Setting Up AI Columns

Table Of Contents

• What Are AI Columns?
• When to Add AI Columns
• How AI Columns Work
• Step-by-Step Setup
• Step 1: Decide What Columns You Need
• Step 2: Update Your Prompt
• Step 3: Create Column Profile in SKU Manager
• Step 4: Update Your Filter
• Step 5: Test It
• Common Use Cases
• Use Case 1: Filter Out Listings You Don’t Buy
• Use Case 2: Visual Scanning with Color Coding
• Use Case 3: Two-Stage Analysis (Save API Costs)
• Use Case 4: Hidden Columns for Logic Only
• Tips & Best Practices
• Keep Values Consistent
• Start Small
• Use “Return Original”
• Column Order Matters
• Test with Edge Cases
• Troubleshooting
• Columns Not Appearing in Grid
• Columns Show Empty/Blank Values
• Columns Show Wrong Values
• Want to Refresh Existing Results?
• Quick Reference
• What’s Next?

Add quick-decision fields directly to your results grid.

What Are AI Columns?

AI Columns are custom fields that appear in your results grid, giving you at-a-glance decisions without opening the External Panel.

Example AI Columns:

• “Buy?” → Yes / No / Maybe
• “Condition” → Excellent / Good / Fair / Poor
• “Risk Level” → High / Medium / Low
• “Model” → iPhone 15 Pro / iPhone 15 / Unknown
• “Est. Profit” → $45 / $20 / -$10

When to Add AI Columns

✅ Add AI Columns AFTER you have:

• A working prompt returning good analysis
• Display template showing correct results
• Tested with 10+ listings successfully
• Identified key decisions you make repeatedly

❌ Don’t start with AI Columns — get the basics working first. They add complexity.

How AI Columns Work

Your prompt outputs JSON. AI Columns pull specific fields from that JSON into grid columns.

Prompt runs → JSON output → AI Columns extract values → Values appear in grid

Example JSON output:

{
  "shouldBuy": "Yes",
  "riskLevel": "Low",
  "estimatedProfit": "$35",
  "modelIdentified": "iPhone 15 Pro 256GB"
}

Each of those fields can become a column in your results grid.

Step-by-Step Setup

Step 1: Decide What Columns You Need

Before touching SKU Manager, decide:

• What quick decisions do you make on every listing?
• What values would help you scan faster?
• Keep it simple — 3-5 columns max to start

Good first columns:

• Buy/Pass decision
• Risk or confidence level
• Key identifier (model, variant, etc.)

Step 2: Update Your Prompt

Go back to your Claude or ChatGPT project and ask:

My prompt is working well. Now I want to add AI Columns for quick decisions.

In the grid, I need:
1. "Can Return" column (Yes/No/Unknown)
2. "Original Owner" column (High/Medium/Low/Unknown)

Can you update my prompt to output these as separate fields with exact values?

The AI will add a section to your prompt like:

## AI COLUMN CONFIGURATION

### 1. "Can Return" Field – For AI Column
Must return EXACTLY: "Yes", "No", or "Unknown"

### 2. "Original Owner" Field – For AI Column  
Must return EXACTLY: "High", "Medium", "Low", or "Unknown"

Important: The prompt must specify EXACT output values. AI Columns need consistent, predictable text.

Step 3: Create Column Profile in SKU Manager

1. Open External Data panel (Data tab > Get Data)

2. Go to “AI Columns” tab

3. Click “Add” to create new profile

4. Name it (e.g., “Phone_Analysis_Columns”)

5. Enter each column on a SEPARATE LINE: Can Return Original Owner

6. Press Enter after each column name

7. Check ✅ “Return Original” (recommended) — keeps original values if AI doesn’t return a match

8. Click Save

📸 [Screenshot: AI Columns tab with column names entered on separate lines]

Step 4: Update Your Filter

1. Close the External Data panel

2. Go to Home > Filters

3. Edit your existing filter

4. In the Columns dropdown, select your new columns profile

5. Click OK to save

Your filter should now have all four profiles connected:

• ✅ Prompt
• ✅ Display Template
• ✅ Fields to Send
• ✅ Columns ← new

Step 5: Test It

1. Reopen External Data panel

2. Restart the script (Stop Script → Script Started!)

3. Run a search that triggers your filter

4. Check your results grid — new columns should appear with values

To refresh columns on existing results: Right-click the column header → “Update LLM Columns”

Common Use Cases

Use Case 1: Filter Out Listings You Don’t Buy

Scenario: You search “iPhone 15” but only buy iPhone 15 Pro models.

