📊AI Extract•In Google Sheets
Extract Structured Data with AI
Transform messy, unstructured text into clean, structured data. Parse addresses, extract entities, and organize information — all with natural language prompts.
data-extraction.xlsx
| A | B | C | |
|---|---|---|---|
| 1 | Raw Text | Formula | Extracted |
| 2 | Contact John at john@acme.com | | — |
| 3 | Total: $1,249.99 USD | =AI_EXTRACT(A3, "price") | 1249.99 |
| 4 | 123 Main St, New York, NY 10001 | =AI_EXTRACT(A4, "city, state") | New York, NY |
Why AI Extract?
Turn chaos into clean data
AI understands context and extracts exactly what you need from any text, no matter how messy.
🎯
Natural Language Extraction
Describe what you want to extract in plain English. AI understands context and finds it.
✨
Entity Recognition
Automatically identify and extract names, companies, emails, phones, dates, and more.
📊
Address Parsing
Parse messy addresses into structured components: street, city, state, zip, country.
🧠
Data Classification
Categorize and tag data automatically based on content, sentiment, or custom criteria.
⚡
Multi-Field Extraction
Extract multiple pieces of information at once and return them as structured columns.
🔧
Cleaning & Normalization
Standardize formats, fix typos, and clean up messy data automatically.
Examples
AI extraction in action
See how AI transforms messy text into clean, structured data.
Entity Extraction•Extract Company Information
Formula
=AI_EXTRACT(A1, "Extract name, email, phone, company")Input Text
Hi, this is John Smith from Acme Corp. You can reach me at john.smith@acmecorp.com or call me at (555) 123-4567. Looking forward to discussing partnership opportunities!
Extracted Data
AI2D Array2 rows × 4 cols
| [0] | Name | Phone | Company | |
| [1] | John Smith | john.smith@acmecorp.com | (555) 123-4567 | Acme Corp |
Use case: extract entities from text google sheets
Data Classification•Extract Contact Details
Formula
=AI_EXTRACT(A1, "Extract job title, company, location, industry")Input Text
Sarah Johnson, VP of Marketing at TechStart Inc, based in Austin, Texas. We're a B2B SaaS company in the project management space.
Extracted Data
AI2D Array2 rows × 4 cols
| [0] | Job Title | Company | Location | Industry |
| [1] | VP of Marketing | TechStart Inc | Austin, Texas | B2B SaaS |
Use case: extract contact info google sheets
Entity Extraction•Classify Products
Formula
=AI_EXTRACT(A1, "Extract product name, price, color, size")Input Text
Premium Wireless Headphones - Black, Over-Ear, Noise Cancelling. Price: $299.99. Available in Black, Silver, and Rose Gold. Weight: 250g.
Extracted Data
AI2D Array2 rows × 4 cols
| [0] | Product | Price | Color | Size |
| [1] | Premium Wireless Headphones | $299.99 | Black, Silver, Rose Gold | Over-Ear |
Use case: categorize data google sheets
Entity Extraction•Parse Invoice Details
Formula
=AI_EXTRACT(A1, "Extract invoice number, date, total amount, vendor name")Input Text
INVOICE #INV-2024-0156 | Date: January 15, 2024 | Bill To: Acme Corp | Total: $1,245.00 | Vendor: Office Supplies Plus
Extracted Data
AI2D Array2 rows × 4 cols
| [0] | Invoice # | Date | Total | Vendor |
| [1] | INV-2024-0156 | January 15, 2024 | $1,245.00 | Office Supplies Plus |
Use case: parse invoices google sheets
Entity Extraction•Extract Event Information
Formula
=AI_EXTRACT(A1, "Extract event name, date, time, location, cost")Input Text
Join us for the Annual Tech Summit 2025 on March 15-17, 2025 at the Austin Convention Center. Sessions run from 9 AM to 5 PM daily. Early bird tickets: $599.
Extracted Data
AI2D Array2 rows × 5 cols
| [0] | Event | Date | Time | Location | Cost |
| [1] | Annual Tech Summit 2025 | March 15-17, 2025 | 9 AM - 5 PM | Austin Convention Center | $599 |
Use case: extract event data google sheets
Entity Extraction•Extract Resume Information
Formula
=AI_EXTRACT(A1, "Extract name, years of experience, education, skills")Input Text
Michael Chen - 8 years of experience in full-stack development. BS in Computer Science from Stanford. Proficient in React, Node.js, Python, AWS.
