Leveraging LLM in Multifamily Revenue Management

As the multifamily real estate industry adapts to rapid advancements in AI and residents' ever-changing needs, an effective revenue management strategy has never been more important. Large language models like ChatGPT are providing the opportunity to improve revenue management systems in ways we are just beginning to understand. In this post, I'll go into how LLMs work, some of their risks/drawbacks with respect to the real estate industry, and how they can be leveraged to boost efficiency in multifamily revenue management.

What are Large Language Models (LLMs)?

Before I talk about the impact of LLMs in revenue management, it's important to understand how they work, and some of the potential risks of using them in real estate. LLMs are trained on a broad range of text from across the internet to predict the likelihood of one sentence or phrase following another. This is a type of "unsupervised learning" because the model is not given any explicit labels or targets to learn from, but rather it learns to understand patterns, structures, and statistical regularities in the language from the data it is trained on. They don't "think" like a human does, but they can generate text that sounds very human-like based on the input, or prompts, they receive. From chatbots and content creation to more complex tasks like data interpretation and prediction, they can add substantial efficiency in the real estate industry.

LLMs do pose some challenges, however. For example, their ability to "hallucinate", or generate inaccurate or invented details, can be a major problem in the real estate sector, where precision in listing descriptions and contracts is crucial. They also have potential to amplify biases present in their training data, which may create issues from a fair housing perspective. Finally, LLMs could cause issues around data privacy and plagiarism because they generate responses based on their training data, which could contain sensitive, copyrighted, or personally identifiable information (PII). LLM providers like OpenAI are working to mitigate these risks, but they cannot be entirely eliminated - so it's important to understand this when using them.

How LLMs are Impacting Multifamily Revenue Management

There are many implications of AI for multifamily revenue management. They primarily revolve around better decision-making, improved communication, and automation of routine tasks, which can ultimately lead to increased revenues. Below are a few areas where LLMs are beginning to add efficiency in revenue management:

Facilitating Data-Driven Decisions

Effective revenue management requires the ability to make data-driven decisions. Large language models can help multifamily property managers organize and interpret large amounts of data, extracting relevant insights to inform decisions on pricing, occupancy rates, and marketing strategies. For example, these models can be used to identify patterns and trends from historical leasing data, market rates, demand trends, and customer feedback. This can help property managers forecast demand, set competitive prices, and optimize marketing campaigns, all of which directly contribute to revenue growth.

Improving Communication

LLMs can also help improve communication between property managers and residents, prospective renters, and on site teams. They are being used to develop chatbots and virtual assistants that provide real-time responses to queries, improving customer service and reducing the burden on human staff. They can also be used to understand the needs and preferences of individual tenants, leading to personalized pricing, discounts and incentives that are more likely to appeal to specific tenants based on their interests and activities.

Automating Routine Tasks

Large language models can automate many of the routine tasks involved in multifamily revenue management. Tasks like drafting lease agreements, sending payment reminders, updating listings, and compiling reports can be automated with AI, saving property managers significant time and resources. This efficiency gives managers more time focus on strategic decision-making and enhancing customer service… both crucial elements for increasing revenues.

Conclusion

LLMs are transforming multifamily revenue management by facilitating data-driven decision-making, enhancing communication, personalizing marketing efforts, and automating routine tasks. As these technologies continue to evolve, they promise to unlock even more potential for the multifamily industry. Property managers that embrace these tools stand to gain a competitive edge in an increasingly dynamic and competitive market. The AI revolution in multifamily revenue management has just begun, and the possibilities are limitless.

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HelloData uses a LLM to extract concessions from text and compute Effective Rent correctly. Check how we compute the best rent comps to learn more about it.