Hotels know their customers in an almost intimate way: they know what their customers order and whether they spend at the bar, restaurant or on room service; how many towels they use and whether they need extra pillows and a firm mattress; who shares their bed. That level of detail may be too personal to treat as simply data, but hotels have plenty of other data they can use. Combine the customer data with travel industry data, weather data, customer opinions in online forums, economic trends and the hotel’s own inventory and pricing data, and it becomes big data that hotels can use to improve their customer interactions, their revenue and the way they run their business.
Using Big Data to Attract Customers
One of the primary uses of big data in all industries, including hotels, is to segment customers and support personalized marketing. For hotels, loyalty programs and surveys are a frequent source of data, but big data allows further refinement. Through customers’ opinions expressed in online surveys, companies can better understand which features and experiences the customers really value and target their marketing along those lines. The data from those sources can also provide other demographic and lifestyle information the hotel wouldn’t otherwise know. Hotels can use the data to identify customers with the highest lifetime value to the hotel.
Using Big Data to Increase Revenue
Hotels can use big data and analytics to support their revenue management. Part of selling each room at the maximum rate is knowing your customer base, and the customer segmentation analytics create is helpful here. Combining loyalty data with opinions expressed in online forums supports these kinds of analytics also. Outside data such as weather and events, plus tourism trends, can help companies estimate the demand for rooms and set a price.
Using Big Data to Increase Operational Efficiency
Big data can also help hotels improve how they run their operations. Analyzing records that show when requests were entered and how long servicing the requests took, hotels can identify opportunities for improving their response times. Another way big data can reduce operational costs is by predicting energy demands and discovering ways to use energy more efficiently and direct whether to pull from the local power grid or onsite batteries or solar power sources.
Big data can also help direct the hotel’s financial management and decision-making. Analytics can help predict whether investing in upgrades will generate a positive financial return. The data generated from a small test investment can be evaluated to predict the impact of a bigger investment.
Big data is also helpful for managing the hotel’s maintenance. Predictive analytics lets maintenance schedules be developed based sensor data that indicates an imminent breakdown. This allows maintenance to be provided on a just-in-time basis, neither waiting for a failure nor replacing elements too early. This strategy can be applied both to customer-facing systems, such as air conditioners, and to back-office items like computer systems.
Working Effectively with Big Data
Getting started with big data isn’t as simple as running some queries against a database. Hotels that want to use big data need to consider questions such as:
- What questions do you want analytics to answer?
- What data will they collect?
- Where will it come from? How will it get into the company’s systems?
- What will the volume be? Will they store it locally or use the cloud?
- Can your existing database technology handle an unstructured data?
- Do you need to bring in new tools, such as Hadoop, Spark, or NoSQL?
- Does your technical team have the skills to build analytics programs?
- How will the results of analytics be presented to management?
By considering these questions and strategically implementing a big data analytics program, hotels will be best able to achieve the benefits and insights that can boost their business.