Extracted Data
AI2D Array2 rows × 4 cols
| [0] | Name | Experience | Education | Skills |
| [1] | Michael Chen | 8 years | BS Computer Science, Stanford | React, Node.js, Python, AWS |
Use case: parse resume data google sheets
Address Parsing•Parse Messy Addresses
Formula
=AI_EXTRACT(A1, "Extract street, city, state, zip code")Input Text
Please ship to: 123 Main Street, Suite 400, San Francisco, CA 94102
Extracted Data
AI2D Array2 rows × 4 cols
| [0] | Street | City | State | Zip |
| [1] | 123 Main Street, Suite 400 | San Francisco | CA | 94102 |
Use case: parse addresses google sheets
Entity Extraction•Clean and Normalize Data
Formula
=AI_EXTRACT(A1, "Extract revenue, expenses, profit margin, growth rate")Input Text
Q4 Results: Revenue $2.4M (+15% YoY), Operating Expenses $1.8M, Net Profit Margin 25%, Customer Growth 32%
Extracted Data
AI2D Array2 rows × 4 cols
| [0] | Revenue | Expenses | Profit Margin | Growth |
| [1] | $2.4M | $1.8M | 25% | 32% |
Use case: clean data google sheets
Real-World Use Cases
From messy text to structured data
See how teams use AI extraction to automate data processing workflows.
Customer Review Analysis
Extract insights, sentiment, and key themes from reviews
Formula
=AI_EXTRACT(A2, "Extract customer name, sentiment (positive/negative/neutral), main issue, urgency (high/medium/low), product mentioned")INPUTRaw text
| Customer Feedback |
|---|
| Hey team, this is Sarah from Account #1234. Really frustrated with the mobile app crashing constantly. This is costing us productivity! Please fix ASAP - high priority. |
| Love the new dashboard! John here from TechCorp. The analytics feature is exactly what we needed. Great work on the update. |
| Quick question - does the premium plan include API access? - Emily Watson |
| URGENT: We can't access our data since yesterday. This is a critical issue for our business. Contact: Mike Johnson, mike@company.com |
EXTRACTEDStructured data
📊 CUSTOMER FEEDBACK ANALYSIS
TICKET #1:
👤 Customer: Sarah (Account #1234)
😤 Sentiment: Negative
🔧 Issue: Mobile app crashing
⚠️ Urgency: High
📦 Product: Mobile App
→ ACTION: Escalate to dev team - critical bug
TICKET #2:
👤 Customer: John (TechCorp)
😊 Sentiment: Positive
💬 Feedback: Analytics feature appreciated
⚠️ Urgency: Low
📦 Product: Dashboard
→ ACTION: Share with product team, request testimonial
TICKET #3:
👤 Customer: Emily Watson
😐 Sentiment: Neutral
❓ Question: API access in premium plan
⚠️ Urgency: Medium
📦 Product: Premium Plan
→ ACTION: Sales follow-up, send pricing info
TICKET #4:
👤 Customer: Mike Johnson (mike@company.com)
😤 Sentiment: Negative
🔥 Issue: Data access blocked
⚠️ Urgency: High
📦 Product: Core Platform
→ ACTION: URGENT - technical support immediately
📈 SUMMARY:
• Total Feedback: 4 items
• Urgent Issues: 2 (50%)
• Sentiment: 50% Negative, 25% Positive, 25% Neutral
• Product Areas: Mobile App, Dashboard, Premium Plan, Core Platform
🎯 IMMEDIATE ACTIONS:
1. Address data access issue (Mike Johnson) - CRITICAL
2. Investigate mobile app crashes (Sarah) - HIGH
3. Follow up on API question (Emily) - MEDIUM
4. Thank positive feedback (John) - LOW
💡 INSIGHTS:
• Mobile app stability issues recurring
• Dashboard update well-received
• Premium plan features need clarification
Lead Enrichment Pipeline
Extract and structure contact information from messy lead data
Formula
=AI_EXTRACT(B2, "Extract full name, job title, company, company size, industry, email, phone, LinkedIn URL, pain points")INPUTRaw text
| Lead Source | Raw Lead Data |
|---|---|
| Jennifer Martinez, Director of Sales at CloudTech Solutions (200 employees). SaaS company struggling with lead generation. jennifer.m@cloudtech.io | linkedin.com/in/jennifermartinez | |
| Conference | Met David Park - CMO @ StartupXYZ, early stage fintech (30 people). Needs marketing automation. Call: 555-0123 |
| Webinar | Amanda Foster signed up. VP Product, MedTech Innovations, healthcare tech, ~500 employees. Looking for better analytics. amanda.foster@medtech.com |
EXTRACTEDStructured data
🎯 ENRICHED LEAD DATABASE
LEAD #1:
👤 Name: Jennifer Martinez
💼 Title: Director of Sales
🏢 Company: CloudTech Solutions
👥 Size: 200 employees
🏭 Industry: SaaS
📧 Email: jennifer.m@cloudtech.io
📱 Phone: -
🔗 LinkedIn: linkedin.com/in/jennifermartinez
💬 Pain Points: Lead generation struggles
📊 Lead Score: 85/100 (Mid-market SaaS, high intent)
🎯 Next Action: Schedule demo, share case study
LEAD #2:
👤 Name: David Park
💼 Title: CMO
🏢 Company: StartupXYZ
👥 Size: 30 employees
🏭 Industry: Fintech
📧 Email: -
📱 Phone: 555-0123
🔗 LinkedIn: -
💬 Pain Points: Marketing automation needs
