Sherlock Holmes once said, “It is my business to know what other people don’t.”
Real estate agents can certainly attest to this as they are inundated with requests from prospective home buyers and sellers for information. This information is a real estate agent’s most valuable asset, but what does this mean for the consumer?
It means we have to wait 5 hours for a response with no real context…
Bots Are Better People
Bots are built by context and what consumers want is a simple, informative response in a timely manner. They don’t want to have to give up their valuable time or information to wait around for you to call/text them, or worse, make them join a drip campaign.
Real estate is a personable business and chatbots are software built for conversation. These artificially intelligent conversational interfaces live inside the messaging apps you use every day and they respond right away, unlike their human counterpart.
At their core, bots are powered by some serious machine learning that agents, brokers and consumers will never have to see. This is the real beauty in bots, where all your technology can be leveraged through a simple conversation.
To start building a bot, you send it to either one of two schools – Rules or Machine Learning. There’s a bad cold start problem when building bots, because even to build one with medium complexity takes a hefty training dataset of conversations.
To make sure Holmes graduates, we put it through both schools. It started at Rules School using manually crafted conversations like the one Drew wrote. Behind the scenes the engine is looking at the text corpus, which is just a bunch of structured text, in order to find context.
Bots Structure Unstructured Data
Holmes found that the context of this conversation was about a school, a listing, and a showing time. This context was derived from N-gram models using the text corpus.
Bots Get To Know You
Bots are great companions. In fact, I talk to multiple bots everyday. The CNN bot knows what news I like, the Weather Channel bot knows where I live and the H&M bot knows my style of clothing.
Holmes also knows the properties you will like and that’s thanks to his best friend, a graph database. This database helps Holmes take the structured data it made from conversation and structure it for models that predict home buying behavior and interests.
Graph databases open up an almost infinite amount of doors for Holmes.
Bots Open Doors
Consumers are always knocking on your door, requesting information of all kinds. Bots open up your technology to all your clients at all times.
For example, our predictive days on market statistical model predicts how long a property in Arizona will be on the market for. A potential home seller could simply converse with Holmes to get an estimate on how long their property would be on the market.
Bots live where context and convenience matter most, which is what leads to conversion. By interfacing with the technology already used by consumers, brokers, agents, lenders, and builders, bots can build real relationships, in house.
With Holmes, it’s never a matter of moving to get what you need, it’s a matter of where you want to move to.
Bots Are In Beta
Questions arise in conversations and conversations live in the messaging apps we use daily. The future of bots will allow us to bypass apps and search engines all together and instead, make purchases or find valuable information with a simple text.
However, to get to an “appless” world takes bots much smarter than we see today. This technology is very raw still. To integrate bots into these platforms takes more red-tape than development and documentation is very scarce. So be leery when building, bots are in beta.
Consumers have access to unimaginable capabilities with bots and all with a simple text message.