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How the Hospitality C-Suite Leverages Big Data and Analytics

by Kevin Wagner

Big data and analytics are a natural fit for the highly competitive hospitality industry, where success is defined by delivering a positive guest experience. By collecting information about how individual guests and groups make choices on where to stay, what guests like and don’t like, and why they return (or don’t), analytics can help hoteliers be more effective across the board – from defining their acquisition strategy to tailoring offers for individual guests.

Here’s a look at the Top 5 ways executives in the hospitality sector can use big data and analytics.

1. Identify growth and investment/divestment opportunities. Big data and analytics can provide insight into supply and demand drivers for hotel space over time. For example, today’s hot-spot may be saturated two years from now with properties that are currently under construction. This can help hospitality CEOs make more informed decisions regarding properties and brands to acquire or divest, where to build or sell and when to consider a merger.

2. Mine financial performance in franchised, owner-managed and brand hotels. Chief Marketing Officers (CMOs) use big data to detect profitability trends across different geographies and service models. Analytics can assess macro trends as well as individual preferences to steer room rate adjustments and optimize occupancy and profitability. For example, a hotelier in Manhattan wouldn’t want to charge $500/night during the holiday season if rooms would fill for $700/night but might fill rooms at bargain rates during the off-season rather than have them sit empty.

3. Identify opportunities to gain wallet share. CMOs for hospitality companies rely on big data to analyze behavior patterns and preferences of guests staying in their properties and to isolate the unique characteristics of spending patterns for different accommodations models. Consider the Disney “MagicBand” wrist bracelet that guests use to make purchases, take rides and visit attractions. The model not only allows guests to tailor visits according to their preferences, but each bracelet provides a massive amount of data to enable greater levels of analysis over time.

4. Identify major deals. Sales executives rely on big data to plan campaigns that target major business meetings and conventions. Understanding demand, capacity, geography, competition and marketing strategies is essential to promoting a healthy, profitable and sustainable business model in these high-risk, high-reward opportunities. Plans for such events (matching facilities with buying decisions) are often years in the making. Big data is a critical tool, providing a window into the art of the sale, huge brand recognition and further marketing opportunities.

5. Build customer loyalty. Sales and marketing teams use big data to proactively manage all aspects of customer loyalty programs, offerings, recognition levels, rewards and awards. These are not your father’s loyalty programs. They are complex programs that often co-exist alongside niche players, partners and competitors. How a company markets its program to the customer depends on demographics, program targets, customer maturity and level. Big data can allow you to keep abreast of changing customer buying patterns, the competition and new opportunities.

ISG has helped many executives navigate the changing landscape of big data and analytics. Contact Kevin Wagner to discuss further.

About the author

Mr. Wagner provides a comprehensive knowledge of information technology outsourcing (ITO) and IT management and services to ISG clients on a global basis. Kevin has a broad range of ITO experience, including work with multinational centers and data center consolidations. His IT expertise spans end user computing, service desk, midrange and mainframes solutions, networks, systems engineering and applications, renegotiations and termination events. In addition to North America, Kevin has international experience in Australia, New Zealand, Malaysia and South Korea.