You just toured a retail pad site, and the broker’s pitch sounded right: strong traffic counts, growing population, national tenants nearby. Now you need to know whether the retail demand actually supports the story. County-level establishment data, employment figures, revenue per capita, category mix, supply and demand gaps: the full picture. The data exists. Census Bureau, BLS, third-party aggregators. But pulling it together into a coherent briefing means bouncing between four or five sources, normalizing formats, and building your own tables before you can even start interpreting the numbers. That is 15 minutes per property on a good day, longer if the county data is messy. So the retail analysis gets simplified, gets delayed, or gets skipped entirely. That’s exactly what this task is built to fix. research 5 min Retail Spending Analysis + Report Generates a county-level retail market briefing for a subject property. Pulls retail establishment, employment, payroll, revenue, category mix, and composite scores from the CRE Agents Retail Spending Data API and delivers a structured analysis in chat alongside an interactive dashboard link. Who It’s For CRE professionals evaluating retail demand, trade area strength, or category mix for a subject property. What You Get Back A structured retail market briefing with composite scores, key metrics, category mix, and an interactive dashboard link. Why It Matters Replaces 15 minutes of manual data pulling across census, BLS, and third-party sources with a 5-minute task that delivers a complete retail demand picture. Task Inputs Property Address Required Property address for the subject property including street number, street name, city, state, and zip code (e.g., 3200 NW 79th St Miami FL 33147). Skills Used CRE Agents Retail Spending Data Methodology Word Document Style Guide Tools Used Generate Retail Spending Data and Insights What This Task Does You give the task one input: a property address. Street number, street name, city, state, and zip code. That is the entire setup. From there, the Market Research Associate AI Coworker calls the CRE Agents Retail Spending Data API, pulls county-level retail data (establishments, employment, payroll, revenue, category mix), calculates six composite scores (Supply/Demand Gap, Diversity, Resilience, Gravity, Momentum, and Maturity), and writes a structured briefing directly in chat. The output includes a Top 5 Findings table, a Retail Market Profile narrative, a Key Metrics reference table, a Retail Category Mix breakdown, a Trade Area Snapshot, and a link to an interactive dashboard for deeper exploration. The whole process takes roughly 5 minutes of your time. The AI does the rest. Who This Task Is For Anyone evaluating a retail location needs to understand the demand environment before making a call. This task eliminates the data assembly so you can focus on what the numbers actually mean. This task is built for: Acquisitions analysts who need a retail demand snapshot before underwriting a retail or mixed-use asset Retail brokers and leasing teams who want to quantify trade area strength for tenant presentations or listing packages Asset managers who need to benchmark a property’s retail environment against national percentiles for investor reporting Developers and site selectors who are screening multiple locations and need a consistent, data-driven comparison across markets In short: if you already have a property address, this task gives you a complete retail demand briefing. Why It Matters Retail underwriting starts with the market, and the market starts with data: how many establishments are operating, what categories dominate, whether demand is being met or leaking to neighboring counties, and whether the trend line is moving in the right direction. Without that picture, you are relying on the broker’s narrative and your gut. You already know this. Every CRE professional who has evaluated a retail location knows the data matters. The problem is not awareness. It is bandwidth. Pulling county-level retail data from Census, BLS, and third-party sources, then normalizing it, calculating ratios, and formatting a briefing takes 15 minutes per property on a clean day. When you are screening five sites in a week, that research competes with everything else on your plate, and the retail analysis is usually what gets cut short. Without this task, the briefing either takes 15 minutes or it does not get done to the depth it deserves. With it, you get a structured retail market analysis in about 5 minutes: composite scores with national percentile rankings, a category mix breakdown, revenue and employment metrics, and a trade area snapshot. All from a single property address. That’s the multiplier. What the Output Looks Like The retail market briefing generated by this task includes: A Top 5 Findings table identifying the most significant data points with implications for each A Retail Market