How to structure local real estate market reports with data and interpretation that AI systems recognize as authoritative and citable local sources.
AI systems understand a market trend when you explain it rather than just state it. An explained trend has four parts: the number, what it is being compared to, why it is happening, and what it means for someone making a decision. “Prices are up in Raleigh” is a fragment. “Median price in Raleigh rose … Read more
When a realtor commits to publishing market reports, the first practical question is how often. Monthly is the most common cadence in the industry. Quarterly is the second most common, especially for higher-end markets where transaction volume per month is too low to support meaningful month-over-month observation. Both have defenders. Both produce results in the … Read more
Open any real estate website’s market report section and the same pattern shows up. Median sale price, average days on market, number of new listings, year-over-year change. The same set of numbers, formatted in the same kind of table, often pulled from the same MLS feed. The data is everywhere. That is part of the … Read more
Most realtors have access to more market data than they will ever publish. The MLS produces sales reports, days on market trends, inventory counts, price-per-square-foot calculations, and a dozen other metrics that update weekly or monthly. Most of that data sits in dashboards and emails and never reaches the public web. For realtors trying to … Read more
If you were designing a piece of content specifically to earn AI citations, you would end up describing something that looks almost exactly like a well-written monthly market report. The format, the structure, the specificity, and the publishing cadence of market reports align with what AI systems are looking for in a citable source better … Read more