The high-level objectives in the multifamily industry are relatively straightforward—to cultivate an enjoyable prospect and resident experience while ensuring that on-site teams are equipped with the tools and guidance to be as efficient as possible.
The path operators choose to meet those ambitions can vary significantly, but it often means investments in new technology. The tech itself, though, won’t magically make a difference. It also takes robust and thorough training to prime these proptech solutions for success.
Perhaps most prominent, operators should not forget that the entire objective of tech is to make things easier, not harder. Tech is designed to create efficiencies and enable associates to work more productively. If it takes prospects or property teams twice as long to complete a task, the tech isn’t working—even if it seems hip and can be described with a series of buzzwords.
Currently, AI and machine learning are among the most commonly used technologies to streamline leasing and resident processes. While these can offer immense benefits and efficiencies when properly implemented, operators should remain mindful to adopt these advancements under the backdrop of a proper foundation—and that foundation does not always equate to more technology. It also involves a tactical strategy to train associates on any new adoptions and instituting a realistic timeline for implementation.
Associates can sometimes be intimidated and even threatened by new technologies, especially those that are reshaping their workflows. Address this by communicating clearly and directly with associates about the purpose of new solutions and detailing specifically how these technologies will improve their efficiency and enable them to provide improved customer service. In addition, collect employee feedback early and often when testing and implementing new technologies—and make sure that feedback is taken seriously and incorporated when appropriate.
With that in mind, here are a few of the innovations that are most effectively making a positive impact in the multifamily world:
Advanced Chatbot Experience
The industry has been utilizing chatbots to answer a prospect’s introductory questions for several years now. The early iterations, however, were not nearly as robust as they are today. Due to their natural language processing abilities, chatbots get smarter with each interaction. The early models could recognize some basic keywords and relay a fair share of rudimentary information about a community, but now they can handle a much wider variety of inquiries. This helps prospects learn as much as they can about a community before talking to an associate, and helps on-site teams by teeing them up with prospects who are already educated about the community.
As an example of the evolving capabilities of chatbots, let’s say a prospect asks: “Do you have cardio machines?” In the past, the chatbot wouldn’t have been able to effectively respond. Now, advanced chatbots can respond to that question with: “Here are our fitness center features” and by offering a list. If a prospect inquires: “Can I smoke weed at your property”—yes, this question comes up—the chatbot can respond with “Here is the smoking policy at our community” and by listing it.
Evolved Applicant Screening
The application and screening processes notoriously can be the most time-consuming portions of the lease application process. Traditional background checks can take several days, often leaving prospects unsure whether they qualify to live at an apartment community. The industry has made headway in recent years to expedite many components of this process, including quicker ways to track rental payment history, bank account information, and other crucial qualifying components.
As with the chatbots, these processes are now refined on the fly. Machine learning algorithms can recognize certain behavior patterns within an application that indicate whether there might be cause for concern. Likewise, this concept can be applied to payment information. Essentially, property teams get a head start in determining whether a potential resident qualifies.
The more behavior patterns it analyzes, the more adept machine learning becomes at predicting certain outcomes. Just as important, these systems are designed to be nondiscriminatory with no factored bias related to ethnicity, gender, age, or any other preexisting characteristic.
Innovative Risk Score Models
In addition to examining behavior patterns for potential red flags, AI can analyze rental applications and determine a numerical risk score based on the cumulative information available. These risk score data points are more thorough and comprehensive than ever before and factor in payment history of all credit lines, income, debt collections, previous and desired lease terms, inquiry counts, and credit score.
Granted, not every market is the same. The most intuitive of these risk score models enable property teams to adjust acceptance criteria to meet property or portfolio needs. They do so by comparing their customer behavior with market-level data, which enables operators to adjust qualifying thresholds accordingly. These customizable optimized settings can help operators better select good renters and mitigate losses from skips and evictions.
As with the concepts above—and virtually anything in the AI and machine learning space—the models become stronger with use and more refined based upon the totality of analyzed data.
As AI becomes a staple of the modern world, residents, prospects, and associates are getting more comfortable and exhibiting more trust in using it. The multifamily industry, however, is only scratching the surface on the potential capabilities. The primary consideration when implementing any new innovations is to remember that the tech is designed to provide efficiencies and enable teams to evolve. If it doesn’t accomplish those objectives, it’s probably not worth adopting.
At its worst, tech can yield feelings of isolation. That’s the wrong type of tech for a people-centric industry. At its best, tech can provide a connected resident experience, streamline the prospect journey, increase the happiness and productivity of on-site teams, and pave the way for the human connection that still means so much to many prospects and residents.
