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Using Small Data to Maximize On-Property Spend

Using Small Data to Maximize On-Property Spend

There is a significant buzz in the industry around the use of big data, but less so around small data. Small data is easily attainable and less complex than big data, which is defined by billions or trillions of records that typically require powerful computational resources to process. In hospitality, small data could include guest records, statistical information housed in hotel systems, customer feedback, or direct transactional data. Given the recent focus on big data, many hoteliers feel overwhelmed and unsure where to start. The answer? With small data.

While bigger data may sometimes be better, no advanced strategy will be successful without a solid foundation that is built on the basics. Understanding smaller pieces before working with big data will provide a better understanding of existing business and opportunities; how to handle data through collection, validation, and application; how to create a proper data program; and how to evaluate and interview potential big data partners.

 

Determining Information Needs

It’s essential for hoteliers to achieve a better understanding and control over the available information, with an eye towards improving overall revenue, efficiency, and profitability.

Understand customers’ buying behaviors.
Break down guests’ ancillary spending. This can be eye-opening when crafting a total revenue management strategy and can provide a more defined sense of how to change or optimize a hotel’s or resort’s offers and outlets. Additionally, buying behavior data can help hone in on the most effective offers, room types, or segments. This is one of the primary opportunities often overlooked in general revenue strategy.

Learn where customers come from.
Small data can be used to review source markets. Generate accurate address data at check-in and require front desk staff to ask for current postal and email addresses from every guest. After pulling a report for source markets, watch for an unusually high number of travelers from a particular state due to pre-filled addresses from OTA channels.

Identify frequent issues in customer reviews.
Both internal and external survey collection methods provide valuable insights into areas that can be optimized for better service, leading to higher revenues, better overall performance, and happier guests.

 

Beginning to Use Small Data

First, list unique data solution goals, then prioritize. Establish the purpose of the program; data collection without a purpose is pointless. Identify a main point of contact as the data program champion to help drive the process.

Next, consider available methods of collection. Comb through the capabilities of each technology system for which fields are a constant or can be customized, and the source of the data. Now, line up goals and available data. Are all the necessary tools in place to collect relevant, meaningful data? Define areas of sufficient data and any gaps, then refine the processes.

 

Foundation Ready

With the basis for a great data program established, define its parameters. Each person involved should understand who will collect data, what data should be collected, when and how that data will be collected, and from where.

Begin setting data validation and cleanliness parameters by merging or cleaning up system profiles. This can be done either with one of several tools available today or manually, but never skip data validation and cleanliness. For example, a boutique portfolio of hotels that implements an advanced business intelligence tool to better collect and analyze their data but lacks cleanliness in their setup may cause the tool to show only 10 room nights across a multi-hotel portfolio in the past 12 months. Lack of data cleanliness procedures may result in completely unusable data.

 

Getting Started

Now it’s time to begin collecting data. The data volume may vary from property to property, but regular checkpoints, re-evaluating data output, validation, and cleanliness procedures are essential. After adequate data has been collected, it can be dissected to make more meaningful business decisions.

No program is perfect, and the ability to adapt to changing needs and attention to systems and staffing is a given, but these steps will deliver the basics to become truly successful champions of small data.

 

Lily Mockerman

 

About the Author
Lily Mockerman founded Total Customized Revenue Management in 2012 and is the company‘s president and CEO. Mockerman is a passionate and devoted leader and practitioner in the revenue management field.

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