FOR IMMEDIATE RELEASE
AUCKLAND, NEW ZEALAND
December 13, 2019

Dexibit, a software company providing big data analytics for visitor attractions, has announced a new feature predicting future revenue down to the day and up to a year ahead.

Unlike traditional financial planning performed through manual analysis, Dexibit’s proprietary revenue outlook machine learning model uses a range of data sources and deep knowledge of the visitor attraction industry to make predictions. This model allows venues to drive commercial growth by using data to inform financial and operational decisions.

“The Dexibit team is proud to extend our suite of machine learning models for the visitor attraction industry with the new revenue outlook model,” says Pip Gilbert, Vice President Product at Dexibit. “This commercial lens on predicting and analyzing visitor behavior aligns with our expansion into the commercial visitor attraction sector whilst also providing value to the cultural sector to support financial sustainability. Regardless of the type of visitor attraction, understanding future revenue predictions and drivers can help inform a range of decisions to optimize performance.”

With at least eighteen months of historic revenue data uploaded to the Dexibit platform, the machine learning model automatically forecasts total revenue and identified lines of business. The revenue outlook model presents a monthly forecast for the year ahead, a weekly forecast for the next six months, and a daily forecast for the next three months. Predictions from the model will help venues manage budgets for variable costs such as staff scheduling, stock purchasing and marketing investment.

For the complex business model of most visitor attractions, many elements of the visitor experience affect revenue: ticketing; merchandise or gift shop sales; onsite food and beverage; and special activities such as events, exhibitions or experiences. With this in mind, a unique feature of the revenue outlook model allows attractions to forecast by line of business – such as ticketing, stores or cafes – providing venues with greater visibility over the levers that affect their commercial outcomes.

The machine learning model also shows the impact of external key factors contributing to the final predictions. This enables venues to understand the role of cruise ship schedules, regional events or other external factors on the attraction’s top line performance, helping to inform messaging and targeted campaigns. Additionally, knowing the impact of weather, opening hours or public holidays can inform staffing and programming decisions, while variable costs can be better managed and optimized to align with top line expectations when there is high confidence in the forecast performance.

Since an early beta release, a number of visitor attractions worldwide have utilized this new feature, including the Rock and Roll Hall of Fame in Cleveland, Ohio.

The revenue outlook model adds to Dexibit’s suite of forecasts which are able to predict visitation, advance pass attrition, exhibition performance and more.

Ends.

About Dexibit

Dexibit is the global market leader of big data analytics and artificial intelligence for visitor attractions. Dexibit’s software as a service includes forecasts, insights, dashboards and reports.

Press Contact

Contact press@dexibit.com, phone +(64) 21 186 9321 or visit press.dexibit.com. For Dexibit’s COVID-19 coverage, see covid.dexibit.com.