PriceLabs creates custom platform for vacation property management analytics
- Property managers see between 10% and 40% revenue increases thanks to the PriceLabs platform’s predictive pricing guidance, prospective market analytics, and portfolio performance monitoring.
- PriceLabs chose Python analytics over traditional BI software to accommodate custom parametrization and display robust, relevant, real-time analytics on their platform.
- Dash abstracts away full-stack workflows, allowing PriceLabs' agile data science team to meet clients’ needs in the face of COVID-19 market changes.
PriceLabs creates analytics and AI tools for small businesses that manage short-term rental properties. Their clients range from individuals with a few investment properties that they have converted into vacation getaways to enterprises that manage hundreds or thousands of properties. Through the power of Python and Dash, the PriceLabs platform gives these property managers custom views of detailed, real-time analytics that aid in maximizing revenue, prospecting future markets, and monitoring their properties’ performance.
"We do a lot of processing and calculations before we display our results to customers; we chose Python and Dash so we could do a lot of that online and quickly show data based on parameters that each customer specifies without having to create tons of infrastructure around it first."
David Witalka, Data Scientist, PriceLabs
To maximize revenue, property managers aim to find the right balance between prices and occupancy: increase the prices too much, and you might not get too many bookings; lower them significantly, and you might get fully booked but at super cheap rates. Fluctuations in demand based on seasons, day of the week, holidays and events, and many other factors make this a constantly evolving problem.
Setting the right price requires access to a large amount of data and a large time investment to monitor and react every day. Small businesses and individual managers find it hard to keep up and remain competitive on platforms like Airbnb and Vrbo, especially as they scale up the number of properties under their management. An ongoing pandemic adds complexity to these tasks.
While COVID-19 has dealt an unprecedented blow to the travel and accommodation industries, it has also been an unexpected boon for the vacation rental sector. “Because of COVID-19, people are hesitant to stay in hotels, and more people are working remotely. People are booking more extended stays,” explains Pedro Borges, a senior data scientist at PriceLabs. “But we’re also seeing changes in booking lead time and fluctuations when the worst parts of the pandemic hit. That’s why being able to stay on top of current market trends is important to our clients.”
At the beginning of the pandemic, the PriceLabs platform was built around their Dynamic Pricing tool, which helps in competitively pricing one’s properties. But PriceLabs’ team found that clients were demanding more tailored views of what was going on in their markets and in their portfolio. How were current properties performing at any given time? Which prospective geographical markets would be good to invest in?
PriceLabs’ team of data scientists wanted to grow the platform to meet their clients’ demands. With over 50 billion market data points to analyze each night, they knew these answers were out there if they could only process and present them in a consumable way.
The team evaluated well-known BI software but encountered bottlenecks when they had to translate their data into a row-column format that the BI tools could ingest. The analytics that PriceLabs displays to clients require a lot of preprocessing and data science to produce, compounded by the fact that each client can specify custom parameters about a specific property type or geographic area. Off-the-shelf tools could allow for the creation of new reports, but not without a lot of work on the part of the data science team to reformat their data, add new columns, and specify requirements for the full-stack team. Developing and shipping even one new visualization type to clients would have required many weeks of iteration, in which the data science team would add new data and the full-stack team would figure out how to visualize it.
PriceLabs’ Dynamic Pricing tool uses Dash to visualize pricing and occupancy projections calculated in Python and customized per client parameters.
Dash enabled PriceLabs to quickly develop new tools for clients, like the Portfolio Analytics view, which makes it easy to identify how properties are performing against each other and the market.
Since Dash is the fastest way to develop rich, interactive data applications in Python, it became a natural extension of PriceLabs’ data science workflow. Reducing full-stack iterations puts more control in the hands of the data science team to innovate responsively to their clients’ needs. And the developments pay off, with property managers reporting anywhere from 10% to 40% increases in revenue after adding PriceLabs to their tech stacks.
With thousands of customers spanning more than 100 countries, PriceLabs continues to grow globally. New challenges and client needs will accompany this growth, and Dash is an important asset to ensure that PriceLabs’ platform remains flexible and future-facing.
Founded in 2014, PriceLabs is a powerful revenue management and dynamic pricing software for vacation and short-term rentals. Data-driven predictive analytics, a powerful rules engine, and industry-leading data tools help their 10,000+ customers in 95+ countries increase revenues and save them hours in the process.
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