Real Results and the Future of Leasing with ELI+ from Entrata

Entrata’s Sage Kralik and Nufar Kalay hosted Shani Nowlin of Westland and Nick Cenatiempo of Campbell Communities to discuss how operators are implementing and scaling this technology across their portfolios. The discussion focused on the real results, implementation strategies, and the evolving role of AI as a powerful tool, not a replacement, for leasing agents.

Overcoming Leasing Challenges with AI

Before implementing ELI+, both Westland and Campbell faced significant hurdles. Campbell Communities lacked a formal process to manage leads, resulting in dropped leads and only strong prospects being nurtured. Meanwhile, Westland’s biggest challenge was liability lawsuits stemming from human error and inconsistencies across numerous agents and properties, making consistent, compliant communication nearly impossible.

The core motivation for adopting AI was to resolve these issues by offloading repetitive tasks, providing consistent, Fair Housing compliant answers, and allowing human agents to focus on high-value interactions and relationship building.

Real-World Impact and Results

Campbell Communities shared compelling metrics demonstrating the immediate impact of adopting ELI+. In roughly half the time they spent using a prior AI partner, they achieved a comparable volume of tour leads and are on pace to double their overall conversion rate. Crucially, the rate of neglected leads dropped from 5% to under 1%, meaning every prospect is now being nurtured 24/7. These results remained strong even while Campbell repositioned several properties from lower-to-medium to competitive market rent.

Operational and Unexpected Benefits:

• Workload Reduction: Leasing agents were freed up to focus on reporting, resident events, and professional growth. This was vital for Campbell's lean staffing model.

• Business Continuity: Campbell was able to maintain leasing velocity and avoid long-term vacancy loss even during periods of staff turnover (e.g., when a property manager and leasing agent position were open simultaneously).

• Required Optimization: The massive increase in tour velocity forced Campbell to reconfigure tour slots and adjust office hours to ensure the human experience matched the efficiency of the AI.

• Empathy and Consistency: Nowlin noted the compassion and humanized empathy of the AI in renewal conversations, providing a level of consistent, supportive communication that would be rare across a large human team.

Implementation and Scaling Strategies

Rollout strategies varied between the operators: Campbell ripped the band-aid off, implementing AI all at once to gain immediate, high-quality data and quickly secured agent buy-in. Westland used a phased pilot across two regions, intentionally choosing properties that represented the full range of technical aptitude (most tech-savvy to least tech-savvy) to gather comprehensive feedback and discover necessary process changes.

Crucially, internal buy-in was achieved by positioning the AI as a tool to help agents succeed and hit metrics, not as a replacement for their jobs. Training was minimal because the system is designed to be largely self-sufficient.

Ongoing Optimization and the Future Roadmap

Success relies on optimizing the AI by ensuring a robust, clean database. Cenatiempo emphasized that the more detailed the property policies (pets, parking, etc.) in the core system, the better the AI performs. Since Eli+ is embedded within the operating system, data updates are seamless and instantaneous, avoiding the data integrity issues common with third-party integrations.

Upcoming Product Enhancements (Releasing October 7th and Beyond):

1. Cross-Channel Memory: AI will now have the ability to ‘remember’ conversations across four channels (chat, SMS, voice, and email) seamlessly, continuing the dialogue and retaining preferences regardless of how the prospect switches communication methods.

2. Post-Tour Nurturing & Application Walkthrough: AI agents already proactively follow up after tours. The next step is a deep Application Walkthrough feature, where the agent will guide prospects through application steps, answer specific questions, and eventually revolutionize the application itself by gathering information via natural language processing instead of requiring a form fill.

3. Centralized Settings: The configuration settings for all Leasing AI, Payments AI, Maintenance AI, and Renewals AI will be centralized, giving users full control to update policies and datasets for AI instantly.