Making Life Easier For Renters, Time-Pressed Leasing Agents

It’s an all-too-familiar problem. Seeking an apartment, a renter spots an available unit in an online search. Eager to check it out, she requests information on a showing date. But her request appears to plummet into a black hole. Either there’s no response, or the reply — maddeningly — comes a bit too late. The apartment has just been snapped up.

There’s a reason this problem plagues the rental industry. Between providing showings, scheduling and other tasks, overburdened leasing agents frequently have more on their plates than they can handle. An estimated 40% of calls to leasing agents go unanswered because the agents are so overworked. Would-be renters turn their attention elsewhere.

Artificial intelligence developers are at work to help ensure leasing agents/property managers and most importantly renters needn’t endure this woe any longer. More on that in a few moments.

No time

Being overburdened is endemic to the profession of leasing agent, according to John Burns Consulting. In a 2018 survey, 25 percent of responding leasing agents and property managers reported their most daunting hurdle was finding sufficient time to focus on business strategy. Asked about factors inhibiting business growth, responding leasing agents cited “too many manual processes” as the second leading factor.

Survey respondents reported the biggest hurdle in managing new business inquiries is “quick turnaround responding to leads,” with nearly 43 percent citing that concern as their number one challenge in garnering new renters. Following in second place on this question was the challenge of “staff training on qualified leads and prospects.”

The fallout from inability to respond to would-be renters has been similarly quantified. It’s been learned 71% of all renters expect a response within a day or less, and a third will move on to presumably greener pastures if the response isn’t quick enough.

A potential renter’s introduction to a property management company’s level of customer service is in the leasing phase, says Elliott Burris, vice president of real estate software company AppFolio.

“The simple first step in any leasing process – an inquiry – offers the biggest area of dissatisfaction for the prospective renter, and the biggest opportunity for property managers and leasing agents. Artificial intelligence is critical in the leasing phase to enable property management professionals to deliver consistent customer service, gain potential revenue and ultimately grow their business.”

There are few property management tasks in recent years that haven’t been automated by software designed to aid managers in virtually every aspect of their lives. They include managing leases, filling vacancies, juggling maintenance requests, and automating rent collection and late fees. One software solution that had appeared to elude developers was the creation of a human-augmented digital aide for the agent.

Such a digital assistant could eliminate such repetitive tasks as answering questions, scheduling showings of available apartments or vetting prospects. When necessary, a real human could step in to provide answers beyond the digital aide’s ability.

An aide named Lisa

That’s what AppFolio recently brought to the apartment industry. Its conversational AI-enabled digital assistant Lisa can consolidate communications with prospective renters. Unlike chatbot, Lisa can engage in fully automated conversations via text, giving prospects the sense they’re communicating with an on staff pro of the human variety.

Remember that painful experience recounted at the top of this story? The power of conversational AI and Lisa can ensure a prospective renter never has to go through that ordeal. Having spotted the ideal listing, the would-be lessee can in minutes get all her questions answered and be scheduled for an apartment showing, 24-7.

As Burris says, the use of a digital assistant, “simply creates more time for humans to do what they do best.”

This post first appeared on Forbes.com. To see the original, click here.