is quickly emerging as the next area of opportunity for driving value through analytics in hospitality.

The guest is at the core of marketing's responsibility, so guest data is at the core of marketing data.

(age, gender, geography),

(personality, values, opinions, attitudes, lifestyles),

(recency, frequency, value).

rewards guests for allowing the hotel to access and track their information. This means that loyalty programs must be designed with enough value to the guest that they are willing to allow this information to be collected.

Marketers also collect data on the content and performance of campaigns, and can use this to report on past performance and predict future performance.

As the digital ecosystem evolves, so too do opportunities for marketing to collect new data. Hospitality and gaming companies are beginning to explore the following data sources.

as the process of researching and purchasing a travel experience moved to the web, and now recently to mobile devices, marketers are having to collect and manage a whole set of new digital data.

hotel and casino managers are becoming more accustomed to the data generated by review sites and social engagement, and well recognize the impact of social data on their businesses.

is also an interesting opportunity for marketers. It is possible for hotels to pinpoint exactly where a guest is at any given time down to a very granular level of detail- using the location services (GPS) in their smartphones and devices installed at the property, called beacons that pick up a signal when the mobile device is in proximity.

Marketers should be heavy users of ____

identifies which variables in the guest profile are related to which outcome measures.

identifies the factors that contribute to overall guest satisfaction and likelihood to return, and how much impact manipulating the values of those variables will have on overall satisfaction

Marketing tends to be more of a forecast consumer than a forecast creator.

is probably the most heavily used category of analytics in marketing.

is a predictive modeling technique of particular importance to marketers.

basically, predictive modeling analyzes the variety of inputs deemed to be significant predictors of an outcome for each guest or patron in the database, and outputs a probability that a guest with a certain combination of values for those inputs will display that outcome.

marketers can leverage a very specific application of optimization to improve campaign results. Hotels, and particularly casinos, tend to have multiple campaigns running at the same time.

Since so much of marketing's role today is focused on digital channels and the digital experience, it is worth addressing the challenges and opportunities associated with this area.

is an umbrella term for the targeted, measurable, and interactive marketing of products or services using digital technologies to reach and convert leads into customers and retain them.

the process of impacting the visibility of a website in natural or organic search-for example, by using phrases or words that are commonly searched for.

promotion of websites in Internet search engines, generally by paying for placement.

A strategic marketing approach focused on creating and distributing valuable, relevant, and consistent content to attract and retain a clearly defined audience-and, ultimately, to drive profitable customer action.

the process of targeting messaging (or content) at a set of individuals who have extensive networks with the hopes that they will advocate for you in your network.

the process of organizing communications into a coordinated marketing effort to a targeted group of consumers.

the process of gaining website traffic or other brand, product, or service attention through social media sites.

the use of a number of social media outlets and communities, social news, bookmarking sites, and social networking sites to generate publicity to increase awareness for a product, brand, or event. SMO is similar to SEO

provides marketing messages directly to a consumer through their email address.

this refers to advertising on websites. It includes many different formats and contains items such as text, images, flash, video, and audio. The main purpose of display advertising is to deliver general advertisements and brand messages to site visitors.

There are three factors that make the sales function at hotels both different from other functions and also a very interesting analytical problem

is all about negotiations

require a slightly different application of analytics. Rather than providing a single best answer, analytics to support negotiations require ranges, best and worst case scenarios, and supporting details.

The numbers need to be presented in such a way that they are flexible enough to account for all the possible permutations of terms and conditions, and also allow for a bit of _____ based on what the salesperson knows about the client and the function.

There's an old saying in sales that each piece of business is about "rates, dates, and space. An organization's ability to measure and manipulate these three factors determines whether the business will be profitable for the property or not.

does the group have a good arrival and departure pattern? Considering the day of the week and seasonal patterns, will the group fill rooms and space during a need period, or are they asking for space during a peak period? Are they willing to shift dates in exchange for a better rate?

how many rooms does the group want to book? Is there sufficient capacity? What is the group's budget? Will they be displacing any transient business or are they filling rooms when the hotel would otherwise be empty?

most sales teams look at the ratio of space to guest rooms booked and try to establish a reasonable balance.

generally, hotels have a standard formula for how much catering spends they would expect depending on the amount of space requested and the time of day the function is booked.

sales teams can offer certain incentives to the groups to book, including free room upgrades for VIPS or free rooms for organizers, food and beverage packages, amenities- basically any of the products or services offered at the hotel can be included to make the hotel's or casino's offering look more attractive.

include some of the same elements that are of interest to other functional areas.

is important to sales, as it is something that the meeting planners and corporate negotiators also look at these days.

now have access to forward-looking demand data, which can help them to benchmark their production against the performance of the market.

