, pricing, and operational capacity. Results vary by store.
Snapshot
What CutSizeGenie improved
Taruni
₹0L+ / month
Incremental sales influenced by recovered size availability (observed).
Not a guarantee. Results vary by assortment and enablement.
Threshold safety No theme edits Ops logs
Works at the inventory layer using Shopify Admin APIs.
Context

The problem Taruni faced

Taruni’s customers are highly size-sensitive. Even when a style is popular, a missing size on PDP can cause users to bounce. At the same time, fashion production realities often lead to stronger availability in jump sizes (M/XL). This mismatch creates hidden revenue loss: traffic arrives, the desired size shows OOS, and the customer exits.

Symptom

S/L frequently OOS while M/XL had sellable inventory.

Impact

Higher PDP drop-offs and wasted marketing clicks.

Solution

How CutSizeGenie was applied

Taruni enabled size mappings only on collections where tailoring/cut-size workflows were feasible.

  • S borrowed from M
  • L borrowed from XL
  • Enablement was selective (not the whole catalog)

CutSizeGenie’s safety model ensured virtual inventory never became “unlimited”.

  • Minimum stock threshold on source sizes (stop sharing below safe limit)
  • Max-share caps (limit virtual allocations)
  • Optional location-aware behavior for practical fulfilment

When a virtual size sold, the source size inventory was consumed and the order was logged.

  • Ops teams had visibility of “virtual” orders
  • Clear audit trails: which source size was used
  • Reduced confusion during picking and tailoring

Taruni monitored improvements using practical indicators tied to size availability:

  • PDP availability for hero styles
  • Size-led drop-offs vs. in-stock experience
  • Incremental orders influenced by recovered sizes
  • Marketing efficiency improvements (directional ROAS impact)
Result

What improved (observed outcomes)

Availability
More “full size run” PDPs
Fewer sessions died at “my size is sold out”.
Revenue influence
₹10L+ / month (observed)
Incremental sales influenced by recovered size demand. Results vary.
Efficiency
Better marketing efficiency
Same traffic → fewer wasted clicks on size-OOS PDPs.
Operations
Cleaner order handling
Logs + clarity improved picking/tailoring workflow.
Disclaimer: This case reflects a specific store context (category, operations, and enablement). Your results may vary.
At a glance
Industry
Women’s ethnicwear (alteration-friendly)
Core use-case
Recover demand when S/L is OOS and M/XL has inventory
Key features used
  • Size mapping rules
  • Threshold safety + caps
  • Virtual order logs
  • Selective enablement
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Want your store featured? Email: support@cutsizegenie.com
Taruni case study: CutSizeGenie Shopify app used virtual inventory and size mapping to reduce out-of-stock size drop-offs. Works for fashion and apparel brands where tailoring/alterations or cut-size workflows are feasible. Uses safety thresholds, max-share caps, and order logs to avoid overselling and keep operations informed.