📊 Lead Score: 72/100 (Early stage, budget conscious)
🎯 Next Action: Call to qualify, send startup pricing
LEAD #3:
👤 Name: Amanda Foster
💼 Title: VP Product
🏢 Company: MedTech Innovations
👥 Size: ~500 employees
🏭 Industry: Healthcare Tech
📧 Email: amanda.foster@medtech.com
📱 Phone: -
🔗 LinkedIn: -
💬 Pain Points: Analytics capabilities
📊 Lead Score: 91/100 (Enterprise healthcare, specific need)
🎯 Next Action: Custom analytics demo, compliance info
📊 PIPELINE SUMMARY:
• Total Leads: 3
• Average Lead Score: 82.7/100
• Industries: SaaS (1), Fintech (1), Healthcare (1)
• Company Sizes: Enterprise (1), Mid-market (1), Startup (1)
🎯 RECOMMENDED APPROACH:
1. Priority: Amanda Foster (highest score, enterprise)
2. Follow-up: Jennifer Martinez (strong fit, active pain point)
3. Qualify: David Park (early stage, confirm budget)
📈 AUTOMATION OPPORTUNITIES:
• Add to CRM (all 3)
• Trigger nurture sequence based on company size
• Assign to appropriate sales rep (enterprise vs SMB)
• Schedule follow-up tasks
Address Standardization
Parse and normalize addresses from various formats
Formula
=AI_EXTRACT(A2, "Extract parties involved, effective date, termination date, payment terms, key obligations")INPUTRaw text
| Document Type | Document Text |
|---|---|
| Service Agreement | This Agreement between Acme Corp (Client) and Tech Services LLC (Provider) effective January 1, 2025 through December 31, 2025. Payment: $5,000/month, due within 30 days. Provider shall deliver monthly reports and maintain 99.9% uptime. |
| Lease Agreement | Lease between Property Owner: Smith Realty and Tenant: Jane's Coffee Shop. Term: March 1, 2025 - February 28, 2028. Rent: $3,500/month due on 1st of month. Tenant responsible for utilities and maintenance. |
EXTRACTEDStructured data
📄 DOCUMENT EXTRACTION REPORT
DOCUMENT #1: Service Agreement
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
👥 Parties:
• Client: Acme Corp
• Provider: Tech Services LLC
📅 Dates:
• Effective: January 1, 2025
• Termination: December 31, 2025
• Duration: 12 months
💰 Payment Terms:
• Amount: $5,000/month
• Due: Within 30 days
• Annual Value: $60,000
📋 Key Obligations:
✓ Provider: Monthly reports
✓ Provider: 99.9% uptime SLA
✓ Client: Timely payment
⚠️ ALERTS:
• Renewal: December 1, 2025 (60 days before)
• SLA Monitoring: Set up uptime tracking
• Payment Tracking: Auto-invoice 30 days before due
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
DOCUMENT #2: Lease Agreement
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
👥 Parties:
• Owner: Smith Realty
• Tenant: Jane's Coffee Shop
📅 Dates:
• Start: March 1, 2025
• End: February 28, 2028
• Duration: 36 months (3 years)
💰 Payment Terms:
• Rent: $3,500/month
• Due: 1st of each month
• Total Value: $126,000 (3 years)
📋 Key Obligations:
✓ Tenant: Pay rent on 1st
✓ Tenant: Utilities
✓ Tenant: Maintenance
✓ Owner: Property ownership
⚠️ ALERTS:
• Renewal Discussion: December 2027 (3 months before)
• Rent Review: March 1, 2026 (annual check)
• Maintenance Budget: Track tenant expenses
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📊 PORTFOLIO SUMMARY:
• Active Contracts: 2
• Total Annual Value: $102,000
• Expiring in 2025: 1 contract
• Expiring in 2026+: 1 contract
🔔 UPCOMING ACTIONS:
1. Q4 2025: Service Agreement renewal (Acme Corp)
2. Q1 2026: First rent review (Jane's Coffee Shop)
3. Monitor SLA compliance (Tech Services)
4. Track tenant maintenance costs
💼 CONTRACT MANAGEMENT:
• Set calendar reminders for all dates
• Create payment tracking dashboard
• Monitor obligation compliance
• Plan renewal negotiations
FAQ
Frequently Asked Questions
AI Extract uses artificial intelligence to parse unstructured text and extract specific data points. Describe what you want to extract in natural language, and AI finds and structures it.
You can extract names, email addresses, phone numbers, dates, addresses, product details, prices, companies, or any custom fields you define. AI understands context and formats.
Use =AI_EXTRACT(A1, "extract email and phone number") where A1 contains your text. The function returns the extracted data in a structured format.
Yes! You can extract multiple fields in one call. Specify all fields in your prompt, and AI returns them as separate columns or in a structured format.
AI Extract is highly accurate for common data types. For best results, be specific in your extraction prompts. Always review output for critical data.
Ready to extract structured data with AI?
AI Extract requires Pro plan (1 credit/request).
Pro: 3,000 credits/month + BYOK unlimited.
No credit card required • Install in 30 seconds • Cancel anytime
