The real estate industry has been expanding the implementation of automation and artificial intelligence for some time, but it’s been heavily focused on back-end processes that improve the experiences of internal processes. Here’s how the industry has been using automation over the years and some things to consider before implementing solutions like chatbots.
Applications of Automation and AI in Real Estate
How many emails do you send every day? How many of them contain about the same instructions or information related to a closing with only a few specific details changed? How many of the same types of questions do you answer for clients?
Implementing technology into your customer service is one of the ways to make your title company more efficient.
With the help of Robotic Process Automation (RPA) technology, much of the repetitive tasks that zap a professional’s time can be quickly processed by a bot.
Rules-based automation has been around for decades, and here are some of the ways that real estate and title professionals have been using it:
- Real Estate CRMs that fetch leads from various sources and score the sources delivering the highest quality leads to help real estate agents decide where to invest their marketing dollars.
- Automated emails triggered by actions of potential customers on your website or based on criteria of your leads to help them find the right home faster. For title agents, implementing automated emails at key points in title production improves the efficiency of processors and closers.
- Workflow management in title production software helps jump-start a file and cut down on mistakes.
- Software task tracking also reduces time by limiting rekeying information and transferring data from one application to another.
- Title searches and examination processes have become faster.
After automation comes artificial intelligence to improve the process. Machine learning is a subset of AI that allows machines to learn from data without being programmed. In the same way that humans learn a new technique and synthesize better ways of doing things based on their learning progress, bots that previously carried out repetitive and simple tasks can be taught to do more.
Three significant ways that artificial intelligence is being implemented in the insurance industry include setting pricing at individual levels based on risk, underwriting and analyzing data, and handling claims.
Are chatbots Automation or Artificial Intelligence?
It depends. Some chatbots may use predefined conversation paths, while others may employ smarter Natural Language Processing and other AI technologies. If the bot follows set guidelines, it’s a form of automation, but if it has machine learning capabilities, it’s AI.
To get a clearer picture of how chatbots differ from RPA bots (automation), it’s important to compare some of the key characteristics of each:
Rules-based Automation robots are:
- Used in routine, repeatable, or predictable internal processes
- Based primarily on automating existing internal processes
- Focused on eliminating or reducing manual input
- Directed by structured instructions and not human inputs or chat
- Optimized to reduce friction caused by human intervention
- Occupied by back-office processes related to finance, operations, HR, and supply chain distribution
- Less flexible to new data or changes in processes
- Typically implemented by IT teams with input from operations leaders
- Applied to a process or journey initiated by message (text, chat, email, web, etc) or via voice
- Primarily based on transformation (understanding and converting requests into actions) rather than strictly automation
- Optimized to simulate human interactions and understand user intent to perform an automated task
- Dictated by less structured free form or guided conversations
- Focused on decreasing friction by limiting human intervention
- More relevant to the front-end or customer-facing processes like customer service, sales, and marketing
- More versatile and capable of adapting to changes and increasing knowledge from data and experience
- Usually implemented by business with input from IT
Engaging customers with chatbots and better AI
Some high-powered chatbots, like Alanna, integrate with title production software to provide a better customer service experience. Title agents can increase their productivity and customer satisfaction by delivering up-to-date information to real estate agents, lenders, buyers, and sellers in a closing.
Other chatbots can help manage leads attracted to your website but may not be as easily integrated into your main software used in everyday operations. At the very least, they can answer commonly asked questions quickly without disrupting your team with a phone call, but without deeper machine learning, the bot may cause more frustration than help. Each solution will have different capabilities and limitations to review carefully.
Should you use a chatbot?
If you’re considering upgrading some of your back-end or customer-facing processes to include bots be sure to make it count for your business and your customers.
A venture capital firm, MMC, conducted a survey of European startups classified as AI companies to find that they “don’t actually use artificial intelligence in a way that is material to their business.” While it’s uncertain what percentage of those companies were intentionally misleading their customers, a company that you think uses AI may not.
Chatbots are one of the most common ways a company deploys artificial intelligence and machine learning, but many people question the benefits of bots in a customer service context.
A survey conducted by Userlike asked people what they thought of chatbots, and the responses are important to consider before adding one to your business website.
Most respondents (60%) said they would prefer to wait in line to speak to a real person, but if given the option, more than half were willing to talk to a chatbot initially with the expectation that they’ll be transferred to an agent.
While a majority of respondents like the fast response time of a chatbot and trust one to help solve simple issues, most customers don’t follow the ideal conversation flow, resulting in frustration when the bot can’t solve or understand a more complex problem.
So, if you do decide to implement an automation tool like a chatbot, be sure that a human isn’t too far away to help.