ChatGPT’s Data Analyst mode turns a friendly chat box into a junior data scientist. Drag in a spreadsheet, PDF, or image, then ask plain-English questions. Behind the scenes, ChatGPT writes and runs Python that cleans messy columns, calculates new metrics, and sketches charts.

Everything happens inside a secure, temporary sandbox, so you never touch code or risk breaking formulas. Real-estate pros can explore suburb-by-suburb sale prices, vendor-paid-ad spend, or rent yields in minutes, and export polished visuals for listing kits. In short, Data Analyst puts powerful number-crunching where agents already spend their day: inside ChatGPT.

Key Features

• Drag-and-drop files: Upload CSV, Excel, PDFs, or images; Data Analyst reads and previews them in seconds.

• Conversational cleaning: Say “remove duplicates and fix dates,” and the tool tidies data automatically—no formulas needed.

• Instant visuals: Ask “plot median sale price by quarter” to receive editable bar or line charts ready to download.

• Cloud integrations: Connect Google Drive or OneDrive to pull the freshest market reports without manual downloads.

• Secure & disposable: Code and data live in an isolated session that wipes when you close the chat, protecting client privacy. (OpenAI, DataCamp)

Use Cases

• Spot market momentum: Chart five-year price trends for each suburb to guide seller pricing.

• Pitch listing campaigns: Show vendors ROI by comparing ad spend to enquiry spikes.

• Optimise open-home timing: Analyse attendance logs to reveal the best inspection hours.

• Track rental yields: Merge rent rolls with purchase prices to highlight cash-flow suburbs for investors.

• Benchmark performance: Compare your agency’s days-on-market against regional averages to refine strategy.