Hotel revenue management platform Lighthouse discovers the value of intelligent event data
Use Case
Demand Forecasting, Visualizations & Insights
Industry
Hospitality, Software, Technology, Travel & Tourism
Products & Features
Learn more
Introducing Lighthouse
Lighthouse, formerly OTA Insight, creates software that enables hotel managers to price and market smarter with real-time intelligence, which enables more accurate continuous forecasting. Their goal is to empower the hotel industry to make better decisions around marketing, revenue, and distribution, so they are constantly evolving their offering to be as well rounded and insightful as possible.
Lighthouse reached out to PredictHQ in 2020 to increase event demand intelligence. The pandemic was hugely disruptive for the accommodation industry, and events became even more dynamic - and important - than ever to track. Lighthouse wanted to ensure that their Rate and Market Insight dashboards included forecast-grade data on impactful events. Having comprehensive and reliable event information enabled hoteliers to factor this into their marketing budget, and how they were pricing and packaging their rooms.
The Lighthouse team knew events mattered. They had pulled together a few automated event data providers to piece together some of the picture of event-driven demand. But in the wake of huge disruptions such as shelter-in-place orders and event capacity restrictions, they realized how dynamic and messy event data could be.
Enlarging event-based datasets
Once they realized they needed a new way to account for event data, Lighthouse evaluated who to partner with in terms of supplementing on top of its existing platform. In late 2020, events driving demand for travel and the accommodation industry were picking back up, but the rate of change was unpredictable and unstable, and most accommodation companies were understaffed and under significant stress.
“For the hotel industry, you simply can’t rely on just historical data anymore,” Lighthouse’s CTO Kristof Elst says. “The pandemic was a wake up call for any hotels relying on previous year’s data. We knew we had an opportunity to be an indispensable tool for recovery strategies but we had to make sure we had the best data about all kinds of factors, including upcoming events.”
Why PredictHQ was the perfect fit
After their internal analysis, Lighthouse opted to seek out an event data vendor and started looking into options. Since they were investing in an external tool, they wanted to make sure the data provided was of the highest possible quality, and ensure that the provider is an expert in their data. They also wanted a solution that would scale worldwide, since they service customers around the world.
Lighthouse sought out PredictHQ’s data because as Elst noted, they were specifically seeking data that was “accurate, up to date, and complete.” As they were evaluating providers, they found that factors such as COVID-related shutdowns and cancellations were seriously affecting the quality of the data they were getting. Lighthouse realized they needed a data provider that had a more dynamic data set that was updated as frequently as events were. Even if they were to do their data verification in-house, that would require building an entire new data pipeline and internal review system for time-consuming manual checks. “Because there are regular, randomized checks on data accuracy on PredictHQ’s side, we were confident the data is complete and correct. The volatility of events was causing our previously automated event data streams to break, and we wanted a partner we could rely on.”
When comparing their internal data set to PredictHQ, they measured the discrepancies between event volume, timing, location, cancellation status, and more. They were able to evaluate that PredictHQ’s dataset was more complete, without the need for maintenance on their part. They paid particular attention to the most impactful events for their customers, such as expos, conferences, sporting events and major concerts.
With the help of data enrichment and ranking features that PredictHQ offers, Lighthouse is able to set their own parameters around event size thresholds. For example, Lighthouse’s models use predicted attendance that PredictHQ calculates for every event. If that event’s predicted attendance is too low, it’s unlikely to cause demand for accommodation bookings, so Lighthouse won’t recommend it in their platform. That way, they ensure that they only surface the impactful events to their customers. Since implementing PredictHQ, the number of support tickets relating to event data dropped significantly.
How can event data help you?
Lighthouse didn’t just partner with PredictHQ for raw event data. Elst says his team appreciated how collaborative the PredictHQ team was, working with them to identify their most impactful events and thresholds for their models, and making sure they had access to thorough technical documentation and strategic support.
Lighthouse needed intelligent event data that their models could make sense of easily and accurately, but also a platform where their team could see events in context and without friction, which they found in PredictHQ’s Control Center interface. This improves synchronicity across business functions within their organization, in that unique way high quality, highly relevant data can.
