CMLS 2015 was two days chock full of content. Rather than try to provide some kind of comprehensive summary, I’m going to focus this blog post on three sessions that laid out some great big ideas but didn’t completely “connect the dots” for the audience. I’m going to fill in the gaps by providing a variety of ways in which some of the presenters’ ideas can be applied by MLSs and their various vendors on behalf of subscribers.
Michael Rogers: “The Practical Futurist.”
Mr. Rogers describes how in the future we will group documents into two categories: “connected documents” and “fossils.” In the future, being connected to the Internet will be the default and our children will need to be taught to go offline. By “connected documents” he means those that are connected to the Internet and are always changing, with alerts to call our attention to important changes. We might today consider those documents today to be web applications, but I won’t quibble; I like where he is going because I think it encourages us to look at our industry’s current “fossil” documents and ask if some of them could be more dynamic, connected documents. Connecting the dots, consider the CMA. Today, most applications generate a static document that, once presented to the seller and used to facilitate a discussion of listing price, is archived and eventually forgotten. Perhaps in the world Mr. Rogers describes, that document continues to evolve as new competitive listings come on the market, go into a pending-sale status, or are sold with sales prices reported. Perhaps the CMA auto-updates with these listings, and informs the agent of potential changes; the agent must “okay” new listings as valid comps. And perhaps once those changes sufficiently affect the pricing recommendation, the CMA alerts the seller. This kind of CMA could provide a good reason for the agent and their client to communicate more during the sales process, resulting in pricing changes driven by the new nature of the CMA rather than by the agent or their client.
Chad Curry, “The Internet of Things.”
Curry describes a world full of sensors – temperature, humidity, noise, and more. These sensors can potentially know where we are at any given time. He describes how “beacons” can be deployed in a building interior, and how our smartphones and wearables can be used to connect to those beacons. Our mobile devices can then provide us additional information and context depending on our location, as reported by the beacons. Connecting the dots further: imagine if, in the future, agents can provide sellers a map showing the path of buyers inside a house during showings and open houses. Imagine being able to show a seller that only 15% of visitors went upstairs and no one went down to the basement – that could start a good conversation, right? Mr. Curry also describes how, in the near future, there might be noise sensors all over a town or city. To connect the dots, imagine we can then have a “heat map” (like a weather map with color coding) of how noisy areas of the city are, built into the MLS and our other property searches. Perhaps visiting a listing on a Sunday, the consumer doesn’t realize how noisy nearby Monday deliveries are or how noisy the more frequent airplane landings can be. Using big data, agents can then help consumers avoid a noisy area – or an occasionally noisy street. These are just a two of many ways in which the “Internet of Things” could be of great use in the future and add new information capabilities for real estate agents.
Patrick Schwerdtfeger, “Big Data Visionary.”
Mr. Schwerdtfeger presents a case, using examples from other industries, about how we can mine our existing data – or analyze it alongside other data sources – in order to come up with insights. He uses the classic example of how Target knew how a particular young lady was pregnant, and sent her advertisements and coupons for baby-related purchases, by analyzing the purchase habits of women they knew had given birth and finding that when women changed their buying habits to start buying vitamins and unscented soaps, that was a good indicator that there was likely a pregnancy. To connect the dots, consider what insights we might be able to provide agents if we analyzed purchase data from stores such as Lowe’s and Home Depot, even just segmented by zip code. We might have a better idea what projects are common in a neighborhood, how the homes were being maintained, and how common it is for certain upgrades to be made. This could help agents better compare a potential listing to other listings in the area. The possibilities for analyzing data from all sorts of sources to provide insights to agents is limitless. Big Data is an area that NAR is already exploring, but it’s also an area where MLSs and software providers can collaborate and create new value.
I hope this post helps stimulate conversation about how some of the big ideas presented at CMLS 2015 can be further applied for the benefit of agents. I look forward to seeing my MLS friends at RESO, NAR, and Clareity events in the next few months!
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