Most of the small local news publishers our team at United Robots talk to in the US battle one common problem. Their newsrooms do not have the resources to produce all the unique local content their readers expect. The two topics that most often come up as underreported are high school sports and real estate. Here, we're going to focus on the latter, and explain how content automation can help underresourced local newsrooms get a thriving real estate section off the ground.
January 2025. Buying and selling a home is the biggest financial decision in most people’s lives, and reliable information and analysis of the local real estate market is an important factor in that decision. Local news publishers who establish themselves as providers of trustworthy and regular real estate coverage have a lot to gain. The key is to be able to publish information about the market on a really local level – the stories closest to home, literally in the case of real estate, are the most valuable and relevant to local readers.
From data to articles. So what part can content automation play in this? Thanks to the existence of high quality, reliable and regular data on house sales, quite a significant one. The text robots we, and providers like us, have built, use structured data as the “raw material” for editorial texts, which are generated using NLG (Natural Language Generation) and rules based AI. This is not generative AI. Rather: word, clause and sentence alternatives are written by humans (our team in our case), and data points (address, price, property size etc) are inserted – generating thousands of combinations of sentences to create unique, factual articles. The robot also performs data analysis, meaning the texts include comparisons over time, across neighbourhoods, counties and so on. We also add an image from Google Streetview to the content package. For some publishers we include a weekly list of All Sales destined for their print product.
A turnkey real estate section. In addition to the short articles about individual house sales, we produce a number of different top lists for any given geography. These include Most Expensive, Most Affordable, What X dollars will get you in Area Y, Best Deals (based on defined price range and home type) and more. We have publisher partners who use the automated content to significantly bulk up their real estate sections – some even use the automated lists and articles to set up such a section from scratch.
Above: examples of an automated article lists published by the Press Democrat in California covering price trends over time.
Once the section is in place, the key is to make sure local readers can find the content. The publishers who are most successful in driving engagement have Real Estate included in the top menu and promote the content elsewhere on the home page. We’ve also seen an uptick of between 100–150% in pageviews when publishers cross link between the top lists and the longer texts about individual sales.
Creating value for you and your readers. By publishing content and analysis about the local real estate market specifically, local news publishers have an opportunity to really add value to their publication – creating a reason for readers to come back and check in with the regularly updated content. We know this type of content drives traffic, engagement and even subscription sales for clients in the US as well as Scandinavia.
And of course, content that is popular with readers is popular with advertisers and sponsors. For real estate specifically, there are obvious opportunities for premium advertising and sponsorships given the context. We have small US publisher partners who drive significant revenue through sponsorships of a package of all real estate content online, in print and in topical newsletters.
By publishing automated real estate content, publishers expand their local coverage and service to readers without impacting newsroom resources. With the added revenue opportunities, this popular local content can also directly support the mission of local journalism.Abo