Don't Get Lost in the Sea of Data

It's safe to say "data" is not on the list of topics nobody is talking about. Data – what data to use, where to use it, how to use it and when to use it - has been strategically dissected at the corners of nearly every industry discussion to date.

Data is also heralded as the core of intelligent and gainful decision-making. It's been reported that companies at the top of their industry for data-driven decision-making are 5% more productive and 6% more profitable than their competitors.

Over the years, the pool of data sources hotels utilize within their business strategies has grown exponentially larger. The propagation of its importance within the development of short- and long-term vision and strategic planning has also become more commonplace than in years past.

Innovative breakthroughs in technology and analytics mean organizations continue to see more opportunities to leverage data in meaningful ways. However, the alternative side is the steep volumes of data can be dauntingly large and intricately complex.

Some organizations liken this complex data environment to needing a bigger boat for a sea of data. But when it comes to capitalizing on industry data, size isn't what matters. Organizations that focus on using the right types of data – with an infrastructure that can effectively leverage it – can confidently reach ambitious profit goals. An era of big data requires that critical business information is not just easily accessible, but easily digested and understood. In many organizations, data related to operational forecasting, revenue forecasting and annual budgets are housed in different systems and accessed by different departments. This disconnect between both systems and departments can inevitably lead to inefficiencies and manual errors.

This article explores how hoteliers can use the right mix of data for a comprehensive picture of the business, while supporting the intricate relationships between departments to improve operations and enhance business performance.

Establishing the Ideal Mix of Data

Profitable outputs require optimal inputs. For hotel organizations, this means data quality has significant implications on the quality of their strategy - especially when it comes to its financial returns. As organizations continue to leverage evolving data sources, it's important to be thoughtful about the data used within their technology and strategies. Simply adding more and more data - rather than focusing on adding the right data - can actually counter positive results.

Here are some common data sources hotels use within their strategies, and how using them impacts their overall profit potential:

• Online Reputation Sentiments
  Online social platforms, such as TripAdvisor and Booking.com, represent an unprecedented purchase power for today's consumers. The reviews on these platforms can also leave a heavy impact an organization's bottom line - either positive or negative. And since reviews are published on many different online websites, they have the potential to reach innumerable prospective consumers. This not only illustrates the importance of guest reviews in today's age of technology, but the opportunity hoteliers have to factor their reputation into short- and long-term business strategies. By evaluating this data, organizations can evaluate their opportunities to influence purchases at the point of decision making, as well as identify their opportunities to increase guest satisfaction. The correlation between a hotel's rate and reputation helps hoteliers identify new pricing opportunities. It has been reported that for every point increase in ratings, hotel bookings increase by 14.1% and average daily rate by 11.2%.
• Competitive Rate Shopping Data
  Price is important to hotel demand, and it has an important role in a revenue management strategy. However, hotel organizations not only have to evaluate their own pricing approaches, but their competitors' pricing as well. This is because competitor pricing can have a direct and indirect impact on their own demand.

  For example, changes to competitor rates could indicate an intent to steal market share, which directly impacts demand as guests are shopping for the best deals. Competitor rates also have the ability to influence fair market price perceptions. A guest might purchase from a hotel if they expect the competitor price to be higher, but might pass on them if they expect the available rates from competitors to be lower. This means that competitor rates could influence guest reference prices for a given hotel.br>
  Organizations can use this data in their revenue technology to understand how guests are reacting to their pricing and how their rates are positioned within the market. Technology can use this data to estimate the effect of price on demand, and help hotels make adjustments based on price position relative to their competition.

• Regrets & Denials Data
  There have been many discussions around using customer traffic data for demand forecasting. Much of this stems around using regrets and denials data to unconstrain hotel demand. Unconstrained demand refers to the amount of demand that exists for a product, independent of any constraints. In the hotel world, this demand represents how many hotel rooms could be sold on a given day if there was unlimited inventory available.

  There are two considerations in the discussions around using regrets and denials data to measure unconstrained demand. The first is the important distinction between "denials" because of unavailability and "regrets" from price or other factors. Secondly, many reservation systems are unable to capture the difference between a regret and a denial. Unconstraining demand affects the entire pricing and revenue management process, and using this data has been largely unsuccessful to date. This is because denial data from direct websites only represents a partial amount of data. When used to determine unqualified transient demand, the demand for other market segments and channel behaviors goes ignored. In addition to this, there is also a high potential of inaccurate coding practices and same person inquiries, as well as high look-to-book ratios against generally flat booking volumes. These are a few of the considerations that make this data unreliable to use in forecasting technologies.

• Cancellations and Re-Bookings
  The practice of cancelling and re-booking is a troubling guest behavior for hotel organizations. Thousands of people cancel and re-book online reservations every single day, and it has left many hotel organizations fighting in a one-sided booking war.

  This particular booking behavior has the potential to negatively impact hotel's forecast and profit potential. This practice can also be difficult to accommodate for within today's technology, especially in solutions using regrets and denials data to forecast. For example, when repeat shoppers are counted as new units of hotel demand, it can significantly inflate the demand forecast over that time period.

  However, recent advancements in technology are helping properties account for potential revenue lost by estimating the effects of rate changes. Cancellation and re-booking patterns vary by property, market, season and day-of-week, so technology that properly accounts for these patterns offers analytical insight to optimally balance price and demand.

Forward-looking Market Intelligence

More recently, hotel organizations have identified newer ways to capitalize on data through increased interdepartmental collaboration. One type of data in particular encouraging a previously unlikely partnership between marketing and revenue management teams: travel intent data.

The availability of travel intent data has become instrumental in developing a hotel's revenue strategy. This data uses search and booking data from third-party booking sites and OTAs to help quantify the demand a hotel can expect for future dates. This powerful market intelligence puts names to faces, and gives hotels human-focused insights.

Hotel revenue managers use this data to strategically futurecast, a practice that builds upon traditional forecasting practices to look beyond the face value of a number and fully understand how and why a particular outcome occurred. It also helps hotel marketing teams develop and execute more specific ad placements, experience packages and personalized offers.

Industry technology plays an extremely critical role in helping hotels profit from this data. The ability to integrate information previously inaccessible to hotels (such as the relationships between intent to book and pricing) elevates a hotel's forecast and its subsequent revenue opportunities, such as offering tailored package add-ons based on guest preferences.

In addition, technologies providing this extensive level of insight offer hotels distinct competitive advantage when it comes to pricing their rooms, personalizing marketing efforts and aligning the overall consumer experience across all booking channels.

Bringing It All Together

Evaluating the ideal data to inform an intelligent revenue strategy is the first step in managing the sea of industry data. The next step for organizations to take is identifying how this data can help their different departments work closely with one another. The most successful hotel organizations achieve this through a strong foundation of education and routine discussions around how to use data to reach mutual department goals.

Selecting the optimal infrastructure has been another topic of interest and area of opportunity for hoteliers in this process. The right infrastructure - also known by its trendier moniker "tech stack" - allows hotels better visibility and control over their revenue streams. "Tech stack" generally refers to the group of integrated solutions that work together to help a hotel achieve its business objectives.

This could include data exchange between their property management system, revenue management system, central reservations system, sales and catering systems, and customer relationship management solutions. It's important for hotel organizations to evaluate their existing integrations between current and prospective software for optimal decisions and insights.

Using an ideal mix of data and an optimal set of technologies provides hotels with a comprehensive view of business intelligence and encourages stronger team alignment - supporting cross-functional marketing, sales, catering and revenue teams in working together productively and profitably.

Revenue Management