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Aging Buckets Explained

What 0–30 / 31–60 / 61–90 / 90+ means and how to prioritize dead stock.

Last updated: February 21, 2026

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Buckets translate "days without sale" into simple urgency bands so you can prioritize without overthinking.

Estimated time: 4 minutes

What you'll accomplish

  • Understand what each bucket means in practice
  • Learn the prioritization model (Age x Value)
  • Know the recommended discount strategy per bucket
  • Avoid common mistakes (discounting too early, ignoring high-value items)

The 4 buckets

StockSweep groups all dead stock into four aging buckets, displayed as a horizontal stacked bar chart on the Dashboard. Each bucket shows both item count and dollar value (frozen capital).

Bucket Color Days without sale What it means
0–30 days Green 0–30 Normal inventory cycle for most stores. Monitor only — no action needed.
31–60 days Yellow 31–60 Early warning. Consider merchandising tweaks (repositioning, bundling, better photos) before discounting.
61–90 days Orange 61–90 Likely dead stock for most stores. This is where discount testing should begin.
90+ days Red 90+ High-confidence dead stock. Strongest candidates for clearance discounts.

How buckets work on the Dashboard

The aging bucket chart is interactive:

  • Click a bucket segment to filter the Dead Stock Table to that age range only
  • Multi-select buckets to combine ranges (e.g., click 61–90 + 90+ to see all likely dead stock)
  • Each segment shows the count and dollar value so you can quickly compare: "90+ days has 45 items worth $12,400 vs. 61–90 days has 120 items worth $8,200"

How buckets relate to your threshold

Your detection threshold (30/60/90 days) determines when an item enters the dead stock list. Buckets help you decide how aggressively to act on items that are already flagged.

Example with threshold = 60 days:

  • Items at 61–90 days are the "first wave" of dead stock — recently flagged, worth a measured approach
  • Items at 90+ days are the "highest confidence" set — they have been sitting for a long time and deserve more aggressive action

Example with threshold = 30 days:

  • Items at 31–60 days are early-stage dead stock — may respond to small merchandising changes
  • Items at 90+ days have been ignored for 3+ months — deep discounts or alternative strategies (bundling, liquidation) may be needed

Prioritization rule: Age x Value

When deciding which items to act on first, use:

Age x Value — start with items that are both the oldest (highest days without sale) AND the most expensive to hold (highest frozen capital).

This maximizes the financial impact of each batch you process.

Practical example:

  • Item A: 95 days without sale, $2,400 frozen capital — high priority
  • Item B: 120 days without sale, $15 frozen capital — old but low impact
  • Item C: 65 days without sale, $5,000 frozen capital — expensive but not the oldest

Processing order: A first (old + expensive), then C (expensive, moderate age), then B (old but low-value).

0–30 days

  • Do nothing. This is normal inventory turnover.
  • If items appear here frequently, your threshold may be set too low.

31–60 days

  • Merchandising first: consider better product photos, repositioning in collections, or bundling with popular items.
  • Do not discount yet unless you have strong evidence that merchandising alone will not work for this category.

61–90 days

  • Start discount testing with conservative percentages: 10–15%
  • Use small batches (10–30 items) to learn what converts before scaling up
  • Track results in Discount History — check conversion rate after 3–7 days

90+ days

  • Larger batches are safe — these items have a long track record of not selling
  • Consider deeper discounts: 20–40% for stubborn categories
  • Use sale collections: enable auto-tagging so discounted items automatically appear in your clearance page
  • Re-evaluate at 50%+: if items remain unsold after a 40% discount, consider bundling, liquidation channels, or donation

Common mistakes to avoid

Discounting too early (31–60 days)

Items in this range may sell naturally with small merchandising changes. Discounting trains customers to wait for sales and erodes margin.

Ignoring high-value items

It is tempting to batch-discount 200 cheap items first. But one $500 dead stock item sitting for 90+ days ties up more capital than fifty $5 items. Use the inventory value sort to catch these.

Same discount for all categories

Different product categories respond to different discount levels. Track results in Discount History by category and build a playbook: "Apparel converts at 15%, Electronics needs 25%."

What success looks like

After 3–4 weekly cycles:

  • The 90+ days bucket shrinks in both count and dollar value
  • Frozen capital trends down on the Dashboard metric card
  • You have a repeatable discount strategy per product category (documented in your Discount History patterns)
  • The 61–90 days bucket becomes your primary working set (90+ is under control)