AI automation cut operating hours by 78% while increasing property revenue by 12%

The Problem

Good Stay Capital operated short-term rental properties across markets where performance depended on hundreds of small decisions happening correctly every day: guest communication, pricing, reviews, property coordination, listing performance, cost control and responding quickly to changes in local demand.

As the portfolio grew, so did the operational burden.

Guest questions and reservation messages required constant attention. Reviews had to be requested and managed. Properties needed ongoing coordination. Pricing decisions depended on seasonality, competitor activity, local events and changing booking behavior. At the same time, management needed a better way to understand where money was being lost and which actions were most likely to improve property-level returns.

Much of this work was repetitive, but traditional automation could only handle simple rules. The business needed systems capable of understanding context, communicating naturally with guests and using operating data to improve decisions—not merely completing tasks faster.

The objective became clear: reduce the manual work required to operate each property while simultaneously improving revenue, guest experience and competitive performance.

Our Approach

We redesigned the operating model around a connected AI and property-management technology stack.

Claude and ChatGPT were incorporated into core workflows to assist with guest communication, operational decision-making, property intelligence and repetitive administrative work. ElevenLabs voice AI extended those capabilities into conversational workflows, allowing more guest and property-management interactions to be handled without requiring continuous human involvement.

Guest messaging was systematized across the reservation lifecycle—from initial inquiries and booking communication through check-in, stay support, checkout and follow-up. Review workflows were automated as well, helping properties consistently capture guest feedback and strengthen their reputation across short-term-rental platforms.

These systems were integrated with property and house-management workflows rather than operating as isolated AI tools. The goal was to create an operating layer where technology handled the repetitive coordination surrounding each reservation while people remained responsible for exceptions, judgment and higher-value decisions.

The second layer focused on revenue intelligence.

Property operating costs, historical performance, market behavior, pricing patterns and competitive conditions were analyzed to identify opportunities that were difficult to see through manual property management alone. That intelligence informed pricing, spending and operating decisions across the portfolio.

We also treated listing position as an operating problem rather than simply a marketing problem. Pricing, response behavior, guest experience, review velocity, listing quality and cross-channel performance were managed together to increase visibility and conversion across booking platforms.

The result was a system designed not simply to automate existing work, but to make the properties better operated and more economically productive.

The Result

The redesigned technology and operating stack reduced the human working hours required to manage the portfolio by 78%, shifting the team away from repetitive guest communication and administrative coordination toward higher-value property and investment decisions.

The revenue-intelligence layer helped identify pricing, cost and operating opportunities that contributed to an average 12% increase in revenue across the investment properties.

At the same time, Good Stay's properties moved from having little or no meaningful search position to achieving #1 ranking in their respective local markets across major short-term-rental channels.

Those gains reinforced one another.

Better communication improved the guest experience. Better guest experiences supported stronger reviews. Stronger reviews and listing performance improved marketplace visibility. Better pricing and operating intelligence improved property economics. Automation made that system possible without requiring labor to grow at the same rate as the portfolio.

The engagement ultimately demonstrated a principle that now carries directly into PezScales' work:

AI creates the most value when it is embedded into the operating system of the business—not added as another disconnected tool.