You just closed on a tour of a 120-unit apartment community. The building looks solid, the numbers are in the right range, and the broker says tenant retention is strong. But before you go any deeper, you want to know what the people who actually live there, shop there, or visit there are saying online. Google reviews, Yelp complaints, forum posts: the unfiltered version of the property’s reputation. The data is out there. But pulling reviews from three or four platforms, reading through dozens of comments, and organizing them into something useful for your deal team takes 20 minutes on a good day. When you’re screening multiple properties in a week, the review analysis is one of the first things that gets skipped or reduced to a quick glance at a star rating. That’s exactly what this task is built to fix. due diligence 10 min Analyze Property Online Reviews Pull and analyze reviews for a property, organized by property type considerations with opportunities and risks. Who It’s For CRE professionals who want to understand what tenants, customers, and visitors are saying about a property before making an investment or management decision. What You Get Back A structured review analysis with sentiment by category, recurring themes, and up to three opportunities and three risks tied to real estate implications. Why It Matters Compresses 20 minutes of manual review research into 10 minutes, with property-type-specific analysis that connects online sentiment to deal-level decisions. Task Inputs Property Type Required Property type from the standard list Property Address Required Full address of the property (street, city, state, ZIP) Property or Tenant Name Required Name of the property or Tenant (e.g., Camp Kalama RV Park, Lloyds Burgers, USA Mall, Gallery Apartments) Skills Used Online Review Analysis by Property Type Tools Used Web Search Web Browser Access Google Places Google Maps: Search Places What This Task Does You give the task three inputs: the property type, the property address, and the property or tenant name. That’s the entire setup. No review accounts to log into, no platforms to search manually, no spreadsheet to build from scratch. From there, your Real Estate Analyst (with Memory) AI Coworker runs three review searches in parallel: web search, the Access Google Places workflow, and the Google Maps: Search Places tool. It combines all results into a single review set, removes duplicates, and analyzes the reviews using consideration categories specific to your property type. The output includes a Google rating summary, a sentiment table organized by category, and up to three opportunities and three risks connecting review patterns to real estate implications. The whole process takes roughly 10 minutes of your time. The AI does the rest. Who This Task Is For Anyone evaluating a property needs to understand what the people who use it actually think. Reviews surface operational issues, tenant satisfaction signals, and reputation risks that financials alone never reveal. This task is built for: Acquisitions analysts who want to flag tenant sentiment and reputation issues before committing to deeper diligence Asset managers who need to monitor how their properties are perceived online and catch operational problems early Due diligence teams who want a structured, repeatable way to assess online reputation risk across multiple properties in a pipeline Property managers and operators who want to understand recurring complaints and identify specific areas for improvement In short: if you already have a property name and address, this task gives you a structured review analysis organized by what matters for that property type. Why It Matters Online reviews are the unfiltered voice of the people who actually use a property. Tenants complaining about maintenance response times, guests flagging parking issues, customers praising a location’s convenience: these patterns tell you things that a rent roll and a T-12 never will. You already know this. Every experienced CRE professional has Googled a property before a site visit. The problem is that a quick glance at a star rating doesn’t give you anything actionable, and a thorough review analysis across multiple platforms takes time you don’t have. So the review research gets reduced to “looks fine” or “a few complaints,” and the deal team moves forward without a structured picture of what the market actually thinks. That’s how reputation risks slip through diligence and operational opportunities get missed. This task compresses 20 minutes of manual review research into 10 minutes, and the output is organized by property-type-specific categories with sentiment scoring, theme identification, and real estate implications. You don’t just see what people are saying; you see what it means for the deal. That’s the multiplier. What the Output Looks Like The review analysis generat