1. Create AI Column: Buying (Yes/No)

2. Prompt logic identifies Pro vs non-Pro

3. Create a second filter:

• Condition: AI Column “Buying” = “No”
• Action: Remove Row (or hide/dim)

4. Condition: AI Column “Buying” = “No”

5. Action: Remove Row (or hide/dim)

Now non-Pro models automatically disappear from your results.

Use Case 2: Visual Scanning with Color Coding

1. Create AI Column: Risk (High/Medium/Low)

2. Create filters to highlight rows:

• Risk = “High” → Red background
• Risk = “Medium” → Yellow background
• Risk = “Low” → Green background

3. Risk = “High” → Red background

4. Risk = “Medium” → Yellow background

5. Risk = “Low” → Green background

Instantly spot risky listings while scanning.

Use Case 3: Two-Stage Analysis (Save API Costs)

Problem: Full analysis on every listing is slow and expensive.

Solution: Chain your analysis:

1. First filter — Quick screening prompt with AI Columns only

• Display Template: (leave blank or minimal)
• Columns: Worth Analyzing (Yes/No)
• Fast, cheap analysis

2. Display Template: (leave blank or minimal)

3. Columns: Worth Analyzing (Yes/No)

4. Fast, cheap analysis

5. Second filter — Triggers only when Worth Analyzing = “Yes”

• Full detailed prompt
• Complete Display Template
• Only runs on promising listings

6. Full detailed prompt

7. Complete Display Template

8. Only runs on promising listings

This can significantly reduce API costs and speed up your workflow.

Use Case 4: Hidden Columns for Logic Only

You can create AI Columns that don’t display in the grid but power your filters.

Example: Create a category_match column that outputs internal codes, then use filters to route listings to different prompts based on the code.

Tips & Best Practices

Keep Values Consistent

AI Columns work best with a small set of exact values:

• ✅ Good: “Yes”, “No”, “Unknown”
• ❌ Bad: “Yes!”, “yes”, “Y”, “Definitely yes”

Your prompt should specify exact allowed values.

Start Small

Begin with 2-3 columns. Add more only after those work reliably. Too many columns slow processing and clutter your grid.

Use “Return Original”

Check this option to preserve values when the AI doesn’t return a recognized response. Helps with debugging.

Column Order Matters

Columns appear in the order you enter them. Put most important columns first.

Test with Edge Cases

Try listings with missing data, unusual conditions, or ambiguous titles. Make sure your columns handle them gracefully.

Troubleshooting

Columns Not Appearing in Grid

• Is the Columns profile selected in your filter?
• Did you restart the script after changes?
• Are column names spelled exactly the same in prompt and profile?

Columns Show Empty/Blank Values

• Check that your prompt outputs the exact field names
• Verify JSON structure is valid
• Look at the full AI response in External Panel for clues

Columns Show Wrong Values

• Review your prompt’s column configuration section
• Make sure allowed values are clearly specified
• Submit feedback trace and refine with your AI project

Want to Refresh Existing Results?

Right-click on any AI Column header → “Update LLM Columns”

Quick Reference

What’s Next?

Once your AI Columns are working:

• Create filters that act on column values (highlight, remove, trigger additional analysis)
• Experiment with chained analysis for speed/cost optimization
• Use Feedback Traces to refine column accuracy

See also: Quick Start Guide | Troubleshooting & FAQ | Using Feedback & Traces

Updated on: 26/01/2026