Recommendations combines your preferences and successes with artificial intelligence, predictive analytics and machine learning.
We’ve all heard the buzz about artificial intelligence (AI) and machine-displayed intelligence that simulates human behavior – but the apps that seem to be getting the most attention are focused on lifestyle assistance (customer support and chatbots, for example) and not business growth.
Despite the recent hype, it’s important to keep in mind that AI is not new. In fact, our company has been using AI for years for such tasks as cloud optimization to manage our server bandwidth, which helps us to keep our costs – and subscription prices – low. We also use it to scan for potential hackers to ensure our network remains reliable and secure.
But our primary use case for AI is process automation to help our subscribers get more listing appointments while spending less time and money. Our AI tools ultimately help our customers grow their businesses.
Our recently released Recommendations service relies heavily on process automation to identify homeowners who are likely to sell their homes. Using machine learning and predictive analytics, we determine homeowners who are most “likely to connect” and then “likely to turn into a lead.” We then combine those two new algorithms with our existing “likely to list” to automatically create a personalized prospecting/marketing list. Over time, Recommendations is fine-tuned based on your success winning listings with different types of owners and homes, as well as areas and statuses.
Currently, Recommendations is available to any customer who subscribes to Premium Neighborhood and at least two other lead services. Every list contains up to 100 leads that are scored, and each lead includes a brief explanation for the score. Most importantly, the technology learns your preferences, tracks your successes, and becomes more personalized – and beneficial – over time.
Scoring 101
- Sales Score: This logarithm has several years of proven science behind it. On average, the “likely to list” analytics provide a minimum of 28% lift over a nine-month time frame. Properties scored at the highest have a 72% chance of listing in nine months.
- Lead Score: This logarithm predicts the likelihood this contact will turn into a lead.
- Contact Score: This logarithm predicts the likelihood this contact will answer their phone.
To build the scoring models we’ve added some additional Neighborhood filters, including:
- High Equity
- Empty Nester
- Free and Clear
- Mover Upper
We also developed advanced financial filters that are available in the Neighborhood service:
- Mortgage Term
- Refinanced Amount
- Loan to Value
- Estimated Net Worth
- Type of Loan
Our goal is simple: We want to help you find additional listings in less time and for less money. Whether you are a new agent or a seasoned pro, we want to help minimize the pressure of competing with other agents to find new leads and make it easy to identify potential listings that you might have otherwise overlooked. With Recommendations’ AI process automation tools, we quickly deliver you a high-quality lead list that helps you be more efficient – and successful!
Steve Cortez is a seasoned real estate professional with decades of experience and owner of ArchAgent. ArchAgent brings together the tools and resources the country’s top real estate agents rely on in a single package for a low cost.