Solutions/Inventory & stockout

Prevent stockouts and overstock across Shopee, Lazada, and TikTok Shop

Stockouts cost more than lost sales — they waste ad spend, kill ranking, and end live sessions mid-stream. DataGlass forecasts stockout days against demand and recommends restocks before the next campaign window.

02/Detection

What DataGlass detects

DataGlass projects stockout days per SKU against current sell-through, scheduled campaign windows, and live-commerce velocity, with stock unified across shops.

  • Stockout-day forecast per SKU vs. the next campaign window
  • Slow movers tying up working capital
  • Cross-platform inventory mismatches (overselling risk on canonical SKUs)
  • Listings with active ad spend on out-of-stock or near-stockout SKUs

03/Action

Recommended actions

Restock and reallocation moves ranked by their margin impact, not just stock level.

  1. 01

    Restock by margin priority

    Reorder the SKUs whose stockout would cost the most contribution margin first.

  2. 02

    Reallocate stock across shops

    Move inventory from low-velocity to high-velocity shops within the same brand.

  3. 03

    Pause ads on near-stockout SKUs

    Stop wasting ad spend on listings that will go out of stock before the spend pays back.

  4. 04

    Liquidate slow movers

    Surface SKUs whose holding cost exceeds the realistic profit of waiting them out.

05/Glossary

Concepts in this solution

04/FAQ

Frequently asked

Yes. The stockout-day model accounts for scheduled campaign windows (11.11, 12.12, Pay Day, Lazada flash sales) and TikTok Shop live events that historically lift demand on specific SKUs.

Yes. The canonical product catalog binds the same product across Shopee shops and platforms so inventory state is one number, not per-listing. Opt-in writeback keeps Shopee total_stock in sync.

Not yet. DataGlass surfaces a ranked restock queue with the recommended quantity and lead time; PO creation is on the roadmap.

Stop guessing. Start deploying.

Join the sellers using DataGlass to turn shop data into the next profit-maximizing action.