Glossary of Hospitality Data Terms
- Business Intelligence (BI)
- Clustering analysis
- Data aggregation
- Data cleansing
- Data collection
- Data governance
- Data integration
- Data model, data modeling
- Data scientist
- Data visualization
- Data warehouse
- Event analytics
- Internet of Things
- Location data
- Machine learning
- Predictive analytics
- Real-time data
- Recommendation engine
- Search data
- Sentiment analysis
- Text analytics
- Unstructured data
- Weather data
A mathematical formula placed in software that performs an analysis on a set of data. We can use algorithms to help make decisions such as serving the best offer for a customer with certain demographics.
The severing of links between people in a database and their records to prevent the discovery of the source of the records. An important concept in privacy, this may be used so that we can keep more records for reporting and statistical analyysis without breaching the customer’s need for privacy.
The general term used for the identification, extraction, and analysis of data. BI allows hospitality businesses to really understand what’s going on and make better decisions.
The process of identifying objects that are similar to each other and cluster them in order to understand the differences as well as the similarities within the data. Cluster analysis can help segment customers who exhibit similar behaviour allowing your marketing to target them better.
The act of collecting data from multiple sources for the purpose of reporting or analysis. A specialty of HostQ is bringing data from different places together. For hospitality businesses this might involve private sources such as your PMS, CRM or booking engine combined with public sources such as Google search and pandemic related data.
The act of reviewing and revising data to remove duplicate entries, correct misspellings, add missing data, and provide more consistency. Hospitality is sadly known for having “dirty” data which means there is no “single source of truth” for guest profiles. How can we recognise a customer when we don’t even know for sure how many times they’ve stayed?
Any process that captures any type of data. The most important part to get right to have clean data. Let’s make sure we are collecting enough data, all the data points which are relevant and of a high quality.
A set of processes or rules that ensure the integrity of the data and that data management best practices are met. Putting in place a data governance program is vital for any hospitality business so that every team from marketing to I.T. and e-Commerce are working together for the best data possible.
The process of combining data from different sources and presenting it in a single view. This maybe in the form of a dashboard that combines reservations data from your PMS with search patterns on your booking engine to see if you’re having good conversion on sales.
A data model defines the structure of the data for the purpose of communicating between functional and technical people to show data needed for business processes, or for communicating a plan to develop how data is stored and accessed among application development team members. HostQ has proprietary data models adapted to the hospitality industry.
A practitioner of data science. A powerful role in any organisation which unfortunately is still rare in the hotel industry.
A visual abstraction of data designed for the purpose of deriving meaning or communicating information more effectively. We register shapes and patterns multiple times quicker that we do with words, data visualisations can help you serve your guests better when you can make faster, better decisions.
A place to store data for the purpose of reporting and analysis. We can help you build your data warehouse so that you can create your own data ecosystem and break free of vendors holding your data hostage.
Shows the series of steps that led to an action. This could be useful for building an attribution model so you can understand the value of every touch point (landing on your website, seeing your social media post, interacting with advertising) and what leads to a sale.
Ordinary devices that are connected to the internet at any time any where via sensors.Is your hotel or resort using IoT effectively such as motion sensors to monitor busy periods of your restaurants or front desk?
Data that describes a geographic location. Location data can help you determine where your customers are finding out about you and help you reach them.
The use of algorithms to allow a computer to analyze data for the purpose of “learning” what action to take when a specific pattern or event occurs. Machine learning can take a deep dive in your guest profile data and find micro-segments of customers which you can target with tailored sales offers and promotions.
Data about data; gives information about what the data is about. This may be tagging data based on scales of privacy or confidentiality to make sure that data is protected and put to good use.
Using statistical functions on one or more datasets to predict trends or future events. An advanced set of analytics to help you forecast your performance such as high occupancy dates to better yield on the demand and to adapt your operations accordingly.
Data that is created, processed, stored, analysed and visualized within milliseconds. Wouldn’t it be helpful to be able to monitor the operations real time so you can deploy your employees to where the business needs them most.
An algorithm that analyzes a customer’s purchases and actions on an e-commerce site and then uses that data to recommend complementary products. By truly understanding your guests, hospitality businesses can also effectively use recommendation engines to upsell packages, auxillary services (late check-out?) and experiences to drive revenue and guest satisfaction.
Aggregated data about search terms used over time. How your guests find out about your hotel or resort could be hidden in serach data, have you reviewed yours yet?
The application of statistical functions on comments people make on the web and through social networks to determine how they feel about a product or company. Hospitality businesses have long had access to reviews on multiple platforms and guest satisfaction surveys. Take the guesswork out and let the data tell you how your customers truly feel about your business and the impacts it has on your commercial performance.
Any means of storing data persistently. This also means having the right type of storage facilitites. HostQ can help you figure out the perfect structure and amount you need so you don’t get overcharged for what you don’t use.
The application of statistical, linguistic, and machine learning techniques on text-based sources to derive meaning or insight.One application of this is analysing the emails you receive so you know the priority of those you need to respond to first.
Data that has no identifiable structure–for example, the text of email messages. As hotels offer more and more ways of being contacted from phone calls to chats and emails, understanding this data is more important than ever.
A visual abstraction of data designed for the purpose of deriving meaning or communicating information more effectively. This could be an interactive dashboard with charts and graphs where you can drill down further to find the details such as what markets are performing through which channels. What promotions are being performing best so you know where to put your spend in advertising.
The amount of data, ranging from megabytes to brontobytes. The volume of data coming out of hospitality is growing each day and needs to be profesionally managed.
Real-time weather data is now widely available for organizations to use in a variety of ways. For example, a logistics company can monitor local weather conditions to optimize the transport of goods. A utility company can adjust energy distribution in real time. Similarly weather can have an impact on your sales, customer satisfaction even employee productivity.