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Predictable Reservations


Background

Any organization that operates through a reservations system understands the importance of predicting customer behavior to manweatherage their business. It is critical for organizations such as restaurants, airlines and hotels to recognize patterns in customer spending so that they can better predict upswings and downswings in revenue. Convergence Consulting Group (CCG) was engaged by a fine dining restaurant group to support historical analysis for predicting future customer behavior.

Challenge

Hospitality organizations that rely on a reservations system often suffer periodic downtimes due to external factors such as weather or economy. As the popularity of online reservations has increased, many hospitality organizations have actually suffered greater gaps in forecasted versus actual revenue due to the low commitment nature of online ordering. In times of economic instability, fine dining is one of the first expenses that consumers cut from their purchasing routine.
CCG was engaged by one of the leading fine dining restaurants, whose goals were to:

• Accurately forecast revenue by location

• Predict lows and highs in reservations

• Analyze customer data for targeted marketing

• Tie specific campaign effectiveness to performance

• Monitor individual store performance

The goal of this engagement was to develop a series of reports that would predict lows and highs in reservations so that the restaurant might deploy additional marketing tactics to fill & staff their locations efficiently. Prior to this engagement, the restaurant was performing their own historical analysis, however the formal reporting process was tedious, absorbing valuable time and resources.

Solution

CCG implemented IBM Watson Analytics, which would allow the fine dining restaurant to quickly join data from multiple sources for predictive analysis and create end-user friendly visualizations. Watson Analytics is a powerful tool for organizations that operate off of reservations because it can adapt quickly and perform prescriptive analytics, even in the hands of non-technical users thanks to its natural language processing and visualization suggestions.

Leveraging Watson Analytics, CCG created a series of reports to analyze historical transactions and compare them to current forecasts. This performance analysis is used to find patterns in customer spending, identify gaps where action must be taken and predict opportunities for additional revenue.

Now that the restaurant is able to identify marketing needs and opportunities, Watson Analytics is leveraged to prescribe specific actions that are likely to increase performance. One such campaign utilized Watson Analytics to join transactional data from the data warehouse with in restaurant gift card purchases to identify store patrons that used gift cards frequently. When Watson Analytics predicted a slow period for those stores with high gift card transactions, marketing was deployed to send gift cards to these restaurant patrons in order to encourage short-term reservations. The visualizations created by CCG not only identified this marketing opportunity but also provided the ability to measure campaign effectiveness after efforts were deployed so that marketing actions can be tied directly to revenue growth and duplicated in the future.

This iterative process, which analyzes upcoming reservations, targets specific markets and monitors campaign effectiveness, has successfully helped the restaurant to not only avoid traditional ”slow seasons” that are so common in hospitality organizations, but also to consistently outperform historical revenue goals.

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Quick Facts

  • Industry - Restaurant/ Hospitality
  • Technology - IBM
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