Hospitality Digital Marketing Glossary and Definitions

Active users are the number of engaged users on your website. This is the number of individuals who have had your website open for at least a second in the time period you are analysing. 

Note: This metric focuses on engagement of users. Universal Analytics previously measured Users and Total Users as the same number, whereas GA4 measures an active user based on their engagement with your website.

Advertising features enables you to collect additional demographic and interest data about your users. This allows you to enhance your advertising by creating audience lists. However you will need to enable the Advertising Features option in settings, this will engage Google’s 3rd party advertising cookies. If you also enable Google Signals, then advertising features will automatically be activated.

Attribution is how you determine or give credit for a conversion. This is very important when running online marketing campaigns, as you will be able to understand your return on investment (ROI) with more precision. GA4 uses data-driven attribution, which will consider all the actions a user took to get to your website across all their visits. Last-click attribution was the default option for Universal Analytics, which gave credit to the very last action a user took before triggering a conversion. You can change your attribution model setting through the admin section of Google Analytics and also change the lookback window for how much historical data is also used for attribution.

A group of users that share similar behaviour or interests can be segmented into audiences. This way you can analyse your data to understand how a particular group engages with your website to identify any emerging trends, such as who is visiting a particular page but not clicking on your ‘book now’ button.

Average engagement time is a measurement of the average amount of time people spend on your website. This metric is calculated by dividing the total time by the total number of active users. Remember, in GA4 a user needs to be engaged for at least one second and have a visible browser to be included in this metric.

This is similar to Average Engagement Time, but is based on sessions instead of users.

GA4 can use machine learning to ‘fill in the gaps’ or provide estimated data if someone doesn’t accept the cookie consent when they arrive on your website. To enable behavioural modelling, you will need to configure consent mode in your setting and also configure this with your cookie consent banner provider on your website.

A single-page visit to the website in which there was no interaction with the page.

In GA4, bounce rate is the percentage of sessions that last less than 10 seconds, have no event conversions and only includes one page view. This is a measurement of sessions that are not engaged.

Campaign name is one of four primary dimensions (along with source, medium and channel) for reporting and analysing marketing campaigns. When you tag a URL with a campaign for your inbound marketing or Google Ads campaigns, you will then enable the campaign name feature in your reports.

If you have multiple users who have access to your Google Analytics account, then you can use the Change History feature within the Admin section to see details about what changes have been made and by who.

Channels are the top-level groups associated with how someone came to your website. Each channel will combine both ‘Source’ and ‘Medium’ so you can get an understanding of the overall performance of that group. An example of this would be ‘Organic Search’ which would combine all users from Google Search or from Bing.

Content Groups are helpful to separate each page of your website into a particular category. This will enable you to report on top-level groupings such as Stay pages, or Wedding pages if your website has these page groups. You can create content groups by sending a value for the content_group parameter with another event to Google Analytics.

A conversion is reported whenever a user triggers an event that has been defined as a conversion. This could be a button click, or scroll depth.

With comparison, you can look at different section of your website traffic to analyse performance. This is helpful to know which parts of your website are performing better or which areas might need improvement. For example, comparing desktop traffic to mobile traffic.

A cookie is used to track and gather information which is stored from a website browser. This is how Google Analytics can identify users and sessions. If someone does not have an existing cookie, then a new cookie will be created, and they will become a new user. If someone already has a cookie, they will be reported as a returning visitor to your website. Cookies also have expiration dates, this is due to how long the information can be stored by a browser.

Cost Per Click, the cost paid per user click on an advert. In GA4, this can be found in the acquisition and advertising reports.

In GA4 you can collect additional data. Beyond the default dimensions and metrics you can also create ‘Custom Definitions’ in the Admin section if you want to measure specific variable unique to your website.

Additional data can be imported into GA4 to expand your reporting metrics and dimensions standard to Google Analytics. For example you could import some data on advertising costs, specific product item data (from your Property Management System – PMS), or user data from offline marketing.

Data Retention controls how long you can view data for in GA4. By default, user data is stored for two months, but you can extend this to 14 months in the Admin section. After this, specific data that can identify the person will be removed from analytics, such as a client ID or events. Aggregated data will continue to be available in reports after the data retention period.

A data stream is used to collect website data for your reports. You can create multiple data streams for each of your GA4 properties if you choose to, but it is best to keep this to one data stream per domain. Each data stream will have its own unique measurement ID which is used in the code added to your website or via Google Tag Manager.

