Structured LLM output means asking an AI model to return values in named fields instead of free text.

For spreadsheet work, this matters because each answer must fit into columns.

Bad output:

This company looks like a strong fit. It sells HR software and seems to target mid-market companies.

Structured output:

Fit: Strong
Industry: HR software
Company size: Mid-market
Reason: Sells software to HR teams

The second answer can be saved into separate columns.

Why structured output matters

Free text is useful for reading. Structured output is useful for operations.

Use structured output when you want to:

  • Filter rows
  • Sort by scores
  • Export to a CRM
  • Deduplicate labels
  • Build segments
  • Review only low-confidence rows
  • Reuse AI results in another enrichment

Structured outputs also make errors easier to spot. If a field is empty, too long, or outside an allowed list, you can filter it.

Common output fields

Structured LLM workflows often return:

  • Category
  • Score
  • Confidence
  • Summary
  • Reason
  • Company type
  • Job title group
  • Language
  • Sentiment
  • Extracted value
  • Source URL

For classification, keep labels short and controlled. For example, use SaaS, Agency, Marketplace, or Ecommerce instead of asking the model to invent a category.

📌 Use allowed values

When you need clean data, give the model a fixed list of possible answers. This reduces duplicates such as Software, SaaS, and Software company.

Structured output examples

For lead scoring:

Return:
- Score from 1 to 5
- Fit: Good, Medium, or Poor
- Reason in one sentence

For review analysis:

Return:
- Sentiment: Positive, Neutral, or Negative
- Topic: Pricing, Support, Product Quality, Delivery, or Other
- Short summary

For web extraction:

Return:
- Company name
- Pricing page URL
- Target customer
- Mentioned integrations

Structured output in Datablist

Datablist LLM enrichments can write AI answers back to columns. Use Ask ChatGPT/OpenAI, Ask Claude AI, Ask Gemini, or Ask Mistral AI for row processing.

Use AI Agent or Website AI Scraper when the output comes from web pages.

Structured output is useful with AI classification, AI data extraction, and AI research agent workflows.