Analytics & Reports

Filters & Date Ranges

All analytics pages share a common filter bar that lets you narrow data by time period and other criteria.

Date Range

Each page has two date pickers — From and To — that default to the last 30 days. Pick any custom start and end date; there are no preset shortcuts (today/yesterday/last 7 days/etc.) in the current UI.

Additional Filters

• Warehouse — Limit data to items currently located in a specific warehouse.
• Auction — Filter to lots in a specific auction.
• Team — Show only data for lots assigned to a specific team.

Receiving Analytics

Receiving analytics track how items enter your system through scanning at the Scanning Station.

Key Metrics

• Total Received — Total items scanned in the selected period (count of items with a scanned_at timestamp in range).
• Daily Trend — A daily chart of items scanned per day.
• By User — Top 20 scanners ranked by item count.
• By Vendor — Top 20 vendors by items received.
• By Warehouse — Items received grouped by warehouse location.
• By Team — Items received grouped by the team assigned to the lot.
• By Hour of Day — Distribution of scanning activity across the 24-hour clock.

Put-Away Analytics

Put-away analytics measure how efficiently items are moved from the receiving area to warehouse locations.

Key Metrics

• Total Put Away — Total put_away activity-log events in the period.
• Daily Trend — Daily chart of put-away events.
• By User — Top 20 users by items put away.
• By Warehouse — Put-away events grouped by warehouse.
• By Location — Top 20 destination locations by put-away count (location code + name).

Picking Analytics

Picking analytics track the throughput of your picking operations.

Key Metrics

• Total Picked — Total pick-list items marked picked in the period.
• Completion Rate — Picked items as a percentage of pick-list items created in the same period.
• Daily Trend — Daily chart of items picked.
• By User — Top 20 pickers by items picked.

Vendor Performance

Compare vendors side by side to identify your most profitable sources and underperformers.

Vendor Comparison Table

The vendor performance report shows a per-vendor table with these columns:

• Items Received — Items created in the period sourced from this vendor.
• Items Sold — Items from this vendor that have status sold.
• Sell-Through — Items Sold ÷ Items Received, expressed as a percentage.
• Cost — Sum of cost on items received from this vendor.
• Revenue — Sum of sold_price on sold items from this vendor.
• Est. Value — Sum of estimated_value across all items received.

Revenue Analytics

Revenue analytics provide a financial view of your auction operations.

Revenue Dashboard

• Total Sold — Count of items sold in the period.
• Total Revenue — Sum of sold_price for sold items.
• Total Cost — Sum of cost for sold items (acquisition cost).
• Avg Sold Price — Mean sold_price across sold items.
• Daily Trend — Line chart of daily item count and revenue.
• By Vendor — Per-vendor breakdown of items sold, revenue, and cost.

Inventory Aging

The inventory aging report shows how long items have been sitting in your warehouse without selling. Aging inventory ties up space and capital.

Aging Buckets

Non-sold items are grouped into buckets based on days since the item was created:

• 0-7 days — Recently received items still in the pipeline.
• 8-14 days — Should be lotted and approaching auction.
• 15-30 days — Should have gone through at least one auction cycle.
• 31-60 days — Aging inventory that needs attention.
• 60+ days — Stale inventory that should be repriced, relisted, or disposed of.

Each bucket shows an item count. The page also surfaces a Stale Items stat — the number of non-sold items whose record has not been updated in 30+ days — and a breakdown by status with the average days each item has spent in that status.

Throughput

Throughput analytics measure the flow of items through each stage of your operation: scanning, cataloging, put-away, and sale.

Pipeline

The page shows a pipeline widget grouping all items by current status with a count for each. This helps you spot bottlenecks — if items are piling up at a particular status, you can see it at a glance.

Stage Timings

Three average-hours stats, computed over items whose end-of-stage timestamp falls in the selected period:

• Scan to Catalog — Average hours from scanned_at to cataloged_at.
• Scan to Put-Away — Average hours from scanned_at to the put-away activity-log event.
• Scan to Sold — Average hours from scanned_at to sold_at (full lifecycle).

Daily Flow

A daily chart overlays four series for each day in the period: scanned, cataloged, put away, and sold. Use it to compare incoming volume against downstream stages and spot where items are stalling.

User Productivity

User productivity reports show how individual team members are performing across scanning, cataloging, put-away, and picking tasks.

Per-User Metrics

One row per user who took any action in the period. Columns:

• Name and Team — User name and the team they belong to (if any).
• Scanned — Items where this user is recorded as scanned_by.
• Cataloged — Items where this user is recorded as cataloged_by.
• Put Away — Put-away activity-log events attributed to this user.
• Picked — Pick-list items where this user is recorded as picked_by.
• Items/Hr — Scanned items divided by the number of distinct one-hour windows during which the user scanned (a rough activity-based rate, not a precise time-clock).