Your hospitality business has countless ways to collect snapshots of consumer data — past travel bookings, seasonal sale trends, and more — but if you never look at all of your data together, you’re missing key business insights.
That’s what Big Data is all about: taking you beyond the snapshots of individual consumers and singular moments, to get a more holistic view of your target market. Travel consumers are an especially tricky bunch for marketers, because they not only vary widely in demographics, but one individual consumer can have different reasons behind each travel experience, resulting in different behaviors and expectations on each trip.
Bernard Marr sums up the challenge for hospitality marketers in a recent Forbes article: “A customer’s lifetime value might not be empirically obvious from observing their behavior during one visit.” Assessing the lifetime value of your consumers requires looking at their behaviors from a much wider angle (not just a snapshot); encompassing more information over longer periods of time.
Hospitality marketers in particular should be taking advantage of Big Data to guide their efforts, as they seek to reach diverse groups of travel consumers, with widely fluctuating desires, needs, and expectations for travel experiences. These tips will guide you in how to use Big Data to propel your hospitality marketing forward and reach big picture goals.
Categorize Your Customer Type
Travel consumers are too widely varied for one marketing strategy to effectively connect with all of them. The successful travel provider, hotelier, or restaurateur picks a primary market and masters it.
Collecting and analyzing Big Data will help you capture those consumers who are perfectly suited for your products and services. The traditional business traveler on a budget looks for a comfortable room, convenient dining, and fast and reliable internet access. The bleisure traveler, on the other hand, is looking for the same budget-friendly amenities, with added entertainment and luxury options to pursue after their working hours. The average family traveling with young children wants a low-cost, clean, and child-friendly facility. The honeymooning couple seeks to splurge on luxury. Which is your business best suited to serve?
Customers come with a myriad of expectations, from those who just want to grab a bite or a night’s sleep and be on their way, to those who want to be thrilled by adventure or enveloped in luxury. Determine which specific travel consumers fit your business, and use Big Data to identify the best opportunities to reach those people, draw them in, and exceed their expectations. This will also help you better identify one-time guests who are unlikely to return to your business, and those customers with a higher overall lifetime value — so you can focus more time and resources where you’ll have the most impact.
2. Find the Highs and Lows
Analyze Big Data to identify peaks and dips in your business cycle — and use that as a guide to set appropriate prices for your goods and services.
Savvy airlines, cruise lines, hotels, and others in the hospitality industry can use this information to their advantage, to fill empty spaces for the best possible net profit. For instance, a cruise ship that charges its highest rate yet sails at only 25% capacity loses money overall, compared to the ship that sails at 90% capacity with lower paying customers. The latter scenario creates a positive ROI, meaning more economical staff-to-customer and resource-to-customer ratios. The ship’s going to burn the same amount of fuel traveling from port to port whether it’s carrying a full load of passengers or not.
Consider the improved customer experience that comes from adjusting your pricing to fit demand. The cruise line with more passengers who paid an affordable rate will likely see repeat customers and receive word-of-mouth recommendations. Those consumers who enjoyed the trip with the other cruise line, but feel like they paid too much for the value received, may not use that cruise ship service again.
3. Cater to Relevant Customer Needs
Big Data analytics doesn’t just focus on your existing customers’ habits — it takes into account the catalysts that cause people to become customers. Capitalize on Big Data to anticipate consumer needs in a timely manner, and tailor your efforts to deliver to those customers who most need your services during a given time period. This often means looking outside of your own internally-collected data and analyzing external factors, such as sales patterns for related hospitality businesses or consumer opinions of your competitors.
In his Forbes article, Marr provides the following example using Red Roof Inn, an economy hotel chain. When flight cancellations hovered around 3%, approximately “90,000 passengers were being left stranded every day.” The chain used data on weather conditions and flight cancellations to target customers who would find themselves searching for overnight accommodations on their mobile devices. Red Roof Inn saw a 10% increase in business thanks to this strategy — just one example of the power of Big Data.
Then, there’s data that goes beyond raw numbers: qualitative data. Qualitative data relies on customer feedback retrieved from customer reviews, social media, travel sites, and front desk personnel. Survey a group of your target consumers, to determine whether your services are actually fulfilling their wants and needs. The information you collect can shed light on the traits your customers value and the issues that drive them away, enabling you to adjust your services. Changes in your services don’t have to be costly. Some can be as simple as enabling your hotel housekeeping, kitchen, or banquet staff to anticipate a guest’s needs and respond accordingly. The ability to anticipate and cater to customer needs results in those personal touches that yield higher reviews — and increased business.
4. Ask the Right Questions
The “right” questions are those that probe beyond the obvious. Deeper analysis into what might appear to be unrelated information can yield insights that enable you to target a specific customer niche and increase sales.
One way to check that you’re asking the right questions is to first define the type of data analysis you’re conducting. There are three common types of data analysis: descriptive, predictive, and prescriptive.
Descriptive
Descriptive analysis focuses on past trends. This often shows evidence of results following changes in action, policy, or property. Did adding a vegan menu really increase sales? Descriptive data helps a restaurateur determine that.
Predictive
Predictive analysis focuses on what is likely to happen in the future. The very nature of forecasting the future adds an element of uncertainty that business executives may not welcome. However, this type of analysis offers valuable insight, especially when combined with information yielded from descriptive analytics.
For instance, predictive analytics may signal a peak season near the end of March (for spring break), which would then incite increased competition for hotel rooms in certain popular vacation destinations. That knowledge may result in a hotel adjusting its rates, to take advantage of the anticipated influx of customers.
Prescriptive
Prescriptive analysis involves advanced algorithms that process Big Data, to suggest possible actions based on future occurrences. For instance, booking engines can personalize the online customer experience, by using past data to predict a consumer’s future needs, and then suggest and deliver a customized vacation package. One online travel agency, CruisingStore.com, is launching just such a booking engine in the first quarter of 2017.
Big Data is available to any hospitality business in plenty — from your own internal systems and published on publicly accessible forums. Once you have centralized and integrated the Big Data you need, you can break it down accordingly to categorize your target market, reach consumers with the highest lifetime value, and exceed consumer expectations by anticipating (and meeting) their needs before they’ve even had time to ask. Isn’t that what hospitality is all about?
