Review Queue Best Practices: Quality Control That Scales

Why Review Matters (Even with AI)

ListForge’s AI is powerful, but it’s not infallible. The Review Queue is your quality control checkpoint—the place where human judgment meets AI efficiency.

Here’s why every item should pass through review:

1. AI isn’t perfect: Even 95% accuracy means 5 wrong identifications per 100 items
2. Condition is subjective: AI estimates from photos; you handled the item
3. Market knowledge matters: You may know things the data doesn’t show
4. Brand protection: Catching errors before buyers see them preserves reputation
5. Pricing edge cases: Rare items need human pricing intuition

The goal isn’t to second-guess every AI decision—it’s to catch the exceptions efficiently.

Review Queue Anatomy

When you open the Review Queue, each item shows:

• Item photos (swipeable gallery)
• AI-generated title and description
• Item specifics (brand, model, condition, etc.)
• Suggested price range with confidence score
• Comparable sales the AI used for pricing
• Overall confidence score for the identification

Green indicators mean high confidence; yellow means review recommended; red means attention required.

The Three-Tier Review Workflow

Based on confidence scores, items need different levels of attention:

Tier 1: Quick Approve (90%+ Confidence)

These items have:

• High-confidence identification
• Strong comparable data
• Clear pricing recommendations

Review process:

1. Glance at photo vs. title (do they match?)
2. Check price range (reasonable?)
3. Approve (one tap)

Time per item: 5-10 seconds

Tip: Use keyboard shortcuts for rapid review. Space to approve, arrow keys to navigate.

Tier 2: Standard Review (70-89% Confidence)

These items need a closer look:

• Identification is probably right, but verify
• Pricing may need adjustment
• Some item specifics might be missing

Review process:

1. Verify title matches the actual item
2. Check key specifics (brand, model, size, color)
3. Review pricing—do comparables actually match your item?
4. Adjust any incorrect fields
5. Approve

Time per item: 30-60 seconds

Tier 3: Deep Review (under 70% Confidence)

These require real attention:

• AI is uncertain about identification
• Limited or no comparable sales found
• Manual research may be required

Review process:

1. Examine photos carefully—what is this item?
2. Compare AI suggestion to your own assessment
3. If identification is wrong, search for correct match
4. Check specialty databases or collector resources if needed
5. Manually set pricing based on your research
6. Approve only when confident

Time per item: 2-5 minutes

Prioritizing Your Review Queue

Don’t work through the queue randomly. Prioritize:

1. High-value items first: Errors on $500 items matter more than $5 items
2. Fresh inventory second: New acquisitions while memory is fresh
3. Aged inventory third: Items sitting in queue too long

ListForge lets you sort and filter the queue by confidence, value, age, and category.

Batch Review Techniques

For high-volume operations:

Category Batching

Review all electronics together, then all clothing, then all books. Context switching is expensive—staying in category makes you faster.

Confidence Batching

Burn through all Tier 1 (high confidence) items first. Quick wins build momentum. Then tackle Tier 2 and 3 with focus.

Time Boxing

Set a timer for 30 minutes. See how many items you can review. Gamifying the process increases throughput.

Common Review Pitfalls

Pitfall 1: Over-reviewing High-Confidence Items

If the AI is 95%+ confident, you don’t need to spend 2 minutes verifying. Trust and verify quickly.

Pitfall 2: Under-reviewing Low-Confidence Items

If confidence is below 70%, don’t just approve anyway. That defeats the purpose of review.

Pitfall 3: Ignoring Pricing

It’s tempting to focus only on identification, but pricing errors cost real money. Always check the comparables.

Pitfall 4: Skipping Condition Review

The AI estimates condition from photos, but you may have noticed flaws not visible in images. Adjust condition ratings as needed.

Pitfall 5: Review Queue Neglect

Items stuck in queue aren’t making money. Set a daily review target and hit it.

Team Review Workflows

For teams with multiple reviewers:

Role-Based Assignment

• Junior reviewers: Tier 1 (high confidence) only
• Senior reviewers: Tier 2 and 3 (complex items)
• Category specialists: Items in their expertise area

Review Quotas

Set daily targets per team member. Track completion rates. Gamify with leaderboards if appropriate.

Quality Audits

Randomly sample approved items for accuracy. Catch systematic errors before they compound.

Approval Thresholds

For high-value items (e.g., >$200), require two approvals. Expensive mistakes are worth preventing.

Metrics to Track

Monitor these review metrics:

• Queue depth: How many items waiting for review?
• Average time in queue: How long from capture to approval?
• Approval rate: What percentage of AI suggestions are approved as-is?
• Edit rate: How often do reviewers modify AI suggestions?
• Error rate: Post-sale, how many items had inaccurate listings?

These metrics reveal whether your review process is too slow, too permissive, or just right.

Keyboard Shortcuts for Speed

Master these shortcuts:

• Space: Approve current item
• Left/Right arrows: Navigate between items
• E: Edit mode (modify fields)
• P: Focus on price field
• Esc: Cancel/exit

With shortcuts, experienced reviewers can process Tier 1 items in 3-5 seconds each.

Building Review into Your Daily Routine

The most successful review workflows are habitual:

Morning routine:

1. Coffee
2. Check overnight captures
3. 30-minute review session
4. All fresh items approved and ready for listing

Post-sourcing routine:

1. Return from sourcing trip
2. Let AI research batch while you unpack
3. Review session before items go to storage
4. Everything processed same day

End-of-day routine:

1. Final queue check
2. Approve any remaining Tier 1 items
3. Queue depth at zero
4. Tomorrow starts fresh

The Review Mindset

Think of review as quality control, not bureaucracy. Every minute spent in review saves five minutes of customer service dealing with inaccurate listings.

The goal is calibrated trust: trust the AI where it’s confident, intervene where it’s not, and always be improving the system based on what you learn.

Your Review Queue is where AI efficiency meets human expertise. Master it, and you’ve mastered scalable quality.