This report is used to test that events are being sent to Google Analytics before you put them into live mode. Using Tag Assistant for Google Tag Manager is a good example of Debugging, so you can see that events are being triggered correctly. Events sent to DebugView (available in Admin) are not included in other reports.

Google Analytics automatically classifies and groups source/medium combinations into marketing channels. For example, a source could be Google and the medium might be cpc, Google will default this into Paid Search channel. This helps to get a top-level overview of the marketing channels that are performing best. Common channels you’ll measure include Organic Search, Paid Search, Direct, Organic Social, Email, Paid Social, Referral and Display.

Demographics reports delve deeper into data about users on your website, such as age, gender, location and browsing interests. To collect demographics data in your reports, you will need to enable Google Signals in the admin settings.

Dimensions (along with metrics) are one of two types of data that makes up reports in GA4. Dimensions are usually displayed as a row of information in Google Analytics reports, whereas metrics are usually displayed as columns.

Direct traffic includes users you ‘directly’ types in your website URL into their browser or have saved it in their bookmarks. This is any user who came to your website where there is no other definable campaign tag or channel assigned.

An ecommerce purchase occurs when Google Analytics collects a purchase event. This needs to be specifically set up with the system that integrates with your website, for hospitality this would be your booking engine. When ecommerce purchases are set up you will be able to see a variety of ecommerce dimensions and metrics in your reports, detailing purchase value, which items were purchased and much more valuable insights.

Need help setting up your hospitality ecommerce tracking? Find out about our packages here

An engaged session lasts longer than ten seconds, includes one or more page views and/or at least one conversion event. Ten seconds is the default engagement time, but you can change this in the admin settings if you want to.

In GA4, the enhanced measurement feature allows you to measure a number of additional actions a website visitor might perform without modifying your tracking code. This lets you automatically track page views, scroll depth, outbound link clicks, internal site searches, video plays and file downloads.

Engagement rate is a metric which is calculated by dividing the number of engaged sessions by the total number of sessions. If there were a total of 60 engaged sessions out of 100 sessions, then the engagement rate would be 60%.

GA4 collects website data, including user actions as Events. Event tracking in GA4 is completely different from previous event tracking in Universal Analytics. In GA4, an event could be a page view, a button click or a file download.

The total number of events that have been measured on your website.

Event Count per users is the average number of events that has been collected for each website user. You can calculate this metric by dividing the total events, by the number of users.

You can collect additional information about events with Event Parameters. When using Event Parameter you can collect information about the page title, page URL and much more. This replaces the previous system of Category and Action labels used in Universal Analytics. To get this additional information, Custom Event Parameters needs to be submitted as a Custom Definition, before being deployed to reports.

The average number of events that take place on your website per session.

This dimension is used to report new users on your website and shows the Medium they used to get your website. If their cookie remains active and they return to the website by another Medium, then this data will not change as it uses the first visit attribution.

This dimension is used to report new users on your website and shows the Source they used to get to your website. If their cookie remains active and they return to the website by another Source, then this data will not change as uses the first visit attribution.

This feature in GA4 enables you to report your demographics in more detail and create audience lists to be used in Google Ads. You will need to enable this feature in the Admin settings.

The global site tag (or gtag.js) is the tracking code used by Google to measure your website. It is unique and specific to your domain and can be installed directly onto your website in the <head> and <body> scripts, or installed using Google Tag Manager. We recommend using Google Tag Manager to setup website measurement.

Google Tag Manager is a Google tool used to manage and deploy code snippets to a website, without adding additional code to a website, causing it to slow down. It is a fantastic tool to manage all your third-party and additional code on your website, as well as DebugView testing capabilities.

GA4 offers an advanced machine learning feature to identify trends or changes in your website data. These observations make it quicker to highlight any specific insights and also ask questions about your data to find answers quickly.

A landing page is the webpage a user views when they first arrive on your website. In Google Analytics you can measure which landing pages people visit the most and which content is most important.

Default reports in GA4 can be edited to configure your own report. These will all go to the Library at the bottom of the Reports tab. You will need to have editor or administrator access to see this option.

Lifetime Value metrics in GA4 can be used to measure total lifetime revenue, lifetime average revenue and split this measurement based on users or sessions. To access this feature you will need to have ecommerce purchases setup in your tracking configuration.

The lookback window is a feature than allows you to change how far back you look into historical data for attribution reporting.

