The hotel and hospitality sector caters to millions of travellers every day, and each one of them checks in with their own set of expectations. Meeting those expectations is the key to getting people to return, and increasingly hotel and leisure operators are turning to advanced analytics solutions for clues about how to keep their customers happy.

Additionally, although their marketing departments would be loathe admit it, not all guests are equal in the eyes of hotel and leisure operators. Some will simply check in and check out with a minimum of fuss. Others will spend hundreds or thousands of dollars on fine dining, entertainments, sports activities and spa treatments.

Identifying those customers with a higher overall lifetime value to a particular business is hugely important in today’s market, but a customer’s lifetime value might not be empirically obvious from observing their behavior during one visit.

For example, a high-rolling customer spending money like it is going out of fashion in the hotel casino may be on a “holiday of a lifetime” following retirement, and unlikely to behave in this way every day. Meanwhile a frugal business customer taking an economy room and spending very little on extra services may be a travelling businessman who will potentially return frequently if the hotel meets his needs, and therefore have a higher lifetime value. Big Data analytics can help make this distinction.

A third overarching use of analytics in the hotel industry revolves around “yield management”. This is the process of ensuring that each room attracts the optimal price – taking into account troughs and peaks in demand throughout the year as well as other factors, such as weather and local events, which can influence the number (and type) of guests checking in.

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