You know the drill. Before a pitch, IC memo, or lease up push, someone asks, "What’s the internet saying about this place?" You open ten tabs, skim reviews, check the website, and try to triangulate against a few comps. It eats time and still feels thin. You get anecdotes instead of a read. This task turns that sprawl into a scored view with context and a short list of risks and opportunities you can act on. Marketing ~5 min to run Audit Online Presence and Reviews Vic prompt Use Vic to audit online presence and reviews for a property with competitive context. Purpose Reveals reputation gaps and competitive positioning that affect leasing velocity and value. Replaces an hour of manual searching with a structured 5-minute output. Inputs Property Name Required Property Type Required Property Address Required Scope Optional Website Url Optional Output Format Optional Internal Quality Docs Optional Outputs Scored screens (1-10) with a one-sentence investment takeaway, Property Assessment and Competitive Context tables, plus a review summary with sentiment themes, mention counts, and up to three opportunities and three risks. Delivered in chat with an optional Word report. Time saved Replaces about an hour of manual searching with a structured 5 minute output. How it works You give Vic the basics: property name, type, and address. Add a website URL, internal quality docs, and pick scope. Web presence only, reviews only, or both. If you need a shareable file, ask for a Word report. Run it with a single line: Use Vic to audit online presence and reviews for a property with competitive context. Within minutes, Vic returns a tight set of outputs in chat. First are scores on a 1 to 10 scale for web presence and reputation, each with a one sentence investment take. It is quick to read and forces a call. Then come two tables. The Property Assessment table sums up the subject. The Competitive Context table sets it against two to three similar assets so you can see where it sits, not just how it looks on its own. The review section goes deeper. It groups feedback into sentiment themes by property type, counts mentions, and pulls out up to three opportunities and three risks. This is where the signal shows up. Repeated complaints about maintenance response, noise, or parking are counted and grouped, not cherry picked. Positive themes are grouped the same way, so you can see what works and whether it stands out or is just table stakes. The output is structured and consistent across deals. That matters. You can compare a Denver multifamily asset to its comps on the same scales, then run the same exercise on an industrial park or office building and keep the format. It drops into an IC memo or a broker pitch without reworking the story each time. There is a point of view built into the task. Scores come with a one sentence take because a number without a stance is not useful in a deal setting. The competitive table is there because a 7 only means something if the comps are 5s or 9s. The review deep read is capped at a short list of opportunities and risks so it stays actionable. Where this shows up in practice: acquisitions teams use it early to flag reputation gaps that could slow leasing or require CapEx. Asset managers use it to spot recurring issues and track whether fixes move the needle in reviews. Brokers use it to frame the story against nearby assets and handle objections before they come up. None of this replaces on site diligence. It does replace the hour of scattered searching that usually comes first. You get a five minute output with scores, comps, and a clear read on what tenants are saying and what that implies for value.