We’ve heard from many multifamily operators that they are experimenting with various forms of centralized operating models, moving responsibilities away from onsite teams and consolidating them within specialized offsite teams to improve operating efficiency and reduce costs without sacrificing resident experience. While this shift in operating model has worked for some, this new way of working presents new operational challenges to overcome. One primary challenge lies in the sheer volume of communications that centralized teams have to handle. This is where automation and artificial intelligence come in.
Jacob Kosior, VP of Client Services at EliseAI, has extensive experience building out centralized teams at organizations like BH Management and The Cardinal Group Companies. He recently hosted a webinar called “Automation for Centralized Support” where he discussed how automation enables centralized support teams to handle high message volume, how successful centralized teams are using AI, and the measurable benefits deploying AI can have. Let’s dive into key takeaways from that session.
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Understanding Centralization and Automation
Centralization is the process of shifting operational tasks from generalist onsite teams to specialized offsite teams. Traditionally, these responsibilities were handled at the property level, requiring leasing staff and property managers to divide their attention between helping residents, replying to leads and scheduling tours, and collecting rent, amongst other ad-hoc tasks. With centralization, operators create specialized teams that manage these functions remotely, enabling a more efficient and streamlined workflow and reducing the need for onsite team members like assistant community managers or temporary leasing agents. The ultimate goal of centralization is to improve operational efficiency and lower costs while maintaining a high level of service quality. Fundamentally, centralization enables management companies to optimize staffing ratios, scale their operations across multiple properties, and create a more consistent level of service.
Automation is a key component of efficiently implementing a centralized model. AI and automation technology streamlines or eliminates repetitive manual tasks that would otherwise eat up your centralized team’s entire day, allowing them to focus on more complex tasks rather than answering questions like “what is the parking situation like at your community?” twenty times a day. AI-powered automation reduces operational inefficiencies like inconsistent staffing, drives faster response times, and provides consistency in messaging that ensures a stable resident and prospect experience. AI can handle resident inquiries, prospect follow-ups, and send out rent collection messages, allowing centralized teams to focus on high-value, complex tasks.
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Rethinking the Scope of Centralized Support with Automation
Automation enables centralized support teams to manage more communities by reducing their manual workload. With AI taking on 90% of repetitive tasks, centralized teams can support more properties without experiencing the same level of burnout that traditional onsite teams often face. One great example of this is rent collection.
In general, rent collection is a time-consuming process for property managers, requiring consistent and thoughtful communication with delinquent residents. A centralized assistant community manager (ACM) handling rent collection across five communities with 1,250 total units might face 250 resident inquiries each month regarding charges, payment plans, or late fees. When AI automates responses to 90% of these conversations, the number of human-managed interactions drops to just 50, allowing the centralized team member to oversee double the number of properties while reducing their manual workload. By leveraging AI in rent collection, companies ensure that they’re consistent in their communications, reducing the risk of human error that could upset a resident or raise compliance issues.
Key Use Cases for AI in Centralized Support
There’s a few primary use cases for AI and automation in centralized services that we’ve seen operators have success with.
Lead Management & Prospect Follow-Ups
Timely follow-ups are crucial for converting leads into leases, yet EliseAI data shows that 60% of calls to leasing offices go unanswered. AI ensures that every lead receives an immediate response, following up according to predefined cadence. This eliminates lead neglect and ensures prospects are followed-up with when their buying interest is at its highest. By automating the lead nurturing, centralized leasing teams can focus on high-value interactions, such as personalized tours and closing leases, rather than repetitive follow-ups. AI’s ability to instantly respond to leads improves conversion rates and shortens the lead-to-lease timeline, as well as allows marketers to optimize their budgeting knowing that no lead goes unanswered.
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Delinquency and Rent Collection
AI plays a critical role in rent collection by automating payment reminders, answering resident questions, and following up with delinquent residents. Instead of relying on your ACMs to do manual follow-ups, which can be inconsistent and time-consuming, AI ensures that residents receive timely and customized payment reminders automatically. AI-powered delinquency management increases the speed and effectiveness of collections, reducing the need for extensive human intervention and also injecting consistency into potentially challenging conversations. Additionally, AI can customize messaging based on a resident’s payment history, ensuring a more personalized approach to financial communications that takes into consideration a resident’s likeness to pay.
Proactive Resident Communication
AI helps centralized teams proactively engage with residents by anticipating resident needs and reaching out before issues escalate. AI can check in with residents regarding maintenance needs, provide updates on community events, and conduct surveys to gauge resident satisfaction. For example, AI can automatically follow up on closed work orders, confirming the task was actually completed and asking for a Google review if the task was done properly. By automating these touchpoints, property management companies enhance the resident experience while also taking tedious work off the plates of their centralized teams.
Measuring the Impact of AI and Automation on Your Centralized Teams
Effectively implementing AI and automation technology means tracking and measuring the right KPIs to get a holistic view of the impact of the new tech on your operations. Here are a few areas Jacob recommended measuring in order to understand the impact of AI across your portfolio.
Efficiency & Productivity Metrics
Companies implementing AI in centralized services should track key efficiency metrics to assess automation’s impact. Important KPIs include AI response time compared to human response time and the number of tasks automated per team member. Measuring these metrics allows property management companies to optimize AI’s role in their workflows and ensure a balance between automation and human interaction.
Lead & Leasing Performance Metrics
AI-driven automation significantly impacts lead-to-lease conversion rates by ensuring timely follow-ups. Companies should track the impact of AI on their conversion rates, the number of touchpoints required to move a lead through the funnel, and the impact of automation on leasing speed. AI also eliminates lead neglect, ensuring that all inquiries receive prompt responses, maximizing the return on marketing investments.
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Resident Experience & Satisfaction Metrics
To assess automation’s effect on customer experience, companies should track resident reply rates, NPS scores, and work order resolution times. AI ensures that residents receive immediate answers to inquiries, reducing frustration and improving overall satisfaction. Additionally, automation allows teams to proactively engage residents, leading to higher retention rates and improved community sentiment.
Cost Savings & Scalability Metrics
Automation enables centralized teams to manage more units without increasing headcount. Companies should measure payroll reductions and cost savings per unit to find the financial ROI on AI tools. Metrics such as the number of units managed per centralized team member and the total cost savings achieved through AI-driven automation highlight the financial benefits of centralization.
The Win-Win-Win of AI-Driven Centralized Support
The benefits of centralized support with support from AI and automation can be felt by all involved stakeholders, from residents to team members to the PMC’s bottom line. For residents, centralized teams supported by AI provide faster, more consistent responses, improving their overall experience. For centralized team members, automation reduces their workload, allowing them to focus on high-value tasks and developing their own careers. For operators, AI-driven centralization results in cost savings through more efficient staffing practices, happier residents, and faster average work order completion times. Fee managers and owner/operators that strategically implement AI to enable a centralized support model will not only improve their bottom line, but also deliver better experiences for both residents and prospects.
Interested in enabling your centralized teams with AI and automation technology? Get in touch with us to learn more about how 450+ operators are using EliseAI’s full suite of AI and automation solutions to deliver better results at their communities.