For decades, legacy multifamily revenue management platforms have made rent recommendations behind secret algorithms with no explanation for pricing decisions. As a result, revenue, operations, and asset teams waste time trying to reverse-engineer the recommendations and struggle to explain decisions to leadership.
Fortunately, a new form of AI called Explainable Artificial Intelligence (XAI) — or just Explainable AI — is changing how revenue teams set pricing and handle renewals, eliminating the guesswork. When paired with the right data, Explainable AI is miles ahead of traditional tools in the transparency and justifications it provides for the recommendations it makes. This guide defines Explainable AI, how it works, and how it can be used for revenue management decisions.
What is Explainable Artificial Intelligence (XAI)?
Explainable AI refers to algorithms that make their reasoning visible and understandable to users. Instead of producing an output with no context or explanation, XAI provides the reasoning behind its decision.
In multifamily revenue management, this means that every pricing recommendation comes with a clear, easy-to-understand explanation, backed by property-specific data inputs that take market conditions into account. The reasoning behind every pricing recommendation is explained in detail and can be traced back to individual data points, your pricing “drivers” for easy verification. Not only does explainable AI give you a clear, human-friendly justification for a price, it also shows the influence each driver had on the recommendation.
So, unlike traditional revenue management tools, explainable tools equip you with the understanding to justify pricing changes to leadership and make more confident decisions faster.
Why Are Traditional Revenue Management Tools a “Black Box?”
The term “black box” refers to an algorithm that produces results without revealing how it got there. These systems produce results based on proprietary calculations, but the reasoning behind their outputs is unclear to users and, at times, to the engineers who designed them.
Unfortunately, these types of revenue management systems have been the norm for the multifamily industry for years. The lack of transparency into how these tools arrive at their recommendations leaves teams confused and asking questions rather than getting actionable insights.
In the end, revenue management teams are left with less confidence in their pricing strategies when they can’t understand the reasoning behind suggestions and subsequently hinder leadership’s ability to see the big picture.
How to Tell If Your Revenue Management Tool Is a Black Box
If you’re unsure if your revenue management tool operates as a black box, here are some signs to look for:
- The tool won’t show you which variables or market signals drove pricing decisions.
- Vendors won’t detail how their models make decisions or are vague about the system’s logic.
- The system expects you to accept its recommendations with no visibility into its calculations.
- You spend more time trying to understand the outputs than using them to take action.
- You don’t understand the system’s recommendations, despite how much time you spend analyzing your own data.
The Risks of Black-Box Algorithms
The nature of black box algorithms exposes revenue management teams and subsequently their properties to a variety of risks.
When your team can’t understand the decisions it recommends, it can lead to the following:
- Eroded Trust: When you and your team can’t explain the reasoning behind your pricing strategy, it erodes trust with leadership.
- Slower Decisions: A lack of understanding of suggestions causes you to hesitate in making decisions, which can stall strategies and growth.
- Missed Opportunities: Hidden logic means you won’t spot potential errors in reasoning or potential biases the model had. Without knowing these issues, the performance of your properties could be impacted.
What Makes Explainable AI Perfect for Revenue Management Teams?
With clear and detailed answers, Explainable AI acts like a pricing analyst sitting next to you. It walks you through its reasoning, showing you the data points it used and how it arrived at its conclusions.
Because of this level of transparency, revenue management teams benefit from:
- Accountability: Every recommendation is traceable to specific data inputs and market signals, making it more accountable than black box models.
- Clarity: Teams can identify which factors influence the model and by how much. Then, teams can spot errors or biases, which helps them further refine their decisions.
- Confidence: With a complete understanding of the model’s recommendations, revenue teams are more confident in explaining the rationale to leadership. It also supports trust across departments for a stronger strategy.
- Agility: Teams can tailor their strategies to property-specific nuances like market dynamics, floor plans, amenities, and more.
- Collaboration: Visibility into the system’s decisions enables departments to align on a stronger, more refined strategy.
What to Look For in Explainable Revenue Management AI
When looking for your next revenue management tool, transparency matters as much as accuracy. Additionally, the onboarding process should be fast, with a reliable customer success team to support you throughout, and the tool should fit your budget.
Here are the qualities to look for in an explainable AI revenue management platform:
- Human-Friendly Explanations: Look for a solution that explains the logic behind its recommendations as if you were sitting next to an analyst. This way, your team can confidently justify decisions to leadership.
- Powered by Public Comp Data: Prioritize solutions that rely on verifiable, accurate public market data rather than private data aggregation that could expose your organization to legal risk.
- Reputation-Friendly: Seek out explainable AI tools that have easy overrides and transparent reasoning.
- Modern Interface: Choose a tool with an intuitive interface that is easy to use, reducing time to onboard employees and frustration when finding the right insights.
- Quality Customer Experience: Ensure the revenue management tool you choose has a robust customer support team behind it. Tools backed by communicative onboarding and customer success teams help your team get up and running quickly, without leaving you confused about how to use the system.
- Affordable: Adopt a revenue management tool that fits your budget. Unlike traditional legacy systems, the right solution provides modern, cutting-edge technology at a fair price.
FAQs
What Is an Explainable AI Example?
An AI platform that provides both a pricing recommendation and a clear summary of the data and the logic that produced it. For example, it recommends raising the rent for a two-bedroom unit from $1,800 to $1,855.
Then it would explain how and why it reached this conclusion, using multiple data points to support its reasoning. So, it explains market comps recently rented units at a higher price, and historical data shows that the specific floor plan has leased three days faster at a slightly higher rate.
How Does Explainable AI Help Revenue Teams Work Faster?
Explainable AI helps revenue teams work faster because its transparent, easy-to-understand recommendations eliminate guesswork and allow teams to take action sooner. Instead of trying to understand the recommendation or manually analyzing data for hours to reach the same conclusion, teams can make pricing and renewal decisions immediately.
How Can Explainable AI Power More Agile Pricing Strategies?
Explainable AI gives teams insight into “why” behind every recommendation, allowing them to adjust pricing strategies quickly in response to ever-evolving market conditions. It can also account for property-specific factors and competitor activity, enabling teams to maximize revenue while keeping pricing defensible and competitive.
How Does Explainable AI Offer Pricing Transparency?
A clear explanation of the data and logic behind it accompanies every pricing recommendation. Teams can trace decisions to specific market data, comps, or property factors, which makes it easy to justify pricing to leadership while complying with regulations.
How Daylight Revenue Management Delivers Explainability
If you’re looking for a transparent revenue management platform for your multifamily properties, Daylight by ApartmentIQ is powered by Explainable AI that delivers clear and logical recommendations for pricing and renewals.
Daylight eliminates guesswork by leaving the black box behind and providing fully detailed pricing recommendations. Every suggestion comes with an easy-to-understand explanation to help teams understand and justify decisions.
Built on ApartmentIQ’s industry-leading, public comp data, Daylight delivers a modern, easy-to-use interface and award-winning customer success to help your team save time and reduce frustration.
Book a demo today to see how Daylight delivers explainable, defensible, and actionable pricing recommendations for your portfolio.