Medium is one of the dimensions (along with source, campaign and channel) that provide powerful data insights on how someone found your website. Medium is a top-level dimension, for example all organic search traffic will be classified as ‘Organic’. It is the medium by which you communicated a message for someone to click and go to your website.

Metrics are one of two types of data (including Dimensions) used to create reports in Google Analytics 4. Metrics are usually displayed as columns of data in pre-configured reports. An example of a metric includes page views, total users or sessions.

New Users are the people who have visited your website for the first time.

When data cannot be seen by Google Analytics, it will display in reports as ‘Not Seen’.

Organic relates to all users that have comes to your website from a ‘free link’ which they have accessed from a search engine, such as Google. The user as typed in a search query and found your website in the results page and clicked on the link.

Page views are measured when a user views a page on your website. Every different page they visit will count as a page view. You can measure the average page views per session as an indicator of user engagement.

A property in Google Analytics is created in an Account. You can create different properties which combine different data streams into a single set of reports. For example if you wanted to measure data from a subdomain as well as a root domain. However in most cases you will only need one property per website.

A referral is measured when a user clicks through to your website from another website. You might pay to have your website link show as a listing on another site, or perhaps you partner with that organisation. You can also exclude certain referral domains by changing the settings in Admin. This is particularly useful if your booking engine is showing as a referral link due to incorrect traffic set up.

Regular Expression, or Regex is an advanced method of pattern matching in text strings. Regex strings can be measured in Google Analytics which includes segments, audience definitions and much more.

Reporting view were an old feature of Universal Analytics. For each property you could view raw data, filtered data and test data. This feature is not default in GA4 and you will need to use filters in your reports to include or exclude data.

Scroll depth is a percentage measure of how far a user might scroll down your web page. This enhanced measurement will need to be enabled to get access to this in your reports. It is particularly helpful to understand how you display and order your most important content on a webpage.

Search query is the specific terms a person has used in a search engine to find your website link on the results page in a search engine, like Google before clicking and landing on your website.

Segments let you review and analyse a predefined subset of your analytics data based on website users, sessions, and events. You can apply up to four segments to a report in the exploration navigation tab.

A session is measured as a single visit to your website but engages in several ways including page views, purchases, or other events. Google Analytics will automatically trigger a session start event from the first engagement trigger, then this will timeout by default after 30 minutes when a user is inactive on the site. A new session will be reported when the user actively engages with your website again. This will not measure a session if your website is open but on a minimised tab on a user’s browser, they must be actively engaging on your website.

Source is one of the dimensions (along with Medium, Campaign and Channel) which allows you to view how many people found your website from a secondary dimension such as which Organic Search engine like Google or Bing.

To prevent individual data that is identifiable displaying in reports, Google Analytics can hide data from a report. To reduce the impact of data threshold you can choose the size of your data set (such as including a larger date range), or you could disable Google Signals.

This is the total number of individual users that have visited your website.

Origin of your user traffic.

·Organic search – from a search engine, influenced by SEO (e.g. Google, Bing, Android search, Yahoo)

·Direct – Where the browser auto-fills the website address or the user types in the full website address

·Email – from a marketing email (e.g. from Email Brilliance or Mailchimp)

·Referral – from a 3rd party (e.g. VisitEngland)

·Social – from a social media platform (e.g. Facebook, Twitter, YouTube, TripAdvisor)

·Paid search – From Google Ads search network

·Display – From Google Ads display network

User Engagement metrics are used to analyse how long people have been on your website or how many items of content they have viewed. In GA4, time is only measured for as long as the website is visible within the browser window. Hidden or minimised tabs will not measure engagement in GA4.

A user is an individual that interacts with your website. Each User can visit your website multiple times and start multiple sessions.

Note: This metric focuses on engagement. Universal Analytics previously measured Users and Total Users as the same number, whereas GA4 measures an active user based on their engagement with your website.

This measurement shows the percentage of new users that return to your website each day. For example, if 40 users came to your website for the first time yesterday, and 8 of them returned today, then your User Retention would be 20%.

UTM Tags are specific parameters that have been added as a query string to a URL. This is to help specifically identify campaigns so that reporting tools can identify the Campaign Name, the Campaign Source and Campaign Medium.

This is the total number of times a specific page has been viewed.

This metric is a measure of how many pages on average each individual user has visited on your website. You can calculate this number by dividing the total number of views by the total number of users.