Apparel & Fashion
Apparel is a variant game. Shelfbot keeps it simple: bins come to a station, picks are confirmed by scan, and throughput stays predictable during promotions and peak seasons.
Key benefits:
- Size/colour variants
- Returns + restocking
- Peak-ready scaling
Common challenges
What you feel day-to-day
- • Huge variant counts (size/colour/style) that bloat pick locations
- • High order volume with small quantities per line
- • Returns and restocking cycles that disrupt slotting
- • Promotions and launches causing sudden peaks
- • Accuracy issues when variants look similar
- • Space pressure (apparel is bulky compared to many small goods)
What's really happening
The constraint isn't always "how fast can someone work" — it's how much time is wasted traveling, searching, and managing complexity.
When operators spend most of their shift walking between pick faces, searching for locations, or handling constant variability, throughput drops and errors increase.
Goods-to-Person removes travel time and makes each cycle consistent, predictable, and measurable.
Why Shelfbot fits
Variants stay controlled
Bins and barcode confirmation reduce 'looks similar' errors. Operators confirm the right item, not the right memory.
Picking becomes a repeatable station workflow
Instead of walking through aisles between picks, operators work between pick stations at aisle ends and follow the same cycle all day.
Returns and restocking are simpler
Returned units can be scanned back into stock and replenished into bins without constantly reworking pick faces.
Peak periods scale predictably
Add robots/stations for more capacity. Scaling is modular rather than a major re-layout.
Typical use cases
- • E-commerce apparel fulfilment (high SKU/variant mix)
- • Wholesale 'top-up' orders with frequent repeats
- • Returns processing and putaway into bins
- • Cycle counting by fetching bins on demand
- • Launch and promotion periods with steep demand spikes
What success looks like
Fewer variant-related picking errors
More consistent throughput during peaks
Reduced walking and less congestion in pick aisles
Cleaner returns workflows and faster restocking
Higher density storage and better use of vertical space
What we'll ask in discovery
- • How many SKUs and variants (size/colour) are active?
- • What percentage of orders are single-line vs multi-line?
- • What's your returns volume and how do you process it today?
- • Do you pick by wave/batch, pick-to-order, or a hybrid?
- • What are the peak events (sales, launches) and how long do they last?
- • Any special handling rules (fragile packaging, inserts, bundling)?
Fastest next step
If you can share a SKU master (with stock on hand) plus outbound order history, we can quickly estimate bins required, storage coverage, aisle count, and robots/stations needed.
Want to see a layout for your site?
We'll keep it practical: confirm fit, size the system, and show how it scales through peak growth.
See it. Understand it. Trust it.
Book a 30-minute demo and we'll show you exactly how Shelfbot would work in your warehouse—with a custom ROI projection for your specific operation.