Sales negotiations can be quite time consuming. Clients value responsiveness

Can be used to predict the materialization of a group (how many rooms will actually book versus the contracted amount), which will improve planning at the property level.

Sales always keep an eye on forecasts. Since they are incentivized to produce a certain amount of demand, sales keeps careful track of the forecast of business they expect to bring in.

would be useful for mining characteristics of groups in the same way it can be used for evaluating customers.

an _________ for the sales function is probably best associated with the revenue management system. Sales should be able to enter the details of the group, the number of rooms, dates, rates, and ancillary revenue.

requesting a lot of space with relatively few rooms that might not be as valuable to the hotel, because they lose the opportunity to use the meeting space to fill the hotel rooms.

is contributing to this trend, but there are certainly complications to this strategy due to the organization of the industry, particularly on the hotels side

a meeting planner's request for an estimate of what the hotel could offer their group.

identify whether you have the right content or compelling enough copy to attract attention

the fundamental concept in digital marketing is centered on ?

is basically a summary of the characteristics of the population represented by your data. This includes things like counts, maximum, minimum, and most frequent values, averages (mean), median, distribution (percentage breakdown), and standard deviation.

are generally used for continuous data (revenue, guest counts), whereas percentages are generally used to describe categorical data (gender, hotel class).

are used to draw meaningful conclusions about the population or scenario that your data represents.

represents the amount of variability in the data, or how "spread out" the observations are from each other and from the mean (average).

means that the individual observations in the data are relatively close to the mean

means that the value can be quite spread out

involves determining if there is enough statistical evidence to say whether something is or is not the case.

says that you are 95% confident that the answer is yes, and smaller p-values increase the confidence.

is a good metric to remember. It is used in many statistical analyses and will be something that your analysts should know. As you can imagine, there is a good deal of research about where the p-value comes from and how it is calculated.

measures the relationship, or association, between two variables.

comes up with an effect size estimate and a confidence interval (low value/high value) around the estimate when an outcome is relatively unknown.

is used when you want to understand the relationship between the independent variables and the dependent variable or when you want to use the independent variables to predict the dependent variable.

is the use of historical data to predict the direction of future trends, in business applications, forecasting is generally used to assist in the planning process, so it is most commonly used to make a prediction of revenue or demand for a product or service.

are subjective, based on the opinions and judgments of experts. They are most appropriate when past data are not available (like new product forecasting), and are usually applied to intermediate or long-range decisions.

are used to forecast future data as a function of past data. They are most appropriate to use when past numerical data is available, and when it is reasonable to assume that some of the patterns in the data will continue into the future. These methods are generally applied to short- or intermediate-range decisions

When data gets sparse, as in very few historical observations are available, accuracy is impacted.

If there are regular day of the week or monthly patterns in the busness, certain forecasting methods will be more appropriate.

If there is a lot of noise in the data, leaning observations jump around quite a bit and there are very few detectable patterns, it will be more difficult to use for prediction.

Certain forecasting methods deal better with unusual observations or factors that influence the patterns that are not easily visible in the historical data (like oil prices, unemployment rates, or weather).

This category uses simple methods to predict future values,

These methods use historical data, but add more complexity for pattern detection and pattern changes, helping to account for elements like trend and seasonality.

These methods account for additional information beyond historical data that might influence the variable that's being forecast.

is generally based on supply and demand relationships, predicting the price sensitivity of demand, the switching behavior in the face of available alternatives, or the impact of certain financial policies on gross domestic product.

As technology has advanced, providing sufficient processing power to solve larger and more complex math problems, additional complex forecasting methods have been developed.

This measure is the average of the absolute value of the difference between each forecasted value and the actual value for that period.

This measure adjusts for the problem of scale just described by expressing the mean absolute error as a percentage of the total forecasted value.

This measure provides a relatively real-time update to the direction of the forecasting error. Generally, this is calculated by dividing the sum of the errors by the MAD. It provides a directional percentage figure.

it is a mathematical model that estimstes the relationships among two or more variables